Train journey times are just one part of the overall trip, which is door-to-door, not just station-to-station. It's important to understand how people get to the rail station and what barriers they might face. For example, if the local station is a 10-minute walk or a 30-minute drive, this can affect how people perceive and use rail travel. Even though rail might be attractive for station-to-station travel, people might still rely on buses or drive to the station. The performance of these feeder modes can either enable or hinder rail journeys.

Connectivity

Some suggested uses for public transport connectivity data

  • The dataset can be used to analyse how reachable a place is by rail, with a maximum journey time of 5 hours, where most of the travel should be by rail. The feeder modes (first and last mile) are varied to test their relative performance. The more places one can reach within 5 hours, the higher the score. For example, places near fast mainline routes score well due to the high speed of rail travel. In contrast, areas with poor local public transport score lower, suggesting that local buses are significantly less effective than cars as feeders for rail.

  • Improving journey times on rail can be costly, and new rail connections, like stations and lines, are even more expensive. However, optimising rail accessibility through analysing feeder modes could be more affordable and practical. The effectiveness of changes to the rail timetable and feeder mode reach and speed can be assessed both nationally and regionally to identify priorities and trade-offs.

  • The rail market is strong for medium and longer distances, especially for journeys over 5 miles to and from employment hubs. This dataset compares rail with other modes, both on its own and in combination with feeder modes, to highlight where rail has an advantage. It also shows where rail can improve its services to become more attractive and encourage people to switch from other modes of transport.