Improving traffic network performance with road banning strategy: A simulation approach comparing user equilibrium and system optimum

Abstract

The purpose of this study is to compare network loadings related to different network equilibria by a simulation-based framework. The direct comparison of path flows or trajectory patterns is hard to achieve so here we propose a more aggregate approach based on the comparison of demand level breakpoints. A breakpoint is a demand threshold value that leads to significant changes in path flow loading. More specifically, we set in this paper a demand breakpoint when the list of effective route alternatives differs by at least one path. This is for example the case when one route is no longer considered for one equilibrium while being used by some vehicles in the second one. We are going to investigate both static and dynamic network loading while scanning all demand levels to identify the breakpoints. We focus on discrete demand formulation and choices and use a trip-based traffic simulator.This study analyzes the breakpoints for the solution of three popular equilibrium conditions: User equilibrium (UE), System optimum (SO) and Boundary Rational User Equilibrium (BRUE). First, we investigate breakpoints on a well-known network (Braess) in the static case in order to better define this concept. Second, breakpoints are investigated on a real network (Lyon, France) where dynamic travel times are provided by a microscopic traffic simulator. When the breakpoints are obtained for a given scenario, we focus on identifying demand ranges where some paths are not used in SO while being travelled in UE or BRUE. Following the concept of Braess paradox, this permits to design banning strategies at some key locations in the network to prevent some alternatives from being used and thus to improve the system performance. We show by simulation that such a strategy is effective, which demonstrates the importance of breakpoint identification.