Procedure Optimization Method Based on GPS Trajectory Data for Transportation Mode Recognition under Different Traffic Conditions

被引：0
作者：
Yang F. [1 ]
Jiang H.-H. [1 ]
Liu H.-D. [2 ]
Yao Z.-X. [3 ]
Huo Y.-M. [1 ]
Zhou Z.-Y. [4 ]
机构：
[1] School of Transportation and Logistics, Southwest Jiaotong University, Chengdu
[2] Urban Transportation Center, China Academy of Transportation Science, Beijing
[3] School of Highway, Chang'an University, Xi'an
[4] School of Transportation, Southeast University, Nanjing
来源：
Jiaotong Yunshu Xitong Gongcheng Yu Xinxi/Journal of Transportation Systems Engineering and Information Technology | 2020年 / 20卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Frequency domain feature; Genetic algorithm; GPS trajectory data; Intelligent transportation; Support vector machine; Transportation mode recognition;
D O I：
10.16097/j.cnki.1009-6744.2020.04.013
中图分类号：
学科分类号：
摘要：
This study focuses on the transportation mode recognition for the Global Positioning System (GPS)-based travel survey technology. The study proposed a procedure optimization method that is based on the Support Vector Machine (SVM) to improve the recognition accuracy of buses and cars. The proposed model included the new frequency domain features generated from Short-time Fourier Transform (STFT). The Genetic Algorithm (GA) was used to optimize the penalty parameter and the nuclear parameter of SVM. The recognition results of the transportation modes and mode transfer time under different traffic conditions were evaluated, and the result showed the newly added frequency domain features effectively improved the recognition accuracy of the transportation modes. In the free-flow and slightly congested traffic conditions, the transportation mode recognition and mode transfer time both obtained satisfied results. In severe congestions, the motorized modes are relatively easy to be mixed with the non-motorized modes. The maximum error of mode transfer time is within 13 minutes, which might still be informative compared with traditional manual questionnaire surveys. Copyright © 2020 by Science Press.
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页码：83 / 89and105
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