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

In this project, we have designed and developed an effective end-to-end system based on advanced Artificial Intelligence (AI), machine learning, and computer vision to automatically monitor, detect, track, and count pedestrians and bicyclists. The main objective of this project is to improve the safety of pedestrians and bicyclists, by applying self-sensed and AI-powered systems to monitor and control the flow of pedestrians/bicyclists. The developed system includes algorithms for detecting the pedestrians and bicyclists, as well as algorithms for tracking and counting the pedestrians. We evaluated the developed system on real videos captured by actual traffic cameras in city of Los Angeles. Despite the low quality of some of the videos, the results demonstrated high accuracy and effectiveness of the developed system in automatically detecting and counting pedestrians and bicyclists.

University: 
Mineta Consortium for Transportation Mobility
Principal Investigator: 
Mohammad Pourhomayoun, PhD
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 September 2020
Project Number: 
1808

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CSUTC
MCEEST
MCTM
NTFC
NTSC

Contact Us

SJSU Research Foundation   210 N. 4th Street, 4th Floor, San Jose, CA 95112    Phone: 408-924-7560   Email: mineta-institute@sjsu.edu