This paper presents a framework for road traffic safety analysis. It is based on a stereo-vision system that, after being installed on-board of public transportation vehicles, collects data of what happens in front of a moving vehicle. The collected data are analysed throughout a process that acquire raw GPS information, video sequences and stereo-based depth maps to compute the surrogate safety measures. These measures are obtained by exploiting the Traffic Conflict Technique in conjunction with computer vision algorithms and a cascade of classifiers. The safety measures are then used for further analysis in order to identify dangerous locations in which an intervention is needed to improve the safety level and prevent accidents. Experiments performed in a real urban environment confirm the effectiveness of the framework.

On-board monitoring system for road traffic safety analysis

Battiato, Sebastiano;Farinella, Giovanni Maria;Gallo, Giovanni;Giudice, Oliver
2018-01-01

Abstract

This paper presents a framework for road traffic safety analysis. It is based on a stereo-vision system that, after being installed on-board of public transportation vehicles, collects data of what happens in front of a moving vehicle. The collected data are analysed throughout a process that acquire raw GPS information, video sequences and stereo-based depth maps to compute the surrogate safety measures. These measures are obtained by exploiting the Traffic Conflict Technique in conjunction with computer vision algorithms and a cascade of classifiers. The safety measures are then used for further analysis in order to identify dangerous locations in which an intervention is needed to improve the safety level and prevent accidents. Experiments performed in a real urban environment confirm the effectiveness of the framework.
2018
On-board systems; Stereo vision; Traffic safety; Computer Science (all); Engineering (all)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11769/335576
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