Day-to-day dynamic transport network model considering travelers' risky route choice behaviors

Abstract

On stochastic transport network, travelers tend to reserve travel time budget (TTB) for every alternative route, to assure their on-time arrive with a predefined confidence level. This paper incorporates the concept of TTB into a deterministic nonlinear dynamic system, to model the day-to-day evolution process of travelers' risk-taking route choices on stochastic degradable road network. This paper also introduces consistent traffic information prediction, which can be provided by Advanced Traveler Information Systems (ATIS), into the dynamic system to investigate its influence on travelers' route choice behaviors and the corresponding day-to-day network flow evolutions. Illustrative examples are presented to demonstrate that, the consistent predictive traffic information can help to stabilize day-to-day network flow fluctuations, while travelers' extreme risk-averse route choice behaviors, on the other hand, would cause greater network flow fluctuations.