Abstract
Taking full account of the advantages and disadvantages of monocular vision and binocular vision in environmental perception, this paper proposes a single-binocular vision conversion strategy based on monocular camera for obstacle detection at non-signalized intersections. Using this strategy we can get fast and accurate identification of obstacles on the lateral anterior of the vehicle, and achieve fast and accurate detection for subsequent distances and speeds of obstacles. To ensure driving safety at the intersections on the premise of effectively detecting cross-conflict, first, the monocular camera conversion model, the number of cameras and the installation position are determined. Second, a single-binocular vision conversion strategy is made: the single-binocular visual composition is determined in real time according to the distance parameter and the angle parameter, and the obstacle information on the lateral anterior of the vehicle is acquired. In the end, compared with the complete monocular vision and complete binocular visual environmental perception method, the comparison results prove the rationality of the conversion strategy, and prove that the strategy is efficient and accurate in environmental perception and obstacle recognition, ranging, and speed measurement.
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Ma, X. et al. (2019). Single-Binocular Vision Conversion Strategy for Obstacle Detection at Non-signalized Intersections. In: Esposito, C., Hong, J., Choo, KK. (eds) Pervasive Systems, Algorithms and Networks. I-SPAN 2019. Communications in Computer and Information Science, vol 1080. Springer, Cham. https://doi.org/10.1007/978-3-030-30143-9_31
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DOI: https://doi.org/10.1007/978-3-030-30143-9_31
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