| With the rapid development of city economic and citifying course. the tendency of the increasing quantity of motor vehicle will lead to traffic flow uprising, traffic congest, and traffic jam. Traffic problem has been important matter which is city government and complete community concerned with. Applying modernizing technology means to manage city traffic, enhance traffic maneuverability and flexibility, make good use of means of transportation, and exert function efficiency of traffic systems to the best of its abilities, which is developing intelligent transportation systems;it is efficient ways of resolve traffic crowd.Researching intelligent transportation systems is the most effective approach to resolve traffic problem, in which wireless position technology plays an important role. Due to construct and development of wireless position in intelligent transportation systems, this thesis does much research on position model based on the discussion. Firstly, it analyzes extensively position model based on wireless network, and put emphasizes on TDOA model in several different position methods such as Time of Arrival (TOA). Angle of Arrival (AOA). Time Difference of Arrival (TDOA). and hybrid method. Aiming at the problems of large compute quuntity. difficult resolve and low precision of TDOA position model, basic genetic algorithm and hybrid genetic algorithm are applied, and model simulation results prove that this method is valid. Secondly, it Emphasizes on difference GPS (Global Position Systems) position method on basis of mobile terminal. Because GPS mobile terminal has bad contradict shade character, and position result computed by difference GPS math model is difficult to keep continuous and exact position information, BP neural network is applied to forecast short time position, guarantee real-time and accurate navigation information, and this method is proved to be practical by data simulation, and simulate result has a definite precision.
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