87 Autonomous Cars

By Jason Danker, December 2015.

Overview. Automation in cars is nothing new. Automatic transmissions and cruise control have been around since 1939 and 1958 respectively, but these systems serve to aid, rather than replace, human drivers. What is new is a near future potential for fully autonomous cars, cars that are capable of full operation without an attending human driver.

While other vehicles, such as light rail and monorail trains, have been capable of fully automatic operation since 1967, these vehicles have the luxury of operating in closed environments and only need to be able to respond to a defined set of inputs. Autonomous cars do not have this luxury. In operating “in the wild,” the systems guiding these cars may be forced to respond to any number of unanticipated situations. As the automation system cannot enumerate all possible situations, it must instead rely on continuous organization of its operating environment.

This is clearly a technical challenge, but it also raises ethical and legal issues. As autonomous cars act based on the organization of sensory inputs, the organizing systems are necessarily developed relative to ethical considerations, whether intentional or not. At the most basic level, the organizing system will direct the autonomous car in making decisions analogous to those posited in the trolley problem, a famous thought experiment in ethics that forces a choice between saving five endangered people or taking the life of an innocent person who had not been in danger. Beyond ethics, autonomous cars also raise legal questions: if an autonomous car crashes, who is liable for the damages?

What is being organized? An autonomous car will organize information about the car itself, the objects in its vicinity, and environmental conditions. The car must keep track of its movements, those of other objects, and the relative positions of itself and the other objects. It must organize this information within the environmental framework of lane markings, speed limits, road signs, traffic signals, weather and traffic conditions, and numerous other constraints. As autonomous cars become common, the cars will likely communicate with one another and this information will also need to be brought into the organizing system. The car will also need to organize, and likely prioritize, inputs from human occupants. Regardless of the exact implementation, the organizing system will necessarily limit what is worthy of organization: it is likely not possible, or desirable, to keep track of every insect in the vicinity of the car.

Why is it being organized? The car organizes its surroundings in order to safely navigate to a destination. While this is the primary interaction enabled by the organization, countless other interactions support this primary interaction. The supporting interactions fall into the two categories of prediction and reaction. The systems being developed by Google use the information that has been organized to predict what is most likely to happen next: “It predicts that the cyclist will ride by and the pedestrian will cross the street.” The systems that have been launched by Tesla tend to be more reactionary: “Side Collision Warning further enhances Model S’s active safety capabilities by sensing range and alerting drivers to objects, such as cars, that are too close to the side of Model S.

How much is it being organized? The extent of organization varies based on the implementation. While Google uses on-board sensors and extremely detailed street maps to implement self-driving functionality, Tesla’s Autopilot relies on-board sensors and standard GPS data. While the exact extent of the organization is not publicly available information, Google has publicly stated “the system is engineered to work hardest to avoid vulnerable road users (think pedestrians and cyclists), then other vehicles on the road, and lastly avoid things that don’t move.” Given this, Google’s categories, and their hierarchy, appear to be defined by their vulnerability.

When is it being organized? For information gathered by on-board sensors, organization takes place as objects enter and leave the vicinity of the autonomous car. The organization is ongoing as the car’s surrounding and environment are constantly changing. In addition to the sensor data, autonomous cars also rely on map data which is organized in advance. Google’s cars rely on specialized, highly detailed maps that are being developed as part of the self-driving car project and, as such, are unable to drive on roads that have not yet been mapped to the necessary level of detail. While Tesla’s Autopilot also relies on maps, it uses standard GPS maps and is not similarly restricted.

How or by whom is it being organized? The car’s computational processes are responsible for the organization. That said, the car is restricted to organizing within the organizing system implemented by the manufacturer. While Google and Tesla are two of the main companies in this space, many traditional automotive companies are also developing autonomous systems.

Where is it being organized? Except for map data, the organization takes place within the car’s onboard systems. The organization must take place in the car itself due to the potential catastrophic consequences of a lag in information flow. Additionally, ensuring all organization takes place within the car provides greater security: a self-contained car is less susceptible to attack than a network dependent one.

Other considerations. While it is likely that fully autonomous cars will be technologically feasible within a few years, the cars may still require human interactions for legal reasons. This is clearly seen in Tesla’s press release for Autopilot: “The driver is still responsible for, and ultimately in control of, the car.” This human-in-the-loop design principle creates a legal buffer for autonomous car manufacturers by treating the “driver” as a “liability sponge” or “moral crumple zone.” As articulated by Madeleine Elish and Tim Hwang, “the human in an autonomous system may become simply a component—accidentally or intentionally—that is intended to bear the brunt of the moral and legal penalties when the overall system fails.

While these issues will ultimately play out through a combination of court rulings and policy decisions, it is interesting to note that there is legal precedent that could either blame, or exonerate, the “driver” of an autonomous car. Drawing parallels to aviation automation, precedent suggests that the human “driver” will be held responsible for liability claims arising from the operation of the car. On the other hand, product liability law offers recourse for consumers when a company’s products fail. Many people have argued that this existing legal framework is sufficient to handle the liability issues brought up by autonomous vehicles.

Regardless of the legal complexities that will arise from specific incidents, autonomous cars have great potential to reduce car crashes and improve overall road safety. The promise of the autonomous technology, even for partially autonomous systems, is so great that the National Highway Traffic Safety Administration is proposing updates to its safety ratings that will penalize manufacturers that don’t include autonomous technologies in their vehicles.


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