Preprints

• “Predictive Trajectory Planning for Vehicles at Intersections with Deep Reinforcement Learning“, Zhang, Ethan, Ruixuan Zhang, and Neda Masoud. (Coming soon)

Manuscripts

• “Predicting Risky Driving in a Connected Vehicle Environment” Zhang, Ethan, Neda Masoud, Mahdi Bandegi, and Rajesh K. Malhan. IEEE Transactions on Intelligent Transportation Systems, 2022
• “Step Attention: Sequential Pedestrian Trajectory Prediction.” Zhang, Ethan, Neda Masoud, Mahdi Bandegi, Joseph Lull, and Rajesh K. Malhan. IEEE Sensors Journal, 2022.
• “A Learning-based Trajectory Prediction Approach for Heterogeneous Traffic Agents: Implications for Transfer Learning.” Zhang, Ethan, Sion Pizzi, and Neda Masoud. 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), 2021.
• “Increasing GPS Localization Accuracy With Reinforcement Learning.” Zhang, Ethan, and Neda Masoud. IEEE Transactions on Intelligent Transportation Systems, 2020.
• “V2Xsim: A V2X Simulator for Connected and Automated Vehicle Environment Simulation.“ Zhang, Ethan, and Neda Masoud. 2020 IEEE International Intelligent Transportation Systems Conference (ITSC), 2020.
• “Parallel Computing Algorithm for Real-time Mapping between Large-scale Networks.” Zhang, Ethan, Amirmahdi Tafreshian, and Neda Masoud. 2019 IEEE Intelligent Transportation Systems Conference (ITSC), 2019.

Patents

• “System for Predicting Aggressive Driving.” Ethan Zhang, Neda Masoud, Wei Zhang, and Rajesh Kumar Malhan. US Patent App. 17/006,470 (2021)
• “Sequential pedestrian trajectory prediction using step attention for collision avoidance“, Ethan Zhang, Neda Masoud and Rajesh Kumar Malhan, filed (2022).