A computation offloading method with distributed double deep Q‐network for connected vehicle platooning with vehicle‐to‐infrastructure communications
Y Shi, J Chu, X Sun, S Ning - IET Intelligent Transport Systems, 2024 - Wiley Online Library
Current connected vehicle applications, such as platooning require heavy‐load computing
capability. Although mobile edge computing (MEC) servers connected to the roadside …
capability. Although mobile edge computing (MEC) servers connected to the roadside …
Augmented Mixed Vehicular Platoon Control With Dense Communication Reinforcement Learning for Traffic Oscillation Alleviation
Traffic oscillations present significant challenges to road transportation systems, resulting in
reduced fuel efficiency, heightened crash risks, and severe congestion. Recently emerging …
reduced fuel efficiency, heightened crash risks, and severe congestion. Recently emerging …
Cooperative traffic optimization with multi-agent reinforcement learning and evolutionary strategy: Bridging the gap between micro and macro traffic control
The emergence of connected and autonomous vehicles (CAVs) holds promise for fine-
grained traffic control. However, due to the longevity of future mixed traffic scenarios, there is …
grained traffic control. However, due to the longevity of future mixed traffic scenarios, there is …
Dynamic traffic graph based risk assessment of multivehicle lane change interaction scenarios
Y Guo, Y Chen, X Gu, J Guo, S Zheng… - Physica A: Statistical …, 2024 - Elsevier
Vehicles' lane-changing behavior can potentially result in traffic conflicts and crash risks,
particularly in scenarios with interactions among multiple vehicles. To assess the crash risk …
particularly in scenarios with interactions among multiple vehicles. To assess the crash risk …
Collaborative Control of Vehicle Platoon based on Deep Reinforcement Learning
J Chen, X Wu, Z Lv, Z Xu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
We propose a novel vehicle platoon collaborative control algorithm based on deep
reinforcement learning. Aiming at the slow convergence speed of traditional reinforcement …
reinforcement learning. Aiming at the slow convergence speed of traditional reinforcement …
Preference-Based Reinforcement Learning for Autonomous Vehicle Control Considering the Benefits of Following Vehicles
Most studies developing car-following controllers for AVs in mixed traffic primarily focus on
maximizing the utility of the AVs. However, the utility of the entire mixed traffic flow is largely …
maximizing the utility of the AVs. However, the utility of the entire mixed traffic flow is largely …
Cooperative decision making for connected automated vehicles in multiple driving scenarios
J Wang, Z Ma, X Zhu, J Bai… - IET Intelligent Transport …, 2023 - Wiley Online Library
To improve the application range of decision‐making systems for connected automated
vehicles, this paper proposes a cooperative decision‐making approach for multiple driving …
vehicles, this paper proposes a cooperative decision‐making approach for multiple driving …
Dynamic Passenger Route Guidance in the Multimodal Transit System With Graph Representation and Attention Based Deep Reinforcement Learning
Recently, the limited capacity of the Urban Rail Transit (URT) has failed to meet passenger
travel demands, especially in peak hours, which leads to crowded stations and …
travel demands, especially in peak hours, which leads to crowded stations and …
Synergizing Autonomous and Traditional Vehicles: A Systematic Review of Advances and Challenges in Traffic Flow Management With Signalized Intersections
The advent of technology has led to substantial progress in the field of autonomous vehicles
(AVs), indicating that AVs will become a generic mode of transport in the near future …
(AVs), indicating that AVs will become a generic mode of transport in the near future …
Towards Cooperative Driving among Heterogeneous CAVs: A Safe Multi-Agent Reinforcement Learning Approach
With the advancement of Intelligent Transportation Systems and Vehicle-to-Everything
communication technologies, the future traffic scenario is anticipated to be a mixed …
communication technologies, the future traffic scenario is anticipated to be a mixed …