Modelling the Impact of ATIS on Travellers? Behaviour: Puget Sound Region Case Study

Modelling the Impact of ATIS on Travellers? Behaviour: Puget Sound Region Case Study


A Polydoropoulou, A Tsirimpa, University of the Aegean, GR; C Antoniou, Massachusetts Institute of Technology, US



The continuous growth of road traffic increased the delays that road users face and negatively affects the overall transportation system performance. Advanced Traveler Information Systems (ATIS) may offer significant benefits, in terms of improving the travel experience of individuals, but their impact on individuals? travel behavior and on the whole transportation system mainly depends on how travelers respond to the traffic information acquired.

This paper presents a case study for the Puget Sound Region (PSRC), where the Regional Council has been running the longest continuous survey in the United States, regarding travel behavior (since 1989). From 2000, a supplement was added to the travel diaries, where individuals were asked about the traveler information sources consulted on each trip and how the information was used. Traveler information sources, available in the region, encompasses both conventional forms of information, such as radio traffic reports and advanced traveler information systems, such as variable message signs (VMS) and web sites. These data are used to examine the rate of ATIS adoption and the impact of information acquisition on travel behavior.

Specifically the case study:

1. Presents a review of the ?State of the Art? of modeling ATIS awareness, usage and impact on travelers? behaviour;
2. Develops a methodological framework that incorporates the effect of Advanced Traveler Information Systems (ATIS) on the daily activity patterns of individuals. This new methodological framework, combines the extended framework that Ben-Akiva and Bowman developed (1996) and the framework that Polydoropoulou proposed for pre-trip and en-route information acquisition (1997);
3. Estimates mixed logit models that predict the effect of ATIS acquisition on trip related decisions (such as, mode choice, route choice, departure time, etc.) and specifically take into account travelers? attitudes and perceptions, (such as, perceptions of ATIS and new technologies usage, risk averse or risk prone etc. ); and
4. Presents a sensitivity analysis on travel responses based on the penetration rates of ATIS

Keywords: Advanced Traveler Information Systems (ATIS), Methodological Framework, Travellers Attitudes and Perceptions, Mixed Logit Models


1. Ben-Akiva Moshe and John L. Bowman (1996). Activity-based disaggregate travel demand model system with activity schedules.
2. Polydoropoulou A. (1997). Modeling User Response to ATIS. Phd. Thesis in Transportation Systems and Decision Sciences, Massachusetts Institute of Technology.


Association for European Transport