Abstract

Abstract Public transit is a backbone for well-functioning cities, forming a complicated system of interconnecting lines each with their own frequency. Defining accessibility for public transit is just as complicated, as travel times can change every minute depending on location and departure time. With Pareto optimal journeys it is possible to look beyond the earliest arrival times and also optimize for the shortest travel time, as travellers base their departure time on the start time given by their smartphone app, especially when service frequencies are low. By querying for all Pareto optimal journeys in a time range it becomes possible to get a grasp of what passengers see as their choice set when it comes to transit route choice. Based on the averages of the Pareto optimal journeys it should become possible to calculate more realistic skim matrices for traffic analysis zones, including reliability factors such as frequencies and the number of transfers. In this study we calculate Pareto optimal journeys in the area in and around Amsterdam, looking at how travel times are distributed and what factors impact them.

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