Title :
Dynamic lane reversal in traffic management
Author :
Hausknecht, Matthew ; Au, Tsz-Chiu ; Stone, Peter ; Fajardo, David ; Waller, Travis
Author_Institution :
Dept. of Comput. Sci., Univ. of Texas at Austin, Austin, TX, USA
Abstract :
Contraflow lane reversal - the reversal of lanes in order to temporarily increase the capacity of congested roads - can effectively mitigate traffic congestion during rush hour and emergency evacuation. However, contraflow lane reversal deployed in several cities are designed for specific traffic patterns at specific hours, and do not adapt to fluctuations in actual traffic. Motivated by recent advances in autonomous vehicle technology, we propose a framework for dynamic lane reversal in which the lane directionality is updated quickly and automatically in response to instantaneous traffic conditions recorded by traffic sensors. We analyze the conditions under which dynamic lane reversal is effective and propose an integer linear programming formulation and a bi-level programming formulation to compute the optimal lane reversal configuration that maximizes the traffic flow. In our experiments, active contraflow increases network efficiency by 72%.
Keywords :
integer programming; linear programming; road traffic; road vehicles; active contraflow; autonomous vehicle technology; bilevel programming formulation; congested roads capacity; contraflow lane reversal; dynamic lane reversal; emergency evacuation; integer linear programming formulation; lane directionality; network efficiency; optimal lane reversal configuration; rush hour; traffic conditions; traffic congestion; traffic flow; traffic management; traffic patterns; traffic sensors; Hardware; Mathematical model; Roads; Throughput; Vectors; Vehicle dynamics; Vehicles;
Conference_Titel :
Intelligent Transportation Systems (ITSC), 2011 14th International IEEE Conference on
Conference_Location :
Washington, DC
Print_ISBN :
978-1-4577-2198-4
DOI :
10.1109/ITSC.2011.6082932