Resident Travel Analysis based on GPS Trajectory

Author:

Dong Ruiqi

Abstract

Taxi is an important means of transportation, and its trajectory data contains a wealth of travel information. Taxi trajectory data processed by trajectory data mining technology can reflect residents' activity rules and behavior patterns, so as to provide a reference for urban planning decisions. with its wide coverage, high sampling rate, good location accuracy, large data scale and rich information, taxi trajectory data has been widely used in traffic management, urban planning, user behavior analysis and intelligent transportation. Analyze the characteristics of residents' travel demand from two dimensions: time and space. Analysis of travel demand time characteristics. firstly, analyze the overall demand characteristics of residents, and secondly, analyze the demand characteristics of residents on workdays and rest days; In the analysis of spatial characteristics of travel demand, the static and dynamic spatial characteristics of residents are analyzed separately.

Publisher

Darcy & Roy Press Co. Ltd.

Reference10 articles.

1. Wang H, Huang H, Ni X, et al. Revealing spatial-temporal characteristics and patterns of urban travel: a large-scale analysis and visualization study with taxi GPS data[J]. International Journal of Geo-Information, 2019, 8(6): 257.

2. LI Ke, DANG Yan-zhong. The Precise Delivery Strategy of LED Advertisement in New Operational Model of Taxi[J]. Chinese Journal of Management Science, 2020, 192(10): 220-230.

3. Park C, Lee J, Sohn S Y C. Recommendation of feeder bus routes using neural network embedding-based optimization[J]. Transportation Research Part A: Policy Practice 2019, 126(3): 329-341.Ma Kunlong. Short term distributed load forecasting method based on big data. Changsha: Hunan University, 2014.

4. LONG Xue-qin, ZHOU Meng, ZHAO Huan, et al. Passenger’s Hot Spots Identification of Online Car-hailing Based on Network Kernel Density [J]. Journal of Transportation Systems Engineering and Information Technology, 2021, 21(03): 86-93+100.

5. DAI Weixiu, CHEN zhanglong, XIE Peng. Research on the interactive mode of resident’s behavior based on trajectory data mining. Acta Geodaetica et Cartographica Sinica, 2021, 50(04): 532-543.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3