The Impact of Real-Time and Predictive Traffic Information on Travelers’ Behavior on the I-4 Corridor
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2003-07-01
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Abstract:Real time and predicted traffic information plays a key role in the successful implementation of advanced traveler information systems (ATIS) and advance traffic management systems (ATMS). Traffic information is essentially valuable to both transportation systems users and providers. In addition to monitoring the operational performance of traffic on freeway facilities, real time information is now communicated to the traveling public by the concerned agencies in order to keep the public informed of the latest conditions and to provide opportunities for better travel decisions. Although real time advisory information on traffic conditions is currently widely available to the public via the Internet and other media sources, such information is of less use at the pre-trip planning stage since traffic conditions are dynamically changing over time. This created the need and the motivation to synthesize predictive information as well. Such predictive information can be effectively used to provide the public with the expected traffic conditions within short-term horizons during which their trip planning stage or en-route via onboard wireless communication devices. Decisions that are likely to be impacted by predictive information include departure time, travel mode, route selection, and possible trip destination. This study presents the full scale implementation of a short-term traffic prediction model that was developed by the University of Central Florida's Transportation Systems Institute (UCF-TSI) to assist I-4 travelers with trip-making decisions along the 40-mile I-4 corridor in Orlando, Florida. This report presents the results of two pilot surveys of the impact of traffic information on travelers' behavior in the I-4 corridor. One pilot survey was conducted via telephone and the other was conducted using the Internet. 3 Appendices, 2 tables, 19 figures, 117 p.
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