Machine Vision to Alert Roadside Personnel of Night Traffic Threats
Author(s)Wang, Liang; Horn, Berthold K. P.
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In the United States, every year, several people whose job takes them to the sides of roads, are injured or killed by roadside collisions. This could be avoided if a warning signal could be sent to them. In this paper, we describe a machine-vision based alerting system which detects and tracks headlamps of cars in night traffic. The system automatically computes a “normal traffic” region in the image. Unusual trajectories of cars are detected when the images of their headlamps move out of that region. The system promptly sends a warning signal once a risk has been identified. The system runs on the Android smart phones, which are mounted on cars or on roadside fixtures.
DepartmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
IEEE Transactions on Intelligent Transportation Systems
Institute of Electrical and Electronics Engineers (IEEE)
Liang, Wang et al. "Machine Vision to Alert Roadside Personnel of Night Traffic Threats." IEEE Transactions on Intelligent Transportation Systems 19, 10 (October 2018): 3245 - 3254 © 2019 IEEE
Author's final manuscript