The Car-Following Model and Its Applications in the V2X Environment: A Historical Review

Junyan Han, Huili Shi, Longfei Chen, Hao Li and Xiaoyuan Wang
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Junyan Han: College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
Huili Shi: College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
Longfei Chen: College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
Hao Li: College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China
Xiaoyuan Wang: College of Electromechanical Engineering, Qingdao University of Science & Technology, Qingdao 266000, China

Future Internet, 2021, vol. 14, issue 1, 1-34

Abstract: The application of vehicle-to-everything (V2X) technology has resulted in the traffic environment being different from how it was in the past. In the V2X environment, the information perception ability of the driver–vehicle unit is greatly enhanced. With V2X technology, the driver–vehicle unit can obtain a massive amount of traffic information and is able to form a connection and interaction relationship between multiple vehicles and themselves. In the traditional car-following models, only the dual-vehicle interaction relationship between the object vehicle and its preceding vehicle was considered, making these models unable to be employed to describe the car-following behavior in the V2X environment. As one of the core components of traffic flow theory, research on car-following behavior needs to be further developed. First, the development process of the traditional car-following models is briefly reviewed. Second, previous research on the impacts of V2X technology, car-following models in the V2X environment, and the applications of these models, such as the calibration of the model parameters, the analysis of traffic flow characteristics, and the methods that are used to estimate a vehicle’s energy consumption and emissions, are comprehensively reviewed. Finally, the achievements and shortcomings of these studies along with trends that require further exploration are discussed. The results that were determined here can provide a reference for the further development of traffic flow theory, personalized advanced driving assistance systems, and anthropopathic autonomous-driving vehicles.

Keywords: vehicle-to-everything technology; traffic flow theory; car-following model; traffic information and control; intelligent and connected vehicle (search for similar items in EconPapers)
JEL-codes: O3 (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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