Safe-D: Safety through Disruption

Prediction of Vehicle Trajectories at Intersections Using Inverse Reinforcement Learning


Abstract

The ability to accurately predict vehicle trajectories is essential in infrastructure-based safety systems which aim to identify critical events such as near crash situations and traffic violations. In a connected environment, important information about these critical events can be communicated to road users or the infrastructure to avoid or mitigate potential crashes. Intersections require special attention in this context because they are hotspots for accidents and involve numerous and complex interactions between road users. The proposed project will investigate approaches to and methodologies for vehicle trajectory prediction at intersections, and identify current challenges and opportunities. The project will also explore the applicability of inverse reinforcement learning (IRL) in developing trajectory prediction models. IRL is a machine learning framework for Learning from Demonstration (LfD) which allows for the learning of the series of actions that dictate driver behavior from expert demonstration. Trajectory prediction, while normally posed as a prediction problem, can readily be cast as a control problem given that the problem is essentially equivalent to finding how to drive a vehicle the way a human driver would. This is crucial in enabling us to use IRL to solve it. The IRL framework makes certain assumptions about the problem to be solved that, when these assumptions hold, improve the generalizability of models that are based on. We hope that by employing this framework we will be able to build models that better capture the behavior of human drivers at intersection.

Project Highlights

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Final Report

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EWD & T2 Products

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Presentations/Publications

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Research Investigators (PI*)

Arash Jahangiri (SDSU)*
Sahar Ghanipoor Machiani (SDSU)
Mohammad Sadegh Jazayeri (SDSU)

Project Information

Start Date: 2020-05-15
End Date: 2021-05-05
Status: Active
Grant Number: 69A3551747115
Total Funding: $150,000
Source Organization: Safe-D National UTC
Project Number: SDSU-01-01

Safe-D Theme Areas

Connected Vehicles
Automated Vehicles

Safe-D Application Areas

Infrastructure Technology
Planning for Safety
Risk Assessment

More Information

RiP URL
UTC Project Information Form

Sponsor Organization

Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC 20590 United States

Performing Organization

San Diego State University
5500 Campanile Dr
San Diego, CA 92182
USA