No abstract

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Système d'Information Routière Intelligible aux Usagers (SIRIUS) is the largest urban field operational test of the advanced traveler information and automated traffic management system in Europe. With variable-message signs, SIRIUS has been in operation in the Paris region for 3 years. A preliminary investigation of the effectiveness of the SIRIUS system in traffic management is presented. The extent to which drivers respond to real-time traffic information and the consequential changes in link flow under SIRIUS is also presented. Time-series traffic data were analyzed to measure changes in mean flow rates at a selected link. It was found that variable-message signs influence drivers to choose less congested routes when drivers are provided with real-time traffic information, and that a driver's decision to divert is closely associated with the information pertaining to the level of congestion. In the Paris region, drivers received information on the length of the queue at the time of this study. As congestion becomes heavier, drivers are more likely to respond to variable-message signs. According to the data analysis, a queue length of 3 km seems to be a threshold at which a significant number of drivers choose to use an alternative route.

Improved information received from public and private advanced traveler information systems can help travelers make more informed decisions, shorten times spent in traffic congestion, and reduce anxiety and stress. The behavioral responses of automobile and transit commuters as well as those of noncommuters to travel information received from radio, television, and telephone are analyzed. The influence of information has seldom been studied in terms of these different users. The data were collected through a computer-aided telephone interview conducted in the San Francisco Bay Area ( n = 947). The study analyzes the impacts of socioeconomic, context, and information variables on individuals’ decisions to adjust travel before beginning their trips; given an adjustment, the frequency of trip changes; and the type of most recent trip changes in terms of route, departure time, or mode shifts. The statistical analysis involves estimation of probit models with and without sample selectivity and a multinomial logit model. The results of the study indicate that a sample selectivity model is more appropriate for understanding respondents’ frequency of trip changes only when members of a subset of the sample population change their trips. Travel time uncertainty and travel information received from the electronic media increase the pretrip adjustment propensity. Furthermore, information from the most widely available and accessed medium, the radio, is highly likely to result in behavioral adjustments. Noncommuters have a high receptivity to canceling their trips in response to travel information. This has important implications for congestion relief in transportation networks.

ABSTRACT-Intelligent Transportation Systems present a well-known innovation opportunity to address urban congestion and allow greater access to transportation networks. New sources of travel information are emerging rapidly and they are likely to significantly impact traveler decisions and transportation network performance. To assess the value and impact of these new sources, this paper develops a comprehensive conceptual model based on information processing and traveler response. Specifically, the model accounts for the effect of information source, content and quality on information access and travel behavior. The paper presents empirical evidence from several behavioral surveys conducted in the San Francisco Bay Area between 1995-1999. The surveys used innovative methods to study the response of the whole population, response of people more inclined to use information technology (early adopters), and traveler decision-making in high-benefit incident situations. The conceptual model helps us integrate and interpret empirical findings from the surveys. We discuss the issues of access to new and conventional technologies and services, their current market penetration levels, switching behavior regarding new information sources/information service providers, desired information content and willingness to pay for dynamic information. The opportunities and limitations of new technologies and the implications for future technology implementations are discussed. 3 INTRODUCTIONContinuing transportation problems such as congestion and pollution and recent developments in advanced traveler information systems (ATIS) raise interesting questions about the effect these innovations will have on travelers. In particular, we wish to know if the new technologies will help people plan for their travel and allow them to travel faster and at lower cost.There are two sets of developments that can offer partial answers to such questions. One is the development of models that characterize how people make their travel decisions and use dynamic travel information. The other is the growing body of empirical evidence regarding traveler decisions and the impacts of new and improved information systems acquired through federally sponsored field operational tests.One such test is TravInfo, which is a regional traveler information system in the San Francisco Bay Area. Its goal is to broadly disseminate accurate, comprehensive, timely, and reliable information about traffic and multi-modal travel options to the public. The TravInfo Field Test officially began operation in September 1996 and ended in September 1998, when it started a transitional phase to full deployment as an integral part of the Bay Area transportation infrastructure (1). To evaluate TravInfo effectiveness, significant resources were devoted to designing surveys and to collecting behavioral data. The surveys were based on a contemporary understanding of traveler behavior and the factors that might influence it, including dynamic information. In the several years over whic...