70 citations · 131 across the 12 of their papers we have counts for
13 papers
Decision-making at Unsignalized Intersection for Autonomous Vehicles: Left-turn Maneuver with Deep Reinforcement Learning
Feng Wang, Dongjie Shi, Teng Liu +1
Decision-making module enables autonomous vehicles to reach appropriate maneuvers in the complex urban environments, especially the intersection situations. This work proposes a de…
A Comparative Analysis of Deep Reinforcement Learning-enabled Freeway Decision-making for Automated Vehicles
Teng Liu, Yuyou Yang, Wenxuan Xiao +2
Deep reinforcement learning (DRL) has emerged as a pervasive and potent methodology for addressing artificial intelligence challenges. Due to its substantial potential for autonomo…
Driving Conditions-Driven Energy Management for Hybrid Electric Vehicles: A Review
Teng Liu, Wenhao Tan, Xiaolin Tang +3
Motivated by the concerns on transported fuel consumption and global air pollution, industrial engineers, and academic researchers have made many efforts to construct more efficien…
Integrated Longitudinal Speed Decision-Making and Energy Efficiency Control for Connected Electrified Vehicles
Teng Liu, Bo Wang, Dongpu Cao +2
To improve the driving mobility and energy efficiency of connected autonomous electrified vehicles, this paper presents an integrated longitudinal speed decision-making and energy…
Adaptive Energy Management for Real Driving Conditions via Transfer Reinforcement Learning
Teng Liu, Wenhao Tan, Xiaolin Tang +2
This article proposes a transfer reinforcement learning (RL) based adaptive energy managing approach for a hybrid electric vehicle (HEV) with parallel topology. This approach is bi…
Digital Quadruplets for Cyber-Physical-Social Systems based Parallel Driving: From Concept to Applications
Teng Liu, Xing Yang, Hong Wang +4
Digital quadruplets aiming to improve road safety, traffic efficiency, and driving cooperation for future connected automated vehicles are proposed with the enlightenment of ACP ba…
Reinforcement Learning-Enabled Decision-Making Strategies for a Vehicle-Cyber-Physical-System in Connected Environment
Teng Liu, Xiaolin Tang, Jinwei Zhang +3
As a typical vehicle-cyber-physical-system (V-CPS), connected automated vehicles attracted more and more attention in recent years. This paper focuses on discussing the decision-ma…
Decision-making Strategy on Highway for Autonomous Vehicles using Deep Reinforcement Learning
Jiangdong Liao, Teng Liu, Xiaolin Tang +3
Autonomous driving is a promising technology to reduce traffic accidents and improve driving efficiency. In this work, a deep reinforcement learning (DRL)-enabled decision-making p…
Transfer Deep Reinforcement Learning-enabled Energy Management Strategy for Hybrid Tracked Vehicle
Xiaowei Guo, Teng Liu, Bangbei Tang +4
This paper proposes an adaptive energy management strategy for hybrid electric vehicles by combining deep reinforcement learning (DRL) and transfer learning (TL). This work aims to…
Dueling Deep Q Network for Highway Decision Making in Autonomous Vehicles: A Case Study
Teng Liu, Xingyu Mu, Xiaolin Tang +3
This work optimizes the highway decision making strategy of autonomous vehicles by using deep reinforcement learning (DRL). First, the highway driving environment is built, wherein…
Transferred Energy Management Strategies for Hybrid Electric Vehicles Based on Driving Conditions Recognition
Teng Liu, Xiaolin Tang, Jiaxin Chen +3
Energy management strategies (EMSs) are the most significant components in hybrid electric vehicles (HEVs) because they decide the potential of energy conservation and emission red…
Human-like Energy Management Based on Deep Reinforcement Learning and Historical Driving Experiences
Hao Chen, Xiaolin Tang, Guo Hu +1
Development of hybrid electric vehicles depends on an advanced and efficient energy management strategy (EMS). With online and real-time requirements in mind, this article presents…
Dimensioning and Power Management of Hybrid Energy Storage Systems for Electric Vehicles with Multiple Optimization Criteria
Huilong Yu, Francesco Castelli-Dezza, Federico Cheli +3
Hybrid energy storage systems that combine lithium-ion batteries and supercapacitors are considered as an attractive solution to overcome the drawbacks of battery-only energy stora…