Exploring Potential Travel Demand of Customized Bus Using Smartcard Data*

2019 IEEE Intelligent Transportation Systems Conference (ITSC) Pub Date : 2019-10-01 DOI:10.1109/ITSC.2019.8916843

Rongge Guo, W. Guan, A. Huang, Wen-yi Zhang

{"title":"Exploring Potential Travel Demand of Customized Bus Using Smartcard Data*","authors":"Rongge Guo, W. Guan, A. Huang, Wen-yi Zhang","doi":"10.1109/ITSC.2019.8916843","DOIUrl":null,"url":null,"abstract":"Customized bus (CB) is an innovation mode of public transportation (PT) system to alleviate the traffic congestion. As a demand-based transport, CB holds promise to provide personalized service by aggregating travel demand of individuals. However, the data collected through online surveys are limited and unreliable for the CB operation planning. This paper introduces a methodology to investigate the potential travel demands of CB based on smartcard data (SCD). The methodology proposed here consists of three processes: trip chain generation, origin-destination (OD) recognition and travel mode comparison. Drawing on Beijing as the case study, the smartcard dataset is processed for analyzing the spatial-temporal properties of passenger travel behavior and exploring potential travel demand of CB. The results indicate that the data have a workplace-oriented pattern and CB is suitable for passengers with long trip distances (beyond 8 km). These findings advance key points to future CB operation as it is associated with the route design and vehicle arrangement.","PeriodicalId":6717,"journal":{"name":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","volume":"195 1","pages":"2645-2650"},"PeriodicalIF":0.0000,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 IEEE Intelligent Transportation Systems Conference (ITSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ITSC.2019.8916843","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 10

Abstract

Customized bus (CB) is an innovation mode of public transportation (PT) system to alleviate the traffic congestion. As a demand-based transport, CB holds promise to provide personalized service by aggregating travel demand of individuals. However, the data collected through online surveys are limited and unreliable for the CB operation planning. This paper introduces a methodology to investigate the potential travel demands of CB based on smartcard data (SCD). The methodology proposed here consists of three processes: trip chain generation, origin-destination (OD) recognition and travel mode comparison. Drawing on Beijing as the case study, the smartcard dataset is processed for analyzing the spatial-temporal properties of passenger travel behavior and exploring potential travel demand of CB. The results indicate that the data have a workplace-oriented pattern and CB is suitable for passengers with long trip distances (beyond 8 km). These findings advance key points to future CB operation as it is associated with the route design and vehicle arrangement.

查看原文本刊更多论文

利用智能卡数据探索定制巴士的潜在出行需求*

定制公交(CB)是一种缓解交通拥堵的公共交通(PT)系统创新模式。CB作为一种基于需求的交通工具，通过聚合个人的出行需求来提供个性化的服务。然而，通过在线调查收集的数据有限，不可靠的CB运营计划。本文介绍了一种基于智能卡数据(SCD)的CB潜在旅行需求研究方法。本文提出的方法包括三个过程:出行链生成、始发目的地识别和出行模式比较。以北京市为例，对智能卡数据进行处理，分析旅客出行行为的时空特征，挖掘潜在的CB出行需求。结果表明，数据具有以工作场所为导向的模式，CB适用于长途旅行(超过8公里)的乘客。这些发现为未来的CB运营提出了关键点，因为它与路线设计和车辆安排有关。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

2019 IEEE Intelligent Transportation Systems Conference (ITSC)

自引率

0.00%

发文量