Technical Papers
Sep 8, 2022

Lane Selection Model Based on Phase-Field Coupling and Set Pair Logic

Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 11

Abstract

Intelligent and connected driving (ICD) is an effective method of the vehicle’s active safety and traffic efficiency. Lane-changing is the critical part of ICD behavior and the basic content of traffic flow theory. Lane selection is the most important during lane-changing, which has a critical influence on traffic safety and efficiency. Focusing on the development of ICD technology, a lane selection model based on phase-field coupling and set pair logic is proposed. In this model, the method of phased-field coupling is used to comprehensively analyze the full information of lanes with the interaction between cluster vehicles considering driving propensity. The certain and uncertain human-vehicle-environment information is fully explored using the method of set pair logic. In the lane selection model, the lane utility and utility gains of lane-changing are calculated to select the candidate target lane. And the overall satisfaction is analyzed to determine the target lane as the final strategy. The proposed lane selection model constructed in this research fully considers the development of ICD technology and adapts to the requirement of an Intelligent and Connected Vehicle. This research could provide a theoretical basis for vehicle autonomous behavior decision-making and ICD.

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Data Availability Statement

Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.

Acknowledgments

This work was supported by the National Key Research and Development Project, Grant No. 2018YFB1601500; the Natural Science Foundation of Shandong Province, Grant No. ZR2020MF082; the Qingdao Top Talent Program of Entrepreneurship and Innovation, Grant No. 19-3-2-11-zhc; the Collaborative Innovation Center for Intelligent Green Manufacturing Technology and Equipment of Shandong Province, Grant No. IGSD-2020-012; and the Joint Laboratory for Internet of Vehicles, Ministry of Education-China Mobile Communications Corporation, Grant No. ICV-KF2018-03.

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Go to Journal of Transportation Engineering, Part A: Systems
Journal of Transportation Engineering, Part A: Systems
Volume 148Issue 11November 2022

History

Received: Mar 28, 2021
Accepted: Jun 30, 2022
Published online: Sep 8, 2022
Published in print: Nov 1, 2022
Discussion open until: Feb 8, 2023

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Graduate Student, College of Electromechanical Engineering, Qingdao Univ. of Science & Technology, Qingdao 266000, China. Email: [email protected]
Xiaoyuan Wang [email protected]
Professor, College of Electromechanical Engineering, Qingdao Univ. of Science & Technology, Qingdao 266000, China; Deputy Director, Collaborative Innovation Center for Intelligent Green Manufacturing Technology and Equipment of Shandong Province, Qingdao 266000, China (corresponding author). Email: [email protected]
Lecturer, School of Automotive and Traffic Engineering, Jiangsu Univ., Zhenjiang 212013, China. Email: [email protected]
Longfei Chen [email protected]
Doctoral Student, College of Electromechanical Engineering, Qingdao Univ. of Science & Technology, Qingdao 266000, China. Email: [email protected]
Graduate Student, College of Electromechanical Engineering, Qingdao Univ. of Science & Technology, Qingdao 266000, China. Email: [email protected]
Doctoral Student, College of Electromechanical Engineering, Qingdao Univ. of Science & Technology, Qingdao 266000, China. Email: [email protected]
Associate Professor, School of Transportation and Vehicle Engineering, Shandong Univ. of Technology, Zibo 255000, China. Email: [email protected]

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