Use of Smart Card Fare Data to Estimate Public Transport Origin–Destination Matrix

Author:

Alsger Azalden A.1,Mesbah Mahmoud1,Ferreira Luis1,Safi Hamid1

Affiliation:

1. School of Civil Engineering, University of Queensland, Building 49, Brisbane Saint Lucia, Queensland 4072, Australia.

Abstract

Over the past few years, several techniques have been developed for using smart card fare data to estimate origin–destination (O-D) matrices for public transport. In the past, different walking distance and allowable transfer time assumptions had been applied because of a lack of information about the alighting stop for a trip. Such assumptions can significantly affect the accuracy of the estimated O-D matrices. Little evidence demonstrates the accuracy of O-D pairs estimated with smart card fare data. Unique smart card fare data from Brisbane, Queensland, Australia, offered an opportunity to assess previous methods and their assumptions. South East Queensland data were used to study the effects of different assumptions on estimated O-D matrices and to conduct a sensitivity analysis for different parameters. In addition, an algorithm was proposed for generating an O-D matrix from individual user transactions (trip legs). About 85% of the transfer time was non-walking time (wait and short activity time). More than 90% of passengers walked less than 10 min to transfer between alighting and the next boarding stop; this time represented about 10% of the allowable transfer time. A change in the assumed allowable transfer time from 15 to 90 min had a minor effect on the estimated O-D matrices. Most passengers returned to within 800 m of their first origin on the same day.

Publisher

SAGE Publications

Subject

Mechanical Engineering,Civil and Structural Engineering

Cited by 65 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

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