Velocity Optimization of Connected Electric Vehicle at Multiple Signalized Intersections for Energy Efficiency and Traffic Throughput Improvement

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Velocity Optimization of Connected Electric Vehicle at Multiple Signalized Intersections for Energy Efficiency and Traffic Throughput Improvement

Dong, Haoxuan / Chen, Hao / Zhou, Yichen / Li, Zhihan / Yin, Guodong / Zhuang, Weichao

Signalized intersection can interrupt the traffic flow, potentially increasing vehicle energy consumption levels and extending travel time. This paper presents an eco-approach and departure strategy (EAD) using a double-layer control scheme, to achieve the optimization of energy economy and traffic throughput for connected electric vehicle (EV) at the route with multiple intersections and varying road slopes. In the first layer, for improving traffic throughput, we design a traffic light green window planning method with consideration of the spatio-temporal coupling of intersections. Then, in the second layer, a distance-domain optimal control problem (OCP) is formulated considering the intersection segment, green window intervals, and speed limitations. This OCP is solved by dynamic programming algorithm, to derive the energy-optimal speed. Finally, a simulation is conducted using the route from a real-world scenario in Nanjing, China, to evaluate the performance of the proposed strategy. The results indicate the proposed EAD strategy can improve EV energy efficiency and traffic throughput dramatically compared with the regular constant speed strategy.

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Dokumentinformationen

Titel :

Velocity Optimization of Connected Electric Vehicle at Multiple Signalized Intersections for Energy Efficiency and Traffic Throughput Improvement

Beteiligte:

Dong, Haoxuan (Autor:in) / Chen, Hao (Autor:in) / Zhou, Yichen (Autor:in) / Li, Zhihan (Autor:in) / Yin, Guodong (Autor:in) / Zhuang, Weichao (Autor:in)

Erschienen in:

2021 6th International Conference on Transportation Information and Safety (ICTIS) ; 1004-1009

Erscheinungsdatum :

2021-10-22

Format / Umfang :

1094423 byte

ISBN :

978-1-6654-9713-8

DOI :

https://doi.org/10.1109/ICTIS54573.2021.9798558

Medientyp :

Aufsatz (Konferenz)