Calibrating travel time thresholds with cluster analysis and AFC data for passenger reasonable route generation on an ur
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Calibrating travel time thresholds with cluster analysis and AFC data for passenger reasonable route generation on an urban rail transit network Wei Zhu1,2 · Wei‑li Fan1,2 · Amr M. Wahaballa3 · Jin Wei1,2
© Springer Science+Business Media, LLC, part of Springer Nature 2019
Abstract Estimating the route choice patterns for transit passengers is important to improve service reliability. The size and composition of a route choice set affects the choice model estimation and passenger flow calculations for urban rail transit (URT) networks. With the existing threshold decision method, there will be omissions or excess routes in the generated route set, which lead to a significant deviation in passenger flow assignments. This paper proposes a data-driven approach to calibrate the travel time thresholds when generating reasonable route choice sets. First, an automatic fare collection (AFC) data-driven framework is established to more accurately calibrate and dynamically update travel time thresholds with changes in the URT system. The framework consists of four steps: data preprocessing, origin–destination-based threshold calculation, cluster analysis-based calibration, and calibrated result output and update. Second, the proposed approach is applied to the Beijing subway as a case study, and several promising results are analyzed that allow the optimization of existing travel time thresholds. The obtained results help in the estimation of route choice behavior to validate current rail transit assignment models. This study is also applicable for other rail transit networks with AFC systems to record passenger passage times at both entry and exit gates. Keywords Urban rail transit · Automatic fare collection data · Route choice set · Travel time threshold · Calibration
* Wei Zhu [email protected] 1
The Key Laboratory of Road and Traffic Engineering, Ministry of Education, Tongji University, 4800 Cao’an Road, Shanghai 201804, China
2
College of Transportation Engineering, Tongji University, 4800 Cao’an Road, Shanghai 201804, China
3
Aswan University, Aboelreesh Kebly, Aswan 81542, Egypt
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Transportation
Introduction The urban rail transit (URT) system has significantly advanced in recent years and become the mainstay of urban passenger transportation systems in many cities around the world. Passenger flow is the foundation to develop and coordinate operational plans for a URT system. Therefore, a variety of studies have been conducted on URT assignment models that have become increasingly complex. However, it is noted that passenger route choice sets also play a crucial role in obtaining precise results. Several research efforts found that the size and composition of a route choice set affects the choice model estimation and passenger flow calculations (Bovy 2009; Ren et al. 2012; Swait and Ben-Akiva 1987). Incorrect route choice sets can lead to misclassification of choice models and calculation biases on passenger flow levels. In most cases, there is no benefit to enumerating r
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