Analysis and extraction of urban real-time traffic circle based on internet open data
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    Abstract:

    In this paper,taking Beijing as the research area,the Python language is used to obtain the real-time traffic data provided by the Baidu map API at the sample point location,then,the sample points are transformed into reachability surface by spatial interpolation,and the surface data is graded. Finally,we get traffic data. Through the Beijing bus credit card data to obtain the space-time circle for the evaluation of confidence,as a basis the two modes of driving and public transport under the peak and non-peak space-time circle are divided. The results show that:①The obtained traffic data has a great correlation with the credit card data,which shows that the real-time traffic data method can be obtained through the Baidu map API.② Compared with the traditional traffic circle acquisition method,the data obtained by Baidu map API is more accurate and more real-time traffic circle information;③ Compared to the driving mode,the Beijing public transport mode traffic circle is in the bias-type extension of the poor support;④ Public transport mode takes into account the distance and time,which will provide a basis for the future study on the balance of the distribution of public transport in the city.

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ZHANG Longsheng, GE Xing, LIU Di. Analysis and extraction of urban real-time traffic circle based on internet open data[J].,2017,34(4):94-98

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History
  • Received:September 25,2017
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  • Online: December 21,2017
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