Effects of Connected Autonomous Vehicles on the Energy Performance of Signal-Controlled Junctions

Yiqing Wen, Yibing Wang, Zhao Zhang, Jiaxin Wu, Liangxia Zhong, Markos Papageorgiou and Pengjun Zheng ()
Additional contact information
Yiqing Wen: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China
Yibing Wang: Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou 310058, China
Zhao Zhang: School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
Jiaxin Wu: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China
Liangxia Zhong: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China
Markos Papageorgiou: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China
Pengjun Zheng: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315000, China

Sustainability, 2023, vol. 15, issue 7, 1-18

Abstract: This study proposes an optimal control method for connected autonomous vehicles (CAVs) through signalized intersections to reduce the energy consumption of mixed human-driven vehicles (HDVs) and CAV traffic. A real-time optimal control model was developed to optimize the trajectory of each CAV by minimizing energy consumption during the control period while ensuring traffic efficiency and safety. The control conditions of the CAVs were analyzed under different driving scenarios considering the impact of signal phase timing and preceding vehicles. Additionally, a method is proposed for CAVs to guide other vehicles directly and reduce the energy consumption of the entire signalized intersection. Simulation experiments using MATLAB and SUMO were conducted to evaluate the performance of the proposed method under various traffic conditions, such as different levels of saturation, market penetration rates (MPRs), and the green ratio. The performance was measured using average energy consumption and an average time delay. The results show that the proposed method can effectively reduce vehicle energy consumption without compromising traffic efficiency under various conditions. Moreover, under traffic saturation, the proposed method performs better at a high MPR and green ratio, especially at 40–60% MPR.

Keywords: connected autonomous vehicles; eco-driving method; optimal control; signalized intersections; consumption performance (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/2071-1050/15/7/5672/pdf (application/pdf)
https://www.mdpi.com/2071-1050/15/7/5672/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:15:y:2023:i:7:p:5672-:d:1105835

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().