HYDRO-3D: Hybrid object detection and tracking for cooperative perception using 3D LiDAR
3D-LiDAR-based cooperative perception has been generating significant interest for its
ability to tackle challenges such as occlusion, sparse point clouds, and out-of-range issues …
ability to tackle challenges such as occlusion, sparse point clouds, and out-of-range issues …
A systematic survey of control techniques and applications in connected and automated vehicles
Vehicle control is one of the most critical challenges in autonomous vehicles (AVs) and
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
connected and automated vehicles (CAVs), and it is paramount in vehicle safety, passenger …
Multi-Agent Reinforcement Learning for Connected and Automated Vehicles Control: Recent Advancements and Future Prospects
Connected and automated vehicles (CAVs) have emerged as a potential solution to the
future challenges of developing safe, efficient, and eco-friendly transportation systems …
future challenges of developing safe, efficient, and eco-friendly transportation systems …
A transfer-based reinforcement learning collaborative energy management strategy for extended-range electric buses with cabin temperature comfort consideration
Electric vehicles (EVs) have received extensive attention as an environmentally friendly and
sustainable mode of transportation. To address “range anxiety” issues, extended-range …
sustainable mode of transportation. To address “range anxiety” issues, extended-range …
A comparative study of energy-oriented driving strategy for connected electric vehicles on freeways with varying slopes
This paper proposes two real-time energy-oriented driving strategies to minimize the energy
consumption for electric vehicles on highways with varying slopes. First, a novel strategy …
consumption for electric vehicles on highways with varying slopes. First, a novel strategy …
Recent Progress in Energy Management of Connected Hybrid Electric Vehicles Using Reinforcement Learning
M Hua, B Shuai, Q Zhou, J Wang, Y He… - arXiv preprint arXiv …, 2023 - arxiv.org
The growing adoption of hybrid electric vehicles (HEVs) presents a transformative
opportunity for revolutionizing transportation energy systems. The shift towards electrifying …
opportunity for revolutionizing transportation energy systems. The shift towards electrifying …
Communication-efficient decentralized multi-agent reinforcement learning for cooperative adaptive cruise control
Connected and autonomous vehicles (CAVs) promise next-gen transportation systems with
enhanced safety, energy efficiency, and sustainability. One typical control strategy for CAVs …
enhanced safety, energy efficiency, and sustainability. One typical control strategy for CAVs …
Planning and tracking control of full drive-by-wire electric vehicles in unstructured scenario
G Chen, M Hua, W Liu, J Wang… - Proceedings of the …, 2023 - journals.sagepub.com
Full drive-by-wire electric vehicles (FDWEV) equipped with X-by-wire technology can enable
independent driving, braking, and steering of each wheel, making them an ideal platform for …
independent driving, braking, and steering of each wheel, making them an ideal platform for …
Optimal Energy Management of Plug-in Hybrid Electric Vehicles Through Ensemble Reinforcement Learning With Exploration-to-Exploitation Ratio Control
B Shuai, M Hua, Y Li, S Shuai, H Xu… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Reinforcement learning (RL) has demonstrated its advantages in the intelligent control of
many vehicle systems. However, controlling the exploration-to-exploitation (E2E) ratio of RL …
many vehicle systems. However, controlling the exploration-to-exploitation (E2E) ratio of RL …
Statistically efficient variance reduction with double policy estimation for off-policy evaluation in sequence-modeled reinforcement learning
H Zhou, T Lan, V Aggarwal - arXiv preprint arXiv:2308.14897, 2023 - arxiv.org
Offline reinforcement learning aims to utilize datasets of previously gathered environment-
action interaction records to learn a policy without access to the real environment. Recent …
action interaction records to learn a policy without access to the real environment. Recent …