Dynamic traffic assignment based trailblazing guide signing for major traffic generator.

Details

• Creators:
  Qiao, Fengxiang ; Zeng, Yan ; Yu, Lei
• Corporate Creators:
  Texas Southern University. Center for Transportation Training and Research
• Subject/TRT Terms:
  • Route choice
  • Traffic control
  • Communication systems
  • Highway traffic control
  • Mathematical methods
  • Route choice--Texas--Houston--Mathematical models
  • Highway communications--Texas--Houston--Mathematical models
  • Electronic traffic controls--Mathematical models
• Publication/ Report Number:
  SWUTC/09/476660-00046-1
• Resource Type:
  Tech Report
• Geographical Coverage:
  Texas
• Corporate Publisher:
  Southwest Region University Transportation Center (U.S.)
• Abstract:
  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).
  More +
• Format:
  PDF
• Funding:
  DTRT07-G-0006
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/17813/dot_17813_DS1.pdf
• File Type:
  [PDF - 832.58 KB]
• Collection(s):
  University Transportation Centers ; US Transportation Collection
• Main Document Checksum:
  urn:sha256:5c2ce48d7c20888cebe3c4c5a2a11d4395c42a18a013cb967d6a38b25b007682