Smart card data use in public transit: A literature review

By Marie-Pier Pelletier, Martin Trépanier, Catherine Morency. 2011

971 citations recorded by the source corpus.

Subfields: Automotive Engineering, Building and Construction, Transportation

View Paper: https://www.semanticscholar.org/paper/b1f59859a31142e916849045fe83f0a2b5920a9d

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Bin Ning
2. Lijun Sun
3. Cynthia Chen
4. Xianfeng Huang
5. Yunpeng Wang
6. Der-Horng Lee
7. A. Erath
8. Xiaolei Ma

In Building and Construction

1. Yinhai Wang
2. Yunpeng Wang
3. Xiaolei Ma
4. Lijun Sun
5. Der-Horng Lee
6. Zhiyong Cui
7. Ruimin Ke
8. Weibin Zhang

In Transportation

1. Yunpeng Wang
2. Xiaolei Ma
3. Yinhai Wang
4. Tao Tang
5. Bin Ning
6. Lijun Sun
7. Huimin Wen
8. Cynthia Chen

Citations in the corpus

• The promises of big data and small data for travel behavior (aka human mobility) analysis (2016, background): “…sightings generated by phone operators for operation purposes (Calabrese et al., 2011), social media data generated voluntarily by users’ online activities (Chen and Schintler, forthcoming), and smartcard data collected at many transit systems worldwide (Pelletier et al., 2011; Ma et al., 2013).”
• Mining smart card data for transit riders’ travel patterns (2013, background): “Extracting transit riders’ travel patterns from smart card data can be particularly challenging because the Automatic Fare Collection (AFC) system was not originally designed to support transit planning and transit performance measures (Pelletier et al., 2011).”
• Big Data Analytics in Intelligent Transportation Systems: A Survey (2019, background): “information on travel behaviour [17], [21], smart card data is becoming a significant component of public transportation services planning and management.”
• Using smart card data to extract passenger's spatio-temporal density and train's trajectory of MRT system (2012, background): “It has been recognized that there are large potential benefits of using this data to improve public transport planning and operation [9].”
• Understanding commuting patterns using transit smart card data (2017, methodology): “As documented by Pelletier et al. (2011), new analytical methods and disaggregate approaches based on smart card data are renovating traditional travel behavior research.”