United States Department of Transportation
i
Dynamic traffic assignment based trailblazing guide signing for major traffic generator.
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2009-11-01
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[PDF-832.58 KB]
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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).
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