A systolic parallel simulation system for dynamic traffic assignment: SPSS-DTA

摘要

This paper presents a new approach to solve dynamic traffic assignment problems. The approach employs a mixed method of real-time simulation and off-line optimization. The fundamental approach to the simulation is systolic parallel processing based on autonomous agent modeling. Agents continuously act on their own initiatives and access to database to get the status of the simulation world. In particular, existing models and algorithms were incorporated in designing the behavior of relevant agents such as car-following and headway distribution. Simulation is based on predetermined routes between centroids that are computed off-line by a conventional optimal path-finding algorithm such as the Frank-Wolf algorithm. Iterating the cycles of optimization and simulation, the proposed system will provide a practical and valuable traffic assignment. Gangnam-Gu district in Seoul, Korea is selected as the target area for the modeling. It is expected that real-time traffic assignment services can be provided on the Internet soon.