Computer Science ›› 2019, Vol. 46 ›› Issue (1): 271-277.doi: 10.11896/j.issn.1002-137X.2019.01.042

• Artificial Intelligence • Previous Articles     Next Articles

Inter-regional Accessibility Evaluation Model of Urban Based on Taxi GPS Big Data

WANG Ying-bo1, SHAN Xiao-chen2, MENG Yu3   

  1. (College of Innovation and Practice,Liaoning Technical University,Fuxin,Liaoning 123000,China)1
    (School of Software,Liaoning Technical University,Huludao,Liaoning 125105,China)2
    (School of Computer Science and Engineering,Northeastern University,Shenyang 110819,China)3
  • Received:2017-12-19 Online:2019-01-15 Published:2019-02-25

Abstract: The evaluation of inter-regional accessibility plays an important role in improving the efficiency of ground traffic in cities.Traditional inter-regional accessibility evaluation methods make use of the inter-regional linear distance to calculate the regional average travel time,leading to big error between average value and actual value,and the result of inter-regional accessibility measurement method based on hotspot statistics of taxi boarding area quantifying the areas with uneven travel destination distribution is unsatisfactory.In order to solve the problem of inaccurate inter-regional accessibility evaluation caused by the above two points,this paper constructed an inter-area accessibility evaluation modelbased on GPS,and extracted a complete trip from the taxi GPS data to calculate the actual travel time,so as to improve the accuracy of average travel time.On this basis,this paper proposed a quantitative calculation model of accessibility rate based on four-dimensional OD matrix,and used the accessibility rate as the quantification standard of accessibility to solve the problem of inaccurate evaluation of inter-regional accessibility caused by uneven travel destination distribution of some areas.Experiments show that the accuracy of the proposed accessibility evaluation model is 9.4%~28.7% higher than the traditional method,especially in the area with uneven distributed travel destination,the improvement of accessibility evaluation is significant.

Key words: Accessibility, Big data, GPS, OD matrix, Transportation

CLC Number: 

  • TP391
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