Policy and society related implications of automated driving: A review of literature and directions for future research
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paper_title: Risk-Averse Autonomous Route Guidance by a Constrained A* Search

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In this article, the authors propose an efficient algorithm for finding a risk-averse path for use in autonomous vehicle navigation systems. When no dynamic traffic information is available, a risk-averse path can be found by a constrained A* search. The accuracy of navigation on the basis of static network data is improved by taking travel-time uncertainty into account. When dynamic traffic information in the form of broadcast traffic messages is available, rerouting is achieved by a constrained A* search, which takes congestion propagation into account. By making use of information computed at the start of the trip, the authors propose a responsive version of the constrained A* search, which reduces the on-demand response time. An experimental performance analysis of the proposed methods on grid graphs demonstrates their efficiency.
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paper_title: That's close enough—A threshold effect of time headway on the experience of risk, task difficulty, effort, and comfort

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Abstract Subjective impressions of task difficulty, risk, effort, and comfort are key variables of several theories of driver behaviour. A point of difference between many of these theories is not only the importance of these variables, but also whether they are continuously present and monitored or only experienced by individuals at certain critical points in the driving task. Both a threshold relationship and evidence of constant monitoring of risk and task difficulty have been found for speed choice. In light of these conflicting findings this study seeks to examine a different part of the driving task, the choice of time headway. Participants (N = 40, aged 19 to 30) drove in a simulator behind a vehicle travelling at 50 km/h at set time headways ranging from 0.5 seconds to 4.0 seconds. After each drive ratings of task difficulty, risk, comfort, and effort were collected. In addition participants were asked to drive at the time headway they preferred. In order to assess familiarity participants also drove on both the left and right hand side of the road and the role of driving experience was also examined. The results show support for a threshold awareness of task difficulty, risk, effort, and comfort in relation to time headway. Participant's ratings of these variables tended to be low or nil at large time headways, but then around the 2.0 second mark began to noticeably increase. Feelings of task difficulty, risk, and effort were also found to be highly correlated with each other. No effect of driving experience or side of the road was found.
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paper_title: Maneuver-Based Trajectory Planning for Highly Autonomous Vehicles on Real Road With Traffic and Driver Interaction

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This paper presents the design and first test on a simulator of a vehicle trajectory-planning algorithm that adapts to traffic on a lane-structured infrastructure such as highways. The proposed algorithm is designed to run on a fail-safe embedded environment with low computational power, such as an engine control unit, to be implementable in commercial vehicles of the near future. The target platform has a clock frequency of less than 150 MHz, 150 kB RAM of memory, and a 3-MB program memory. The trajectory planning is performed by a two-step algorithm. The first step defines the feasible maneuvers with respect to the environment, aiming at minimizing the risk of a collision. The output of this step is a target group of maneuvers in the longitudinal direction (accelerating or decelerating), in the lateral direction (changing lanes), and in the combination of both directions. The second step is a more detailed evaluation of several possible trajectories within these maneuvers. The trajectories are optimized to additional performance indicators such as travel time, traffic rules, consumption, and comfort. The output of this module is a trajectory in the vehicle frame that represents the recommended vehicle state (position, heading, speed, and acceleration) for the following seconds.
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paper_title: Model Predictive Multi-Objective Vehicular Adaptive Cruise Control

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This paper presents a novel vehicular adaptive cruise control (ACC) system that can comprehensively address issues of tracking capability, fuel economy and driver desired response. A hierarchical control architecture is utilized in which a lower controller compensates for nonlinear vehicle dynamics and enables tracking of desired acceleration. The upper controller is synthesized under the framework of model predictive control (MPC) theory. A quadratic cost function is developed that considers the contradictions between minimal tracking error, low fuel consumption and accordance with driver dynamic car-following characteristics while driver longitudinal ride comfort, driver permissible tracking range and rear-end safety are formulated as linear constraints. Employing a constraint softening method to avoid computing infeasibility, an optimal control law is numerically calculated using a quadratic programming algorithm. Detailed simulations with a heavy duty truck show that the developed ACC system provides significant benefits in terms of fuel economy and tracking capability while at the same time also satisfying driver desired car following characteristics.
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paper_title: In the Passenger Seat: Investigating Ride Comfort Measures in Autonomous Cars

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The prospect of driverless cars wide-scale deployment is imminent owing to the advances in robotics, computational power, communications, and sensor technologies. This promises highway fatality reductions and improvements in traffic and fuel efficiency. Our understanding of the effects arising from commuting in autonomous cars is still limited. The novel concept of the loss of driver controllability is introduced here. It requires a reassessment of vehicle's comfort criteria. In this review paper, traditional comfort measures are examined and autonomous passenger awareness factors are proposed. We categorize path-planning methods in light of the offered factors. The objective of the review presented in this article is to highlight the gap in path planning from a passenger comfort perspective and propose some research solutions. It is expected that this investigation will generate more research interest and bring innovative solutions into this field.
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paper_title: Intersection Management via Vehicle Connectivity: The Intersection Cooperative Adaptive Cruise Control System Concept

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Since the introduction of the vehicle infrastructure integration (VII) and connected vehicle (CV) initiatives in the United States, numerous in-vehicle technologies based on wireless communications are currently being deployed. One of these technologies is cooperative adaptive cruise control (CACC) systems, which provide better connectivity, safety, and mobility by allowing vehicles to travel in denser platoons through vehicle-to-vehicle (V2V) communication. Accordingly, the research presented in this article develops a simulation/optimization tool that optimizes the movement of CACC-equipped vehicles as a replacement for traditional intersection control. This system, which is named iCACC, assumes that the intersection controller receives vehicle requests to travel through an intersection and advises each vehicle on the optimum course of action ensuring no crashes occur while at the same time minimizing the intersection delay. Four intersection control scenarios are compared, namely: a traffic signal, an ...
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paper_title: Application of gas-kinetic theory to modelling mixed traffic of manual and ACC vehicles

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In this article, we propose an extended multiclass gas-kinetic theory applicable to mixed traffic flow of manual and adaptive cruise control (ACC) vehicles. In the model, the acceleration/deceleration of ACC vehicles is specified explicitly using microscopic models. The macroscopic multiclass traffic equations are obtained from the proposed gas-kinetic model using the well-known method of moments. The influencing conditions to traffic flow stability with respect to a small perturbation are derived by the linear stability method. The analytical results show that ACC vehicles contribute to the improved stabilisation of traffic flow. The numerical simulations of our developed multiclass macroscopic model on a circular freeway support our analytical findings and indicate that increasing the penetration of ACC vehicles results in more stable traffic flow. Simulations of merging flows at an on-ramp in an open freeway are carried out to describe the effects of the penetration of ACC vehicles on the bottleneck ca...
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paper_title: Intelligent Hybrid Electric Vehicle ACC With Coordinated Control of Tracking Ability, Fuel Economy, and Ride Comfort

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Adaptive cruise control (ACC) of hybrid electric vehicles (HEVs) has been traditionally developed without an efficient integration with active safety and energy management systems of hybrid powertrains, mainly for facilitating its implementation. This, however, leads to a compromise in the fuel economy of HEVs, since the predictive driving information provided by ACC is not exploited by the energy management system. In order to enhance the energy efficiency and control system integration, a novel ACC system for intelligent HEVs (i-HEV ACC) is developed in this study. The controller is proposed within the framework of nonlinear model predictive control, and a position-based nonlinear longitudinal intervehicle dynamics model is developed. A coordinated optimal control problem for both the tracking safety and the fuel consumption is formulated subject to the constraints on stable tracking. A multistep offline dynamic programming optimization and an online lookup table are used to implement the real-time control algorithm. Experiments are further conducted, which demonstrate that the proposed i-HEV ACC achieves enhanced performance and cooperation in traffic safety, fuel efficiency, and ride comfort.
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paper_title: Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation

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This paper examines the impact of having cooperative adaptive cruise control (CACC) embedded vehicles on traffic flow characteristics of a multilane highway system. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce traffic congestion resulting from the acceleration/deceleration of the operating vehicles. An agent-based microscopic traffic simulation model (Flexible Agent-based Simulator of Traffic) is designed specifically to examine the impact of these intelligent vehicles on traffic flow. The flow rate of cars, the travel time spent, and other metrics indicating the evolution of traffic congestion throughout the lifecycle of the model are analyzed. Different CACC penetration levels are studied. The results indicate a better traffic flow performance and higher capacity in the case of CACC penetration compared to the scenario without CACC-embedded vehicles.
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paper_title: Design, tuning, and evaluation of a full-range adaptive cruise control system with collision avoidance

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Abstract This paper describes the design, tuning, and evaluation of a full-range adaptive cruise control (ACC) system with collision avoidance (CA). The control scheme is designed to improve drivers’ comfort during normal, safe-driving situations and to completely avoid rear-end collision in vehicle-following situations. Driving situations are divided into safe, warning, and dangerous modes. Three different control strategies have been proposed, depending on the driving situation. The driving situations are determined using a non-dimensional warning index and the time-to-collision (TTC). The control parameters of the proposed ACC/CA system are tuned by a confusion-matrix method using manual-driving data in no-crashing driving situations. The vehicle-following characteristics of the subject vehicle were compared to real-world, manual-driving data. Finally, the ACC/CA system was also implemented in a real vehicle and tested in both safe-traffic and severe-braking situations. It is shown that the proposed control strategy can provide natural following performance that is similar to human manual-driving in both high-speed driving and low-speed stop-and-go situations. Furthermore, it can prevent the vehicle-to-vehicle distance from dropping to an unsafe level in a variety of driving conditions.
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paper_title: The influence of time headway on subjective driver states in adaptive cruise control

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Abstract There is no agreement on the relation between driving parameters and drivers’ subjective states. A linear as well as a threshold relationship for different subjective variables and driving parameters has been put forward. In this study we investigate the relationship between time headway and the ratings of risk, task difficulty, effort, and comfort. Knowledge about this interrelation may advance the development of adaptive cruise control and autonomous driving and can add to the discussion about driver behavior models. An earlier study (Lewis-Evans, De Waard, & Brookhuis, 2010) found a threshold effect for drivers’ ratings of subjective variables for time headways between 0.5 and 4.0 s at a speed of 50 km/h. This study aims to replicate the threshold effect and to expand the findings to time headways at different speeds. A new measure for criticality was added as a categorical variable, indicating the controllability of a driving situation to give indications for the appliance of time headway in adaptive cruise control systems. Participants drove 24 short routes in a driving simulator with predefined speed and time headway to a leading vehicle. Time headway was varied eightfold (0.5–4 s in 0.5 s increments) and speed was varied threefold (50, 100, 150 km/h). A threshold effect for the ratings of risk, task difficulty, effort, and comfort was found for all three different speeds. Criticality proved to be a useful variable in assessing the preferred time headway of drivers.
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paper_title: Adaptive cruise control design for active congestion avoidance

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We present an adaptive cruise control (ACC) strategy where the acceleration characteristics, that is, the driving style automatically adapts to different traffic situations. The three components of the concept are the ACC itself, implemented in the form of a car-following model, an algorithm for the automatic real-time detection of the traffic situation based on local information, and a strategy matrix to adapt the driving characteristics (that is, the parameters of the ACC controller) to the traffic conditions. Optionally, inter-vehicle and infrastructure-to-car communication can be used to improve the accuracy of determining the traffic states. Within a microscopic simulation framework, we have simulated the complete concept on a road section with an on-ramp bottleneck, using empirical loop-detector data for an afternoon rush-hour as input for the upstream boundary. We found that the ACC vehicles improve the traffic stability and the dynamic road capacity. While traffic congestion in the reference scenario was completely eliminated when simulating a proportion of 25% ACC vehicles, travel times were already significantly reduced for much lower penetration rates. The efficiency of the proposed driving strategy even for low market penetrations is a promising result for a successful application in future driver assistance systems.
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paper_title: A Multiagent Approach to Autonomous Intersection Management

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Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. ::: ::: We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology--traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.
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paper_title: Fuzzy motion control strategy for cooperation of multiple automated vehicles with passengers comfort

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This paper considers motion control for a cooperative system of automated passenger vehicles. It develops a cooperative scheme based on a decentralized planning algorithm which considers the vehicles in an initial open chain configuration. In this scheme the trajectories are intersections-free, and each trajectory is planned independently of the others. To ensure the stabilization of each vehicle in the planned trajectory, a fuzzy closed loop motion control is presented, where, based on the properties of the Fuzzy maps, the Lyapunov's stability of the motion errors is demonstrated for all the vehicles. Based on the ISO 2631-1 standard, the saturation property of the Fuzzy maps guarantees low values of longitudinal and lateral accelerations, to ensure comfort of the human body during the motion. The validity of this control algorithm is supported by simulation experiments.
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paper_title: Variable speed limit: A microscopic analysis in a connected vehicle environment

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Abstract This paper presents a Variable Speed Limit (VSL) control algorithm for simultaneously maximizing the mobility, safety and environmental benefit in a Connected Vehicle environment. Development of Connected Vehicle (CV)/Autonomous Vehicle (AV) technology has the potential to provide essential data at the microscopic level to provide a better understanding of real-time driver behavior. This paper investigated a VSL control algorithm using a microscopic approach by focusing on individual driver’s behavior (e.g., acceleration and deceleration) through the use of Model Predictive Control (MPC) approach. A multi-objective optimization function was formulated with the aim of finding a balanced trade-off among mobility, safety and sustainability. A microscopic traffic flow prediction model was used to calculate Total Travel Time (TTT); a surrogate safety measure Time To Collision (TTC) was used to measure instantaneous safety; and, a microscopic fuel consumption model (VT-Micro) was used to measure the environmental impact. Real-time driver’s compliance to the posted speed limit was used to adjust the optimal speed limit values. A sensitivity analysis was conducted to compare the performance of the developed approach for different weights in the objective function and for two different percentages of CV. The results showed that with 100% penetration rate, the developed VSL approach outperformed the uncontrolled scenario consistently, resulting in up to 20% of total travel time reductions, 6–11% of safety improvements and 5–16% reduction in fuel consumptions. Our findings revealed that the scenario which optimized for safety alone, resulted in more optimum improvements as compared to the multi-criteria optimization. Thus, one can argue that in case of 100% penetration rates of CVs, optimizing for safety alone is enough to achieve simultaneous and optimum improvements in all measures. However, mixed results were obtained in case of lower % penetration rate which showed higher collision risk when optimizing for only mobility or fuel consumption. This indicates that with such % penetration rate, multi-criteria optimization is crucial to realize optimum and balanced benefits for the examined measures.
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paper_title: Entrance Capacity of an Automated Highway System

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This paper evaluates the entrance capacity and queueing delay for Automated Highway Systems through use of simulations and analytical modeling. Queueing statistics are also used to determine the sustainable capacity of alternative concepts, taking trip length distribution and spacing between ramps into consideration. Based on safety-spacing headways (produced in a separate analysis), the most promising concept utilizes platoons both on the highway and on on-ramps. However, it is unclear whether comparable capacity can be achieved on exit, when vehicles must be decoupled from their platoons, and whether it is safe for vehicles to enter the highway in closely spaced platoons. The analytical evaluation indicates that entrance/exit spacing on the order of one per 2 km or closer would be required to support highways with total capacity on the order of 20,000 vehicles per hour. Most likely, this would be achieved most efficiently if separate dedicated entrances are provided for automated vehicles, to minimize weaving on manual lanes.
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paper_title: Macroscopic traffic flow modeling with adaptive cruise control: Development and numerical solution

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The incorporation of two macroscopic approaches reflecting Adaptive Cruise Control (ACC) and Cooperative Adaptive Cruise Control (CACC) traffic dynamics in a gas-kinetic (GKT) traffic flow model is presented. The first approach was recently analyzed in the literature aiming to describe the effects induced by the ACC and CACC systems due to changes of the speed of the leading car(s) by the introduction of an acceleration/deceleration term. The second approach is a novel one and is based on the introduction of a relaxation term that satisfies the time/space-gap principle of ACC or CACC systems. In both approaches, the relaxation time is assigned on multiple leading vehicles in the CACC case; whereas in the ACC case this relaxation time is only assigned to the direct leading vehicle. We numerically approximate the resulting models by an accurate and robust high-resolution finite volume relaxation scheme, where the nonlinear system of partial differential equations is first recast to a diagonalizable semi-linear system and is then discretized by a higher-order WENO scheme. Numerical simulations investigate the effect of the different ACC and CACC approaches to traffic flow macroscopic stability with respect to perturbations introduced in a ring road and to flow characteristics in open freeways with merging flows at an on-ramp. Following from the numerical results, it can be concluded that CACC vehicles increase the stabilization of traffic flow, with respect to both small and large perturbations, compared to ACC ones. Further, the proposed CACC approach can better improve the dynamic equilibrium capacity and traffic dynamics, especially at the on-ramp bottleneck. A novel macroscopic modeling approach for Adaptive Cruise Control (ACC) in traffic flow dynamics.The proposed model is incorporated to a gas-kinetic (GKT) traffic flow model.A comparison with an alternative approach from the literature is performed.A high-resolution relaxation finite volume discretization (in space and time) is implemented.
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paper_title: Effects of a Cooperative Variable Speed Limit System on Traffic Performance and Exhaust Emissions

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Variable Speed Limit Systems (VSLS) where variable message signs show speed limits based on traffic or road conditions exist on motorways in many countries. The purpose of the VSLS is to decrease the number of accidents while increasing efficiency of traffic system. Cooperative systems are a type of intelligent transport system that has received increasing interest lately. The central part of a cooperative system is communication between vehicles and/or vehicles and the infrastructure. In this paper, a cooperative systems extension of a VSLS is proposed and evaluated by means of microscopic traffic simulation. In the proposed cooperative VSLS, communication between the vehicles and the infrastructure is made available via a roadside unit communicating the speed limits to vehicles upstream on the road. Both aggregate and micro-scale emission models are used to estimate emission from vehicle states in traffic flow. The results of the study show that the cooperative VSLS has a potential to contribute to flow harmonization and to reduce environmental impacts. The emission estimates in the study are dependent on the emission models being applied.
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paper_title: The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics

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Cooperative adaptive cruise control (CACC) is an extension of ACC. In addition to measuring the distance to a predecessor, a vehicle can also exchange information with a predecessor by wireless communication. This enables a vehicle to follow its predecessor at a closer distance under tighter control. This paper focuses on the impact of CACC on traffic-flow characteristics. It uses the traffic-flow simulation model MIXIC that was specially designed to study the impact of intelligent vehicles on traffic flow. The authors study the impacts of CACC for a highway-merging scenario from four to three lanes. The results show an improvement of traffic-flow stability and a slight increase in traffic-flow efficiency compared with the merging scenario without equipped vehicles
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paper_title: Impacts of Cooperative Adaptive Cruise Control on Freeway Traffic Flow

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This study used microscopic simulation to estimate the effect on highway capacity of varying market penetrations of vehicles with adaptive cruise control (ACC) and cooperative adaptive cruise control (CACC). Because the simulation used the distribution of time gap settings that drivers from the general public used in a real field experiment, this study was the first on the effects of ACC and CACC on traffic to be based on real data on driver usage of these types of controls. The results showed that the use of ACC was unlikely to change lane capacity significantly. However, CACC was able to increase capacity greatly after its market penetration reached moderate to high percentages. The capacity increase could be accelerated by equipping non-ACC vehicles with vehicle awareness devices so that they could serve as the lead vehicles for CACC vehicles.
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paper_title: Autonomous cars: The tension between occupant experience and intersection capacity

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Abstract Systems that enable high levels of vehicle-automation are now beginning to enter the commercial marketplace. Road vehicles capable of operating independently of real-time human control under an increasing set of circumstances will likely become more widely available in the near future. Such vehicles are expected to bring a variety of benefits. Two such anticipated advantages (relative to human-driver vehicle control) are said to be increased road network capacity and the freeing up of the driver-occupant’s time to engage in their choice of leisurely or economically-productive (non-driving) tasks. In this study we investigate the implications for intersection capacity and level-of-service of providing occupants of automated (without real-time human control), autonomously-operating (without vehicle-to-X communication) cars with ride quality that is equivalent (in terms of maximum rates of longitudinal and lateral acceleration) to two types of rail systems: [urban] light rail transit and [inter-urban] high-speed rail. The literature suggests that car passengers start experiencing discomfort at lower rates of acceleration than car drivers; it is therefore plausible that occupants of an autonomously-operating vehicle may wish to instruct their vehicle to maneuver in a way that provides them greater ride comfort than if the vehicle-control algorithm simply mimicked human-driving-operation. On the basis of traffic microsimulation analysis, we found that restricting the dynamics of autonomous cars to the acceleration/deceleration characteristics of both rail systems leads to reductions in a signalized intersection’s vehicle-processing capacity and increases in delay. The impacts were found to be larger when constraining the autonomous cars’ dynamics to the more-restrictive acceleration/deceleration profile of high-speed rail. The scenarios we analyzed must be viewed as boundary conditions, because autonomous cars’ dynamics were by definition never allowed to exceed the acceleration/deceleration constraints of the rail systems. Appropriate evidence regarding motorists’ preferences does not exist at present; establishing these preferences is an important item for the future research agenda. This paper concludes with a brief discussion of research needs to advance this line of inquiry.
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paper_title: Design and performance evaluation of mixed manual and automated control traffic

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We present a technology which allows manually controlled and automatically controlled vehicles to co-exist, thereby reducing much of the cost and infrastructure requirements in highway automation. An autonomous vehicle driving system (AVDS) is presented which only uses information from vehicle sensors, thereby eliminating the requirement that vehicles communicate with one another. This format allows gradual market penetration of AVDS, which makes the technology attractive from a systems implementation standpoint. To evaluate the performance of the mixed traffic, we simulate manual and automated vehicles together and show that our AVDS can lead to potentially large gains in capacity and smoother flow without the loss of safety.
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paper_title: AN EXPERIMENTAL COMPARATIVE STUDY OF AUTONOMOUS AND CO-OPERATIVE VEHICLE-FOLLOWER CONTROL SYSTEMS

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Abstract This paper is a comparative study of the performance of constant-time-gap autonomous control systems and co-operative longitudinal control systems that use inter-vehicle communication. Analytical results show that the minimum time gap that can be achieved in autonomous control is limited by the bandwidth of the internal dynamics of the vehicle. Experimental results from typical sensors and actuators are used to show that in practice it is very difficult to achieve a time gap less than 1 s with autonomous vehicle following. This translates to an inter-vehicle spacing of 30 m at highway speeds and a theoretical maximum traffic flow of about 3000 vehicles per hour. The quality of radar range and range rate measurements pose limitations on the spacing accuracy and ride quality that can be achieved in autonomous control. Dramatic improvements in the trade-off between ride quality and spacing accuracy can be obtained merely by replacing radar range rate in the autonomous control algorithm with the difference between the measured velocities of the two cars (a rudimentary form of co-operation). As a baseline comparison, the experimental performance of fully co-operative control is presented. An inter-vehicle spacing of 6.5 m is maintained in a platoon of 8 co-operative vehicles with an excellent ride quality and an accuracy of ±20 cm. Extending this to a 10-vehicle platoon makes it possible to achieve theoretical maximum traffic flows of about 6400 vehicles per hour. Another issue of importance addressed in the paper is the need to accommodate malfunctions in radar (ranging sensor) measurements. Measurement errors can occur due to hardware malfunctions as well as due to road curves, grades and the highway environment in the case of large inter-vehicle spacing. The ability of a co-operative control system to monitor the health of the radar and correct for such errors and malfunctions is demonstrated experimentally.
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paper_title: Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation

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This paper examines the impact of having cooperative adaptive cruise control (CACC) embedded vehicles on traffic flow characteristics of a multilane highway system. The study identifies how CACC vehicles affect the dynamics of traffic flow on a complex network and reduce traffic congestion resulting from the acceleration/deceleration of the operating vehicles. An agent-based microscopic traffic simulation model (Flexible Agent-based Simulator of Traffic) is designed specifically to examine the impact of these intelligent vehicles on traffic flow. The flow rate of cars, the travel time spent, and other metrics indicating the evolution of traffic congestion throughout the lifecycle of the model are analyzed. Different CACC penetration levels are studied. The results indicate a better traffic flow performance and higher capacity in the case of CACC penetration compared to the scenario without CACC-embedded vehicles.
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paper_title: Safety and Capacity Analysis of Automated and Manual Highway Systems

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This paper compares safety of automated and manual highway systems with respect to resulting rear-end collision frequency and severity. Safety is related to driver, vehicle and highway operating characteristics. Our safety analysis method maps the variation in these operating characteristics, modeled by probability distributions, to the probability and severity of the first rear-end crash due to a hard braking disturbance on the highway. The results show that automated driving is safer than the most alert manual drivers, at similar speeds and capacities. We also present a detailed safety-capacity trade-off study for four different automated highway system concepts that differ in their information structure and separation policy. This study quantifies the impact of inter-vehicle cooperation and operating speed of the Automated Highway System (AHS). It also compares and contrasts the safety characteristics of individual vehicle and platoon based Automated Highway Systems.
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paper_title: Towards reducing traffic congestion using cooperative adaptive cruise control on a freeway with a ramp

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Purpose: In this paper, the impact of Cooperative Adaptive Cruise Control (CACC) systems on traffic performance is examined using microscopic agent-based simulation. Using a developed traffic simulation model of a freeway with an on-ramp - created to induce perturbations and to trigger stop-and-go traffic, the CACC system’s effect on the traffic performance is studied. The previously proposed traffic simulation model is extended and validated. By embedding CACC vehicles in different penetration levels, the results show significance and indicate the potential of CACC systems to improve traffic characteristics and therefore can be used to reduce traffic congestion. The study shows that the impact of CACC is positive but is highly dependent on the CACC market penetration. The flow rate of the traffic using CACC is proportional to the market penetration rate of CACC equipped vehicles and the density of the traffic. Design/methodology/approach: This paper uses microscopic simulation experiments followed by a quantitative statistical analysis. Simulation enables researchers manipulating the system variables to straightforwardly predict the outcome on the overall system, giving researchers the unique opportunity to interfere and make improvements to performance. Thus with simulation, changes to variables that might require excessive time, or be unfeasible to carry on real systems, are often completed within seconds. Findings: The findings of this paper are summarized as follow: • Provide and validate a platform (agent-based microscopic traffic simulator) in which any CACC algorithm (current or future) may be evaluated. • Provide detailed analysis associated with implementation of CACC vehicles on freeways. • Investigate whether embedding CACC vehicles on freeways has a significant positive impact or not. Research limitations/implications: The main limitation of this research is that it has been conducted solely in a computer laboratory. Laboratory experiments and/or simulations provide a controlled setting, well suited for preliminary testing and calibrating of the input variables. However, laboratory testing is by no means sufficient for the entire methodology validation. It must be complemented by fundamental field testing. As far as the simulation model limitations, accidents, weather conditions, and obstacles in the roads were not taken into consideration. Failures in the operation of the sensors and communication of CACC design equipment were also not considered. Additionally, the special HOV lanes were limited to manual vehicles and CACC vehicles. Emergency vehicles, buses, motorcycles, and other type of vehicles were not considered in this dissertation. Finally, it is worthy to note that the human factor is far more sophisticated, hard to predict, and flexible to be exactly modeled in a traffic simulation model perfectly. Some human behavior could occur in real life that the simulation model proposed would fail to model. Practical implications: A high percentage of CACC market penetration is not occurring in the near future. Thus, reaching a high penetration will always be a challenge for this type of research. The public accessibility for such a technology will always be a major practical challenge. With such a small headway safety gap, even if the technology was practically proven to be efficient and safe, having the public to accept it and feel comfortable in using it will always be a challenge facing the success of the CACC technology. Originality/value: The literature on the impact of CACC on traffic dynamics is limited. In addition, no previous work has proposed an open-source microscopic traffic simulator where different CACC algorithms could be easily used and tested. We believe that the proposed model is more realistic than other traffic models, and is one of the very first models to model the behavior CACC vehicles on freeways.
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paper_title: SIMPLE PLATOON ADVANCEMENT: A MODEL OF AUTOMATED VEHICLE MOVEMENT AT SIGNALISED INTERSECTIONS

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Abstract The Simple Platoon Advancement (SPA) model describes a conceptual Intelligent Transportation System in which vehicles are progressed through signalised intersections under the automatic control of roadside and in-vehicle infrastructure. The objective is to increase the throughput of vehicles by moving the queue as a closely-spaced platoon on the start-of-green. Comparisons of stopline throughput are made between the SPA model and a valid representation of current road traffic behaviour. The paper contains a description of a basic model—the homogeneous SPA model with constant acceleration—where all vehicles behave the same in terms of their acceleration characteristics, the time headway they desire and the target speed each is trying to reach after passing through the intersection. The acceleration characteristics in question are the rate and the style: that of this model has no smoothing effect and is instantaneously wrought on a vehicle. Though this is somewhat unrealistic for a working system, the constant acceleration model serves as a yardstick for which to check and compare the development of future models. The framework for this model is defined to enable calculations of measurable goals such as stopline throughput for comparison with the EQD model of current road traffic behaviour. In terms of throughput, the homogeneous SPA model shows that even with a very cautious approach using conservative parameter values, the number of vehicles that would pass the stopline of a SPA-equipped intersection is a little more than 150% compared with the throughput found in today’s road systems. Reductions in jam spacing increase the throughput still further.
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paper_title: Using connected vehicle technology to improve the efficiency of intersections

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Information from connected vehicles, such as the position and speed of individual vehicles, can be used to optimize traffic operations at an intersection. This paper proposes such an algorithm for two one-way-streets assuming that only a certain percentage of cars are equipped with this technology. The algorithm enumerates different sequences of cars discharging from the intersection to minimize the objective function. Benefits of platooning (multiple cars consecutively discharging from a queue) and signal flexibility (adaptability to demand) are also considered. The goal is to gain insights about the value (in terms of delay savings) of using connected vehicle technology for intersection control. Simulations are conducted for different total demand values and demand ratios to understand the effects of changing the minimum green time at the signal and the penetration rate of connected cars. Using autonomous vehicle control systems, the signal could rapidly change the direction of priority without relying on the reaction of drivers. However, without this technology a minimum green time is necessary. The results of the simulations show that a minimum green time increases the delay only for the low and balanced demand scenarios. Therefore, the value of using cars with autonomous vehicle control can only be seen at intersections with this kind of demand patterns, and could result in up to 7% decrease in delay. On the other hand, using information from connected vehicles to better adapt the traffic signal has proven to be indeed very valuable. Increases in the penetration rate from 0% up to 60% can significantly reduce the average delay (in low demand scenarios a decrease in delay of up to 60% can be observed). That being said, after a penetration rate of 60%, while the delays continue to decrease, the rate of reduction decreases and the marginal value of information from communication technologies diminishes. Overall, it is observed that connected vehicle technology could significantly improve the operation of traffic at signalized intersections, at least under the proposed algorithm.
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paper_title: A New Extended Multiple Car-Following Model Considering the Backward-Looking Effect on Traffic Flow

paper_content:

To make full use of the newly available information provided by the intelligent transportation system (ITS), we presented a new car-following model applicable to automated driving control, which will be realized in the near future along with the rapid development of ITS. In this model, the backward-looking effect and the information inputs from multiple leading cars in traffic flow are considered at the same time. The linear stability criterion of this model is obtained using linear stability theory. Furthermore, the nonlinear analysis method is employed to derive the modified Korteweg-de Vries (mKdV) equation, whose kink-antikink soliton solution is then used to describe the occurrence of traffic jamming transitions. The numerical simulation of the presented model is carried out. Both the analytical analysis and numerical simulation show that the traffic jam is suppressed efficiently by just considering the information of two leading cars and a following one.
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paper_title: Capacity Analysis of Traffic Flow over a Single-Lane Automated Highway System

paper_content:

Abstract We calculate bounds on per-lane Automated Highway System (AHS) capacity as a function of vehicle capabilities and control system information structure. We assume that the AHS lane is dedicated for use by fully automated vehicles. Capacity is constrained by the minimum inter-vehicle separation necessary for safe operation. A methodology for deriving the safe minimum inter-vehicle separation for a particular safety criterion is presented. The inter-vehicle separation, which depends on the vehicle braking capability, control loop delays and operating speed, is then used to compute site-independent upper bounds on AHS capacity for a given mix of vehicle classes. The sensitivity of the capacity with respect to the degree of inter-vehicle cooperation, check-in policies (governing minimum acceptable vehicle-braking capability), highway speed limits, and lane-use policies (governing the sharing of a lane by multiple vehicle classes) is also investigated.
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paper_title: Multiplatooning Leaders Positioning and Cooperative Behavior Algorithms of Communicant Automated Vehicles for High Traffic Capacity

paper_content:

Multiplatooning leaders positioning and cooperative behavior strategies are proposed in this paper, to improve the efficiency of a traffic system of communicant automated vehicles evolving on dedicated lanes. Novel algorithms to ensure high traffic capacity are presented and MATLAB/Simulink-based simulation results are reported. In previous research work, we proposed new algorithms to mitigate communication delays effects on platoon string stability using anticipatory information. In this paper we consider constant spacing between platoons' leaders as a fundamental condition to attain high traffic capacity. New algorithms to maintain interplatoon leaders' constant spacing are proposed, as well as novel algorithms allowing vehicles to enter the main track cooperatively. Furthermore, a new set of algorithms to improve safety is also presented. A novel agent-based architecture was developed, in which each vehicle consists of two distinct modules, a leader and a follower. Based on MATLAB/Simulink simulations of several scenarios, the new algorithms are assessed and the simulation results presented, confirming that the proposed algorithms ensure high traffic capacity and vehicle density and avoid traffic congestion. These features were validated through simulations performed on the Simulation for Urban Mobility simulation platform, using a new car-following model implementation [10]. The results proved that the proposed algorithms enable a clear benefit of a platooning system, when compared with bus- and light-rail-based transit systems.
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paper_title: Microscopic cooperative traffic flow: Calibration and simulation based on a next generation simulation dataset

paper_content:

The deployment of new emerging technologies, such as cooperative systems, allows the traffic community to foresee relevant improvements in terms of traffic safety and efficiency. Autonomous vehicles are able to share information about the local traffic state in real time, which could result in a better reaction to the mechanism of traffic jam formation. An upstream single-hop radio broadcast network can improve the perception of each cooperative driver within a specific radio range and hence the traffic stability. The impact of vehicle to vehicle cooperation on the onset of traffic congestion is investigated analytically and through simulation. A next generation simulation field dataset is used to calibrate the full velocity difference car-following model, and the MOBIL lane-changing model is implemented. The robustness of the calibration as well as the heterogeneity of the drivers is discussed. Assuming that congestion can be triggered either by the heterogeneity of drivers' behaviours or abnormal lane-changing behaviours, the calibrated car-following model is used to assess the impact of a microscopic cooperative law on egoistic lane-changing behaviours. The cooperative law can help reduce and delay traffic congestion and can have a positive effect on safety indicators.
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paper_title: Instability of cooperative adaptive cruise control traffic flow: A macroscopic approach

paper_content:

Abstract This paper proposes a macroscopic model to describe the operations of cooperative adaptive cruise control (CACC) traffic flow, which is an extension of adaptive cruise control (ACC) traffic flow. In CACC traffic flow a vehicle can exchange information with many preceding vehicles through wireless communication. Due to such communication the CACC vehicle can follow its leader at a closer distance than the ACC vehicle. The stability diagrams are constructed from the developed model based on the linear and nonlinear stability method for a certain model parameter set. It is found analytically that CACC vehicles enhance the stabilization of traffic flow with respect to both small and large perturbations compared to ACC vehicles. Numerical simulation is carried out to support our analytical findings. Based on the nonlinear stability analysis, we will show analytically and numerically that the CACC system better improves the dynamic equilibrium capacity over the ACC system. We have argued that in parallel to microscopic models for CACC traffic flow, the newly developed macroscopic will provide a complete insight into the dynamics of intelligent traffic flow.
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paper_title: A Vehicle-Intersection Coordination Scheme for Smooth Flows of Traffic Without Using Traffic Lights

paper_content:

This paper presents a coordination scheme of automated vehicles at an intersection without using any traffic lights. Using a two-way communication network, vehicles approaching the intersection from all sections are globally coordinated, by considering their states all together in a model predictive control framework, in order to achieve smooth traffic flows at the intersection. The optimal trajectories of the vehicles are computed based on avoidance of their cross-collision risks around the intersection under relevant constraints and preferences. The scheme efficiently utilizes the intersection area by preventing each pair of conflicting vehicles from approaching their cross-collision point at the same time, instead of reserving the whole intersection area for the conflicting vehicles one after another. The scheme also enables left- or right-turning movements of vehicles under constrained velocity without using any auxiliary lanes. The proposed vehicle-intersection coordination scheme is evaluated through numerical simulation in a typical test intersection consisting of both multilanes and single-lane approaches with turning movements of vehicles. Observations under different traffic flow conditions reveal that the proposed scheme significantly improves intersection performance compared with the traditional signalized intersection scheme.
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paper_title: Will Greeks Cycle? Exploring Intention and Attitudes in the Case of the New Bicycle Network of Patras

paper_content:

In this paper, social psychology methods were employed to explore the intention of a Greek city's residents to use a new bicycle network for their mobility needs, the factors affecting this intention, and the residents’ attitudes toward the environment, car use, and alternative means of transport. A strong intention to use the new bicycle network was found, complemented by pro-environment, pro-alternative means of transport views and realization of car-related problems. The construction of the bicycle network, along with soft cycle-promotion policies and car-restriction measures, may strengthen the perceived behavioral control and attitude and, consequently, this intention.
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paper_title: Bounding the Potential Increases in Vehicles Miles Traveled for the Non-Driving and Elderly Populations and People with Travel-Restrictive Medical Conditions in an Automated Vehicle Environment

paper_content:

Automated vehicles represent a technology that promises to increase mobility and accessibility not only to the senior population but also to non-drivers and people with medical conditions. This paper estimates the impact of a fully automated vehicle environment on the total vehicle miles traveled (VMT) by the current U.S. population 19 and older due to an increase in mobility from the non-driving and elderly populations and people with travel-restrictive medical conditions. The primary source of data for this project is the 2009 National Household Transportation Survey (NHTS), which provides information on current travel characteristics of the U.S. population. The changes to the total VMT are estimated by examining three possible demand wedges. In demand wedge one, the assumption made is that non-drivers would travel as much as the drivers within each age group and gender. Demand wedge two assumes that the driving elderly without medical conditions will travel as much as young adults (ages 19-64) within each gender. Demand wedge three makes the assumption that drivers with medical conditions will travel as much as the drivers without medical conditions within each age group and gender in a fully autonomous and connected vehicle environment. The combination of the results from all three demand wedges represents an upper bound of 297 billion miles or a 12% increase in overall VMT. Since traveling has other costs than driving effort, this estimate serves to bound the potential increase from these populations to inform the scope of the challenges, rather than forecast specific VMT scenarios.
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paper_title: The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios

paper_content:

Abstract Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles. This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers. Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.
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paper_title: How Do Activities Conducted while Commuting Influence Mode Choice? Testing Public Transportation Advantage and Autonomous Vehicle Scenarios

paper_content:

From early studies of time allocation onward, it has been acknowledged that the “productive” nature of travel could affect its utility. At the margin, an individual may choose transit over a shorter automobile trip, if thereby she is able to use the travel time more productively. Alternatively, the recent advancements toward partly/fully automated vehicles are poised to revolutionize the perception and utilization of travel time in cars, and are further blurring the role of travel as a crisp transition between location-based activities. To quantify these effects, the authors created and administered a survey to measure multitasking attitudes and behavior while commuting, together with general attitudes, mode-specific perceptions, and standard socioeconomic traits (N = 2120 Northern California commuters). The authors present a revealed preference mode choice model that accounts for the impact of multitasking attitudes and behavior on the utility of various alternatives. The authors find that engaging in productive activities (i.e. electronic reading/writing and using a laptop/tablet) significantly influences utility and could account for a small but non-trivial portion of the current mode shares. For example, the model estimates that commuter rail and car/vanpool shares would respectively be 0.38 and 3.22 percentage points lower, and the drive-alone share 3.00 percentage points higher, if the option to use time productively while traveling were not available. Conversely, in a hypothetical autonomous vehicles scenario, where the car would allow a high level of engagement in productive activities, driving alone and car/vanpool shares increased by 0.95 percentage points and 1.08 percentage points, respectively.
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paper_title: Factors associated with proportions and miles of bicycling for transportation and recreation in six small US cities

paper_content:

The majority of bicycling in the US is for recreation rather than transportation purposes but few studies have examined the question of bicycling purpose. We use data from an online survey conducted in 2006 in six small cities in the western US to examine factors affecting bicycling for transportation compared to bicycling for recreation. The results indicate that individual, social-environment, and physical-environment factors have important influences on the balance between transportation and recreational bicycling and on miles of bicycling for each purpose. Bicycling comfort and an aversion to driving are associated with more transportation bicycling. A culture of utilitarian bicycling and short distances to destinations are also key factors for transportation bicycling. Bicycle infrastructure appears to play an indirect role through its effect on perceived bicycling safety and through the self-selection effect, by attracting bicycling-inclined people to bicycling-supportive communities.
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paper_title: Toward a Systematic Approach to the Design and Evaluation of Automated Mobility-on-Demand Systems: A Case Study in Singapore

paper_content:

The objective of this work is to provide analytical guidelines and financial justification for the design of shared-vehicle mobility-on-demand systems. Specifically, we consider the fundamental issue of determining the appropriate number of vehicles to field in the fleet, and estimate the financial benefits of several models of car sharing. As a case study, we consider replacing all modes of personal transportation in a city such as Singapore with a fleet of shared automated vehicles, able to drive themselves, e.g., to move to a customer’s location. Using actual transportation data, our analysis suggests a shared-vehicle mobility solution can meet the personal mobility needs of the entire population with a fleet whose size is approximately 1/3 of the total number of passenger vehicles currently in operation.
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paper_title: Effects of a Cooperative Variable Speed Limit System on Traffic Performance and Exhaust Emissions

paper_content:

Variable Speed Limit Systems (VSLS) where variable message signs show speed limits based on traffic or road conditions exist on motorways in many countries. The purpose of the VSLS is to decrease the number of accidents while increasing efficiency of traffic system. Cooperative systems are a type of intelligent transport system that has received increasing interest lately. The central part of a cooperative system is communication between vehicles and/or vehicles and the infrastructure. In this paper, a cooperative systems extension of a VSLS is proposed and evaluated by means of microscopic traffic simulation. In the proposed cooperative VSLS, communication between the vehicles and the infrastructure is made available via a roadside unit communicating the speed limits to vehicles upstream on the road. Both aggregate and micro-scale emission models are used to estimate emission from vehicle states in traffic flow. The results of the study show that the cooperative VSLS has a potential to contribute to flow harmonization and to reduce environmental impacts. The emission estimates in the study are dependent on the emission models being applied.
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paper_title: Intersection Management via Vehicle Connectivity: The Intersection Cooperative Adaptive Cruise Control System Concept

paper_content:

Since the introduction of the vehicle infrastructure integration (VII) and connected vehicle (CV) initiatives in the United States, numerous in-vehicle technologies based on wireless communications are currently being deployed. One of these technologies is cooperative adaptive cruise control (CACC) systems, which provide better connectivity, safety, and mobility by allowing vehicles to travel in denser platoons through vehicle-to-vehicle (V2V) communication. Accordingly, the research presented in this article develops a simulation/optimization tool that optimizes the movement of CACC-equipped vehicles as a replacement for traditional intersection control. This system, which is named iCACC, assumes that the intersection controller receives vehicle requests to travel through an intersection and advises each vehicle on the optimum course of action ensuring no crashes occur while at the same time minimizing the intersection delay. Four intersection control scenarios are compared, namely: a traffic signal, an ...
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paper_title: Rolling horizon control framework for driver assistance systems. Part I: Mathematical formulation and non-cooperative systems

paper_content:

In this contribution, we put forward a novel rolling horizon control framework for driver assistance systems. Under this framework, accelerations of equipped vehicles are controlled to optimise a cost function reflecting different control objectives, taking into account the predicted behaviour of other vehicles. A new numerical solution based on Pontryagin's Principle is proposed to solve the optimal control problem. The control framework is generic such that a large variety of objective functions can be optimised and it allows us to control not only one vehicle but a platoon of heterogeneous vehicles as well. The linear constant time gap algorithm widely used for Adaptive Cruise Control (ACC) systems can be derived under the framework. The framework is applied to derive algorithm for a non-linear model predictive ACC controller. Simulation results for several representative scenarios demonstrate the desired performance of the proposed ACC controller and the sensitivity of control parameters on controller characteristics. The resultant flow capacity is largely determined by the desired time gap setting. To show the flexibility of the framework, it is also applied to controller design for Ecological ACC (EcoACC) systems, where the controlled vehicle minimises fuel consumption in addition to the objectives of the ACC systems. Compared to ACC systems, EcoACC systems lead to smoother following behaviour and a 18 % reduction of consumed fuels in the accelerating phase of the simulation. Part II of this research is devoted to controller design of cooperative driving systems, where controlled vehicles communicate and collaborate with each other.
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paper_title: Intelligent Hybrid Electric Vehicle ACC With Coordinated Control of Tracking Ability, Fuel Economy, and Ride Comfort

paper_content:

Adaptive cruise control (ACC) of hybrid electric vehicles (HEVs) has been traditionally developed without an efficient integration with active safety and energy management systems of hybrid powertrains, mainly for facilitating its implementation. This, however, leads to a compromise in the fuel economy of HEVs, since the predictive driving information provided by ACC is not exploited by the energy management system. In order to enhance the energy efficiency and control system integration, a novel ACC system for intelligent HEVs (i-HEV ACC) is developed in this study. The controller is proposed within the framework of nonlinear model predictive control, and a position-based nonlinear longitudinal intervehicle dynamics model is developed. A coordinated optimal control problem for both the tracking safety and the fuel consumption is formulated subject to the constraints on stable tracking. A multistep offline dynamic programming optimization and an online lookup table are used to implement the real-time control algorithm. Experiments are further conducted, which demonstrate that the proposed i-HEV ACC achieves enhanced performance and cooperation in traffic safety, fuel efficiency, and ride comfort.
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paper_title: Minimum Fuel Control Strategy in Automated Car-Following Scenarios

paper_content:

Fuel consumption of traditional ground vehicles is significantly affected by how the vehicles are driven. This paper focuses on the servo-loop control design of a Pulse-and-Gliding (PnG) strategy to minimize fuel consumption in automated car following. A switching-based framework is proposed for real-time implementation. The corresponding controller was synthesized for ideal conditions and subsequently enhanced to compensate for practical factors such as powertrain dynamics, speed variations, and plant uncertainties. Simulations in both uniform and naturalistic traffic flows demonstrate that, compared with a linear quadratic (LQ)-based benchmark controller, the PnG controller improves fuel economy up to 20%. The significant fuel saving is achieved while maintaining precise range bounds so that the negative impact on safety/traffic flow is contained. The developed algorithm can potentially be embedded in adaptive cruise control systems to achieve fuel-saving function.
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paper_title: Autonomous taxis could greatly reduce greenhouse-gas emissions of US light-duty vehicles

paper_content:

Autonomous vehicles move passengers without human intervention. Modelling suggests that autonomous taxis could reduce transport emissions by 87–94% per mile in 2030 and save approximately 7 billion barrels of oil.
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paper_title: Model predictive control for adaptive cruise control with multi-objectives: comfort, fuel-economy, safety and car-following

paper_content:

For automated vehicles, comfortable driving will improve passengers’ satisfaction. Reducing fuel consumption brings economic profits for car owners, decreases the impact on the environment and increases energy sustainability. In addition to comfort and fuel-economy, automated vehicles also have the basic requirements of safety and car-following. For this purpose, an adaptive cruise control (ACC) algorithm with multi-objectives is proposed based on a model predictive control (MPC) framework. In the proposed ACC algorithm, safety is guaranteed by constraining the inter-distance within a safe range; the requirements of comfort and car-following are considered to be the performance criteria and some optimal reference trajectories are introduced to increase fuel-economy. The performances of the proposed ACC algorithm are simulated and analyzed in five representative traffic scenarios and multiple experiments. The results show that not only are safety and car-following objectives satisfied, but also driving comfort and fuel-economy are improved significantly.
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paper_title: The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios

paper_content:

Abstract Carsharing programs that operate as short-term vehicle rentals (often for one-way trips before ending the rental) like Car2Go and ZipCar have quickly expanded, with the number of US users doubling every 1–2 years over the past decade. Such programs seek to shift personal transportation choices from an owned asset to a service used on demand. The advent of autonomous or fully self-driving vehicles will address many current carsharing barriers, including users’ travel to access available vehicles. This work describes the design of an agent-based model for shared autonomous vehicle (SAV) operations, the results of many case-study applications using this model, and the estimated environmental benefits of such settings, versus conventional vehicle ownership and use. The model operates by generating trips throughout a grid-based urban area, with each trip assigned an origin, destination and departure time, to mimic realistic travel profiles. A preliminary model run estimates the SAV fleet size required to reasonably service all trips, also using a variety of vehicle relocation strategies that seek to minimize future traveler wait times. Next, the model is run over one-hundred days, with driverless vehicles ferrying travelers from one destination to the next. During each 5-min interval, some unused SAVs relocate, attempting to shorten wait times for next-period travelers. Case studies vary trip generation rates, trip distribution patterns, network congestion levels, service area size, vehicle relocation strategies, and fleet size. Preliminary results indicate that each SAV can replace around eleven conventional vehicles, but adds up to 10% more travel distance than comparable non-SAV trips, resulting in overall beneficial emissions impacts, once fleet-efficiency changes and embodied versus in-use emissions are assessed.
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paper_title: EVALUATION OF THE ENVIRONMENTAL EFFECTS OF INTELLIGENT CRUISE CONTROL (ICC) VEHICLES

paper_content:

Intelligent Cruise Control (ICC) vehicles are already commercially available in Japan and should be ready for the North American market by next year. Though ICC controllers are local and string stable however, it is not clear how these vehicles perform environmentally. In this paper we show that ICC vehicles can accurately track a lead vehicle and attenuate position errors generated by the lead vehicle during smooth transients. Furthermore, the smooth response of ICC vehicles designed for human factor considerations filters out traffic disturbances caused by rapid acceleration transients. Such ICC vehicle properties have beneficial air pollution and fuel consumption effects that are significant when the manual vehicles perform aggressive rapid acceleration maneuvers. These results are obtained using Pipes human driver vehicle following model which models the slinky type effects observed in today's manual driving. In this paper the response of the Pipes model is compared with that of human drivers. It is observed that Pipes model gives a smooth approximation of human driver response during the presence of transients. We have demonstrated using simulations that the fuel consumption and pollution levels present in manual traffic can be reduced during rapid acceleration transients by 28.5% and 1.5%-60.6% respectively due to the presence of 10% semi- automated vehicles
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paper_title: Leveraging Connected Vehicle Technology and Telematics to Enhance Vehicle Fuel Efficiency in the Vicinity of Signalized Intersections

paper_content:

Driving on highways and arterial roadways involves vehicle acceleration, braking, cruising, coasting, and idling episodes. As the vehicle speed deviates from its “fuel optimum speed,” additional fuel is consumed, thus reducing the vehicle fuel efficiency. The research presented in this article develops a connected vehicle application entitled Eco-Cooperative Adaptive Cruise Control (ECACC) that uses infrastructure-to-vehicle (I2V) communication to receive signal phasing and timing (SPaT) data, predict future constraints on a vehicle's trajectory, and optimize its trajectory to minimize the vehicle's fuel consumption level. The trajectory optimization is made using a moving horizon dynamic programming (DP) approach. A modified A-star algorithm is developed to enhance the computational efficiency of the DP for use in real-time implementations. The model is calibrated and tested on 30 top-sold vehicles in the United States and is demonstrated to provide fuel savings within the vicinity of signalized intersec...
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paper_title: Fuel economy improvements for urban driving: Hybrid vs. intelligent vehicles

paper_content:

The quest for more fuel-efficient vehicles is being driven by the increasing price of oil. Hybrid electric powertrains have established a presence in the marketplace primarily based on the promise of fuel savings through the use of an electric motor in place of the internal combustion engine during different stages of driving. However, these fuel savings associated with hybrid vehicle operation come at the tradeoff of a significantly increased initial vehicle cost due to the increased complexity of the powertrain. On the other hand, telematics-enabled vehicles may use a relatively cheap sensor network to develop information about the traffic environment in which they are operating, and subsequently adjust their drive cycle to improve fuel economy based on this information – thereby representing ‘intelligent’ use of existing powertrain technology to reduce fuel consumption. In this paper, hybrid and intelligent technologies using different amounts of traffic flow information are compared in terms of fuel economy over common urban drive cycles. In order to develop a fair comparison between the technologies, an optimal (for urban driving) hybrid vehicle that matches the performance characteristics of the baseline intelligent vehicle is used. The fuel economy of the optimal hybrid is found to have an average of 20% improvement relative to the baseline vehicle across three different urban drive cycles. Feedforward information about traffic flow supplied by telematics capability is then used to develop alternative driving cycles firstly under the assumption there are no constraints on the intelligent vehicle’s path, and then taking into account in the presence of ‘un-intelligent’ vehicles on the road. It is observed that with telematic capability, the fuel economy improvements equal that achievable with a hybrid configuration with as little as 7 s traffic look-ahead capability, and can be as great as 33% improvement relative to the un-intelligent baseline drivetrain. As a final investigation, the two technologies are combined and the potential for using feedforward information from a sensor network with a hybrid drivetrain is discussed. � 2006 Elsevier Ltd. All rights reserved.
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paper_title: Rolling horizon control framework for driver assistance systems. Part II: Cooperative sensing and cooperative control

paper_content:

This contribution furthers the control framework for driver assistance systems in Part I to cooperative systems, where equipped vehicles can exchange relevant information via vehicle-to-vehicle communication to improve the awareness of the ambient situation (cooperative sensing) and to manoeuvre together under a common goal (cooperative control). To operationalize the cooperative sensing strategy, the framework is applied to the development of a multi-anticipative controller, where an equipped vehicle uses information from its direct predecessor to predict the behaviour of its pre-predecessor. To operationalize the cooperative control strategy, we design cooperative controllers for sequential equipped vehicles in a platoon, where they collaborate to optimise a joint objective. The cooperative control strategy is not restricted to cooperation between equipped vehicles. When followed by a human-driven vehicle, equipped vehicles can still exhibit cooperative behaviour by predicting the behaviour of the human-driven follower, even if the prediction is not perfect. The performance of the proposed controllers are assessed by simulating a platoon of 11 vehicles with reference to the non-cooperative controller proposed in Part I. Evaluations show that the multi-anticipative controller generates smoother behaviour in accelerating phase. By a careful choice of the running cost specification, cooperative controllers lead to smoother decelerating behaviour and more responsive and agile accelerating behaviour compared to the non-cooperative controller. The dynamic characteristics of the proposed controllers provide new insights into the potential impact of cooperative systems on traffic flow operations, particularly at the congestion head and tail.
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paper_title: Predictive Cruise Control: Utilizing Upcoming Traffic Signal Information for Improving Fuel Economy and Reducing Trip Time

paper_content:

This brief proposes the use of upcoming traffic signal information within the vehicle's adaptive cruise control system to reduce idle time at stop lights and fuel consumption. To achieve this goal an optimization-based control algorithm is formulated that uses short range radar and traffic signal information predictively to schedule an optimum velocity trajectory for the vehicle. The control objectives are: timely arrival at green light with minimal use of braking, maintaining safe distance between vehicles, and cruising at or near set speed. Three example simulation case studies are presented to demonstrate the potential impact on fuel economy, emission levels, and trip time.
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paper_title: An Analysis of Possible Energy Impacts of Automated Vehicles

paper_content:

Automated vehicles (AVs) are increasingly recognized as having the potential to decrease carbon dioxide emissions and petroleum consumption through mechanisms such as improved efficiency, better routing, and lower traffic congestion, and by enabling advanced technologies. However, AVs also have the potential to increase fuel consumption through effects such as longer distances traveled, increased use of transportation by underserved groups, and increased travel speeds. Here we collect available estimates for many potential effects and use a modified Kaya Identity approach to estimate the overall range of possible effects. Depending on the specific effects that come to pass, widespread AV deployment can lead to dramatic fuel savings, but has the potential for unintended consequences.
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paper_title: Variable speed limit: A microscopic analysis in a connected vehicle environment

paper_content:

Abstract This paper presents a Variable Speed Limit (VSL) control algorithm for simultaneously maximizing the mobility, safety and environmental benefit in a Connected Vehicle environment. Development of Connected Vehicle (CV)/Autonomous Vehicle (AV) technology has the potential to provide essential data at the microscopic level to provide a better understanding of real-time driver behavior. This paper investigated a VSL control algorithm using a microscopic approach by focusing on individual driver’s behavior (e.g., acceleration and deceleration) through the use of Model Predictive Control (MPC) approach. A multi-objective optimization function was formulated with the aim of finding a balanced trade-off among mobility, safety and sustainability. A microscopic traffic flow prediction model was used to calculate Total Travel Time (TTT); a surrogate safety measure Time To Collision (TTC) was used to measure instantaneous safety; and, a microscopic fuel consumption model (VT-Micro) was used to measure the environmental impact. Real-time driver’s compliance to the posted speed limit was used to adjust the optimal speed limit values. A sensitivity analysis was conducted to compare the performance of the developed approach for different weights in the objective function and for two different percentages of CV. The results showed that with 100% penetration rate, the developed VSL approach outperformed the uncontrolled scenario consistently, resulting in up to 20% of total travel time reductions, 6–11% of safety improvements and 5–16% reduction in fuel consumptions. Our findings revealed that the scenario which optimized for safety alone, resulted in more optimum improvements as compared to the multi-criteria optimization. Thus, one can argue that in case of 100% penetration rates of CVs, optimizing for safety alone is enough to achieve simultaneous and optimum improvements in all measures. However, mixed results were obtained in case of lower % penetration rate which showed higher collision risk when optimizing for only mobility or fuel consumption. This indicates that with such % penetration rate, multi-criteria optimization is crucial to realize optimum and balanced benefits for the examined measures.
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paper_title: A fuel economy optimization system with applications in vehicles with human drivers and autonomous vehicles

paper_content:

Abstract Motor vehicle powered by regular gasoline is one of major sources of pollutants for local and global environment. The current study developed and validated a new fuel-economy optimization system (FEOS), which receives input from vehicle variables and environment variables (e.g., headway spacing) as input, mathematically computes the optimal acceleration/deceleration value with Lagrange multipliers method, and sends the optimal values to drivers via a human-machine interface (HMI) or automatic control systems of autonomous vehicles. FEOS can be used in both free-flow and car-following traffic conditions. An experimental study was conducted to evaluate FEOS. It was found that without sacrificing driver safety, drivers with the aid of FEOS consumed significant less fuel than those without FEOS in all acceleration conditions (22–31% overall gas saving) and the majority of deceleration conditions (12–26% overall gas saving). Compared to relative expensive vehicle engineering system design and improvement, FEOS provides a feasible way to minimize fuel consumptions considering human factors. Applications of the optimal model in the design of both HMI for vehicles with human drivers and autonomous vehicles were discussed.
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paper_title: ACCESSIBILITY EVALUATION OF LAND-USE AND TRANSPORT STRATEGIES: REVIEW AND RESEARCH DIRECTIONS

paper_content:

Abstract A review of accessibility measures is presented for assessing the usability of these measures in evaluations of land-use and transport strategies and developments. Accessibility measures are reviewed using a broad range of relevant criteria, including theoretical basis, interpretability and communicability, and data requirements of the measures. Accessibility impacts of land-use and transport strategies are often evaluated using accessibility measures, which researchers and policy makers can easily operationalise and interpret, such as travelling speed, but which generally do not satisfy theoretical criteria. More complex and disaggregated accessibility measures, however, increase complexity and the effort for calculations and the difficulty of interpretation. The current practice can be much improved by operationalising more advanced location-based and utility-based accessibility measures that are still relatively easy to interpret for researchers and policy makers, and can be computed with state-of-the-practice data and/or land-use and transport models. Research directions towards theoretically more advanced accessibility measures point towards the inclusion of individual's spatial–temporal constraints and feedback mechanisms between accessibility, land-use and travel behaviour. Furthermore, there is a need for theoretical and empirical research on relationships between accessibility, option values and non-user benefits, and the measurement of different components of accessibility.
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paper_title: Lane-keeping assistance control algorithm using differential braking to prevent unintended lane departures

paper_content:

Abstract This paper describes a hierarchical lane keeping assistance control algorithm for a vehicle. The proposed control strategy consists of a supervisor, an upper-level controller and a lower-level controller. The supervisor determines whether lane departure is intended or not, and whether the proposed algorithm is activated or not. To detect driver′s lane change intention, the steering behavior index has been developed incorporating vehicle speed and road curvature. To validate the detection performance on the lane change intention, full-scale simulator tests on a virtual test track (VTT) are conducted under various driving situations. The upper-level controller is designed to compute the desired yaw rate for the lane departure prevention, and for the guidance with ride comfort. The lower-level controller is designed to compute the desired yaw moment in order to track the desired yaw rate, and to distribute it into each tire′s braking force in order to track the desired yaw moment. The control allocation method is adopted to distribute braking forces under the actuator’s control input limitation. The proposed lane keeping assistance control algorithm is evaluated with human driver model-in-the-loop simulation and experiments on a real vehicle.
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paper_title: Real-Time Motion Planning With Applications to Autonomous Urban Driving

paper_content:

This paper describes a real-time motion planning algorithm, based on the rapidly-exploring random tree (RRT) approach, applicable to autonomous vehicles operating in an urban environment. Extensions to the standard RRT are predominantly motivated by: 1) the need to generate dynamically feasible plans in real-time; 2) safety requirements; 3) the constraints dictated by the uncertain operating (urban) environment. The primary novelty is in the use of closed-loop prediction in the framework of RRT. The proposed algorithm was at the core of the planning and control software for Team MIT's entry for the 2007 DARPA Urban Challenge, where the vehicle demonstrated the ability to complete a 60 mile simulated military supply mission, while safely interacting with other autonomous and human driven vehicles.
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paper_title: Semi-automated versus highly automated driving in critical situations caused by automation failures

paper_content:

The purpose of this study was to examine the effects of vehicle automation and automation failures on driving performance. Previous studies have revealed problems with driving performance in situations with automation failures and attributed this to drivers being out-of-the-loop. It was therefore hypothesized that driving performance is safer with lower than with higher levels of automation. Furthermore, it was hypothesized that driving performance would be affected by the extent of the automation failure. A moving base driving simulator was used. The design contained semi-automated and highly automated driving combined with complete, severe, and moderate deceleration failures. In total the study involved 36 participants. The results indicate that driving performance degrades when the level of automation increases. Furthermore, it is indicated that car drivers are worse at handling complete than partial deceleration failures.
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paper_title: Security vulnerabilities of connected vehicle streams and their impact on cooperative driving

paper_content:

Autonomous vehicles capable of navigating unpredictable real-world environments with little human feedback are a reality today. Such systems rely heavily on onboard sensors such as cameras, radar/LIDAR, and GPS as well as capabilities such as 3G/4G connectivity and V2V/V2I communication to make real-time maneuvering decisions. Autonomous vehicle control imposes very strict requirements on the security of the communication channels used by the vehicle to exchange information as well as the control logic that performs complex driving tasks such as adapting vehicle velocity or changing lanes. This study presents a first look at the effects of security attacks on the communication channel as well as sensor tampering of a connected vehicle stream equipped to achieve CACC. Our simulation results show that an insider attack can cause significant instability in the CACC vehicle stream. We also illustrate how different countermeasures, such as downgrading to ACC mode, could potentially be used to improve the security and safety of the connected vehicle streams.
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paper_title: Autonomous vehicle collision avoidance system using path planning and model-predictive-control-based active front steering and wheel torque control

paper_content:

Autonomous vehicles have attracted more attention in recent years as vehicle applications are evolving to a more intelligent and autonomous stage. This paper presents the development of a collision avoidance system for an autonomous vehicle application which consists of a motion planner and model-predictive-control-based active vehicle steering and active wheel torque control. A motion planner, based on polynomial parameterization, determines a collision-free trajectory when a vehicle collision with obstacles is likely to happen. Then an MPC-based control system controls the front steering and individual wheel torques to track the desired collision-free reference trajectory. The proposed system is evaluated through simulation, using an eight-degrees-of-freedom vehicle model with a ‘magic formula’ tire model, active front steering, and active wheel torque distribution systems. The simulation results show that it effectively performs collision avoidance maneuvers.
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paper_title: Active collision avoidance system for steering control of autonomous vehicles

paper_content:

The study proposes an active collision avoidance system to allow safe lane-changing manoeuvres by self-steering vehicles in the presence of the uncertainties associated with nearby vehicles and the surrounding environment. This system integrates estimation of conflict probability, model predictive control and dedicated short-range communications (DSRC) techniques to ensure a collision-free operation. To accomplish this, the proposed system uses model predictive control to predict the future positions of vehicles and estimates the conflict probability so as to reduce the risk of collision. The system also exploits DSRC techniques to facilitate the gathering of information from nearby vehicles so that potential conflicts can be detected at an earlier stage. Autonomous vehicles can thus make adjustments based on the acquired data to avoid collisions in a real communication environment. The effectiveness of the method has been verified under experimental conditions. The influences of key parameters in the control method are examined.
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paper_title: Safety and Capacity Analysis of Automated and Manual Highway Systems

paper_content:

This paper compares safety of automated and manual highway systems with respect to resulting rear-end collision frequency and severity. Safety is related to driver, vehicle and highway operating characteristics. Our safety analysis method maps the variation in these operating characteristics, modeled by probability distributions, to the probability and severity of the first rear-end crash due to a hard braking disturbance on the highway. The results show that automated driving is safer than the most alert manual drivers, at similar speeds and capacities. We also present a detailed safety-capacity trade-off study for four different automated highway system concepts that differ in their information structure and separation policy. This study quantifies the impact of inter-vehicle cooperation and operating speed of the Automated Highway System (AHS). It also compares and contrasts the safety characteristics of individual vehicle and platoon based Automated Highway Systems.
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paper_title: Situation assessment and decision making for lane change assistance using ensemble learning methods

paper_content:

Lane change assistance system was developed using ensemble learning methods.Proposed system has potential to prevent lane change crashes and thus reducing injuries and fatalities.Random forest and AdaBoost outperformed Bayes/Decision tree classifier.Higher classification accuracy and lower false positive rates achieved.Accuracies of 99.1% and 98.7% were achieved for lane keeping. Lane change maneuvers contribute to a significant number of road traffic accidents. Advanced driver assistance systems (ADAS) that can assess a traffic situation and warn drivers of unsafe lane changes can offer additional safety and convenience. In addition, ADAS can be extended for use in automatic lane changing in driverless vehicles. This paper investigated two ensemble learning methods, random forest, and AdaBoost, for developing a lane change assistance system. The focus on increasing the accuracy of safety critical lane change events has a significant impact on lowering the occurrence of crashes. This is the first study to explore ensemble learning methods for modeling lane changes using a comprehensive set of variables. Detailed vehicle trajectory data from the Next Generation Simulation (NGSIM) dataset in the US were used for model development and testing. The results showed that both ensemble learning methods produced higher classification accuracy and lower false positive rates than the Bayes/Decision tree classifier used in the literature. The impact of misclassification of lane changing events was also studied. A sensitivity analysis performed by varying the accuracy of lane changing showed that the lane keeping accuracy can be increased to as high as 99.1% for the AdaBoost system and 98.7% for the random forest system. The corresponding true positive rates were 96.3% and 94.6%. High accuracy of lane keeping and high true positive rates are desirable due to their safety implications.
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paper_title: Back to the future: Brake reaction times for manual and automated vehicles

paper_content:

Rear-end collisions are often quoted as being a major cause of road traffic accidents. In response to this, a great deal of ergonomics research effort has been directed towards the analysis of brake reaction times. However, the engineering solution has been to develop advanced systems for longitudinal control, which, it is argued, will mitigate the problem of rear-end collisions. So far, though, there have been few empirical studies to determine how brake reaction times will be affected by such vehicle automation. This paper presents a literature review summarizing the current state of knowledge about driver responses in non-automated vehicles. The review covers driver factors, vehicle factors and situational factors. Following the review, some empirical data are presented from a driving simulator experiment assessing brake reaction times of skilled and unskilled drivers under two different levels of automation. When compared to previous data gathered during manual driving, there seems to be a striking increase in reaction times for these automated conditions. Implications for the design and safety of automated vehicle systems are discussed.
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paper_title: A Safe Longitudinal Control for Adaptive Cruise Control and Stop-and-Go Scenarios

paper_content:

In this paper, we propose a novel reference model-based control approach for automotive longitudinal control. The reference model is nonlinear and provides dynamic solutions consistent with safety constraints and comfort specifications. The model is based on physical laws of compliant contact and has the particularity that its solutions can be explicitly described by integral curves. This allows to characterize the set of initial condition for which the constraints can be met. This model is combined with a simple feedback loop used to compensate unmodeled dynamics and external disturbances. Model simulations together with experimental results are also presented
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paper_title: Autonomous collision avoidance system by combined control of steering and braking using geometrically optimised vehicular trajectory

paper_content:

This study proposes an autonomous obstacle avoidance system not only by braking but also by steering, as one of the active safety technologies to prevent traffic accidents. The proposed system prevents the vehicle from colliding with a moving obstacle like a pedestrian jumping out from the roadside. In the proposed system, to avoid the predicted colliding position based on constant-velocity obstacle motion assumption, the avoidance trajectory is derived as connected two identical arcs. The system then controls the vehicle autonomously by the combined control of the braking and steering systems. In this paper, the proposed system is examined by real car experiments and its effectiveness is shown from the results of the experiments.
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paper_title: Game theoretic approach for predictive lane-changing and car-following control

paper_content:

This contribution puts forward a receding horizon control approach for automated driving systems, where tactical-level lane change decisions and control-level accelerations are jointly evaluated under a central mathematical framework. The key idea is that controlled vehicles predictively determine discrete desired lane sequences and continuous accelerations to minimise a cost function reflecting undesirable future situations. The interactions between controlled vehicles and surrounding vehicles are captured in the cost function. The approach is flexible in terms of application to controller design for both non-cooperative control systems where controlled vehicles only optimise their own cost and cooperative control systems where controlled vehicles coordinate their decisions to optimise the collective cost. To determine the controller behaviour, the problem is formulated as a differential game where controlled vehicles make decisions based on the expected behaviour of other vehicles. The control decisions are updated at regular frequency, using the newest information regarding the state of controlled vehicles and surrounding vehicles available. A problem decomposition technique is employed to reduce the dimensionality of the original problem by introducing a finite number of sub-problems and an iterative algorithm based on Pontryagin’s Principle is used to solve sub-problems efficiently. The proposed controller performance is demonstrated via numerical examples. The results show that the proposed approach can produce efficient lane-changing manoeuvres while obeying safety and comfort requirements. Particularly, the approach generates optimal lane change decisions in the predicted future, including strategic overtaking, cooperative merging and selecting a safe gap.
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paper_title: ITS Solutions and Accident Risks: Prospective and Limitations

paper_content:

This article investigates the prospective and limitations in the application of potential intelligent transport system (ITS) functions to reduce accident risks, using a cause‐treatment relationship. The main causes of road accidents are described and appropriate ITS solutions (including advanced driver assistance systems and advanced traveller information systems) are presented as countermeasures. Anticipated impacts are discussed and indicate that several ITS have the potential of improving road safety and addressing specific accident causes. However, attention is required on particular aspects of their implementation as they may trigger adverse effects by imposing behavioural adaptation risks, and overestimation and over‐reliance on system capabilities. Further, user acceptability and strategic implementation issues are paramount to the successful introduction of these systems.
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paper_title: A Multiagent Approach to Autonomous Intersection Management

paper_content:

Artificial intelligence research is ushering in a new era of sophisticated, mass-market transportation technology. While computers can already fly a passenger jet better than a trained human pilot, people are still faced with the dangerous yet tedious task of driving automobiles. Intelligent Transportation Systems (ITS) is the field that focuses on integrating information technology with vehicles and transportation infrastructure to make transportation safer, cheaper, and more efficient. Recent advances in ITS point to a future in which vehicles themselves handle the vast majority of the driving task. Once autonomous vehicles become popular, autonomous interactions amongst multiple vehicles will be possible. Current methods of vehicle coordination, which are all designed to work with human drivers, will be outdated. The bottleneck for roadway efficiency will no longer be the drivers, but rather the mechanism by which those drivers' actions are coordinated. While open-road driving is a well-studied and more-or-less-solved problem, urban traffic scenarios, especially intersections, are much more challenging. ::: ::: We believe current methods for controlling traffic, specifically at intersections, will not be able to take advantage of the increased sensitivity and precision of autonomous vehicles as compared to human drivers. In this article, we suggest an alternative mechanism for coordinating the movement of autonomous vehicles through intersections. Drivers and intersections in this mechanism are treated as autonomous agents in a multiagent system. In this multiagent system, intersections use a new reservation-based approach built around a detailed communication protocol, which we also present. We demonstrate in simulation that our new mechanism has the potential to significantly outperform current intersection control technology--traffic lights and stop signs. Because our mechanism can emulate a traffic light or stop sign, it subsumes the most popular current methods of intersection control. This article also presents two extensions to the mechanism. The first extension allows the system to control human-driven vehicles in addition to autonomous vehicles. The second gives priority to emergency vehicles without significant cost to civilian vehicles. The mechanism, including both extensions, is implemented and tested in simulation, and we present experimental results that strongly attest to the efficacy of this approach.
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paper_title: Variable speed limit: A microscopic analysis in a connected vehicle environment

paper_content:

Abstract This paper presents a Variable Speed Limit (VSL) control algorithm for simultaneously maximizing the mobility, safety and environmental benefit in a Connected Vehicle environment. Development of Connected Vehicle (CV)/Autonomous Vehicle (AV) technology has the potential to provide essential data at the microscopic level to provide a better understanding of real-time driver behavior. This paper investigated a VSL control algorithm using a microscopic approach by focusing on individual driver’s behavior (e.g., acceleration and deceleration) through the use of Model Predictive Control (MPC) approach. A multi-objective optimization function was formulated with the aim of finding a balanced trade-off among mobility, safety and sustainability. A microscopic traffic flow prediction model was used to calculate Total Travel Time (TTT); a surrogate safety measure Time To Collision (TTC) was used to measure instantaneous safety; and, a microscopic fuel consumption model (VT-Micro) was used to measure the environmental impact. Real-time driver’s compliance to the posted speed limit was used to adjust the optimal speed limit values. A sensitivity analysis was conducted to compare the performance of the developed approach for different weights in the objective function and for two different percentages of CV. The results showed that with 100% penetration rate, the developed VSL approach outperformed the uncontrolled scenario consistently, resulting in up to 20% of total travel time reductions, 6–11% of safety improvements and 5–16% reduction in fuel consumptions. Our findings revealed that the scenario which optimized for safety alone, resulted in more optimum improvements as compared to the multi-criteria optimization. Thus, one can argue that in case of 100% penetration rates of CVs, optimizing for safety alone is enough to achieve simultaneous and optimum improvements in all measures. However, mixed results were obtained in case of lower % penetration rate which showed higher collision risk when optimizing for only mobility or fuel consumption. This indicates that with such % penetration rate, multi-criteria optimization is crucial to realize optimum and balanced benefits for the examined measures.
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paper_title: Potential Cyberattacks on Automated Vehicles

paper_content:

Vehicle automation has been one of the fundamental applications within the field of intelligent transportation systems (ITS) since the start of ITS research in the mid-1980s. For most of this time, it has been generally viewed as a futuristic concept that is not close to being ready for deployment. However, recent development of “self-driving” cars and the announcement by car manufacturers of their deployment by 2020 show that this is becoming a reality. The ITS industry has already been focusing much of its attention on the concepts of “connected vehicles” (United States) or “cooperative ITS” (Europe). These concepts are based on communication of data among vehicles (V2V) and/or between vehicles and the infrastructure (V2I/I2V) to provide the information needed to implement ITS applications. The separate threads of automated vehicles and cooperative ITS have not yet been thoroughly woven together, but this will be a necessary step in the near future because the cooperative exchange of data will provide vital inputs to improve the performance and safety of the automation systems. Thus, it is important to start thinking about the cybersecurity implications of cooperative automated vehicle systems. In this paper, we investigate the potential cyberattacks specific to automated vehicles, with their special needs and vulnerabilities. We analyze the threats on autonomous automated vehicles and cooperative automated vehicles. This analysis shows the need for considerably more redundancy than many have been expecting. We also raise awareness to generate discussion about these threats at this early stage in the development of vehicle automation systems.
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paper_title: Driving next to automated vehicle platoons: How do short time headways influence non-platoon drivers’ longitudinal control?

paper_content:

Abstract Advanced driver assistance systems (ADAS) are taking over an increasing part of the driving task and are supporting the introduction of semi- and fully automated vehicles. As a consequence, a mixed traffic situation is developing where vehicles equipped with automated systems taking over the lateral and longitudinal control of the vehicle will interact with unequipped vehicles (UV) that are not fitted with such automated systems. Different forms of automation are emerging and it appears that regardless of which form is going to become popular on our roads, there is a consensus developing that it will be accompanied by a reduction in time headway (THW). The present simulator study examined whether a ‘contagion’ effect from the short THW held in platoons on the UV drivers would occur. Thirty participants were asked to follow a lead vehicle (LV) on a simulated motorway in three different traffic conditions: surrounding traffic including (1) platoons with short following distance (THW = 0.3 s), (2) large following distance (THW = 1.4 s) or (3) no platoons at all. Participants adapted their driving behaviour by displaying a significant shorter average and minimum THW while driving next to a platoon holding short THWs as when THW was large. They also spent more time keeping a THW below a safety threshold of 1 s. There was no carryover effect from one platoon condition to the other, which can be interpreted as an effect that is not lasting in time. The results of this study point out the importance of examining possibly negative behavioural effects of mixed traffic on UV drivers.
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paper_title: Behavioural adaptation to driving with an adaptive cruise control (ACC)

paper_content:

Abstract The present paper describes a study that aims at assessment of driver behaviour in response to new technology, particularly Adaptive Cruise Control Systems (ACCs), as a function of driving style. In this study possible benefits and drawbacks of Adaptive Cruise Control Systems (ACCs) were assessed by having participants drive in a simulator. The four groups of participants taking part differed on reported driving styles concerning Speed (driving fast) and Focus (the ability to ignore distractions), and drove in ways which were consistent with these opinions. The results show behavioural adaptation with an ACC in terms of higher speed, smaller minimum time headway and larger brake force. Driving style group made little difference to these behavioural adaptations. Most drivers evaluated the ACC system very positively, but the undesirable behavioural adaptations observed should encourage caution about the potential safety of such systems.
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paper_title: Behavioural adaptation to adaptive cruise control (ACC): implications for preventive strategies

paper_content:

This test-track study assessed whether adaptive cruise control (ACC) induces behavioural adaptation in drivers. Eighteen experienced drivers drove a test vehicle while following a lead vehicle in three counterbalanced conditions: No ACC (self-maintained average headway of 2 s), ACC-Short (headway of 1.4 s) and ACC-Long (headway of 2.4 s). Results demonstrate that ACC can induce behavioural adaptation in drivers in potentially safety-critical ways. Compared to driving unsupported, participants located significantly more items per minute on a secondary task when using ACC, while their response times to a hazard detection task increased. This effect was particularly pronounced in those scoring high on a sensation-seeking scale. Using ACC resulted in significantly more lane position variability, an effect that was also more pronounced in high sensation-seekers. Drivers' trust in ACC increased significantly after using the system, and these ratings did not change despite a simulated failure of the ACC system during the ACC-Long condition. Response time to the simulated ACC failure was related to a driver's locus of control: Externals intervened more slowly than Internals. All drivers reported relying on the ACC system to keep their vehicle at a safe distance from the lead vehicle. Results are consistent with similar research conducted on lane departure warning systems. Driver awareness training is a potential preventive strategy that could minimize the behavioural adaptation associated with novel in-vehicle systems such as ACC.
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paper_title: The influence of cruise control and adaptive cruise control on driving behaviour--a driving simulator study.

paper_content:

Although Cruise Control (CC) is available for most cars, no studies have been found which examine how this automation system influences driving behaviour. However, a relatively large number of studies have examined Adaptive Cruise Control (ACC) which compared to CC includes also a distance control. Besides positive effects with regard to a better compliance to speed limits, there are also indications of smaller distances to lead vehicles and slower responses in situations that require immediate braking. Similar effects can be expected for CC as this system takes over longitudinal control as well. To test this hypothesis, a simulator study was conducted at the German Aerospace Center (DLR). Twenty-two participants drove different routes (highway and motorway) under three different conditions (assisted by ACC, CC and manual driving without any system). Different driving scenarios were examined including a secondary task condition. On the one hand, both systems lead to lower maximum velocities and less speed limit violations. There was no indication that drivers shift more of their attention towards secondary tasks when driving with CC or ACC. However, there were delayed driver reactions in critical situations, e.g., in a narrow curve or a fog bank. These results give rise to some caution regarding the safety effects of these systems, especially if in the future their range of functionality (e.g., ACC Stop-and-Go) is further increased.
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paper_title: Velocity-Based Driver Intent Inference at Urban Intersections in the Presence of Preceding Vehicles

paper_content:

Predicting turn and stop maneuvers of potentially errant drivers is a basic requirement for advanced driver assistance systems for urban intersections. Previous work has shown that an early estimate of the driver's intent can be inferred by evaluating the vehicle's speed during the intersection approach. In the presence of a preceding vehicle, however, the velocity profile might be dictated by car-following behavior rather than by the need to slow down before doing a left or right turn. To infer the driver's intent under such circumstances, a simple, real-time capable approach using a parametric model to represent both car-following and turning behavior is proposed. The performance of two alternative parameterizations based on observations at an individual intersection and a generic curvature-based model is evaluated in combination with two different Bayes net classification algorithms. In addition, the driver model is shown to be capable of predicting the future trajectory of the vehicle.
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paper_title: Health benefits of cycling: a systematic review

paper_content:

The purpose of this study was to update the evidence on the health benefits of cycling. A systematic review of the literature resulted in 16 cycling-specific studies. Cross-sectional and longitudinal studies showed a clear positive relationship between cycling and cardiorespiratory fitness in youths. Prospective observational studies demonstrated a strong inverse relationship between commuter cycling and all-cause mortality, cancer mortality, and cancer morbidity among middle-aged to elderly subjects. Intervention studies among working-age adults indicated consistent improvements in cardiovascular fitness and some improvements in cardiovascular risk factors due to commuting cycling. Six studies showed a consistent positive dose–response gradient between the amount of cycling and the health benefits. Systematic assessment of the quality of the studies showed most of them to be of moderate to high quality. According to standard criteria used primarily for the assessment of clinical studies, the strength of this evidence was strong for fitness benefits, moderate for benefits in cardiovascular risk factors, and inconclusive for all-cause mortality, coronary heart disease morbidity and mortality, cancer risk, and overweight and obesity. While more intervention research is needed to build a solid knowledge base of the health benefits of cycling, the existing evidence reinforces the current efforts to promote cycling as an important contributor for better population health.
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paper_title: Cycling to work in 90 large American cities: new evidence on the role of bike paths and lanes

paper_content:

This article analyzes the variation in bike commuting in large American cities, with a focus on assessing the influence of bike paths and lanes, which have been the main approach to increasing cycling in the USA. To examine the role of cycling facilities, we used a newly assembled dataset on the length of bike lanes and paths in 2008 collected directly from 90 of the 100 largest U.S. cities. Pearson’s correlation, bivariate quartile analysis, and two different types of regressions were used to measure the relationship between cycling levels and bikeways, as well as other explanatory and control variables. Ordinary Least Squares and Binary Logit Proportions regressions confirm that cities with a greater supply of bike paths and lanes have significantly higher bike commute rates—even when controlling for land use, climate, socioeconomic factors, gasoline prices, public transport supply, and cycling safety. Standard tests indicate that the models are a good fit, with R 2 ranging between 0.60 and 0.65. Computed coefficients have the expected signs for all variables in the various regression models, but not all are statistically significant. Estimated elasticities indicate that both off-street paths and on-street lanes have a similar positive association with bike commute rates in U.S. cities. Our results are consistent with previous research on the importance of separate cycling facilities and provide additional information about the potentially different role of paths vs. lanes. Our analysis also revealed that cities with safer cycling, lower auto ownership, more students, less sprawl, and higher gasoline prices had more cycling to work. By comparison, annual precipitation, the number of cold and hot days, and public transport supply were not statistically significant predictors of bike commuting in large cities.
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paper_title: Walking and Cycling to Health: A Comparative Analysis of City, State, and International Data

paper_content:

OBJECTIVES ::: We sought to determine the magnitude, direction, and statistical significance of the relationship between active travel and rates of physical activity, obesity, and diabetes. ::: ::: ::: METHODS ::: We examined aggregate cross-sectional health and travel data for 14 countries, all 50 US states, and 47 of the 50 largest US cities through graphical, correlation, and bivariate regression analysis on the country, state, and city levels. ::: ::: ::: RESULTS ::: At all 3 geographic levels, we found statistically significant negative relationships between active travel and self-reported obesity. At the state and city levels, we found statistically significant positive relationships between active travel and physical activity and statistically significant negative relationships between active travel and diabetes. ::: ::: ::: CONCLUSIONS ::: Together with many other studies, our analysis provides evidence of the population-level health benefits of active travel. Policies on transport, land-use, and urban development should be designed to encourage walking and cycling for daily travel.
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paper_title: The relationship between traffic congestion, driver stress and direct versus indirect coping behaviours

paper_content:

Drivers experiencing rush hour congestion were interviewed using cellular telephones to study stress and coping responses. Measures were taken of each driver's predisposition to stress (trait stress) as well as their reactions to the experience of either low or high traffic congestion (state stress). Two interviews were conducted during the trip when drivers experienced both low and high congestion conditions. Although state stress was greatest for all drivers experiencing the high congestion condition, a trait X situation interaction was obtained, indicating that stress levels were highest for high trait stress drivers experiencing the congested roadway. In terms of trait coping behaviours, participants indicated a preference for direct over indirect behaviours. A greater variety of direct and indirect behaviours were reported in high congestion. Reports of aggressive behaviours showed the greatest increase from low to high congestion. Comments on the use of cellular telephones in methodology are offered.
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paper_title: Threats from car traffic to the quality of urban life : problems, causes, and solutions

paper_content:

Introduction Part 1: Threats to the Quality of Urban Life from Car Traffic Part 2: Determinants of Private Car Use Part 3: Policy Measures Aimed at Reducing Private Car Use Concluding chapter
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Title: Policy and society related implications of automated driving: A review of literature and directions for future research

Section 1: First--order implications of automated driving
Description 1: In this section, write about the immediate impacts of automated driving on travel cost, road capacity, and travel choices.

Section 2: Travel cost Assumptions
Description 2: Discuss the potential implications on both the fixed cost of owning an automated vehicle and the generalized transport cost.

Section 3: Road capacity Assumptions
Description 3: Describe how automated vehicles could influence free flow capacity, vehicle distribution, traffic flow stability, and congestion.

Section 4: Travel choices Assumptions
Description 4: Explore the implications of automated driving on vehicle travel demand, destination choices, mode shifts, and the use of public transport.

Section 5: Second--order implications of automated driving
Description 5: Analyze the impacts of automated driving on vehicle ownership and sharing, location choices, land use, and transport infrastructure.

Section 6: Vehicle ownership and sharing Assumptions
Description 6: Examine how automated vehicles could facilitate the development of ride-sharing and vehicle-sharing services, reducing the need for car ownership.

Section 7: Location choices and land use Assumptions
Description 7: Discuss the potential impacts of automated vehicles at both regional and local scales on accessibility, urban sprawl, and land use patterns.

Section 8: Transport infrastructure Assumptions
Description 8: Evaluate how automated vehicles could influence future needs for road and parking infrastructures and public transport services.

Section 9: Third--order implications of automated driving
Description 9: Investigate the wider societal impacts of automated driving on energy consumption, air pollution, safety, social equity, the economy, and public health.

Section 10: Energy consumption and air pollution Assumptions
Description 10: Assess how automated vehicles might result in energy and emission benefits and the possible mitigation of these benefits by increased long-term travel demand.

Section 11: Safety Assumptions
Description 11: Explore the potential safety benefits of automated vehicles, factors influencing these benefits, and the risk of cyber attacks.

Section 12: Social equity Assumptions
Description 12: Analyze the potential positive and negative implications of automated vehicles for different vulnerable social groups.

Section 13: Economy Assumptions
Description 13: Discuss the economic benefits, restructuring effects, and possible job losses induced by the introduction of automated vehicles.

Section 14: Public health Assumptions
Description 14: Evaluate the potential public health benefits and negative impacts of automated vehicles, focusing on congestion, emissions, and physical activity levels.

Section 15: Conclusions
Description 15: Summarize the explored effects and the general conclusions drawn from the literature review. Also, include suggestions for future research on the implications of automated driving.

Section 16: Directions for future research
Description 16: Highlight various research areas that remain unexplored and discuss the methodological challenges for the exploration of the implications of automated vehicles.