Dynamic Mixed Behavior Traffic Network Equilibrium Based on Genetic Algorithm Approach (ID: 8-120)

摘要

A new simulation algorithm based on Genetic algorithm idea is proposed for solving the differential game model in discrete time in this paper. The dynamic mixed behavior traffic network equilibrium model is formulated as a noncooperative N-person nonzero-sum differential game under the open-loop information structure. A simple network is considered where one origin-destination pair is connected by parallel arcs and two types of players-User Equilibrium and Coumot-Nash-interact through the congestion phenomenon. Genetic algorithm does not require continuous and differential of objective function and the suitability of the model are substantially improved. The numerical example is referred to Wie, and the values of some of the parameters are modified, and this make the result fit the traffic reality, which can improve the model practicality a lot. Furthermore, results from the test road network have shown that the values of the performance index were significantly improved.