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Tabu search algorithm is introduced in Monte Carlo localization algorithm to improve the car networking quickly locate performance.Ad-hoc car networking vehicles moving at high speed and network topology rapidly changing,the use of traditional Monte Carlo localization algorithm,can not quickly converge location information.Tabu search algorithm is introduced in the filtering stage of the traditional Monte Carlo localization algorithm to filter optimization and exclude the small possibility points, to obtain approximate optimal sample set of the estimated position.Simulation results show that the improved algorithm in the number of sample collection,computation time,positioning precision,has been significantly improved,the improved algorithm can better solve the positioning of car networking.