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Exploring equity in public transportation planning using smart card data
ID Ghasemlou, Kiarash (Author), ID Ergun, Murat (Author), ID Dadashzadeh, Nima (Author)

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Abstract
Existing public transport (PT) planning methods use a trip-based approach, rather than a user-based approach, leading to neglecting equity. In other words, the impacts of regular users—i.e., users with higher trip rates—are overrepresented during analysis and modelling because of higher trip rates. In contrast to the existing studies, this study aims to show the actual demand characteristic and users’ share are different in daily and monthly data. For this, 1-month of smart card data from the Kocaeli, Turkey, was evaluated by means of specific variables, such as boarding frequency, cardholder types, and the number of users, as well as a breakdown of the number of days traveled by each user set. Results show that the proportion of regular PT users to total users in 1 workday, is higher than the monthly proportion of regular PT users to total users. Accordingly, users who have 16–21 days boarding frequency are 16% of the total users, and yet they have been overrepresented by 39% in the 1-day analysis. Moreover, users who have 1–6 days boarding frequency, have a share of 66% in the 1-month dataset and are underrepresented with a share of 22% in the 1-day analysis. Results indicated that the daily travel data without information related to the day-to-day frequency of trips and PT use caused incorrect estimation of real PT demand. Moreover, user-based analyzing approach over a month prepares the more realistic basis for transportation planning, design, and prioritization of transport investments.

Language:English
Keywords:public transportation, smart card data, equity, cost benefit analysis, travel behavior, mobility pattern, transport planning, human centric planning
Work type:Article
Typology:1.01 - Original Scientific Article
Organization:FGG - Faculty of Civil and Geodetic Engineering
Publication status:Published
Publication version:Version of Record
Year:2021
Number of pages:23 str.
Numbering:Vol. 21, iss. 9, art. 3039
PID:20.500.12556/RUL-135000 This link opens in a new window
UDC:656.1
ISSN on article:1424-8220
DOI:10.3390/s21093039 This link opens in a new window
COBISS.SI-ID:62208003 This link opens in a new window
Publication date in RUL:16.02.2022
Views:622
Downloads:110
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Record is a part of a journal

Title:Sensors
Shortened title:Sensors
Publisher:MDPI
ISSN:1424-8220
COBISS.SI-ID:10176278 This link opens in a new window

Licences

License:CC BY 4.0, Creative Commons Attribution 4.0 International
Link:http://creativecommons.org/licenses/by/4.0/
Description:This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Licensing start date:01.05.2021

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