Research Reports

Real-Time Collison Warning and Avoidance at Intersections

Principal Investigator:

Stefan Atev, Osama Masoud, Ravi Janardan, Nikolaos P Papanikolopoulos

November 2004

Report no. Mn/DOT 2004-45

Projects: Real-time Collision Warning and Avoidance at Intersections

Topics: Safety, Traffic Operations

Monitoring traffic intersections in real-time as well as predicting possible collisions is an important first step towards building an early collision warning system. We present the general vision methods used in a system addressing this problem and describe the practical adaptations necessary to achieve real-time performance. A novel method for three dimensional vehicle size estimation is presented. We also describe a method for target localization in real-world coordinates, which allows for sequential incorporation of measurements from multiple cameras into a single target's state vector. Additionally, a fast implementation of a false-positive reduction method for the foreground pixel masks is developed. Finally, a low-overhead collision prediction algorithm using the time-as-axis paradigm is presented. The proposed system was able to perform in real-time on videos of quarter-VGA (320 times 240) resolution. The errors in target position and dimension estimates in a test video sequence are quantified.

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