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Lu Xiong - IEEE Xplore Author Profile

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Author details

Lu Xiong

Publications

106

Citations

1,373

Publications by Year

20102025

Co-Authors:

Jie BaiXin BiLewen CaiYingfeng CaiJing Cao

Show All Co-Authors (198)

Lu Xiong

Affiliation

School of Automotive Studies

Tongji University

Shanghai, China

Clean Energy Automotive Engineering Center

Tongji University

Shanghai, China

Publication Topics

Autonomous Vehicles,
Model Predictive Control,
Steering Angle,
Lane Change,
Lateral Acceleration,
Vehicle Dynamics,
Yaw Rate,
Optimization Problem,
Reward Function,
Sideslip Angle,
Vehicle Stability,
Control Input

Biography

Lu Xiong was born in 1978. He received the B.S. degree in mechanical design and manufacture and the master’s and Ph.D. degrees in vehicle engineering from Tongji University, Shanghai, China, in 1999, 2002, and 2005, respectively. He conducted the post-doctoral research at the University of Stuttgart, Germany, from 2008 to 2009. He is currently the Associate Dean, a Professor, and a Doctoral Supervisor with the School of Automotive Studies, Tongji University. His research interests include vehicle system dynamics and control, distributed drive electric vehicles, electro-hydraulic brake systems, and intelligent vehicles.(Based on document published on 8 September 2021).

Publications

106

Citations

1,373

Publications by Year

20102025

Co-Authors:

Jie Bai
Xin Bi
Lewen Cai
Yingfeng Cai
Jing Cao

Show All Co-Authors (198)

Author's Published Works

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Showing 1-25 of 106 results

Conferences (70)

Journals (33)

Early Access Articles (3)

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Lu Xiong(106)
Zhuoping Yu(41)
Bo Leng(29)
Zhiqiang Fu(13)
Junqiao Zhao(11)
School of Automotive Studies, Tongji University, Shanghai, China(59)
Clean Energy Automotive Engineering Center, Tongji University, Shanghai, China(6)
School of Automotive Studies, Tongji University, Shanghai(4)
Institute of Intelligent Vehicles, Tongji University, Shanghai, China(4)
Department of Computer Science and Technology, School of Electronics and Information Engineering, Tongji University, Shanghai, China(4)
IEEE Transactions on Vehicular Technology(7)
2021 5th CAA International Conference on Vehicular Control and Intelligence (CVCI)(6)
2021 IEEE International Intelligent Transportation Systems Conference (ITSC)(6)
IEEE Transactions on Intelligent Vehicles(6)
2018 IEEE Intelligent Vehicles Symposium (IV)(4)
IEEE(106)
Media(3)
Indianapolis, IN, USA(6)
Tianjin, China(6)
Chongqing, China(5)
Changsha, China(4)
Changshu, China(4)
Autonomous Vehicles(32)
Steering Angle(21)
Vehicle Dynamics(19)
Inertial Measurement Unit(18)
Lane Change(18)

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A Hierarchical Motion Control Framework for Reference Trajectory Tracking of Autonomous Vehicles Considering Decoupling Vehicle Kinematics and Dynamics

Wei Han;Quan Zhou;Lu Xiong

IEEE Transactions on Transportation Electrification

Year: 2025 | Early Access Article |

With the development of automated driving intelligence, autonomous vehicles have been developed to partially take place of the advanced driver assistance system(ADAS), especially under the closed or low-interactive scenarios, such as navigation pilot on highway and automated valet parking, having the advantage of safety guarantee and driver workload reduction. Trajectory tracking control, one of t...Show More

A Hierarchical Motion Control Framework for Reference Trajectory Tracking of Autonomous Vehicles Considering Decoupling Vehicle Kinematics and Dynamics

Wei Han;Quan Zhou;Lu Xiong

IEEE Transactions on Transportation Electrification

Year: 2025 | Early Access Article |

Boost Query-Centric Network Efficiency for Multi-Agent Motion Forecasting

Yuyao Huang;Kai Chen;Wei Tian;Lu Xiong

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

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Real-time multi-agent motion forecasting is essential for autonomous vehicles to safely navigate on urban roads. Recent advancements in this field exhibit the superior performance of Query-Centric Networks for large-scale data and long-term prediction. However, these methods often suffer from high space and time complexity, which limits their practicality and impedes further research. E.g., traini...Show More

Boost Query-Centric Network Efficiency for Multi-Agent Motion Forecasting

Yuyao Huang;Kai Chen;Wei Tian;Lu Xiong

IEEE Robotics and Automation Letters

Year: 2025 | Volume: 10, Issue: 4 | Journal Article |

A Self-organizing Cooperative Control Framework for Connected Automated Vehicles at Unsignalized Roundabouts

Xuekai Liu;Qian Chen;Peng Hang;Lu Xiong;Jian Sun

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2024 | Conference Paper |

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Due to the huge traffic flow and complex weaving, unsignalized roundabout is one of the most challenging scenarios for autonomous driving. Though cooperative autonomous driving has the potential to address this challenge, solving the multi-vehicle cooperation problem usually can't meet the real-time requirement. To efficiently solve this problem, this paper proposes a self-organizing cooperative c...Show More

A Self-organizing Cooperative Control Framework for Connected Automated Vehicles at Unsignalized Roundabouts

Xuekai Liu;Qian Chen;Peng Hang;Lu Xiong;Jian Sun

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2024 | Conference Paper |

Stability Enhanced Hierarchical Reinforcement Learning for Autonomous Driving with Parameterized Trajectory Action

Guizhe Jin;Zhuoren Li;Bo Leng;Wei Han;Lu Xiong;Jia Hu;Nan Li

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2024 | Conference Paper |

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Reinforcement Learning (RL) has become a potential method for autonomous driving to adapt to complex driving environments with high flexibility. However, the popular RL paradigm directly outputting the vehicle control commands makes the future motion with fluctuation. To improve the driving behavior stability of RL method while ensuring the motion flexibility, this paper proposes a stability enhan...Show More

Stability Enhanced Hierarchical Reinforcement Learning for Autonomous Driving with Parameterized Trajectory Action

Guizhe Jin;Zhuoren Li;Bo Leng;Wei Han;Lu Xiong;Jia Hu;Nan Li

2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC)

Year: 2024 | Conference Paper |

Handling Enhancement through Active Rear-Wheel Steering with 4WS Vehicle Reference Model

Jing Cao;Yujie Cao;Bo Leng;Ming Liu;Huanxi Wen;Lu Xiong;Yi Luo

2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2024 | Conference Paper |

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Active Rear Steering (ARS) is an effective means to enhance vehicle steering responsiveness. To fully explore the handling characteristics of four-wheel steering (4WS) vehicles, this paper proposes an ARS control approach founded on a time-varying parameter reference model for 4WS vehicles, with the controller employing model predictive control (MPC). This reference model is established by analyzi...Show More

Handling Enhancement through Active Rear-Wheel Steering with 4WS Vehicle Reference Model

Jing Cao;Yujie Cao;Bo Leng;Ming Liu;Huanxi Wen;Lu Xiong;Yi Luo

2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2024 | Conference Paper |

High-Precision Dynamics Modeling of Electric Vehicle Based on Hybrid Physical and Data-Driven Methods

Langtao Tan;Bo Leng;Ming Liu;Xihua Hu;Huanxi Wen;Lu Xiong;Kuifeng Su;Chufan Guo

2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2024 | Conference Paper |

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Vehicle modeling is a key technology in the field of vehicle dynamics control, and high-precision vehicle modeling not only accelerates the iteration of dynamics control algorithms during the simulation development phase, but also improves the accuracy of model-based vehicle dynamics control methods. In recent years, the introduction of data-driven methods in vehicle dynamics has provided new idea...Show More

High-Precision Dynamics Modeling of Electric Vehicle Based on Hybrid Physical and Data-Driven Methods

Langtao Tan;Bo Leng;Ming Liu;Xihua Hu;Huanxi Wen;Lu Xiong;Kuifeng Su;Chufan Guo

2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2024 | Conference Paper |

Preview Longitudinal Control with Delay Compensation for Intelligent Connected Vehicle Under Cloud Control

Yu Che;Peizhi Zhang;Xinrui Zhang;Zhuoren Li;Bo Leng;Lu Xiong

2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2024 | Conference Paper |

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Communication delay significantly affects tracking control accuracy and system stability of intelligent connected vehicles (ICVs) in a cloud control environment. Without properly compensating for the delay, it can lead to instability or limit the vehicle's driving speed. In this paper, we propose a vehicle longitudinal control method considering delay to ensure the accuracy and comfort of ICV s sp...Show More

Preview Longitudinal Control with Delay Compensation for Intelligent Connected Vehicle Under Cloud Control

Yu Che;Peizhi Zhang;Xinrui Zhang;Zhuoren Li;Bo Leng;Lu Xiong

2024 8th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2024 | Conference Paper |

Nonlinear Model Predictive Clamping Force Control for Electromechanical Brake System

Wenpeng Wei;Tianyi He;Yifan Men;Jinxiang Wang;Lu Xiong;Guodong Yin

2024 International Conference on Advanced Robotics and Mechatronics (ICARM)

Year: 2024 | Conference Paper |

Cited by: Papers (1)

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In this paper, the problem of clamping force control for the Electromechanical Brake (EMB) system in autonomous vehicles is addressed. A nonlinear model predictive control framework is proposed to solve for the optimal maneuver at each optimization step to realize accurate clamping force tracking. First, the EMB system is modeled to a state-space representation through the first-principle modeling...Show More

Nonlinear Model Predictive Clamping Force Control for Electromechanical Brake System

Wenpeng Wei;Tianyi He;Yifan Men;Jinxiang Wang;Lu Xiong;Guodong Yin

2024 International Conference on Advanced Robotics and Mechatronics (ICARM)

Year: 2024 | Conference Paper |

DiffusionRegPose: Enhancing Multi-Person Pose Estimation Using a Diffusion-Based End-to-End Regression Approach

Dayi Tan;Hansheng Chen;Wei Tian;Lu Xiong

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2024 | Conference Paper |

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This paper presents the DiffusionRegPose, a novel approach to multi-person pose estimation that converts a one-stage, end-to-end keypoint regression model into a diffusion-based sampling process. Existing one-stage deterministic re-gression methods, though efficient, are often prone to missed or false detections in crowded or occluded scenes, due to their inability to reason pose ambiguity. To add...Show More

DiffusionRegPose: Enhancing Multi-Person Pose Estimation Using a Diffusion-Based End-to-End Regression Approach

Dayi Tan;Hansheng Chen;Wei Tian;Lu Xiong

2024 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)

Year: 2024 | Conference Paper |

Cloud Control with Communication Delay Prediction for Intelligent Connected Vehicles*

Xinrui Zhang;Lu Xiong;Peizhi Zhang;Bo Leng;Yu Che

2024 IEEE Intelligent Vehicles Symposium (IV)

Year: 2024 | Conference Paper |

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In this paper, we propose a cloud control method with communication delay prediction for intelligent connected vehicles (ICVs), which not only constructs a prediction model using real-world 5G communication delay data, but also evaluate the effectiveness of the cloud control method considering delay in typical application scenarios. Firstly, for the application data interaction of 5G vehicle-to-ne...Show More

Cloud Control with Communication Delay Prediction for Intelligent Connected Vehicles*

Xinrui Zhang;Lu Xiong;Peizhi Zhang;Bo Leng;Yu Che

2024 IEEE Intelligent Vehicles Symposium (IV)

Year: 2024 | Conference Paper |

An Efficient Two-Layer Optimal Torque Split Strategy for PHEV Considering Time-Delay Compensation

Shengru Chen;Ronghui Zhang;Chuan Hu;Lu Xiong;Zhijun Qiu;Guodong Yin

IEEE Transactions on Vehicular Technology

Year: 2024 | Volume: 73, Issue: 11 | Journal Article |

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Improper torque division strategy in vehicles leads to unnecessary energy consumption as well as poor driving comfort and safety. Previous research ignores the time-delay phenomenon of vehicle power systems, hindering the further improvement of related performance. In this work, an efficient two-layer torque split strategy with the consideration of the time-delay phenomenon is proposed to improve ...Show More

An Efficient Two-Layer Optimal Torque Split Strategy for PHEV Considering Time-Delay Compensation

Shengru Chen;Ronghui Zhang;Chuan Hu;Lu Xiong;Zhijun Qiu;Guodong Yin

IEEE Transactions on Vehicular Technology

Year: 2024 | Volume: 73, Issue: 11 | Journal Article |

Driver Distraction Behavior Recognition for Autonomous Driving: Approaches, Datasets and Challenges

Dayi Tan;Wei Tian;Cong Wang;Long Chen;Lu Xiong

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

Cited by: Papers (1)

Driver distraction behavior recognition is currently a significant study area that involves analyzing and identifying various movements, actions, and patterns exhibited by drivers while operating vehicles. This field has received considerable attention due to its potential to enhance driving safety through driver monitoring tasks, widely implemented in advanced driver assistance systems and autono...Show More

Driver Distraction Behavior Recognition for Autonomous Driving: Approaches, Datasets and Challenges

Dayi Tan;Wei Tian;Cong Wang;Long Chen;Lu Xiong

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Early Access Article |

EPro-PnP: Generalized End-to-End Probabilistic Perspective-N-Points for Monocular Object Pose Estimation

Hansheng Chen;Wei Tian;Pichao Wang;Fan Wang;Lu Xiong;Hao Li

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Early Access Article |

Cited by: Papers (3)

Locating 3D objects from a single RGB image via Perspective-n-Point (PnP) is a long-standing problem in computer vision. Driven by end-to-end deep learning, recent studies suggest interpreting PnP as a differentiable layer, allowing for partial learning of 2D-3D point correspondences by backpropagating the gradients of pose loss. Yet, learning the entire correspondences from scratch is highly chal...Show More

EPro-PnP: Generalized End-to-End Probabilistic Perspective-N-Points for Monocular Object Pose Estimation

Hansheng Chen;Wei Tian;Pichao Wang;Fan Wang;Lu Xiong;Hao Li

IEEE Transactions on Pattern Analysis and Machine Intelligence

Year: 2024 | Early Access Article |

An Integrated of Decision Making and Motion Planning Framework for Enhanced Oscillation-Free Capability

Zhuoren Li;Jia Hu;Bo Leng;Lu Xiong;Zhiqiang Fu

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 6 | Journal Article |

Cited by: Papers (4)

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Autonomous driving requires efficient and safe decision making and motion planning in dynamic and uncertain environments. Future movement of surrounding vehicles is often difficult to represent. Besides, most existing studies consider decision making and planning/control separately. Both them may lead to the oscillation and unsafe for autonomous driving. This paper proposes an integrated framework...Show More

An Integrated of Decision Making and Motion Planning Framework for Enhanced Oscillation-Free Capability

Zhuoren Li;Jia Hu;Bo Leng;Lu Xiong;Zhiqiang Fu

IEEE Transactions on Intelligent Transportation Systems

Year: 2024 | Volume: 25, Issue: 6 | Journal Article |

4DRVO-Net: Deep 4D Radar–Visual Odometry Using Multi-Modal and Multi-Scale Adaptive Fusion

Guirong Zhuo;Shouyi Lu;Huanyu Zhou;Lianqing Zheng;Mingyu Zhou;Lu Xiong

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Volume: 9, Issue: 6 | Journal Article |

Cited by: Papers (7)

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Four-dimensional (4D) radar–visual odometry (4DRVO) integrates complementary information from 4D radar and cameras, making it an attractive solution for achieving accurate and robust pose estimation. However, 4DRVO may exhibit significant tracking errors owing to three main factors: 1) sparsity of 4D radar point clouds; 2) inaccurate data association and insufficient feature interaction between th...Show More

4DRVO-Net: Deep 4D Radar–Visual Odometry Using Multi-Modal and Multi-Scale Adaptive Fusion

Guirong Zhuo;Shouyi Lu;Huanyu Zhou;Lianqing Zheng;Mingyu Zhou;Lu Xiong

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Volume: 9, Issue: 6 | Journal Article |

Efficient Deep-Learning 4D Automotive Radar Odometry Method

Shouyi Lu;Guirong Zhuo;Lu Xiong;Xichan Zhu;Lianqing Zheng;Zihang He;Mingyu Zhou;Xinfei Lu;Jie Bai

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Volume: 9, Issue: 1 | Journal Article |

Cited by: Papers (9)

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Odometry is a crucial technology for the autonomous positioning of intelligent vehicles. While estimating the odometry from LiDAR and cameras has progressed recently, it remains to be seen how to estimate the odometry from a 4D radar, an emerging sensor with unique advantages over cameras and LiDAR. In this study, a deep-learning-based 4D radar odometry method, named 4DRO-Net, is proposed. The met...Show More

Efficient Deep-Learning 4D Automotive Radar Odometry Method

Shouyi Lu;Guirong Zhuo;Lu Xiong;Xichan Zhu;Lianqing Zheng;Zihang He;Mingyu Zhou;Xinfei Lu;Jie Bai

IEEE Transactions on Intelligent Vehicles

Year: 2024 | Volume: 9, Issue: 1 | Journal Article |

Nonlinear Model Predictive Path-Following Control with Steering Lag Compensation for Autonomous Vehicles

Lu Xiong;Yuqin Qi;Bo Leng;Xing Yang;Ming Liu;Yi Luo

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

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Autonomous driving is a cutting-edge field of automotive intelligence development that can effectively improve driving safety and alleviate traffic congestion. Path-following control is a vital control task for autonomous vehicles. However, the lag of the steering actuator can deteriorate path-following accuracy and system stability. This paper presents an efficient path-following control strategy...Show More

Nonlinear Model Predictive Path-Following Control with Steering Lag Compensation for Autonomous Vehicles

Lu Xiong;Yuqin Qi;Bo Leng;Xing Yang;Ming Liu;Yi Luo

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

Non-uniform Image Down-sampling for Efficient Dense Perception

Yuyao Huang;Wei Tian;Lu Xiong;Kai Chen

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

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Dense perception tasks such as Semantic Segmentation, Depth Estimation and Object Detection can provide rich perceptual information for self-driving vehicles. As the Deep Neural Network is becoming a trend for these tasks, most of these networks face the great challenge of taking a balance between performance and speed. Typically, downsampling high-resolution input images before feeding it into th...Show More

Non-uniform Image Down-sampling for Efficient Dense Perception

Yuyao Huang;Wei Tian;Lu Xiong;Kai Chen

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

Safe reinforcement learning for autonomous vehicles to make lane-change decisions: Constraint based on Incomplete Information Game Theory

Ruolin Yang;Zhuoren Li;Bo Leng;Lu Xiong

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

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Autonomous Vehicles (AV) driving is one of the latest research points in variety fields, a high-qualified decision method is an essential part of the autonomous driving system. Reinforcement learning (RL) is widely used in autonomous driving decision to handle the interaction, has proved boost in application. But RL trains strategy is uninterpretable due to the stochastic exploration of learning p...Show More

Safe reinforcement learning for autonomous vehicles to make lane-change decisions: Constraint based on Incomplete Information Game Theory

Ruolin Yang;Zhuoren Li;Bo Leng;Lu Xiong

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

Maneuverability Control Through Rear Wheel Steering with Time-Varying Vehicle Parameters

Ming Liu;Bo Leng;Langtao Tan;Dong Huang;Guofang Chen;Yuanjian Zhang;Lu Xiong

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

Cited by: Papers (1)

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Through the implementation of active rear-wheel steering (ARS), the steering response of the vehicle is significantly improved. In order to enhance the maneuverability of the vehicle, a time-varying parameter-based Linear Quadratic Regulator (LQR) rear wheel steering control method is proposed in this paper. A rear wheel steering dynamic model is established to analyze the load transfer. Steady-st...Show More

Maneuverability Control Through Rear Wheel Steering with Time-Varying Vehicle Parameters

Ming Liu;Bo Leng;Langtao Tan;Dong Huang;Guofang Chen;Yuanjian Zhang;Lu Xiong

2023 7th CAA International Conference on Vehicular Control and Intelligence (CVCI)

Year: 2023 | Conference Paper |

An Emergency Collision-Avoidance Controller for Distributed Drive Autonomous Vehicles Based on AFS and DYC

Zhuoping Yu;Peng Han;Bo Leng;Ming Liu;Lu Xiong;Bing Li

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

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An emergency collision avoidance controller which integrates trajectory planning and tracking based on Model Predictive Control (MPC) is proposed. A collision avoidance safety domain considering vehicle’s space safety and stability safety is established as safety constraints. Moreover, the proposed controller combines Active Front Steering (AFS) and Direct Yaw-moment Control (DYC) to improve yaw r...Show More

An Emergency Collision-Avoidance Controller for Distributed Drive Autonomous Vehicles Based on AFS and DYC

Zhuoping Yu;Peng Han;Bo Leng;Ming Liu;Lu Xiong;Bing Li

2023 35th Chinese Control and Decision Conference (CCDC)

Year: 2023 | Conference Paper |

A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

Wei Liu;Min Hua;Zhiyun Deng;Zonglin Meng;Yanjun Huang;Chuan Hu;Shunhui Song;Letian Gao;Changsheng Liu;Bin Shuai;Amir Khajepour;Lu Xiong;Xin Xia

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 24 | Journal Article |

Cited by: Papers (52)

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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 comfort, transportation efficiency, and energy saving. This survey attempts to provide a comprehensive and thorough overview of the current state of vehicle control technology, focusing on the evolution from vehicle state ...Show More

A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles

Wei Liu;Min Hua;Zhiyun Deng;Zonglin Meng;Yanjun Huang;Chuan Hu;Shunhui Song;Letian Gao;Changsheng Liu;Bin Shuai;Amir Khajepour;Lu Xiong;Xin Xia

IEEE Internet of Things Journal

Year: 2023 | Volume: 10, Issue: 24 | Journal Article |

Integrated Decision Making and Planning Based on Feasible Region Construction for Autonomous Vehicles Considering Prediction Uncertainty

Lu Xiong;Yixuan Zhang;Yuanzhi Liu;Hongyu Xiao;Chen Tang

IEEE Transactions on Intelligent Vehicles

Year: 2023 | Volume: 8, Issue: 11 | Journal Article |

Cited by: Papers (4)

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For autonomous vehicles, scene understanding is still one of the major challenges, which needs to be well handled to avoid jittery decisions and unsmooth trajectories. Furthermore, uncertainty in trajectory prediction of traffic participants directly affects decision results, and thus contributes to safety, comfort and efficiency. This article proposes an integrated decision-making and planning (D...Show More

Integrated Decision Making and Planning Based on Feasible Region Construction for Autonomous Vehicles Considering Prediction Uncertainty

Lu Xiong;Yixuan Zhang;Yuanzhi Liu;Hongyu Xiao;Chen Tang

IEEE Transactions on Intelligent Vehicles

Year: 2023 | Volume: 8, Issue: 11 | Journal Article |

Tire-Road Peak Adhesion Coefficient Estimation Based on Multisource Information Assessment

Bo Leng;Cheng Tian;Xinchen Hou;Lu Xiong;Wenrui Zhao;Zhuoping Yu

IEEE Transactions on Intelligent Vehicles

Year: 2023 | Volume: 8, Issue: 7 | Journal Article |

Cited by: Papers (10)

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The tire-road peak adhesion coefficient (TRPAC) is defined as the ratio of the peak adhesion to the vertical load of the tire, which can characterize the ability of a tire to adhere to the road. Reliable TRPAC estimation can not only benefit the vehicle active safety system, but also serve the intelligent transportation system to improve the safety of traffic participants. Considering the problems...Show More

Tire-Road Peak Adhesion Coefficient Estimation Based on Multisource Information Assessment

Bo Leng;Cheng Tian;Xinchen Hou;Lu Xiong;Wenrui Zhao;Zhuoping Yu

IEEE Transactions on Intelligent Vehicles

Year: 2023 | Volume: 8, Issue: 7 | Journal Article |

An Efficient Trajectory-Planning Method With a Reconfigurable Model for Any Tractor-Trailer Vehicle

Xinyao Ruan;Yanjun Huang;Yulei Wang;Zhiqiang Fu;Lu Xiong;Zhuoping Yu

IEEE Transactions on Transportation Electrification

Year: 2023 | Volume: 9, Issue: 2 | Journal Article |

Cited by: Papers (5)

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Trajectory planning for a tractor-trailer vehicle (TTV) is a tough task even in a static environment because of its complicated kinematic constraints. This article aims to efficiently plan an optimal trajectory with a reconfigurable model for any TTV in the static environment. A reconfigurable modeling method is first proposed to simulate the TTV with an arbitrary number of trailers and hitching m...Show More

An Efficient Trajectory-Planning Method With a Reconfigurable Model for Any Tractor-Trailer Vehicle

Xinyao Ruan;Yanjun Huang;Yulei Wang;Zhiqiang Fu;Lu Xiong;Zhuoping Yu

IEEE Transactions on Transportation Electrification

Year: 2023 | Volume: 9, Issue: 2 | Journal Article |

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