Novel Approaches for Road Congestion Mitigation.

摘要

Transportation planning process mainly involves the solution of two important problems, namely, the traffic assignment problem, which minimizes the total travel delay among all travelers, and the toll pricing problem which settles, based on data derived from the first problem, the tolls that would collectively benefit all travelers and would lead to a user equilibrium solution at the same time. These are challenging computational problems for large scale transportation networks. In this research, we proposed an approach to solve the two problems jointly, making use of a Hybrid Genetic Algorithm (HGA) for the optimization of transportation network performance by strategically allocating tolls on some of the links. Since a regular transportation network may have thousands of intersections and hundreds of roads, the proposed algorithm took advantage of a series of mechanisms for speeding up shortest path algorithms. In this project, we have adapted the evolutionary algorithm from Buriol et al. (2005) and Ericsson et al. (2002) to a transportation problem that deals with multicommodity flow and toll pricing. We have also formulated the equivalent nonlinear programming problem.