Route Planning in Transportation Networks

We survey recent advances in algorithms for route planning in transportation networks. For road networks, we show that one can compute driving directions in milliseconds or less even at continental scale. A variety of techniques provide different trade-offs between preprocessing effort, space requirements, and query time. Some algorithms can answer queries in a fraction of a microsecond, while others can deal efficiently with real-time traffic. Journey planning on public transportation systems, although conceptually similar, is a significantly harder problem due to its inherent time-dependent and multicriteria nature. Although exact algorithms are fast enough for interactive queries on metropolitan transit systems, dealing with continent-sized instances requires simplifications or heavy preprocessing. The multimodal route planning problem, which seeks journeys combining schedule-based transportation (buses, trains) with unrestricted modes (walking, driving), is even harder, relying on approximate solutions even for metropolitan inputs.Comment: This is an updated version of the technical report MSR-TR-2014-4, previously published by Microsoft Research. This work was mostly done while the authors Daniel Delling, Andrew Goldberg, and Renato F. Werneck were at Microsoft Research Silicon Valle

Efficient Route Planning in Flight Networks

We present a set of three new time-dependent models with increasing flexibility for realistic route planning in flight networks. By these means, we obtain small graph sizes while modeling airport procedures in a realistic way. With these graphs, we are able to efficiently compute a set of best connections with multiple criteria over a full day. It even turns out that due to the very limited graph sizes it is feasible to precompute full distance tables between all airports. As a result, best connections can be retrieved in a few microseconds on real world data

UniALT for regular language contrained shortest paths on a multi-modal transportation network

Shortest paths on road networks can be efficiently calculated using Dijkstra\u27s algorithm (D). In addition to roads, multi-modal transportation networks include public transportation, bicycle lanes, etc. For paths on this type of network, further constraints, e.g., preferences in using certain modes of transportation, may arise. The regular language constrained shortest path problem deals with this kind of problem. It uses a regular language to model the constraints. The problem can be solved efficiently by using a generalization of Dijkstra\u27s algorithm (D_RegLC). In this paper we propose an adaption of the speed-up technique uniALT, in order to accelerate D_RegLC. We call our algorithm SDALT. We provide experimental results on a realistic multi-modal public transportation network including time-dependent cost functions on arcs. The experiments show that our algorithm performs well, with speed-ups of a factor 2 to 20

Agent-based modeling and simulation of individual traffic as an environment for bus schedule simulation

To re-establish the regular driving operations of a tram network, which was disturbed significantly by unforeseen external events, traffic schedulers apply rescheduling and rerouting strategies. These strategies are usually multi-modal; they consider the interaction of trams, buses, even taxis. Thus, to evaluate the applicability of a given rescheduling or rerouting strategy prior to its implementation in the real-world system, a multi-modal simulation software is needed. In this article we present an agent-based model of individual traffic which will be applied as background to a planned simulation of bus traffic. These combined models are to be integrated with an existing tram schedule simulation; the resulting multi-modal model will then be applied to evaluate the usefulness of given rescheduling or rerouting strategies. After a short introduction to agent-based modeling and simulation, as well as to existing models of individual traffic, this paper proposes to model the behavior of individual traffic as an environment for agent-based bus schedule simulation. Finally, some experiments are conducted by modeling and simulating individual traffic in Cologne's highly frequented Barbarossaplatz area

Agent-based modeling and simulation of individual traffic as an environment for bus schedule simulation

To re-establish the regular driving operations of a tram network, which was disturbed significantly by unforeseen external events, traffic schedulers apply rescheduling and rerouting strategies. These strategies are usually multi-modal; they consider the interaction of trams, buses, even taxis. Thus, to evaluate the applicability of a given rescheduling or rerouting strategy prior to its implementation in the real-world system, a multi-modal simulation software is needed. In this article we present an agent-based model of individual traffic which will be applied as background to a planned simulation of bus traffic. These combined models are to be integrated with an existing tram schedule simulation; the resulting multi-modal model will then be applied to evaluate the usefulness of given rescheduling or rerouting strategies. After a short introduction to agent-based modeling and simulation, as well as to existing models of individual traffic, this paper proposes to model the behavior of individual traffic as an environment for agent-based bus schedule simulation. Finally, some experiments are conducted by modeling and simulating individual traffic in Cologne's highly frequented Barbarossaplatz area

Algorithm Engineering for Realistic Journey Planning in Transportation Networks

Diese Dissertation beschäftigt sich mit der Routenplanung in Transportnetzen. Es werden neue, effiziente algorithmische Ansätze zur Berechnung optimaler Verbindungen in öffentlichen Verkehrsnetzen, Straßennetzen und multimodalen Netzen, die verschiedene Transportmodi miteinander verknüpfen, eingeführt. Im Fokus der Arbeit steht dabei die Praktikabilität der Ansätze, was durch eine ausführliche experimentelle Evaluation belegt wird

Engineering Algorithms for Route Planning in Multimodal Transportation Networks

Practical algorithms for route planning in transportation networks are a showpiece of successful Algorithm Engineering. This has produced many speedup techniques, varying in preprocessing time, space, query performance, simplicity, and ease of implementation. This thesis explores solutions to more realistic scenarios, taking into account, e.g., traffic, user preferences, public transit schedules, and the options offered by the many modalities of modern transportation networks

Transport in the Trans-Pennine Corridor: Present Conditions and Future Options. Interregional Study Working Paper 3.

This paper reports on a desk study carried out by the Institute for Transport Studies as part of a wider study of opportunities for inter-regional working in the trans-Pennine corridor, considering economic, environmental and transport issues. It draws together available information on transport and movement flows in the trans-Pennine corridor. These patterns of movement are examined from a broad perspective which considers intra-regional, inter- regional and international movements within and across the study area. The report proposes a regional package approach to transport, based on demand management and modal transfer

Capabilities of a Periodic Containerised Railfreight System in Germany

Based on an analysis of the developments to date, this article originates from and then substantiates long-discussed approaches of a fast, periodic unaccompanied combined rail freight transport network for Germany that corresponds to the target modal split. A four-stage scenario of a market entry is developed. The presented solution incorporates potentially novel aspects such as a network design based on the Deutschlandtakt Cargo integrated periodic timetable framework, the prospective quantity structures as of 2030, and a segmentation for a route-specific mix of two major shipping container types. The set of assessment indicators derived by the model allows to gain insights on the achievable capacities and service levels versus the addressable freight transport demand as well as consequential cost/benefit functions