The Impact of Memory on Travelers' Behaviour and the Evolution of Transportation System

Abstract

This paper presents three types of learning behaviors with complete information, partial information and no information respectively, and thus models travelers’ route choice for investigating the impact of memory on the evolution of transportation system. Simulation results on a three-parallel-route network show that it is uncertain whether the information released by advanced traveler information systems (ATIS) can make the flow pattern evolve to a logit stochastic user equilibrium, which depends on the length of memory. If memory length is larger than a threshold value, the provided information drives the flow pattern to a stochastic user equilibrium state; otherwise, the logit stochastic user equilibrium is unattainable and the system evolution can not converge to a stable state. Furthermore, it is also shown that the fluctuation of traffic flow under full information exceeds that under partial information on the same route, when the length of memory remains unchanged.