Analysis of Driving Session Videos by Reverse Temporal Order Processing

Abstract

Technology based driver training is still in its infancy. There is a strong need for improved and integrated computer-based screening tools in order to facilitate objective and reliable driver training assessments. This paper describes a system that analyses videos of driving sessions collected by on-board web-cameras. The system detects and tracks lane markings in order to estimate the relative position of the vehicle with respect to its lane. The system is computationally efficient as it exploits fully the off-line nature of the data. The analysis of the video recording is performed in reverse temporal order. The benefits of this approach compared to the forward analysis traditionally used are an improved robustness and a lower computational cost.