Planning Strategies for Lane Reversals in Transportation Networks
Abstract
This paper studies strategies to optimize the lane configuration of a transportation network for a given set of Origin-Destination demands using a planning macroscopic network flow model. The lane reversal problem is, in general, NP-hard since the optimization is made over integer variables. To overcome this burden, we reformulate the problem using a piecewise affine approximation of the travel latency function which allows us to exploit the total unimodularity property of Integer Linear Programming (ILP). Consequently, we transform the ILP problem to a linear program by relaxing the integer variables. In addition, our method is capable of solving the problem for a desired number of lane reversals which serves to perform cost-benefit analysis. We perform a case study using the transportation network of Eastern Massachusetts (EMA) and we test our method against the original lane configuration and a projected lower bound solution. Our empirical results quantify the travel time savings for different levels of demand intensity. We observe reduction in travel times up to 40% for certain links in the network.
Keywords
Cite
@article{arxiv.2107.06937,
title = {Planning Strategies for Lane Reversals in Transportation Networks},
author = {Salomon Wollenstein-Betech and Ioannis Ch. Paschalidis and Christos G. Cassandras},
journal= {arXiv preprint arXiv:2107.06937},
year = {2021}
}
Comments
Proc. IEEE Int. Conf. on Intelligent Transportation Systems, Indianapolis, USA, 2021. (In Press)