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Low Speed Vehicle Localization using WiFi FingerPrinting

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Recently, the problem of fully autonomous navigation of vehicle has gained major interest from research institutes and private companies. In general, these researches rely on GPS in fusion with other sensors to track vehicle in outdoor environment. However, as indoor environment such as car park is also an important scenario for vehicle navigation, the lack of GPS poses a serious problem. This study presents an approach to use WiFi Fingerprinting as a replacement for GPS information in order to allow seamlessly transition of localization architecture from outdoor to indoor environment. Often, movement speed of vehicle in indoor environment is low (10-12km/h) in comparison to outdoor scene but still surpasses human walking speed (3-5km/h, which is usually maximum movement speed for effective WiFi localization). This paper proposes an ensemble classification method together with a motion model in order to deal with the above issue. Experiments show that proposed method is capable of imitating GPS behavior on vehicle tracking.
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hal-01395973 , version 1 (13-11-2016)


  • HAL Id : hal-01395973 , version 1


Dinh-Van Nguyen, Myriam Vaca Recalde, Fawzi Nashashibi. Low Speed Vehicle Localization using WiFi FingerPrinting. International Conference on Control, Automation, Robotics and Vision, ICARCV 2016, Nov 2016, Phuket, Thailand. ⟨hal-01395973⟩


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