Transit trip distribution model considering land use differences between catchment areas

Abstract

Sustainable land use planning and advanced public transport system are believed to be effective solutions to traffic congestion. To this end, it is important to reveal the relationship between transit ridership and land use. However, current Direct Ridership Models only focus on the relationship between single station's boarding volume and the corresponding catchment area land use. This paper analyzed the ridership distribution between transit stations by considering the land use difference between catchment areas. Land use difference was calculated from point of interest (POI) data extracted from an electronic map of Beijing; transit trip distribution volume was obtained from 'automatic fare collection' facility. After data specification, a transit ridership distribution model was proposed and calibrated. The calibration results suggest that land use difference has a directly proportional correlation with transit ridership distribution. The research findings build a bridge between detailed urban form and public transport, which is of significance for the further research of sustainable urban planning.

How Do Land Use Types and Transport Conditions Affect Population Aggregation Around Suburban Metro Stations: A Case Study in Shanghai

“…Some factors can reflect the locations of stations. Distance to city center has been taken into account most frequently in previous studies and it turned out that this factor had a considerably negative influence on station ridership [30,31]. Besides, average distances to adjacent stations, nearest commercial centers, schools or other facilities were also regarded as possible influential factors of station catchment areas [29].…”

Considering context and dynamics: A classification of transit-orientated development for New York City

“…Input to the Land Use and Built Environment, and Location and Accessibility domains were drawn from a range of sources including the Census and other public survey data, but also Points of Interest (POI) databases either as supplements or alternatives to conventional land-use measures (see Wang et al, 2016;Lyu et al, 2016;Wang et al, 2017). These studies advocated that POI data may capture finer-grained and more up to date information depicting the land use composition and urban facilities.…”

Site Selection for New Point to Point (P2p) Bus Endpoints and Routes in Metro Manila, Philippines

“…Vital to transportation planning especially for urbanized areas, gravity model for trip distribution can be used to assess the current transportation efficiency and improve transportation system in the area (Boukebbab, et al, 2015;Jung, et al, 2007;Tsekeris, et al, 2006). Since this model evaluates the connectivity and distribution between zones, transportation modes can be assessed and improved through the number of trips and its distribution as manifested in the studies of Cordera, et al (2018), Wang, et al (2016), and Asmael, et al (2018). In the case of this study, trip distribution values shall be used for the determination of endpoints of P2P bus system and improve its efficiency for better alternative for mass transportation.…”