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Car travel characteristics is one of the important factors affecting of the urban road network operation. To provide support for traffic refinement management and policy making, collecting car travel data and having in depth analysis of its travel behavior characteristics, is the key aspect in encouraging car travel behavior change and reducing the vehicle use intensity. Based on the travel data and track data collecting by the vehicle OBD data, car travel characteristics analysis method is put forward, and the quantitative indicators such as trip rate, travel frequency, travel distance can be get, and the travel index variation characteristics were analyzed under the different stages, different regions and different policy. Studying the travel rule by using the big data analysis method, on a deep level, traffic characteristics of user portrait, road network non-linear coefficient can be further obtained. The analysis results show that the intelligent driving data can better reflect the characteristics of the car travel behavior, and make quantitative evaluation of the implementation of the transport demand management policies.

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