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Haoji's Homepage
Haoji Liu
Ph.D. student in Systems Engineering
Department of Systems and Information Engineering
Unversity of Virginia
Email: haojiliu@email.virginia.edu
Hi there! I am Haoji Liu, a first-year Ph.D. student in Systems and Information Engineering at the University of Virginia (UVA). Prior to UVA, I received my master's degree in Mechanical Engineering from Southeast University, China in 2022. I was with the Research Center for Intelligent Eletrified Mobility, where I worked with Prof. Guodong Yin and Associate Prof. Weichao Zhuang. My previous research works focus on vehicle dynamics and control, and cooperative control for connected automated vehicles (CAVs) in mixed traffic.
Research Bio | Keywords: connected automated vehicles (CAVs), cooperative driving, eco-driving, mixed traffic.
My research endeavors to bridge the gap between microscopic vehicle control and macroscopic traffic harmonization. I am interested in leveraging control theory and reinforcement learning techniques to explore how cooperative control of CAVs can transform future transportation systems in terms of safety, efficiency, ecology, and equity. Currently, my research encompasses the following areas:
1) Cooperative formation and platooning of CAVs in mixed traffic flow;
2) Cooperative merging of CAVs in mixed traffic;
3) Cooperative energy-efficient driving for connected vehicles.
I'm willing to discuss and collaborate with fellow researchers! Please feel free to reach out via email!
News
May 2024- I served as a Session Chair for the Optimization, Data, and System Design session at 2024 IEEE Systems and Information Engineering Design Symposium.
Mar. 2024- Our paper entitled "Evaluation of Connected Vehicle Identification-Aware Mixed Traffic Freeway Cooperative Merging" was accepted by 2024 35th IEEE Intelligent Vehicles Symposium (IV) [arXiv]
Feb. 2024- Our paper on energy-oriented driving strategy for connected electric vehicles was published in Energy [Online]
Feb. 2024- Our paper on eco-routing strategy for vehicles with different powertrain types was accepted by Energy [Online]
Nov. 2023- Our paper on eco-routing for electric vehicles using deep reinforcement learning was published in Applied Energy [Online]
Oct. 2023- Our paper on traffic-aware ecological cruising control was published in IEEE Transactions on Transportation Electrification [Online]
Aug. 2023- Moved to Charlottesville to begin my PhD research journey!
Feb. 2023- Our paper on cooperative on-ramp merging in mixed traffic was published in IEEE Transactions on Intelligent Transportation Systems [Online]
Selected Publications
Safety-Critical and Flexible Cooperative On-Ramp Merging Control of Connected and Automated Vehicles in Mixed Traffic
Haoji Liu, Weichao Zhuang, Guodong Yin, Zhaojian Li, and Dongpu Cao.
IEEE Transactions on Intelligent Transportation Systems, March 2023. [IF: 8.5]
Revealed the advantage of the flexible-position merging policy for CAVs in mixed traffic.
Proposed a hierarchical cooperation framework to achieve safety-critical and flexible cooperative merging by exploiting optimal control and safe barriers.
Decentralized On-Ramp Merging Control of Connected and Automated Vehicles in the Mixed Traffic Using Control Barrier Functions
Haoji Liu, Weichao Zhuang, Guodong Yin, Rongcan Li, Chang Liu, and Shanxing Zhou.
2021 IEEE International Intelligent Transportation Systems Conference (ITSC).
Proposed a cooperative on-ramp merging strategy for nonlinear CAV systems in mixed traffic considering safety-critical constraints and objectives, by utilizing control barrier functions and control Lyapunov functions.
Energy-optimal routing for electric vehicles using deep reinforcement learning with transformer
Mengcheng Tang, Weichao Zhuang, Bingbing Li, Haoji Liu, Ziyou Song, and Guodong Yin.
Applied Energy, Nov. 2023. [IF: 11.2]
Build an energy consumption model of electric vehicle for Electric Vehicle Routing Problem (EVRP).
Proposed a deep reinforcement learning with transformer-based neural network to solve the Electric Vehicle Routing Problem.
A comparative study of energy-oriented driving strategy for connected electric vehicles on freeways with varying slopes
Bingbing Li, Weichao Zhuang, Hao Zhang, Ruixuan Zhao, Haoji Liu, Linghu Qu, Jianrun Zhang, and Boli Chen.
Energy, Feb. 2024. [IF: 9.0]
Developed the Normalized-Energy Consumption Minimization Strategy (NCMS), utilizing a kinetic energy conversion factor for efficient energy-oriented vehicle control.
Proposed an Improved Model Predictive Control (MPC) with a hierarchical framework, striking a balance between optimization and computational efficiency for real-time adaptability.