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Driving Assistance: Pedestrians and Bicycles Accident Risk Estimation using Onboard Front Camera

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Abstract

In this study, we propose a collision detection system by detecting and estimating the risk posed by pedestrians and bicycles in the images captured by a monocular onboard camera. In the proposed intrusion system, after initial detection, the pedestrians and bicycles are tracked to obtain their location, the direction of movement, and posture information using lane detection information, velocity calculation and, pose estimation respectively. Finally, this information is evaluated using fuzzy rules to estimate the risk the pedestrian and/or bicycle poses. The results are transmitted to the driver using voice and sound. We tested the system using 89 video scenes and achieved recall and precision accuracies of 0.94 and 0.87 respectively.

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Authors and Affiliations

  1. Tokushima University, 2-1 Minami Josanjima, Tokushima, Japan

    Stephen Karungaru, Ryosuke Tsuji & Kenji Terada

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  1. Stephen Karungaru
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  2. Ryosuke Tsuji
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  3. Kenji Terada
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Correspondence to Stephen Karungaru.

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Karungaru, S., Tsuji, R. & Terada, K. Driving Assistance: Pedestrians and Bicycles Accident Risk Estimation using Onboard Front Camera. Int. J. ITS Res. 20, 768–777 (2022). https://doi.org/10.1007/s13177-022-00324-2

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