Modelling heterogeneous drivers' responses to route guidance and parking information systems in stochastic and time-dependent networks

Advanced Traveller Information Systems (ATIS) are generally expected to be efficient in reducing travel time and parking search time uncertainties. This article presents a mixed-behaviour multi-class equilibrium model for investigating heterogeneous drivers' responses to route guidance and parking information systems in stochastic and time-dependent networks. The proposed model simultaneously considers the drivers' choices of departure time, route and parking location under network uncertainty. All drivers are differentiated by their values of time and values of reliability, and each class of them is further divided into two groups, equipped and unequipped with ATIS, respectively. Suppose that the equipped drivers can predict travel disutility more accurately than the unequipped ones due to the information services provided by ATIS. The model is formulated as a fixed-point problem and is solved by a heuristic solution algorithm via a combination of the Monte Carlo simulation approach and the method of successive averages. The effectiveness of the modelling framework is illustrated by a numerical example and some new insights about the complex travel and parking behaviour under ATIS are obtained.