A procedure for public transit OD matrix generation using smart card transaction data
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A procedure for public transit OD matrix generation using smart card transaction data Masood Jafari Kang1 · Shervin Ataeian2 · S. M. Mahdi Amiripour3 Accepted: 14 September 2020 © Springer-Verlag GmbH Germany, part of Springer Nature 2020
Abstract Most fare collection systems are initially installed as single-purpose devices which are only used for collecting fare; however, many transit planners consider them as a rich source of data required for studying the passengers’ trip trends. Although, usually, there is no transaction made at the destination stop, making some assumptions can help us infer the destination. In this study, we present an integrated procedure that can generate origin–destination matrices and passenger load profiles as essential tools for public transport planning processes. Moreover, this procedure can be used to detect and analyze trips that include transfers. In an attempt to employ the proposed algorithm in the Tehran bus rapid transit network, 52% of the transactions could be used to trace the trips in an origin–destination format. The trips that include transfers are recognized and analyzed further. Our detailed results of the method application indicate that the proposed algorithm is a productive and economical public transport planning method. Keywords OD matrix estimation · Smart card transaction · Automatic fare collection · Passenger load profile · Public transport planning
* Shervin Ataeian [email protected] Masood Jafari Kang [email protected] S. M. Mahdi Amiripour [email protected] 1
Industrial Engineering, Lamar University, Beaumont, USA
2
Industrial Engineering, Urmia University, Urmia, Iran
3
Toos Institute of Higher Education, Mashhad, Iran
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1 Introduction The primary application of Automated Fare Collection (AFC) systems is to provide passengers with an easy payment service. Additionally, many transit companies are using data gathered by AFC systems for planning purposes. If studied closely, this data can provide valuable information regarding the patterns of passenger trips, which is the key input for generating origin–destination (OD) matrices. One of the primary steps of public transport planning processes is studying passenger demand trends and estimating OD relations of the trips. This valuable data can also be used to determine the passenger load profile as a necessary management tool for the transit planning (Goulet Langlois et al. 2016; Kieu et al. 2015; Kusakabe and Asakura 2014). An OD matrix is a simple tool to demonstrate passenger flow between any origin and destination in a transit network. It is an essential component of the transportation planning process and a key input for several planning decisions. Such input needs to be generated or estimated in the early stages of the planning process. A passenger load profile is also a useful tool that illustrates the total number of passengers on board of a given line and direction in specific time periods. Once the passenger load profile is ge
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