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Travel Behavior

Two different survey types has been done by the Transit Lab team to study the effects of providing real-time bus arrival infromation to passengers. The main motivating for these studies was the fact that real-time bus arrival information—for example, delivered to prospective passengers waiting at bus stops via variable messages signs (VMSs)—can be useful to transit passengers for a multitude of reasons. Passengers can use their waiting time more productively, select which route they would want to take, or choose to select an alternative mode of transportation. Whatever the prospective passengers’ choices are, providing them with real-time information reduces the uncertainty inherent to transit systems. In general, reducing waiting time uncertainty is expected to improve passenger satisfaction, and ultimately increase bus ridership.

Impact of Real Time Passenger Information

Web-based surveys of the entire campus population (including students, faculty, and staff), have been implemented to elicit information about general travel behavior, transit service use,  effects of passenger information system, and perceptions of Campus Area Bus Services (CABS) as a component of the multi modal transportation system. Responses from over 3,500 students, 2,400 faculty members, and 3,300 staff employees have been collected to date. The results of the web-based survey of the campus community prior to the provision of passenger information system which provides predicted bus arrival times, revealed previously unidentified and in some cases surprising attitudes towards the relation between campus transit bus services and campus safety, green environment, and traffic congestion. After the passenger information system had reached a steady-state, a second survey was implemented. The data was analyzed to quantify the effect of real-time traveler information on service perceptions, and travel choices and attitudes. Higher overall evaluation of CABS was related to users level of appreciation for Reasonableness of CABS routes, travel times, waiting times, and their reliability. In addition, passengers who had used other forms of metropolitan public transportations had a higher overall evaluation of CABS. These types of investigations has attracted attention from transit agencies as they aim to improve the provision of real-time passenger information system or consider investing in such capabilities.

Waiting Time Perceptions

Another study conducted by the Transit Lab team was done to quantify the relationship between perceived and actual waiting times experienced by passengers awaiting the arrival of a bus at a bus stop. Understanding such a relationship would be useful in quantifying the value of providing real‑time information to passengers on the time until the next bus is expected to arrive at a bus stop.

The results of this study indicate that passengers do perceive time to be greater than the actual amount of time waited. However, the hypothesis that the rate of change of perceived time does not vary with respect to the actual waiting time could not be rejected (over a range of 3 to 15 minutes). Assuming that a passenger’s perceived waiting time is equal to the actual time when presented with accurate real-time bus arrival information, the value of the eliminated additional time is assessed in the form of reduced vehicle‑hours per day resulting from a longer headway that produces the same mean passenger waiting time. The eliminated additional time is also assessed in the form of uncertainty in the headway resulting in the same extra waiting time. Naturally, such benefits of passenger information can only be confirmed when the actual effect of information on the perception of waiting time is quantified.

This study demonstrated that because passengers perceive waiting times to be greater than actual waiting times at a bus stop, real‑time passenger information systems could potentially reduce the perceived waiting time for busses when providing accurate information. The reduction in perceived waiting times could potentially be translated into reduced operating costs or increased passenger satisfaction and, ultimately, into increased ridership for public transit, depending on the policies adopted by the transit agency in conjunction with the introduction of real-time passenger information systems. The estimation results with socio-economic variables included are shown in the table.