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Access and Connectivity Trade-Offs in Transit Stop Location
A formulation is proposed to address the trade-off between transit user access and trip connectivity. Transit access is typically regarded as the physical proximity to transit service. Additional stops can provide greater access to the service and reduce walking distance to stops. However, closer st...
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Published in: | Transportation research record 2014-01, Vol.2466 (1), p.1-11 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | A formulation is proposed to address the trade-off between transit user access and trip connectivity. Transit access is typically regarded as the physical proximity to transit service. Additional stops can provide greater access to the service and reduce walking distance to stops. However, closer stops do not guarantee that routes serving the stops are well connected to desired trip destinations. In general, transit riders are willing to walk longer distances to access a stop that has frequent transit service, requires less wait time, and is well connected to their desired destinations. Frequent stops on the way to these desired destinations, although they provide shorter walking distance for some passengers, increase dwell time; this dwell time results in a smaller portion of the network's being connected within a certain travel time, which is an important element of the connectivity of the system. The proposed methodology considers both the impact of access distance to transit stops and trip connections to destinations for determining optimal stop locations and setting optimal transit line frequencies. The bus stop location model is formulated as a mixed-integer program and the coin-or branch-and-cut solver is used to solve the problem. Sensitivity analyses are performed and computational results are presented for an illustrative example. To illustrate the usefulness of the model, the formulation is applied to the bus transit network in New Haven, Connecticut, as a case study. |
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ISSN: | 0361-1981 2169-4052 |
DOI: | 10.3141/2466-01 |