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

129 citations · 276 across the 10 of their papers we have counts for

collaborators

11 papers

cs.RO2026

From Optimizable to Interactable: Mixed Digital Twin-Empowered Testing of Vehicle-Infrastructure Cooperation Systems

Jianghong Dong, Chunying Yang, Mengchi Cai +4

Sufficient testing under corner cases is critical for the long-term operation of vehicle-infrastructure cooperation systems (VICS). However, existing corner-case generation methods…

cs.RO2026

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…

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

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…

cs.LG2023★ 75 cited

Distributional Soft Actor-Critic with Three Refinements

Jingliang Duan, Wenxuan Wang, Liming Xiao +6

Reinforcement learning (RL) has shown remarkable success in solving complex decision-making and control tasks. However, many model-free RL algorithms experience performance degrada…

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…

cs.RO2022★ 69 cited

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…

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…

math.OC2021★ 3 cited

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…

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…