Abstract
In transit modeling, access and egress conditions are often overlooked. The most common modeling technique of these conditions relies on the use of centroid connectors. This definition often uses the geographic position of zone centroids and sets constraints on the maximum number and length of connectors. This definition is subject to spatial aggregation issues and has already been proven to bias car assignment outcomes. The impact on transit assignment outcomes has not yet been demonstrated. The current paper investigates the statistical impact of connectors on transit assignment outcomes in an urban model of Lyon in France. Findings suggest that transit ridership, total passenger-kilometers and transit transfers are dependent on the definition of centroid connectors. Setting arbitrary values for the maximum number and length of connectors statistically affects transit results. The pattern and magnitude of this impact vary, however, between transit modes. The bus and rapid bus systems have been shown to be more sensitive towards the definition of connectors than the subway and the light rail systems. These findings question, to a certain extent, the validity and reliability of transit modeling outcomes.
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Notes
In fact, the calibration of transportation models often relies on “fine-tuning” the definition of connectors. In our case, this practice would mask the impact of the definition of centroid connectors on assignment outcomes.
Onboard Travel Surveys were conducted by the local transit authority between 2012 and 2016.
A trip is considered here as a travel, journey or movement between an origin and a destination using a specific travel mode or a combination of modes.
The Gaussian form is derived from a Gaussian Kernel-density estimation (KDE) method.
For these zones, all their centroid connectors are drawn but not necessarily used. Travel demand is distributed between connectors that produce shortest travel strategies.
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Acknowledgements
The authors are grateful to the reviewers of this paper. Their valuable comments and suggestions have contributed to the final version of this paper.
This work has been funded by ForCity, Agence Nationale de la Recherche et de la Technologie (ANRT), and Laboratoire Aménagement Economie Transports (LAET) under the CIFRE funding Grant no. 2015/0341. This financial support is gratefully acknowledged.
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