190 citations · 744 across the 35 of their papers we have counts for
37 papers
Orchestrating Wheeled Mobile Robots Online without Conflicts
Jianghong Dong, Yifeng Zhang, Jiawei Wang +4
Formation control of wheeled mobile robots (WMRs) has been widely studied due to its broad applications. However, existing studies primarily focus on tracking predefined formations…
Multisource human-in-the-loop digital twin testbed for connected and autonomous vehicles in mixed traffic flow
Jianghong Dong, Chunying Yang, Mengchi Cai +5
In the emerging mixed traffic environments, Connected and Autonomous Vehicles (CAVs) have to interact with surrounding human-driven vehicles (HDVs). This paper introduces MSH-MCCT…
cuNRTO: GPU-Accelerated Nonlinear Robust Trajectory Optimization
Jiawei Wang, Arshiya Taj Abdul, Evangelos A. Theodorou
Robust trajectory optimization enables autonomous systems to operate safely under uncertainty by computing control policies that satisfy the constraints for all bounded disturbance…
Towards Resilient Transportation: A Conditional Transformer for Accident-Informed Traffic Forecasting
Hongjun Wang, Jiawei Yong, Jiawei Wang +2
Traffic prediction remains a key challenge in spatio-temporal data mining, despite progress in deep learning. Accurate forecasting is hindered by the complex influence of external…
Approximation Algorithms for the UAV Path Planning with Object Coverage Constraints
Jiawei Wang, Vincent Chau, Weiwei Wu
We study the problem of the Unmanned Aerial Vehicle (UAV) such that a specific set of objects needs to be observed while ensuring a quality of observation. Our goal is to determine…
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…
Human-Machine Shared Control Approach for the Takeover of CACC
Haoran Wang, Zhexi Lian, Zhenning Li +5
Cooperative Adaptive Cruise Control (CACC) often requires human takeover for tasks such as exiting a freeway. Direct human takeover can pose significant risks, especially given the…
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…
Decentralized Robust Data-driven Predictive Control for Smoothing Mixed Traffic Flow
Xu Shang, Jiawei Wang, Yang Zheng
In a mixed traffic with connected automated vehicles (CAVs) and human-driven vehicles (HDVs) coexisting, data-driven predictive control of CAVs promises system-wide traffic perform…
UAV Path Planning for Object Observation with Quality Constraints: A Dynamic Programming Approach
Jiawei Wang, Weiwei Wu, Yijing Wang +2
This paper addresses a UAV path planning task that seeks to observe a set of objects while satisfying the observation quality constraint. A dynamic programming algorithm is propose…
Smoothing Mixed Traffic with Robust Data-driven Predictive Control for Connected and Autonomous Vehicles
Xu Shang, Jiawei Wang, Yang Zheng
The recently developed DeeP-LCC (Data-EnablEd Predictive Leading Cruise Control) method has shown promising performance for data-driven predictive control of Connected and Autonomo…
Learning Optimal Robust Control of Connected Vehicles in Mixed Traffic Flow
Jie Li, Jiawei Wang, Shengbo Eben Li +1
Connected and automated vehicles (CAVs) technologies promise to attenuate undesired traffic disturbances. However, in mixed traffic where human-driven vehicles (HDVs) also exist, t…
Feasibility of Local Trajectory Planning for Level-2+ Semi-autonomous Driving without Absolute Localization
Sheng Zhu, Jiawei Wang, Yu Yang +1
Autonomous driving has long grappled with the need for precise absolute localization, making full autonomy elusive and raising the capital entry barriers for startups. This study d…
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…
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…
Robust Dynamic Bus Control: A Distributional Multi-agent Reinforcement Learning Approach
Jiawei Wang, Lijun Sun
Bus system is a critical component of sustainable urban transportation. However, the operation of a bus fleet is unstable in nature, and bus bunching has become a common phenomenon…
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…