최소 단어 이상 선택하여야 합니다.
최대 10 단어까지만 선택 가능합니다.
다음과 같은 기능을 한번의 로그인으로 사용 할 수 있습니다.
NTIS 바로가기Transportation research. Part C, Emerging technologies, v.74, 2017년, pp.81 - 96
Zhou, Yuyang (Corresponding author.) , Yao, Lin , Chen, Yanyan , Gong, Yi , Lai, Jianhui
Abstract Bus arrival time is usually estimated using the boarding time of the first passenger at each station. However, boarding time data are not recorded in certain double-ticket smart card systems. As many passengers usually swipe the card much before their alighting, the first or the average al...
Transp. Res. Part B Methodol. Berrebi 81 377 2015 10.1016/j.trb.2015.05.012 A real-time bus dispatching policy to minimize passenger wait on a high frequency route
Transp. Res. Part C Emerg. Technol. Brakewood 53 59 2015 10.1016/j.trc.2015.01.021 The impact of real-time information on bus ridership in New York City
Tourism Manage. Cantis 52 133 2016 10.1016/j.tourman.2015.06.018 Cruise passengers’ behavior at the destination: investigation using GPS technology
Transp. Res. Part C Emerg. Technol. Carrion 35 9 305 2013 10.1016/j.trc.2012.10.010 Valuation of travel time reliability from a GPS-based experimental design
J. Highway Transp. Res. Dev. Chen 29 05 102 2012 An approach on station ID and trade record match based on GPS and IC Card Data
Transp. Res. Part C Emerg. Technol. Cortes 19 4 695 2011 10.1016/j.trc.2010.12.008 Commercial bus speed diagnosis based on GPS-monitored data
Transp. Res. Record, No.2063 Chu 63 2008 10.3141/2063-08 Enriching archived smart card transaction data for transit demand modeling
Guo 2005 The 1st Conference of China Intelligent Transportation The method confirming the station of bus IC card passengers and its application
10.3141/2418-13 Hernandez, T, 2014. Flex-scheduling for bus arrival time prediction. Transportation Research Board 93st Annual Meeting.
Jin Young Park, Dong Jun Kim, 2008. The potential of using smart card data to define the use of public transit in Seoul. CD-ROM. Transportation Research Board 87st Annual Meeting.
Transp. Res. Part C: Emerg. Technol. Kusakabe 46 179 2014 10.1016/j.trc.2014.05.012 Behavioral data mining of transit smart card data: A data fusion approach
Niu 2010 Research on Bus Arrival Time Prediction
Acta Geographica Sinica Long 67 10 1339 2012 Identifying commuting pattern of Beijing using bus smart card data
Shi Xinyi, Lin Hangfei, 2014. The analysis of bus commuters’ travel characteristics using smart card data: the case of Shenzhen, China. Transportation Research Board 93st Annual Meeting.
Transp. Res. Part A Policy Practice Sun 69 C 447 2014 10.1016/j.tra.2014.09.007 Models of bus boarding and alighting dynamics
Transp. Res. Part C Emerg. Technol. Tang 22 5 146 2012 10.1016/j.trc.2012.01.001 Ridership effects of real-time bus information system: a case study in the City of Chicago
Transp. Res. Part C: Emerg. Technol. Tirachini 30 5 239 2013 10.1016/j.trc.2011.11.007 Estimation of travel time and the benefits of upgrading the fare payment technology in urban bus services
*원문 PDF 파일 및 링크정보가 존재하지 않을 경우 KISTI DDS 시스템에서 제공하는 원문복사서비스를 사용할 수 있습니다.
※ AI-Helper는 부적절한 답변을 할 수 있습니다.