Mr. Abdessattar Hayouni Profile

Abdessattar Hayouni

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Proceedings Article | 21 April 2020 Presentation + Paper

Towards cognitive vehicles: location cognizance

Abdessattar Hayouni, Mihai Florea, Henry Leung

Proceedings Volume 11413, 1141317 (2020) https://doi.org/10.1117/12.2557539

KEYWORDS: Global Positioning System, Detection and tracking algorithms, Video, Brain, Cameras, Satellite navigation systems, Signal attenuation, Buildings, Visualization, Error analysis

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In the context of cognitive vehicles, it is essential to have full awareness of the vehicle location to have a better insight of the operational environment and enhance the driver perception. Although the global navigation satellite system (GNSS) is commonly a practical solution for vehicle localization, it may suffer quality deterioration, accuracy decay and even track loss due to signal blockage and reflection off buildings and big structures. These limitations usually manifest in big cities with dense traffic and active roads which means losing the sense of location, even for a short time, might blur the cognitive system decision making process and jeopardize the safe driving of the vehicle. Consequently, cognitive vehicles should not count only on the GNSS solution for vehicle localization. In this work we establish that the cognitive vehicle location awareness can be achieved through the inner process of interaction with the surrounding environment and observing its static reference elements. This approach is inspired by the way the human brain can assess its position in a known environment by recognizing some landmarks and referential objects. Our proposed solution allows the cognitive vehicle to ascertain its location by interacting with its surroundings. we train a deep neural network to detect some objects of reference, create a prior knowledge of the vehicle environment and estimate the vehicle location by recognizing the objects detection pattern. Finally, the proposed solution will be endorsed by promising results from a real-world scenario, and further work will be proposed to improve the solution.

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