Dynamic Traffic Assignment Based Trailblazing Guide Signing for Major Traffic Generator
Fengxiang Qiao, Yan Zeng and Lei Yu, Texas Southern University, November 2009, 41 pp. (476660-00046-1)
The placement of guide signs and the display of dynamic massage signs greatly affect drivers’ understanding of the network and therefore their route choices. Most existing dynamic traffic assignment models assume that drivers heading to a Major Traffic Generator (MTG) have sufficient knowledge of roadway networks. In this report, the concept of recognition level is defined to categorize drivers based on their unfamiliarity of the network and of the alternative routes between origins and destinations. Each catalog is assigned a specific utility function that is dependent on travel time, length of route and recognition parameters. Drivers’ route choice behavior is determined by these specific utility functions. A sample network is first employed to test the feasibility of the proposed model, and the result complies with the specified travel patterns. After that, a real network near Downtown Houston is used to further test the proposed model. An experiment is conducted based on the information collected from an on-site survey and the on-line real-time traffic map from Houston TranStar. In order to validate the necessity of the proposed model, a control experiment is carried out with all parameters being set in the same way as the designed experiment except that drivers are assumed to be fully familiar with the network layout and alternative routes. Test results show that the proposed model can fit the real case very well. The developed algorithm and the assessment procedure results are not only awfully imperative in trailblazing guide signing for MTGs, but also indispensable in both the modern Route Guidance System (RGS) and the Advanced Traveler Information System (ATIS), which are important components of the Intelligent Transportation System (ITS).
Keywords: Traveler Information and Guidance, Dynamic Traffic Assignment, Traveler Services Information, Guide Signing, Simulation and Modeling
ENTIRE REPORT (Adobe Acrobat File – 829 KB)