Correlation between public transport stop demand and the number of people living in different distances in regions

Abstract

Properly developed public transport infrastructure, a well-organised public transport route network and mixed territorial development contribute to regional development, strengthen the regional labour market and help reduce social exclusion. Mobility issues in sparsely populated areas receive less attention from policy makers and territorial planners than in cities. The accessibility of public transport in sparsely populated and difficult to reach rural areas is less studied. The need for public transport for residents depends not only on the distribution of places of work, education, and leisure of residents, on their transport mobility, but also on public transport infrastructure and the supply of transport. It is accepted that in European cities the average distances to public transport stops are less than 500 m. In remote, sparsely populated areas, the distances are much greater. The analysed foreign examples showed that in rural areas the distance varies from 500 m to 4.5 km. Collectively, these studies demonstrate that no consensus has yet been reached on the optimal walking distance to public transport stops that would ensure adequate service accessibility for residents of sparsely populated areas. The purpose aim of this study, based on data from one Lithuanian region (Klaipėda district municipality), is to identify statistically significant distance thresholds that influence public transport use by integrating Geographic Information System (GIS) based spatial population data with passenger demand analysis, thereby creating a data-driven basis for optimizing public transport stop locations in sparsely populated regions. The study was conducted in 4 steps. In the Step 1, a database of stops was prepared, where groups of stops serving the same population were combined. In the Step 2, data on the need for stops were collected and the main service distances of stops that will be studied were determined. In the Step 3, the population of residents living at selected distances from specific stops was calculated, thus forming the main database that will be studied in the Step 4. In the Step 4, the level of dependence between stop demand and population was found at different distances. The study showed that the maximum distance at which the dependence remains strong is 1.5 km from the stops. Longer distances do not seem attractive to residents and they no longer consider public transport as an option for making a trip and private vehicles are most often chosen. It has also been found that with smaller distances between stops, the speed of public transport decreases significantly and thus increases travel time for residents who already travel long distances, thus taking up a significant part of their daily journey, and at the same time the correlation between 500 m and 300 m does not have a significant difference. Based on this, it is not recommended to arrange stops more often than every 500 m in rural regions.