Cooperative Driving and Lane Changing Modeling for Connected Vehicles in the Vicinity of Traffic Signals: A Cyber-Physical Perspective

The vicinity of traffic signals is one of the most critical areas in road systems. New information technology paradigms like vehicle-to-vehicle and vehicle-to-infrastructure communication are applied to improve traffic operations at intersections; for example, a typical cyber-physical system enables...

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Bibliographic Details
Published in:IEEE access 2018-01, Vol.6, p.13891-13897
Main Authors: He, Yuchu, Sun, Dihua, Zhao, Min, Cheng, Senlin
Format: Article
Language:English
Subjects:
Acceleration
Analytical models
Computational modeling
cooperative driving
Cyber-physical systems
Driving
Driving conditions
Lane changing
Mathematical model
Modelling
Roads
State estimation
Traffic
Traffic intersections
Traffic models
Traffic signals
Trajectory
Travel time
Vehicle to X (V2X) technology
Vehicle-to-infrastructure
Vehicles
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Summary:The vicinity of traffic signals is one of the most critical areas in road systems. New information technology paradigms like vehicle-to-vehicle and vehicle-to-infrastructure communication are applied to improve traffic operations at intersections; for example, a typical cyber-physical system enables efficient traffic state estimation and traffic modeling. A new model of vehicle cooperative driving under a typical scenario vicinity of traffic signals and Vehicle to X environment was proposed in this paper. Based on the intelligent driver model, the model planned trajectories for vehicles in the vicinity of traffic signals in advance to reduce stopping frequency and travel time and improve the throughput of the road according to traffic conditions, such as signal cycle state, the distance to traffic signals, and the situation regarding adjacent vehicles. In accordance with the relationship between the host vehicle and the surrounding vehicles, the model also planed the cooperative lane changing strategy in this scenario to improve safety and comfort in the process of lane changing. A simulation experiment compared the proposed model with the traditional intelligent driver model, and analyzed its performance in different traffic conditions. The feasibility and superiority of the model were confirmed.
ISSN:2169-3536
2169-3536
DOI:10.1109/ACCESS.2018.2813539