Markov traffic assignment models are attractive tools for representing the day-to-day evolution of traffic flows over road networks. They are simpler than microscopic ('car-following') simulation models, but incorporate considerable flexibility in the manner in which traveller route choice is related to past experience and pre-trip information. In this paper we describe our own Markov traffic assignment model, and its implementation in a new software package MARTS (Markov Assignment for Road Traffic Systems) that we are developing. The authors illustrate the capabilities of MARTS for analyzing the effects of pre-trip information using an example based on the road network in a region of the UK city of Leicester. Simulation of this system under various scenarios suggests that provision of high quality pre-trip information can have unexpected results if travellers react in a very volatile fashion. (Author/publisher) For the covering entry of this conference, please see ITRD abstract no. E209471.
Abstract