Consensus and optimal speed advisory model for mixed traffic at an isolated signalized intersection
Shaowei Yu,
Rui Fu,
Yingshi Guo,
Qi Xin and
Zhongke Shi
Physica A: Statistical Mechanics and its Applications, 2019, vol. 531, issue C
Abstract:
Due to the accessibility for connected vehicle (CV) to obtain the V2X covered traffic conditions and signal phase and timing (SPaT) information, the CV becomes able to follow its predecessors and adjust its speed in a different way with comparison to human driving vehicle (HDV). Aiming at promoting energy economy and keeping safety, a consensus and optimal speed advisory model(SAM) is proposed for CV platoon at an isolated signalized intersection in the presence of mixed traffic scenario. To ensure that CV followers track their leader’s speed and time headway spacing with uniform performance being achieved, a consensus based CV platoon model is proposed with V2X network topology being taken into account. To determine average desired speed of the leader and prevent itself from red light running, two kinds of intersection passing decisions considering amber light duration time are presented for CV and HDV, respectively. To plan a speed trajectory for CV leader, a safety and energy conservation oriented SAM based on trigonometric-curve and logistic-curve is employed to guide CV leader approaching and departing from signalized intersection in a smooth driving behavior at the moment of queue discharging entirely at green light. Numerical simulations show that taking speed profile governed by consensus and optimal SAM as CV platoon’s recommended speed can improve safety and fuel economy performance of the mixed traffic on signal controlled highways.
Keywords: Speed advisory model; Signal phase and timing; Consensus based platoon control; Mixed traffic; Sigmoid profiles (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (10)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:531:y:2019:i:c:s0378437119310313
DOI: 10.1016/j.physa.2019.121789
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