6 citations · 28 across the 10 of their papers we have counts for
12 papers
Driving Tasks Transfer in Deep Reinforcement Learning for Decision-making of Autonomous Vehicles
Hong Shu, Teng Liu, Xingyu Mu +1
Knowledge transfer is a promising concept to achieve real-time decision-making for autonomous vehicles. This paper constructs a transfer deep reinforcement learning framework to tr…
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…
Defining Digital Quadruplets in the Cyber-Physical-Social Space for Parallel Driving
Teng Liu, Yang Xing, Long Chen +2
Parallel driving is a novel framework to synthesize vehicle intelligence and transport automation. This article aims to define digital quadruplets in parallel driving. In the cyber…
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…