Eco-Driving Strategy Design of Connected Vehicle among Multiple Signalized Intersections Using Constraint-enforced Reinforcement Learning
Optimizing speed profiles at urban signalized intersections, commonly referred to as an eco-
driving strategy, is acknowledged as a promising approach to improving vehicle energy …
driving strategy, is acknowledged as a promising approach to improving vehicle energy …
Eco-driving at signalized intersections: a parameterized reinforcement learning approach
X Jiang, J Zhang, D Li - Transportmetrica B: Transport Dynamics, 2023 - Taylor & Francis
This paper proposes an eco-driving framework for electric connected vehicles (CVs) based
on reinforcement learning (RL) to improve vehicle energy efficiency at signalized …
on reinforcement learning (RL) to improve vehicle energy efficiency at signalized …
Learning-based eco-driving strategy design for connected power-split hybrid electric vehicles at signalized corridors
The eco-driving strategy that targets driving speed optimization is recognized as a promising
technique to improve vehicle energy efficiency. However, it is difficult to achieve real-time …
technique to improve vehicle energy efficiency. However, it is difficult to achieve real-time …
Eco-driving for Electric Connected Vehicles at Signalized Intersections: A Parameterized Reinforcement Learning approach
X Jiang, J Zhang, D Li - arXiv preprint arXiv:2206.12065, 2022 - arxiv.org
This paper proposes an eco-driving framework for electric connected vehicles (CVs) based
on reinforcement learning (RL) to improve vehicle energy efficiency at signalized …
on reinforcement learning (RL) to improve vehicle energy efficiency at signalized …
Deep reinforcement learning-based eco-driving control for connected electric vehicles at signalized intersections considering traffic uncertainties
Eco-driving control poses great energy-saving potential at multiple signalized intersection
scenarios. However, traffic uncertainties can often lead to errors in ecological velocity …
scenarios. However, traffic uncertainties can often lead to errors in ecological velocity …
[PDF][PDF] An enhanced eco-driving strategy based on reinforcement learning for connected electric vehicles: Cooperative velocity and lane-changing control
H Ding, W Li, N Xu, J Zhang - Journal of Intelligent and …, 2022 - ieeexplore.ieee.org
Purpose-This study aims to propose an enhanced eco-driving strategy based on
reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the …
reinforcement learning (RL) to alleviate the mileage anxiety of electric vehicles (EVs) in the …
Hybrid reinforcement learning-based eco-driving strategy for connected and automated vehicles at signalized intersections
Taking advantage of both vehicle-to-everything (V2X) communication and automated driving
technology, connected and automated vehicles are quickly becoming one of the …
technology, connected and automated vehicles are quickly becoming one of the …
A Critical Evaluation of Eco-Driving Strategies for Connected Autonomous Electric Vehicles at Signalized Intersections
Signalized intersections are significant spots of energy consumption because of frequent
stop-and-go behavior. Eco-driving aims to reduce energy usage by optimizing driving …
stop-and-go behavior. Eco-driving aims to reduce energy usage by optimizing driving …
Predictive energy-efficient driving strategy design of connected electric vehicle among multiple signalized intersections
Signalized intersections dominate traffic flow in urban areas, resulting in increased energy
consumption and travel delay for the vehicles involved. To mitigate the negative effect of …
consumption and travel delay for the vehicles involved. To mitigate the negative effect of …
Developing an adaptive strategy for connected eco-driving under uncertain traffic and signal conditions
The Eco-Approach and Departure (EAD) application has been proved to be environmentally
efficient for a Connected and Automated Vehicles (CAVs) system. In the real-world traffic …
efficient for a Connected and Automated Vehicles (CAVs) system. In the real-world traffic …