Enhanced Huff model for estimating Park and Ride (PnR) catchment areas in Perth, WA

Lin, Ting (Grace), Xia, Jianhong (Cecilia), Todd P. Robinson, Doina Olaru, Brett Smith, John Taplin and Buyang Cao

Journal of Transport Geography, 2016, vol. 54, issue C, 336-348

Abstract: A train station catchment area delineates the spatial territory from which the users of a train station are drawn. The size and shape of this catchment can be influenced by a variety of factors, such as the transport network, the location of stations and the service quality they offer, as well as the land use density and diversity in the transport corridor. Although numerous studies have been conducted to understand the size of catchment areas, limited research has focused on determining the spatial boundary (shape) of train station catchments. This paper develops a framework for deriving a spatial boundary of a Park and Ride (PnR) catchment area by incorporating the Huff model and Geographic Information Systems (GIS) technologies. The approach is staged, firstly determining the PnR station choice as a function of the attractiveness of a train station and the cost of access between the origin (such as a suburb) and the destination of a trip (such as the Perth CBD). Linear referencing method is then applied to re-define the origins to train stations based on the derived station choice probability. Finally, the spatial boundary of a catchment area is determined according to the adjusted origins, using GIS technologies. The model outputs were evaluated against licence plate survey of station users, where the Kappa coefficient (0.74) and overall accuracy (0.88) statistic suggested that the model's results are robust. The paper then shows how catchment area data can be used to better manage travel demand and plan design solutions aimed at increased accessibility to train stations.

Keywords: Urban rail transport; Station choice; Modified Huff model; Linear referencing; Station attractiveness (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:jotrge:v:54:y:2016:i:c:p:336-348

DOI: 10.1016/j.jtrangeo.2016.06.011

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