Public Transit Labeling

Abstract

We study the journey planning problem in public transit networks. Developing efficient preprocessing-based speedup techniques for this problem has been challenging: current approaches either require massive preprocessing effort or provide limited speedups. Leveraging recent advances in Hub Labeling, the fastest algorithm for road networks, we revisit the well-known time-expanded model for public transit. Exploiting domainspecific properties, we provide simple and efficient algorithms for the earliest arrival, profile, and multicriteria problems, with queries that are orders of magnitude faster than the state of the art.

Trip-Based Public Transit Routing

“…5 We have faster query times than CSA [11] and RAPTOR [10], geo-rank (2 r ) running time (ms) Figure 2: Profile query times by geo-rank on Germany at the cost of a few minutes of preprocessing time. Transfer Patterns (TP) [1,3] and Public Transit Labeling (PTL) [8] have faster query times (especially on larger instances), however, their preprocessing times are several orders of magnitude above ours.…”

Improved Public Transit Routing Algorithm for Finding the Shortest K-Path

“…As research related to this study, there are studies on timetablebased public transit routing, studies related to multiple-routing, and studies related to transfer penalty. First, as typical timetable-based public transit routing algorithms being recently developed, RAPTOR (Round-bAsed Public Transit Optimized Router), CSA (Connection Scanning Algorithm), and Tripbased (Delling et al, 2015;Dibbelt et al, 2013;Madkour et al, 2017) can be cited. Delling et al (2012) proposed the RAPTOR algorithm, in which they stored route"s vehicle arrival time at each stop, searched for vehicles passing by each stop, and computed the minimum arrival time and path to the end arrival stop.…”

Public transportation network design: a geospatial data-driven method

“…Another of their work [8] offers a routing mechanism for calculating traffic directions in large-scale road networks. And in [9], we suggest public transit transportation as the solution of the journey in the future. Turning to other works, one can distinguish [10].…”