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Modeling Motorcyclist-Pedestrian Near Misses: A Multiagent Adversarial Inverse Reinforcement Learning Approach.

, , and . J. Comput. Civ. Eng., (2022)

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Do road users play Nash Equilibrium? A comparison between Nash and Logistic stochastic Equilibriums for multiagent modeling of road user interactions in shared spaces., and . Expert Syst. Appl., (2022)Multiple Instance Learning by Discriminative Training of Markov Networks., , , , and . UAI, AUAI Press, (2013)Modeling Motorcyclist-Pedestrian Near Misses: A Multiagent Adversarial Inverse Reinforcement Learning Approach., , and . J. Comput. Civ. Eng., (2022)Do Simulated Traffic Conflicts Predict Crashes? An Investigation Using the Extreme Value Approach., , , and . ITSC, page 631-636. IEEE, (2019)Classifying Road Users in Urban Scenes Using Movement Patterns., , and . J. Comput. Civ. Eng., 27 (4): 395-406 (2013)Florida International University - University of Miami TRECVID 2015., , , , , , , and . TRECVID, National Institute of Standards and Technology (NIST), (2015)Florida International University - University of Miami TRECVID 2013., , , , , , , , and . TRECVID, National Institute of Standards and Technology (NIST), (2013)Enforcing Traffic Safety: A Deep Learning Approach for Detecting Motorcyclists' Helmet Violations Using YOLOv8 and Deep Convolutional Generative Adversarial Network-Generated Images., , , , , and . Algorithms, 17 (5): 202 (May 2024)A Methodology for the Microscopic Calibration of Agent-Based Pedestrian Simulation Models., and . ITSC, page 3773-3778. IEEE, (2018)Comparing the Crash Risk of Vehicle-Pedestrian Interactions using Autonomous Vehicle Data., , and . IV, page 1-6. IEEE, (2023)