Reliability in public transit networks considering backup itineraries

Abstract

Itinerary planning serves an important purpose for travelers navigating through a public transit network. The uncertainty of travel times within the network must be considered since this uncertainty can lead to delays or missed transfers. If an initial transit service or a transfer between services is missed, then the traveler must have a contingency plan for reaching their destination. However, finding reliable itineraries with contingency plans is computationally challenging. This paper outlines an a priori policy that maximizes the reliability, i.e. the probability of reaching the destination within a travel time budget, while considering the most reliable primary itinerary and backup itineraries in case a transfer is missed. We develop a network search algorithm that finds the most reliable itinerary with backups, which accurately accounts for the uncertainty of travel times and frequency of alternative options in the recommendation. We compare our approach to state-of-the-art contingency research, Dynamic Journeying Under Uncertainty by Häme and Hakula (2013), and show that it more accurately calculates the reliability, is more intuitive to the traveler, and has a faster runtime. Additionally, we highlight the differences in reliability across times of day, travel time budgets, and city regions for a real-world transit network in Göttingen, Germany. This approach offers travelers an easy-to-understand tool for planning reliable public transit travel itineraries.