Asymmetrically distributed traveler-perceived errors in the travel time disutility function for stochastic user-equilibrium traffic assignment.

详细信息   

• 作者：Li ; Min-Tang.
• 学历：Doctor
• 年：1999
• 导师：Long, Gary
• 毕业院校：University of Florida
• 专业：Engineering, Civil.;Transportation.;Operations Research.
• ISBN：9780599654846
• CBH：9956440
• Country：USA
• 语种：English
• FileSize：1015928
• Pages：153

文摘

Most of the current approaches for applying a stochastic user equilibrium (SUE) traffic assignment model have been based on iterative applications of the Dial multi-path assignment algorithm. The errors of perceived travel times by motorists in the route choice model are assumed to be symmetrically Gumbel-distributed. Yet observations suggest the errors are asymmetrical. This study describes an alternative for solving the SUE optimization problem by treating errors of perception as being asymmetrically-distributed for competitive paths that are enumerated. Paths are generated by a modified shortest-path algorithm which imposes a penalty to the links along an associated shortest path. The competitive paths are then simulated to obtain expected travel time variations, due to different perceptions by motorists, which allows more refined travel time estimation. The path-based variations of travel time are implemented in a random disutility model for route choice. The assumptions of this approach are more reasonable than those of the other popular methodologies and can be integrated into the Florida Standard Urban Transportation Model Structure (FSUTMS) with minor modification to the existing structure. The model was applied and tested with a network from a typical urban transportation study and found to converge on assigned volumes that provided better agreement with traffic counts than the results from a standard user-equilibrium assignment. Although it provided both a better conceptual foundation and more accurate numerical results, the model is currently not yet cost-effective for real-world applications due to exorbitant computer running times.