Capacity Optimization of an Isolated Intersection under the Phase Swap Sorting Strategy

27 Pages Posted: 14 May 2013 Last revised: 1 Nov 2014

See all articles by Chiwei Yan

Chiwei Yan

Uber Technologies, Inc.; University of Washington

Hai Jiang

Tsinghua University - Department of Industrial Engineering

Siyang Xie

Tsinghua University - Department of Civil Engineering

Date Written: May 17, 2013

Abstract

It is well recognized that the left turn reduces the intersection capacity significantly, because some of the traffic lanes cannot be used to discharge vehicles during its green phases. In this paper, we operationalize the phase swap sorting strategy (Xuan, 2011) to use most, if not all, traffic lanes to discharge vehicles at the intersection cross section to increase its capacity. We explicitly take into consideration all through, left- and right-turning movements on all arms and formulate the capacity maximization problem as a Binary-Mixed-Integer-Linear-Programming (BMILP) model. The model is efficiently solved by standard branch-and-bound algorithms and outputs optimal signal timings, lane allocations, and other decisions. Numerical experiments show that substantially higher reserve capacity can be obtained under our approach.

Keywords: signal control, signal timing, sorting strategy, pre-signal, capacity optimization

JEL Classification: L92, R41

Suggested Citation

Yan, Chiwei and Jiang, Hai and Xie, Siyang, Capacity Optimization of an Isolated Intersection under the Phase Swap Sorting Strategy (May 17, 2013). Available at SSRN: https://ssrn.com/abstract=2261809 or http://dx.doi.org/10.2139/ssrn.2261809

Chiwei Yan

Uber Technologies, Inc. ( email )

San Francisco, CA 94158
United States

HOME PAGE: http://web.mit.edu/chiwei/www

University of Washington ( email )

Seattle, WA 98195
United States

Hai Jiang (Contact Author)

Tsinghua University - Department of Industrial Engineering ( email )

Beijing, 100084
China

Siyang Xie

Tsinghua University - Department of Civil Engineering ( email )

Haidian District
Beijing, 100084
China

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