Traffic Monitoring and Management for Pedestrian and Cyclist Safety Using Deep Learning and Artificial Intelligence

Improving the safety of pedestrians and bicyclists has always been one of the priorities of transportation officials in California. Two of the main goals of Pedestrian and Bicycle Safety Branch under Caltrans’ Traffic Operations are developing programs to improve the safety of transportation infrastructures for pedestrians and bicycles; and encouraging research and technology transfer in the field of pedestrian and bicycle fatality.

Understanding the movement of people, bicycles, and their interaction with vehicles is critical to avoid traffic accidents and improve safety. Currently, there is not an efficient automated system for monitoring the movement of pedestrians and bicyclists across the state of California and in major urban areas. Such system can also provide valuable information about the traffic stream parameters once implemented and calibrated.

This research project will facilitate the aforementioned goals by providing a platform that allows for enhancing and improving safety measures for pedestrians and bicyclists in California using automated systems to monitor, detect, track, and count the flow of pedestrians and bicyclists.

University: 

Mineta Consortium for Transportation Mobility

Principal Investigator: 

Mohammad Pourhomayoun, Ph.D.

PI Contact Information: 

Mineta Transportation Institute
San José State University
210 N. 4th St., 4th Floor
San José, CA 95112
mpourho@calstatela.edu

Funding Source(s) and Amounts Provided (by each agency or organization): 

California Department of Transportation - $81,674

Total Project Cost: 

$81,674

Agency ID or Contract Number: 

65A0660

Dates: 

December 2018 to August 2020

Project Number: 

1808