Yongqi Dong

Yongqi Dong

Ph.D. Researcher at TU Delft, Visiting Scholar at UC Berkeley

Publications

My publications will be regularly updated on Google Scholar profile and ResearchGate profile.

Working Papers

  1. Dong, Y., Farah, H., & van Arem, B. (2023). “Safe and Socially-compliant Automated Driving through Integrating Deep Reinforcement Learning with SVO and MPCC”, in preparation, to be submitted to The Proceedings of the National Academy of Sciences, PNAS.
  2. Dong, Y., Farah, H., & van Arem, B. (2023). “Towards Developing Socially-Compliant Automated Vehicles: State of the Practice, Experts Expectations, and a Conceptual Framework”, accepted by the 4th Symposium on Management of Future Motorway and Urban Traffic Systems 2022 (MFTS2022), to be submitted to Journal of Transport Reviews.
  3. Patil, S.#, Dong, Y.#,*, Farah, H., & Hellendoorn, J. (2023). “Sequential Neural Network Model with Spatial-Temporal Attention Mechanism for Robust Lane Detection Using Multi Continuous Image Frames”, Joint first author and corresponding author, Accepted by the TRB 2023, Submitted to Journal of Transportation Research Part C: Emerging Technologies, Preprint.
  4. Lingam, N., de Winter, J., Dong, Y., Tsapi, A., van Arem, B., & Farah, H. (2023). “eHMI on the vehicle or just a traffic light? A driving simulator study”, Under Review by Journal of Accident Analysis & Prevention, Preprint.
  5. Dong, Y.#,*, Lu, X.#, Li, R., Song, W., van Arem, B., & Farah, H. (2023). “Intelligent Anomaly Detection for Lane Rendering Using Transformer with Self-Supervised Pre-Training and Customized Fine-Tuning”, accepted by TRB2024 and under review by Transportation Research Record: Journal of the Transportation Research Board, accepted (presentation) by the 23rd COTA International Conference of Transportation Professionals for presentation, CICTP 2023, Preprint.
  6. Zhang, Y., & Dong, Y.* (2023). “Optimization of coordinated flow restriction and skip-stopping schemes for urban rail stations considering platform carrying capacity”, Accepted by the TRB 2023. Under Review by Transportation Research Record: Journal of the Transportation Research Board, Preprint.
  7. Liu, W., Li, S., Dong, Y., Zhang, X., & Xu, L. (2023). “Unified Model Predictive Control Method of Automated Vehicles for Lane Changing and Lane Keeping Maneuvers”, submitted to the Journal of IEEE Transactions on Intelligent Vehicles.
  8. Zhang, L.#, Dong, Y.#,*, Farah, H., Zgonnikov, A., & van Arem, B. (2023). “Data-driven Semi-supervised Machine Learning with Surrogate Safety Measures for Abnormal Driving Behavior Detection”, Accepted for presentation at the 35th annual meeting of International Co-operation on Theories and Concepts in Traffic Safety (ICTCT Catania 2023), accepted by TRB2024 and under review by Transportation Research Record: Journal of the Transportation Research Board, Preprint.
  9. Berge, B., de Winter, J., Dodou, D., Pooyan Afghari, A., Papadimitriou, E., Reddy, N., Dong, Y., Raju, N., & Farah, H. (2023). Understanding cyclists’ perception of driverless vehicles through eye-tracking and interviews (Accepted for presentation at the 35th annual meeting of International Co-operation on Theories and Concepts in Traffic Safety (ICTCT Catania 2023), under review by Journal of Safety Science), Preprint.

Journal Papers

  1. Dong, Y., Patil, S., van Arem, B., & Farah, H. (2023). A Hybrid Spatial-temporal Deep Learning Architecture for Lane Detection. Computer-Aided Civil and Infrastructure Engineering, 38(1), pp.67–86. Q1, IF:9.6, SJR:2.962
  2. Li, R.#, & Dong, Y.#,* (2023). Robust Lane Detection through Self Pre-training with Masked Sequential Autoencoders and Fine-tuning with Customized PolyLoss. IEEE Transactions on Intelligent Transportation Systems, vol. 24, no. 12, pp. 14121-14132, DOI: https://doi.org/10.1109/TITS.2023.3305015. (Joint first author and corresponding author)
  3. Farah, H., Postigo, I., Reddy, N., Dong, Y., Rydergren, C., Raju, N. & Olstam, J. (2022). Aspects to Consider for Modeling Automated Driving in Microscopic Traffic Simulations: State of the Practice and Research Needs. IEEE Transactions on Intelligent Transportation Systems, 2022,
  4. Raju, N., Schakel, W., Reddy, N., Dong, Y., & Farah, H. (2022). Car-Following Properties of a Commercial Adaptive Cruise Control System- A Pilot Field Test. Transportation Research Record: Journal of the Transportation Research Board.
  5. Dong, Y., Wang, Sh., Li, L., & Zhang, Z. (2018). An Empirical Study on Travel Patterns of Internet Based Ride-Sharing, Transportation Research Part C: Emerging Technologies 86: 1-22. Highly cited; Q1, IF:8.3, SJR:2.882

Conference Presentations & Proceedings

  1. Zhang, L.#, Dong, Y.#,*, Farah, H., & van Arem, B. (2023). Social-aware Planning and Control for Automated Vehicles based on Driving Risk Field and Model Predictive Contouring Control: Driving through Roundabouts as a Case Study. 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Oahu, HI, USA, 2023, pp. 3297-3304. (Joint first author and corresponding author, accepted and presented at TRB’s 2023 Automated Road Transportation Symposium, Demo video).
  2. Dong, Y.#,*, Chen, K.#, & Ma, Z. (2023). Comparative Study on Semi-supervised Learning Applied for Anomaly Detection in Hydraulic Condition Monitoring System. 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), Honolulu, Oahu, HI, USA, 2023, pp. 1702-1708.
  3. Dong, Y., Li, R., & Farah, H. (2023). Robust Lane Detection through Self Pre-training with Masked Sequential Autoencoders and Fine-tuning with Customized PolyLoss. Poster session presented at The 102nd Annual Meeting Transportation Research Board, Washington DC, United States. TRBAM-23-02979 poster.
  4. Dong, Y., Datema, T., Wassenaar, V., van de Weg, J., Kopar, T., & Suleman, H. (2023). Comprehensive Training and Evaluation on Deep Reinforcement Learning for Automated Driving in Various Simulated Driving Maneuvers. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 6165-6170.
  5. Yuan, H., Li, P., van Arem, B., Kang, L., Farah, H., & Dong, Y.* (2023). Safe, Efficient, Comfort, and Energy-Saving Automated Driving Through Roundabout Based on Deep Reinforcement Learning. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 6074-6079. (Corresponding author and PI)
  6. Zhang, Y., & Dong, Y. (2023). Optimization of Coordinated Flow Control and Skip-stopping Schemes for Urban Rail Stations Considering Platform Carrying Capacity. 1-2. Poster session presented at The Transportation Research Board (TRB) 102nd Annual Meeting, Washington, D.C., District of Columbia, United States. TRBAM-23-04413 poster.
  7. Dong, Y., Patil, S., Farah, H., & Hellendoorn, J. (2023). Sequential Neural Network Model with Spatial-Temporal Attention Mechanism for Robust Lane Detection Using Multi Continuous Image Frames. 1. Poster session presented at The Transportation Research Board (TRB) 102nd Annual Meeting, Washington, D.C., District of Columbia, United States. TRBAM-23-04409 poster.
  8. Xue, C.#, Dong, Y.#, Liu, J.* , Liao, Y., & Li, L. (2023). Design of the Reverse Logistics System for Medical Waste Recycling Part I: System Architecture and Disposal Site Selection Algorithm. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 1741-1746. (Joint first author, Supplementary)
  9. Xue, C.#, Dong, Y.#, Liu, J.* , Liao, Y., & Li, L. (2023). Design of the Reverse Logistics System for Medical Waste Recycling Part II: Route Optimization with Case Study under COVID-19 Pandemic. 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), Bilbao, Spain, 2023, pp. 4011-4017. (Joint first author, Supplementary)
  10. Dong, Y., Chen, K., Peng, Y., & Ma, Z. (2022). Comparative Study on Supervised versus Semi-supervised Machine Learning for Anomaly Detection of In-vehicle CAN Network. 2022 IEEE 25th International Conference on Intelligent Transportation Systems (ITSC), 2022, pp. 2914-2919.
  11. Dong, Y., Yang, Z., Yue, Y., Pei, X., & Zhang, Z. (2018). Revealing Travel Patterns of Sharing-bikes in a Spatial-temporal Manner using Non-negative Matrix Factorization Method. In CICTP 2018: Intelligence, Connectivity, and Mobility (pp. 1665-1674). Reston, VA: American Society of Civil Engineers.
  12. Yue, Y., Pei, X., Yang, Z., Dong, Y., & Yao, D. (2018). A Trip Building and Chaining Methodology Using Traffic Surveillance Data. In CICTP 2018: Intelligence, Connectivity, and Mobility (pp. 2254-2262). Reston, VA: American Society of Civil Engineers.
  13. Dong, Y., Zhang, Z., Fu, R., & Xie, N. (2016). Revealing New York Taxi Drivers’ Operation Patterns Focusing on the Revenue Aspect. In 12th World Congress on Intelligent Control and Automation (WCICA), (pp. 1052-1057). IEEE.

Workshop

  1. Dong, Y., Farah, H., Tang, C., Huang, P., Ferranti, L., and de Groot, O. (2023). “Development of socially-compliant driving behaviour for automated vehicles to enhance safety and efficiency in mixed traffic” in IEEE Intelligent Vehicles Symposium (IV 2023).
  2. Wang, Y., Dong, Y., Rahmani, S., Martínez, I., Farah, H., Pei, X., Jia, Sh., Yu, R., Zhu M., and Stern, R. (2023). “Data-driven and Empirical Research for Emerging Mixed Traffic of Automated Vehicles and Human-driven Vehicles” in 26th IEEE International Conference on Intelligent Transportation Systems (ITSC 2023).

Patents

Chinese Invention Patent:

  1. Intelligent Demonstration Instrument of Simple Harmonic Oscillation Composition and Five Polarization States of Light, Application ID: 201310123700.5, Date: 2013.08.07, Publication Patent Number CN103236211B, Publication Patent Date: 2016.07.06.

European Patent:

  1. Automated lane detection through self supervised pre-training with masked sequential auto-encoders, fine-tuning with customized PolyLoss, and post-processing with clustering and curve fitting (IDF OCT-22-060, N2033551, submitted and filed)
  2. Socially compliant Planning and Control for Automated Vehicles using Model-backend Deep Reinforcement Learning with Driving Risk Field and Model Predictive Contouring Control (OCT-23-056, N2035943, submitted and filed)
  1. Spatial-Temporal Attention Integrated Sequential Neural Network Model for Vision-based Robust Lane Detection Using Multi Continuous Image Frames (i-DEPOT 142731, OCT-23-056, submitted and filed)

The superscript # indicates equal contribution, and * indicates corresponding author.