N. Huynh

ADAPTIVE SPEED ESTIMATION USING TRANSFER FUNCTION MODELS FOR REAL-TIME DYNAMIC TRAFFIC ASSIGNMENT OPERATION

The application of a transfer function model (TFM) in a real-time dynamic traffic assignment system is investigated. The motivation is to improve the speed estimation method to enable better system consistency with reality in real-time operation. The study is conducted by adopting a TFM derived from actual detector data in San Antonio, Texas. This model is then used in the traffic simulation module of the DYNASMART-X dynamic traffic assignment system to update the network link speeds. A nonlinear least-squares optimization algorithm, implemented for this study, is coupled with DYNASMART-X to enable adaptive estimation of the TFM parameters. Simulation-based experiments are carried out on the Fort Worth test network. These experiments are designed to evaluate the TFM performance and to gain insight into its operational properties under different conditions. The results show that the TFM, both adaptive and nonadaptive, can consistently approximate the true underlying speed-density dynamics. Of significant importance is the transfer-ability and robustness of TFMs in different settings. The outcome of this research substantiates the premise that good speed estimation can be achieved through the use of TFMs.

TRAVELER RESPONSES TO ADVANCED TRAVELER INFORMATION SYSTEMS FOR SHOPPING TRIPS: INTERACTIVE SURVEY APPROACH

This survey research describes an experiment that addresses travel decisions of trip makers for noncommuting trips. The survey considers recreational shopping trips for which trip makers can choose both destination and desired arrival time. An interactive stated preference instrument, the survey was designed and implemented for access and administration via the Internet. It was easily accessible and completely self-administered; participants could run the survey without the help of a project staff member. Data were also gathered automatically. Survey respondents were asked to make two shopping trips. They were provided with pretrip and en route traffic information for trips to shopping malls by predetermined routes. Respondents were asked their preferences concerning information items, factors affecting their mall choice, demographics, and familiarity with their residence and the shopping malls. The recruitment method by e-mail and the requirement to have Internet access led to a slightly biased sample—young males, many with higher education, were overrepresented in the sample. Results showed that respondents choose their shopping mall based on characteristics of the mall but that trip makers divert from their route when provided with delay information during their trip. It was found that about 25 percent of respondents even change their destination. Of the respondents who did not change their destination, nearly half chose to divert from their current route, whereas the other half stayed on the current route. Despite its current sample bias, the interactive Internet survey has proven to be a successful tool for gathering data on travel decisions. It is inexpensive, easy to administer, and provides reliable responses.