129 citations · 368 across the 26 of their papers we have counts for
27 papers
High-dimensional Multi-objective Bayesian Optimization with Learned Variable Interactions
Hongyan Wang, Jiayu Huang, Haotian Zheng +6
Multi-objective Bayesian optimization (MOBO) is effective in identifying the Pareto fronts for expensive black-box problems. However, most current MOBO approaches are limited to lo…
Robust Nonlinear Data-Driven Predictive Control for Mixed Vehicle Platoons via Koopman Operator and Reachability Analysis
Shuai Li, Jiawei Wang, Kaidi Yang +3
Mixed vehicle platoons, comprising connected and automated vehicles (CAVs) and human-driven vehicles (HDVs), hold significant potential for enhancing traffic performance. However,…
Mixed Platoon Control under Noise and Attacks: Robust Data-Driven Predictive Control and Human-in-the-Loop Validation
Shuai Li, Chaoyi Chen, Haotian Zheng +4
Controlling mixed platoons, which consist of both connected and automated vehicles (CAVs) and human-driven vehicles (HDVs), poses significant challenges due to the uncertain and un…
Vision-Driven 2D Supervised Fine-Tuning Framework for Bird's Eye View Perception
Lei He, Qiaoyi Wang, Honglin Sun +5
Visual bird's eye view (BEV) perception, due to its excellent perceptual capabilities, is progressively replacing costly LiDAR-based perception systems, especially in the realm of…
Hierarchical and Decoupled BEV Perception Learning Framework for Autonomous Driving
Yuqi Dai, Jian Sun, Shengbo Eben Li +4
Perception is essential for autonomous driving system. Recent approaches based on Bird's-eye-view (BEV) and deep learning have made significant progress. However, there exists chal…
OE-BevSeg: An Object Informed and Environment Aware Multimodal Framework for Bird's-eye-view Vehicle Semantic Segmentation
Jian Sun, Yuqi Dai, Chi-Man Vong +5
Bird's-eye-view (BEV) semantic segmentation is becoming crucial in autonomous driving systems. It realizes ego-vehicle surrounding environment perception by projecting 2D multi-vie…
Robust Data-EnablEd Predictive Leading Cruise Control via Reachability Analysis
Shuai Li, Chaoyi Chen, Haotian Zheng +3
Data-driven predictive control promises model-free wave-dampening strategies for Connected and Autonomous Vehicles (CAVs) in mixed traffic flow. However, its performance relies on…
Information Flow Topology in Mixed Traffic: A Comparative Study between "Looking Ahead" and "Looking Behind"
Shuai Li, Haotian Zheng, Jiawei Wang +4
The emergence of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic where human-driven vehicles (HDVs) also exist, existing research mostly fo…
Cloud Control of Connected Vehicle under Bi-directional Time-varying delay: An Application of Predictor-observer Structured Controller
Ji-An Pan, Qing Xu, Keqiang Li +2
This article is devoted to addressing the cloud control of connected vehicles, specifically focusing on analyzing the effect of bi-directional communication-induced delays. To miti…
Mixed Cloud Control Testbed: Validating Vehicle-Road-Cloud Integration via Mixed Digital Twin
Jianghong Dong, Qing Xu, Jiawei Wang +5
Reliable and efficient validation technologies are critical for the recent development of multi-vehicle cooperation and vehicle-road-cloud integration. In this paper, we introduce…
Distributed data-driven predictive control for cooperatively smoothing mixed traffic flow
Jiawei Wang, Yingzhao Lian, Yuning Jiang +3
Cooperative control of connected and automated vehicles (CAVs) promises smoother traffic flow. In mixed traffic, where human-driven vehicles with unknown dynamics coexist, data-dri…
Implementation and Experimental Validation of Data-Driven Predictive Control for Dissipating Stop-and-Go Waves in Mixed Traffic
Jiawei Wang, Yang Zheng, Jianghong Dong +4
In this paper, we present the first experimental results of data-driven predictive control for connected and autonomous vehicles (CAVs) in dissipating traffic waves. In particular,…
DeeP-LCC: Data-EnablEd Predictive Leading Cruise Control in Mixed Traffic Flow
Jiawei Wang, Yang Zheng, Keqiang Li +1
For the control of connected and autonomous vehicles (CAVs), most existing methods focus on model-based strategies. They require explicit knowledge of car-following dynamics of hum…
Experimental Validation of Multi-lane Formation Control for Connected and Automated Vehicles in Multiple Scenarios
Mengchi Cai, Qing Xu, Chunying Yang +5
Formation control methods of connected and automated vehicles have been proposed to smoothly switch the structure of vehicular formations in different scenarios. In the previous re…
Multi-vehicle experiment platform: A Digital Twin Realization Method
Chunying Yang, Jianghong Dong, Qing Xu +4
With the development of V2X technology, multiple vehicles cooperative control has been widely studied. However, filed testing is rarely conducted due to financial and safety consid…
Data-Driven Predictive Control for Connected and Autonomous Vehicles in Mixed Traffic
Jiawei Wang, Yang Zheng, Qing Xu +1
Cooperative control of Connected and Autonomous Vehicles (CAVs) promises great benefits for mixed traffic. Most existing research focuses on model-based control strategies, assumin…
Cooperation Method of Connected and Automated Vehicles at Unsignalized Intersections: Lane Changing and Arrival Scheduling
Chaoyi Chen, Mengchi Cai, Jiawei Wang +4
The cooperation of connected and automated vehicles (CAVs) has shown great potential in improving traffic efficiency during intersection management. Existing research mainly focuse…
Multi-lane Unsignalized Intersection Cooperation with Flexible Lane Direction based on Multi-vehicle Formation Control
Mengchi Cai, Qing Xu, Chaoyi Chen +4
Unsignalized intersection cooperation of connected and automated vehicles (CAVs) is able to eliminate green time loss of signalized intersections and improve traffic efficiency. Mo…
Conflict-free Cooperation Method for Connected and Automated Vehicles at Unsignalized Intersections: Graph-based Modeling and Optimality Analysis
Chaoyi Chen, Qing Xu, Mengchi Cai +4
Connected and automated vehicles have shown great potential in improving traffic mobility and reducing emissions, especially at unsignalized intersections. Previous research has sh…
Formation Control with Lane Preference for Connected and Automated Vehicles in Multi-lane Scenarios
Mengchi Cai, Chaoyi Chen, Jiawei Wang +4
Multi-lane roads are typical scenarios in the real-world traffic system. Vehicles usually have preference on lanes according to their routes and destinations. Few of the existing s…
Formation Control for Connected and Automated Vehicles on Multi-lane Roads: Relative Motion Planning and Conflict Resolution
Mengchi Cai, Qing Xu, Chaoyi Chen +4
Multi-vehicle coordinated decision making and control can improve traffic efficiency while guaranteeing driving safety. Formation control is a typical multi-vehicle coordination me…
A Graph-based Conflict-free Cooperation Method for Intelligent Electric Vehicles at Unsignalized Intersections
Chaoyi Chen, Qing Xu, Mengchi Cai +6
Electric, intelligent, and network are the most important future development directions of automobiles. Intelligent electric vehicles have shown great potentials to improve traffic…
Leading Cruise Control in Mixed Traffic Flow: System Modeling, Controllability, and String Stability
Jiawei Wang, Yang Zheng, Chaoyi Chen +2
Connected and autonomous vehicles (CAVs) have great potential to improve road transportation systems. Most existing strategies for CAVs' longitudinal control focus on downstream tr…
Coordinated Formation Control for Intelligent and Connected Vehicles in Multiple Traffic Scenarios
Qing Xu, Mengchi Cai, Keqiang Li +3
In this paper, a unified multi-vehicle formation control framework for Intelligent and Connected Vehicles (ICVs) that can apply to multiple traffic scenarios is proposed. In the on…