Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles

This manuscript investigated coordinated intersection signal design problem for mixed traffic flow of Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs). Two main macroscopic impact of the mixed flow on signal setting are considered: saturation flow rate and the platoon disper...

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Main Authors: Hongsheng Qi, Rumeng Dai, Qing Tang, Xianbiao Hu
Format: Article
Language:English
Published: IEEE 2020-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8972368/
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author Hongsheng Qi
Rumeng Dai
Qing Tang
Xianbiao Hu
author_facet Hongsheng Qi
Rumeng Dai
Qing Tang
Xianbiao Hu
author_sort Hongsheng Qi
collection DOAJ
description This manuscript investigated coordinated intersection signal design problem for mixed traffic flow of Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs). Two main macroscopic impact of the mixed flow on signal setting are considered: saturation flow rate and the platoon dispersion. In order to capture the traffic flow operational characteristics on coordinated intersections, three locations, namely entrance location where the loop detector was located at, and upstream intersection and downstream intersection were defined. Two types of vehicle cumulative curves, namely cumulative arrival profile and cumulative departure profile were constructed. The mixed-flow traffic dynamics were analyzed, and the arrival-departure curves relationship was derived using a combination of Newell car-following and Akçelik acceleration model. A mixed-flow platoon dispersion model was proposed to describe the vehicle's progression between two locations. Due to the nonlinear nature of the problem, a particle swarm optimization (PSO) method was employed to obtain the optimal signal parameters, including the cycle length, green duration, and optimal offset. The algorithm was implemented and validated in a case study involving two intersections, with the demand formulated and simulated by the Markov chain. The results showed that the proposed model could effectively decrease delays when compared with current signal control methods.
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spelling doaj.art-701713ddfa37420ea16ee3af65fdacc52022-12-21T18:20:07ZengIEEEIEEE Access2169-35362020-01-018260672608410.1109/ACCESS.2020.29701158972368Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous VehiclesHongsheng Qi0https://orcid.org/0000-0002-2934-7601Rumeng Dai1https://orcid.org/0000-0003-3121-2906Qing Tang2https://orcid.org/0000-0003-0465-9737Xianbiao Hu3https://orcid.org/0000-0002-0149-1847Department of Civil Engineering, Zhejiang University, College of Civil Engineering and Architecture, Hangzhou, ChinaDepartment of Civil Engineering, Zhejiang University, College of Civil Engineering and Architecture, Hangzhou, ChinaDepartment of Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology, Rolla, MO, USADepartment of Civil, Architectural and Environmental Engineering, Missouri University of Science and Technology, Rolla, MO, USAThis manuscript investigated coordinated intersection signal design problem for mixed traffic flow of Human-Driven Vehicles (HDVs) and Connected and Autonomous Vehicles (CAVs). Two main macroscopic impact of the mixed flow on signal setting are considered: saturation flow rate and the platoon dispersion. In order to capture the traffic flow operational characteristics on coordinated intersections, three locations, namely entrance location where the loop detector was located at, and upstream intersection and downstream intersection were defined. Two types of vehicle cumulative curves, namely cumulative arrival profile and cumulative departure profile were constructed. The mixed-flow traffic dynamics were analyzed, and the arrival-departure curves relationship was derived using a combination of Newell car-following and Akçelik acceleration model. A mixed-flow platoon dispersion model was proposed to describe the vehicle's progression between two locations. Due to the nonlinear nature of the problem, a particle swarm optimization (PSO) method was employed to obtain the optimal signal parameters, including the cycle length, green duration, and optimal offset. The algorithm was implemented and validated in a case study involving two intersections, with the demand formulated and simulated by the Markov chain. The results showed that the proposed model could effectively decrease delays when compared with current signal control methods.https://ieeexplore.ieee.org/document/8972368/Coordinated signal controlconnected and autonomous vehiclescumulative curvesplatoon dispersiontraffic flow modeling
spellingShingle Hongsheng Qi
Rumeng Dai
Qing Tang
Xianbiao Hu
Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
IEEE Access
Coordinated signal control
connected and autonomous vehicles
cumulative curves
platoon dispersion
traffic flow modeling
title Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
title_full Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
title_fullStr Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
title_full_unstemmed Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
title_short Coordinated Intersection Signal Design for Mixed Traffic Flow of Human-Driven and Connected and Autonomous Vehicles
title_sort coordinated intersection signal design for mixed traffic flow of human driven and connected and autonomous vehicles
topic Coordinated signal control
connected and autonomous vehicles
cumulative curves
platoon dispersion
traffic flow modeling
url https://ieeexplore.ieee.org/document/8972368/
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AT rumengdai coordinatedintersectionsignaldesignformixedtrafficflowofhumandrivenandconnectedandautonomousvehicles
AT qingtang coordinatedintersectionsignaldesignformixedtrafficflowofhumandrivenandconnectedandautonomousvehicles
AT xianbiaohu coordinatedintersectionsignaldesignformixedtrafficflowofhumandrivenandconnectedandautonomousvehicles