Impact of lane-changing behavior on traffic emissions of road sections in multi-dimensional mixed traffic flow environment

ABSTRACT

This study analyzed the effect of lane-changing behavior on traffic flow emissions and energy consumption of road sections in fuel vehicle-battery electric vehicle (FV-BEV) and human-driven vehicle-cooperative adaptive cruise control (HDV-CACC) multi-dimensional mixed traffic flow environments. Based on the traditional energy consumption model, a multi-dimensional mixed traffic flow energy consumption model was established by considering the BEV and CACC penetration rates. The microscopic traffic flow theory approach was used to analyze lane-changing behavior and the influencing mechanism of lane-changing behavior on the energy consumption of multi-dimensional mixed traffic flow, and MATLAB was used for the experimental simulation. The lane-changing behavior of the leading vehicle had a negative impact on the energy consumption of road segment traffic flow. Within the 95% effective impact range, the average energy consumption of traffic flow with respect to lane-changing behavior was 7.8% higher than that of the following traffic flow. The BEV penetration rate was beneficial for reducing the energy consumption of mixed traffic flow. At an economic velocity, the energy consumption of homogeneous BEV traffic flow was only 58.3% of that of homogeneous FV traffic flow. The CACC penetration rate could increase the traffic flow toughness. When the BEV penetration rate was constant, the higher the CACC penetration rate, the smaller the impact of lane-changing behavior on emissions. When traffic flow was completely transformed to homogeneous CACC traffic flow, lane-changing behavior only increased the overall energy consumption of the traffic flow by 4.99%, which was lower than the average level. Consequently, the promotion of BEV and CACC can improve the impact of traffic emissions on air pollution. When CACC penetration is low, reducing unnecessary lane-changing behavior to ensure the stability of traffic flow is also an effective way to reduce emissions.

Implications:

1. Multi-dimensional mixed traffic flow energy consumption model is proposed.

2. CACC penetration rate, BEV penetration rate and lane-changing behavior will change traffic energy consumption. In this paper, different influencing factors are analyzed one by one.

3. It provides a theoretical basis for relevant departments of traffic management to optimize vehicle emissions and traffic organization.

Disclosure statement

No potential conflict of interest was reported by the authors.

CRediT authorship contribution statement

Xinghua Hu: Conceptualization, Methodology, Software, Writing-original draft, Writing-review & editing, Data curation, Visualization, Supervision. Mintanyu Zheng: Conceptualization, Methodology, Software, Writing-original draft, Writing-review & editing. Jianpu Guo: Methodology, Formal analysis, Writing-original draft, Data curation, Supervision. Xinghui Chen: Software, Data curation, Writing-review & editing, Investigation. Gao Dai: Data curation, Investigation, Project Administration. Jiahao Zhao: Data curation, Visualization. Bing Long: Investigation, Formal analysis.

Data availability statement

Due to the nature of this research, participants of this study did not agree for their data to be shared publicly, so supporting data is not available.

Abbreviations

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Additional information

Funding

This research was supported in part by Sichuan Science and Technology Program under [Grant No. 2022YFG0132], and in part by the Chongqing Postgraduate Joint Training Base Project (Chongqing Jiaotong University-Chongqing YouLiang Science & Technology Co., Ltd Joint Training Base for Postgraduates in Transportation) under [Grant JDLHPYJD2019007].

Notes on contributors

Xinghua Hu

Xinghua Hu is a professor in the School of Traffic and Transportation at the Chongqing Jiaotong University. His research interest include on green transportation, intelligent transportation and transportation planning.

Mintanyu Zheng

Mintanyu Zheng is currently a postgraduate student in the School of Traffic and Transportation at the Chongqing Jiaotong University. His research focus is on the traffic flow energy consumption.

Jianpu Guo

Jianpu Guo is associate researcher in the Development of Science and Technology Statistics and Innovation, Chongqing Productivity Council.

Xinghui Chen

Xinghui Chen is currently a postgraduate student in the School of Traffic and Transportation at the Chongqing Jiaotong University.

Gao Dai

Gao Dai is professor level senior engineer in the Department of Technology R&D at the Chongqing YouLiang Science & Technology Co., Ltd.

Jiahao Zhao

Jiahao Zhao has a doctoral degree from the Beijing Jiaotong University. He is currently a senior lecturer in the School of Traffic and Transportation at the Chongqing Jiaotong University.

Bing Long

Bing Long is senior engineer in the Development of Traffic Engineering, Institute of Chongqing Transport Planning.