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Modeling Electric Vehicle Community-Charging Problem with Link-Charger-Flow Interactions: A Cross-Layer Modeling Approach
Jan 2025, Poster, Transportation Research Board Annual Meeting, D.C. Full-paper: Coming Soon #EV #Network Modeling
25TRB.pdfA Two-Stage Demand Prediction and Optimization Modeling Framework for Charging Station Location Problem
Jan 2023, Poster, Transportation Research Board Annual Meeting, D.C. Full-paper: 10.1016/j.trd.2023.103975 #EV #Machine Learning #Optimization
23_TRB.pdfAn Efficient and Explainable Ensemble Learning Model forAsphalt Pavement Condition Prediction Based on LTPP Dataset
Jan 2022, Poster, Transportation Research Board Annual Meeting, D.C. Full-paper: 10.1109/TITS.2022.3164596 #Infrastructure #Machine Learning
22TRB.pdfRapid Estimation of Road Friction for Anti-Skid Autonomous Driving
Full-paper: https://doi.org/10.1109/TITS.2019.2918567 #Infrastructure #CAV #Deep LearningÂ
A dynamic computer vision-based method is proposed to estimate road friction for autonomous vehicles (AVs), addressing the lack of real-time skid resistance measurement.
The model, trained on 100 road images, utilizes texture identification techniques and a deep neural network (TLDKNet) for accurate friction estimation, achieving 90.67% accuracy with minimal underestimation error (2.67%).
An anti-skid control framework for AVs is developed, enhancing safety during car-following and turning movements.
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