Positioning algorithms for transport telematics applications
journal contributionposted on 18.11.2009 by Washington Y. Ochieng, Mohammed Quddus, Robert B. Noland
Any type of content formally published in an academic journal, usually following a peer-review process.
This paper develops two integrated positioning algorithms for transport telematics applications and services. The first is an Extended Kalman Filter (EKF) algorithm for the integration of GPS and low cost DR sensors to provide continuous positioning in built-up areas. The second takes this further by integrating the GPS/DR output with map data in a novel a map-matching process to both identify the physical location of a vehicle on the road network and improve positioning capability. The proposed MM algorithm is validated using a higher accuracy reference (truth) of the vehicle trajectory as determined by high precision positioning achieved by the carrier phase observable from GPS
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