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Sensors 2018, 18(5), 1403;

VeLoc: Finding Your Car in Indoor Parking Structures

1,* , 1
School of Software Engineering, Beijing Jiaotong University, Beijing 100044, China
Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY 13244, USA
Author to whom correspondence should be addressed.
Received: 12 April 2018 / Revised: 27 April 2018 / Accepted: 29 April 2018 / Published: 2 May 2018
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While WiFi-based indoor localization is attractive, there are many indoor places without WiFi coverage with a strong demand for localization capability. This paper describes a system and associated algorithms to address the indoor vehicle localization problem without the installation of additional infrastructure. In this paper, we propose VeLoc, which utilizes the sensor data of smartphones in the vehicle together with the floor map of the parking structure to track the vehicle in real time. VeLoc simultaneously harnesses constraints imposed by the map and environment sensing. All these cues are codified into a novel augmented particle filtering framework to estimate the position of the vehicle. Experimental results show that VeLoc performs well when even the initial position and the initial heading direction of the vehicle are completely unknown. View Full-Text
Keywords: vehicle localization; inertial tracking; virtual landmarks; mobile crowdsensing vehicle localization; inertial tracking; virtual landmarks; mobile crowdsensing

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Gao, R.; He, F.; Li, T. VeLoc: Finding Your Car in Indoor Parking Structures. Sensors 2018, 18, 1403.

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