Practical Modelling of Trip Rescheduling under Congested Conditions

There is plenty of anecdotal evidence that drivers may make small changes in their time of travel to take advantage of lower levels of congestion. However, progress in modelling such “micro” re-scheduling within peak period traffic remains slow. While there exist research papers describing theoretical solutions, there are no techniques available for practical use. Most commonly used assignment programs are temporally aggregate, while packages which do allow some “dynamic assignment” typically assume a fixed demand profile. The aim of the paper is to present a more heuristic method which could at least be used on an interim basis. The assumption is that the demand profile can be demanded into a number of mutually exclusive “windows” in relation to the “preferred arrival time”, while on the assignment side, independently defined sequential “timeslices” are used in order to respect some of the dynamic processes relating to the build-up of queues. The demand process, whereby some drivers shift away from their preferred window, leads to an iterative procedure with the aim of achieving reasonable convergence. Using the well-known scheduling theory developed by Vickrey, Small, and Arnott, de Palma & Lindsey, the basic approach can be described, extending from the simple “bottleneck”, to which the theory was originally applied, to a general network. So far, insufficient research funds have been made available to test the approach properly. It is hoped that by bringing the ideas into the public domain, further research into this area may be stimulated.