Development of an Algorithm for Real Time Vehicle Positioning on Failure of GPS
|Deepak Raj.R1, Vidya.V2
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Positioning is an important area where the researches are going on. This work is related to the area of an automotive transportation system. The real time vehicle positioning is an important area for intelligent transportation system (ITS) applications. Normally low cost GPS receivers do not guarantee accurate continuous data to the positioning system. This is because of the temporary loss of satellite connection and signal error. So in this work to avoid these problems an algorithm would be developed. The algorithm is based on Extended Kalman Filter (EKF) that integrates low-cost GPS data and in-vehicle sensors data to adapt the vehicle model in various driving conditions and to avoid the error due to GPS problem. The proposed system composed of two types of vehicle model set, a kinematic vehicle model and a dynamic vehicle model. These two models are developed using Extended Kalman Filter (EKF) and based on the driving condition a suitable model will be selected.