A platform for research: civil engineering, architecture and urbanism
Practical modelling of trip re-scheduling under congested conditions
AbstractThere is plenty of evidence that drivers may make small changes in their time of travel to take advantage of lower levels of congestion. However, progress in the practical modelling of such “micro” re-scheduling within peak period traffic remains slow. While there exist research papers describing theoretical solutions, techniques for practical use are not generally available. 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 segmented 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.
Practical modelling of trip re-scheduling under congested conditions
AbstractThere is plenty of evidence that drivers may make small changes in their time of travel to take advantage of lower levels of congestion. However, progress in the practical modelling of such “micro” re-scheduling within peak period traffic remains slow. While there exist research papers describing theoretical solutions, techniques for practical use are not generally available. 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 segmented 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.
Practical modelling of trip re-scheduling under congested conditions
Bates, John (author)
Transportation Research Part A: Policy and Practice ; 41 ; 788-801
2006-11-09
14 pages
Article (Journal)
Electronic Resource
English
Practical modelling of trip re-scheduling under congested conditions
Online Contents | 2007
|Car-Following Under Congested Conditions: Empirical Findings
British Library Online Contents | 1998
|Road built under congested conditions in Ohio
Engineering Index Backfile | 1928
|Speed Harmonization: Evaluation of Effectiveness Under Congested Conditions
British Library Online Contents | 2013
|Building under congested conditions in inner-cities Opportunities for prefabrication
British Library Online Contents | 2010
|