A Vision-Based Approach to Collision Prediction at Traffic Intersections

Stefan Atev, Hemanth Arumugam, Osama Masoud, Ravi Janardan, Senior Member, IEEE, and
Nikolaos P. Papanikolopoulos, Senior Member, IEEE

Abstract

Monitoring traffic intersections in real time and predicting
possible collisions is an important first step towards building
an early collision-warning system. We present a vision-based
system addressing this problem and describe the practical adaptations
necessary to achieve real-time performance. Innovative
low-overhead collision-prediction algorithms (such as the one
using the time-as-axis paradigm) are presented. The proposed
system was able to perform successfully in real time on videos
of quarter-video graphics array (VGA) (320 × 240) resolution
under various weather conditions. The errors in target position
and dimension estimates in a test video sequence are quantified
and several experimental results are presented.

Index Terms

Collision prediction, machine vision, real-time
systems, tracking, traffic control (transportation).

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