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Recognition of Operating Characteristics of Heavy Trucks Based on the Identification of GPS Trajectory Stay Points.

Authors :
Wei, Long
Chen, Gang
Sun, Wenjie
Li, Guoqi
Source :
Security & Communication Networks; 6/12/2021, p1-12, 12p
Publication Year :
2021

Abstract

As an emerging data source, feature identification based on GPS trajectory data has become a hot issue in the field of data mining and freight management. A method of trajectory data extraction, classification, and visualization based on stay points was proposed in this paper to analyze the operation characteristics of heavy trucks from the perspectives of intracity transportation, intraprovincial transportation, and interprovincial transportation. The GPS trajectory data of heavy trucks in Sichuan Province in March 2019 were taken as an example to analyze the operation characteristics. The results show that the heavy trucks in Sichuan Province are mainly transported within the province, and the freight efficiency is slightly better than the average level of the national freight trucks in the same period, failing to give full play to the advantages of long transport distance. The manufacturing industry is the main service object of heavy trucks, and the vehicles engaged in transportation within the province are more dependent on logistics enterprises and their ancillary facilities. The north-south longitudinal line and east-west horizontal line are the main interprovincial transport channels, and the provincial and municipal transport is mainly concentrated in some urban trunk lines, ring lines, and express routes. The proposed technical method can describe the operating characteristics of freight trucks from the perspective of microscopic and service market, not only to guide the layout of highway freight yards, logistics parks, and logistics hubs and the determination of service functions but also to provide a reference basis for freight management-related departments and drivers to formulate transportation plans and establish freight information platforms to improve freight efficiency and safety. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
19390114
Database :
Complementary Index
Journal :
Security & Communication Networks
Publication Type :
Academic Journal
Accession number :
150878364
Full Text :
https://doi.org/10.1155/2021/9998405