activity
20202026
most citedLeading Cruise Control in Mixed Traffic Flow: System Modeling, Controllability, and String Stability

129 citations · 368 across the 26 of their papers we have counts for

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16 papers · 1 filter

eess.SY2025

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,…

eess.SY2024

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…

eess.SY2024

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…

eess.SY2023

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…

eess.SY2023

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…

eess.SY2022

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…

eess.SY2022★ 1 cited

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,…

eess.SY2022★ 99 cited

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…

eess.SY2021★ 1 cited

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…

eess.SY2021★ 1 cited

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…

eess.SY2021★ 2 cited

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…

eess.SY2021

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…

eess.SY2021★ 2 cited

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…

eess.SY2020★ 129 cited

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…

eess.SY2020★ 3 cited

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…

eess.SY2020★ 12 cited

Leading Cruise Control in Mixed Traffic Flow

Jiawei Wang, Yang Zheng, Chaoyi Chen +2

Vehicle-to-vehicle (V2V) communications have a great potential to improve traffic system performance. Most existing work of connected and autonomous vehicles (CAVs) focused on adap…