Xuerun Yan

ORCID: 0009-0000-1515-4019
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About
Contact & Profiles
Research Areas
  • Traffic control and management
  • Autonomous Vehicle Technology and Safety
  • Transportation Planning and Optimization
  • Vehicle emissions and performance
  • Real-time simulation and control systems
  • Transportation and Mobility Innovations
  • Reinforcement Learning in Robotics
  • Traffic Prediction and Management Techniques
  • Safety Systems Engineering in Autonomy
  • Traffic and Road Safety
  • Human-Automation Interaction and Safety
  • Energy, Environment, and Transportation Policies
  • Vehicle Dynamics and Control Systems
  • Software Testing and Debugging Techniques

Tongji University
2022-2025

Truck platooning is a promising technology in freight transport. To commercialize truck as early possible, its evaluation urgent need. For evaluation, simulation platforms play crucial role. However, there has not been platform to meet the needs of various stakeholders, including Original Equipment Manufacturers (OEMs), Freight Operators (FOs) and Transportation Management Administrations (TMAs). fill research gap, this paper proposes next-generation platform. It integrates traffic...

10.1109/tits.2024.3388161 article EN IEEE Transactions on Intelligent Transportation Systems 2024-04-24

A cooperative adaptive cruise control (CACC) system may be impeded by slow-moving traffic in the application. To improve mobility of CACC, this research proposes a CACC controller with successive platoon lane-change capability. The goal is to help cut through successively like snake via smaller windows. proposed has following features: i) capability; ii) string stability and lateral stability; iii) consideration vehicle dynamics. evaluated on simulation platform context joint consisting...

10.1080/15472450.2022.2114081 article EN Journal of Intelligent Transportation Systems 2022-08-24

10.4271/12-06-01-0006 article EN SAE International Journal of Connected and Automated Vehicles 2022-04-20

Reinforcement Learning (RL) offers a promising solution to enable evolutionary automated driving. However, the conventional RL method is always concerned with risk performance. The updated policy may not obtain performance enhancement, even leading deterioration. To address this challenge, research proposes High Confidence Policy Improvement Learning-based (HCPI-RL) planner. It intended achieve monotonic evolution of A novel update paradigm designed newly learned consistently surpass that...

10.48550/arxiv.2412.10822 preprint EN arXiv (Cornell University) 2024-12-14

Truck platooning is a promising technology in freight transport, and needs to be commercialized as earlier possible. Therefore, the evaluation of truck urgent needs. To conduct evaluation, simulation platforms play an important role. This paper proposes next-generation platform for evaluation. The proposed bears following features: i) compatibility with various decision-makers controllers; ii) modularized design manufactures; iii) able evaluate platoon performance on lateral dimension....

10.1109/itsc55140.2022.9921956 article EN 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) 2022-10-08

Automated Vehicle (AV) safety is a matter of great importance and has garnered global attention. To ensure the AVs, extensive testing evaluation AV functions across wide range scenarios are necessary. However, conducting such tests time-consuming. In order to streamline process, scenario filters have been developed identify prioritize safety-critical while excluding ordinary ones. Nevertheless, existing do not offer sufficient coverage critical scenarios. Hence, this paper introduces filter...

10.1109/itsc57777.2023.10422068 article EN 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) 2023-09-24

An eco-CACC controller is established to realize cooperative adaptive cruising with enhanced fuel efficiency on rolling terrain. It has the following features: i) better performance terrain; ii) fuel-saving benefits; iii) ready for real-time implementation while guaranteeing optimality; iv) enabling transportation mobility and ecology improvement. The of proposed was evaluated. influence different road types analyzed. Experiment results showed that applying system can improve economy...

10.1109/itsc57777.2023.10422405 article EN 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC) 2023-09-24
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