|Table of Contents|

Mining method of floating car data based on link travel time estimation(PDF)

《交通运输工程学报》[ISSN:1671-1637/CN:61-1369/U]

Issue:
2014年06期
Page:
100-109,116
Research Field:
交通信息工程及控制
Publishing date:

Info

Title:
Mining method of floating car data based on link travel time estimation
Author(s):
LI Hui-bing1;  YANG Xiao-guang2;  LUO Li-hua1
1. School of Transport and Communications, Shanghai Maritime University, Shanghai 201306, China; 2. School of Transportation Engineering, Tongji University, Shanghai 201804, China
Keywords:
intelligent transportation system;  link travel time estimation;  floating car data;  signal timing;  coarse-grained data
PACS:
U491.1
DOI:
-
Abstract:
Based on floating car data, a link travel time estimation method without signal timing data was proposed. The method consisted of four modules,which were intersection boundary dynamic partition module, link influence range partition module, floating car data extraction module, and link travel time estimation module, and the implementation of each module relied greatly on the output of previous one. According to vehicle travel state under the influence of signal control, link unit was divided into different segments by using density method in intersection boundary dynamic partition module and link influence range partition module. According to link travel time estimation mechanism, floating car data that were seriously affected by signal control were filtered off in floating car data extraction module, so the target floating car data could be obtained. Historical floating car data were excavated in link travel time estimation module, and floating car data were divided into 3 types according to different exsited regions of target data. Corresponding section travel time estimation methods were used for different types of data, and corresponding section travel time estimation models were established. Link travel time estimation method was simulated and verified by using software VISSIM, and its result was compared with the results of direct and indirect methods. Analysis result indicates that for coarse-grained floating car data, the average absolute error and average relative error of link travel time estimation method are 12 s and 8.67% respectively, so it performs better than traditional direct and indirect methods. 3 tabs, 22 figs, 20 refs.

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Last Update: 2014-12-20