In this paper, an integrated framework and a smart algorithm for vehicle positioning are proposed. The standalone Global Positioning System (GPS) cannot provide accurate location information in dense and indoor environments. Therefore, an integrated framework is proposed which exploits additional positioning technologies including vehicle-to-infrastructure and vehicle-to-vehicle communications, radio-frequency identification, map matching, and dead reckoning for vehicle localization. Since different applications require different location accuracy, a smart algorithm is also provided which shows how different localization technologies under various situations are selected and used to obtain the desired accuracy with the least amount of complexity. A series of comprehensive MATLAB simulations are conducted to evaluate the performance of the algorithms. Simulation results show that standalone GPS is not a reliable positioning technique in all situations; second, an integrated technique using several positioning technologies is required to achieve the minimum application requirements in all situations; third, using the smart algorithm, the required accuracy and latency can be achieved by selectively adding or removing localization resources.
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