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http://dx.doi.org/10.9708/jksci.2019.24.05.067

Localization of Mobile Users with the Improved Kalman Filter Algorithm using Smart Traffic Lights in Self-driving Environments  

Jung, Ju-Ho (Computer Information Technology, Korea National University of Transportation)
Song, Jung-Eun (Computer Information Technology, Korea National University of Transportation)
Ahn, Jun-Ho (Computer Information Technology, Korea National University of Transportation)
Publication Information
Journal of the Korea Society of Computer and Information / v.24, no.5, 2019 , pp. 67-72 More about this Journal
Abstract
The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.
Keywords
Self-driving; Localization; Rssi; Smart traffic lights; Kalman filter;
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