A Signal Coordination Model for Long Arterials Considering Link Traffic Flow Characteristics

Xiaoyue Wen, Dianhai Wang, Sheng Jin, Guomin Qian () and Yixuan Zhu
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Xiaoyue Wen: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Dianhai Wang: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Sheng Jin: College of Civil Engineering and Architecture, Zhejiang University, Hangzhou 310058, China
Guomin Qian: Enjoyor Technology Co., Ltd., Hangzhou 311422, China
Yixuan Zhu: Enjoyor Technology Co., Ltd., Hangzhou 311422, China

Sustainability, 2023, vol. 15, issue 20, 1-19

Abstract: In order to improve the travel efficiency on a long arterial with massive signals, this paper proposed a mixed integer linear programming model, MaxBandLAM, to simultaneously optimize the arterial partition scheme and signal coordination schemes with the consideration of link traffic flow characteristics. The weighted sum of the two-way green bandwidths on links across the arterial was taken as its objective. The link volume to capacity rations were taken as the weights. The number of sub-zones, the allocation of signals and links, signal cycle, offset and phase sequence, the coordination speed, as well as the two-way green bandwidths of sub-zones and of links are the decision variables. A numerical test was carried out on a virtual arterial with twenty signals. The results indicate the scheme generated by the MaxBandLAM model can provide a more reasonable partition scheme and coordination schemes compared to those generated by Synchro and the models with no traffic flow characteristics of links consideration. For the scenario of dominating the main road through flows, the average delay, average stop number, and average travel speed at intersections for all-turning flows and main road through flows in the MaxBandLAM scheme, all performed well.

Keywords: long arterial; signal coordination; arterial partition; traffic flow characteristics; collaborative optimization (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
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