Dynamic Evaluation Model of Urban Public Transport Service Level

DOI

10.2991/icesame-17.2017.350How to use a DOI?

Keywords

OD Matrix, Gauss filtering, The least square method

Abstract

With today's urban public transport system's functions becoming increasingly perfect, how to make the dynamic evaluation of the existing traffic facilities and service based on the card consumption data of bus and the GPS data of taxi or other large data information, whose target is to improve the quality specially has gradually became a major concern to relevant government departments. In view of the given information and data, we make the following work to solve the problem of the topic proposed. We use the vehicle flow rate recognition algorithm and cross section calculation method after successfully importing the original data into MATLAB and making classification by screening in the database. According to the vehicle's GPS data, we finally work out a figure for bus and subway traffic statistics, and furthermore, forecast the citizens-traveling-figure in that city. On this basis, we explore a more intuitive citizens-traveling-histogram. At last, according to the information of time-determained passenger's number, the eventually mapped the entire network section of passenger flow rate information was created to reflect the city traffic flow changes of the different time and space. On the basis of above, added the GPS data and bus brush calorie of consumption data of residents, the matrix of OD was made to help deepen the comprehension.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lang Liu
PY  - 2017/06
DA  - 2017/06
TI  - Dynamic Evaluation Model of Urban Public Transport Service Level
BT  - Proceedings of the 2017 2nd International Conference on Education, Sports, Arts and Management Engineering (ICESAME 2017)
PB  - Atlantis Press
SP  - 1637
EP  - 1641
SN  - 2352-5398
UR  - https://doi.org/10.2991/icesame-17.2017.350
DO  - 10.2991/icesame-17.2017.350
ID  - Liu2017/06
ER  -