Day-to-Day Evolution of Network Flows Under Route-Choice Dynamics in Commuter Decisions

Abstract

The day-to-day dynamics of commuter decisions on urban traffic networks induced by route-choice dynamics is investigated. More specifically, this investigation analyzes the stability and reliability of system performance due to route-choice dynamics under real-time information, relaxing key restrictions associated with user equilibrium models. A simulation-based framework is developed to analyze day-to-day dynamics by integrating an empirically calibrated model of route-choice decisions with a dynamic network assignment model. Computational experiments are used to investigate the effect of certain experimental factors—recurrent network congestion level, market penetration, nature of information, and frequency of information updates—on network performance stability and reliability. The findings provide evidence of considerable day-to-day variations and stochasticity in network flows and performance, even when departure-time decisions and the origin-destination matrix are assumed to be fixed. The results indicate that (a) network performance may deviate significantly from equilibrium because of route-choice decisions under information; (b) within-day route choices have a significant effect on day-to-day network flow evolution; (c) user equilibrium path flows may not be reached or may not be stable when uncoordinated route-choice decisions are made under real-time information; (d) route-choice decisions do not exhibit convergence to an equilibrium, although the switching rate may be near steady-state conditions; (e) advanced traveler information systems (ATIS) information strategies can affect both within-day and day-to-day dynamics; and (f) some information strategies can lead to improved reliability and stability but at the expense of longer trip times. The results indicate that the trade-off between trip time performance and stability must be considered in network analysis and design. These results have important implications for the design of traffic control strategies, more-effective ATIS implementation guidelines, and incident management strategies.