Project: #317 Effect of Pedestrian and Crowds on Vehicle Motion and Traffic Flow Progress Report - Reporting Period Ending: Sept. 30, 2020 Principal Investigator: Umit Ozguner Status: Active Start Date: Feb. 1, 2020 End Date: June 30, 2022 Research Type: Advanced Grant Type: Research Grant Program: FAST Act - Mobility National (2016 - 2022) Grant Cycle: Mobility21 - The Ohio State University Progress Report (Last Updated: Oct. 5, 2020, 6:35 a.m.) % Project Completed to Date: 30 % Grant Award Expended: 0 % Match Expended & Document: 0 USDOT Requirements Accomplishments We have proposed a framework by incorporating an improved multi-state social force pedestrian model for the simulation of vehicle-pedestrian interaction in uncontrolled pedestrian crossing scenarios. The pedestrian model can provide more diverse and realistic pedestrian motion. The framework was evaluated by testing different vehicle control algorithms to achieve pedestrian avoidance. A series of repeated simulations were conducted, which showed the effectiveness of the proposed framework. We have improved the social force based pedestrian/crowd motion modeling for vehicle-pedestrian interaction. An improved design of the vehicle effect has been tested. A new way of utilizing vehicle-pedestrian interaction trajectory datasets was proposed and utilized to calibrate the pedestrian model parameters. Promising preliminary results were obtained although further work is still required. We have explored the MDP-based longitudinal vehicle speed control algorithms for pedestrian crossing. Specifically, some preliminary experiments were conducted using the partially observable Markov decision process (POMDP) and the deep deterministic policy gradient (DDPG). Future work is still expected. We have explored the decision-making of a combination of steering and braking maneuvers for an automated vehicle to deal with crossing pedestrians. A preliminary literature review was conducted. The simulation program is in the process of development. Impacts New attention was generated for the interaction between pedestrians and automated vehicles. We had a visit from a group from the GAO that interviewed us on this issue and reported to congress. A database we had developed in our previous study is still generating worldwide attention and as the follow on project we are responding in advise and collaboration. Other None new. Outcomes New Partners None new. Issues Due to pandemic related constraints some of the experimental studies planned were not doable. Instead we concentrated further algorithmic studies based on simulations.