Fully Dynamic Maintenance of Arc-Flags in Road Networks

International audienceThe problem of finding best routes in road networks can be solved by applying Dijkstra's shortest paths algorithm. Unfortunately, road networks deriving from real-world applications are huge yielding unsustainable times to compute shortest paths. For this reason, great research efforts have been done to accelerate Dijkstra's algorithm on road networks. These efforts have led to the development of a number of speed-up techniques, as for example Arc-Flags, whose aim is to compute additional data in a preprocessing phase in order to accelerate the shortest paths queries in an on-line phase. The main drawback of most of these techniques is that they do not work well in dynamic scenarios. In this paper we propose a new algorithm to update the Arc-Flags of a graph subject to edge weight decrease operations. To check the practical performances of the new algorithm we experimentally analyze it, along with a previously known algorithm for edge weight increase operations, on real-world road networks subject to fully dynamic sequences of operations. Our experiments show a significant speed-up in the updating phase of the Arc-Flags, at the cost of a small space and time overhead in the preprocessing phase

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

Recent Advances in Fully Dynamic Graph Algorithms

In recent years, significant advances have been made in the design and analysis of fully dynamic algorithms. However, these theoretical results have received very little attention from the practical perspective. Few of the algorithms are implemented and tested on real datasets, and their practical potential is far from understood. Here, we present a quick reference guide to recent engineering and theory results in the area of fully dynamic graph algorithms

Evolution and Evaluation of the Penalty Method for Alternative Graphs

Computing meaningful alternative routes in a road network is a complex problem -- already giving a clear definition of a best alternative seems to be impossible. Still, multiple methods describe how to compute reasonable alternative routes, each according to their own quality criteria. Among these methods, the penalty method has received much less attention than the via-node or plateaux based approaches. A mayor cause for the lack of interest might be the unavailability of an efficient implementation. In this paper, we take a closer look at the penalty method and extend upon its ideas. We provide the first viable implementation --suitable for interactive use-- using dynamic runtime adjustments to perform up to multiple orders of magnitude faster queries than previous implementations. Using our new implementation, we thoroughly evaluate the penalty method for its flaws and benefits

Poor Philanthropist III: A Practice-relevant Guide for Community Philanthropy

This is a guide for a research study carried out between 2003 and 2005, the purpose of which was to explore the local ethos of caring and sharing in poor African communities.This guide is intended to assist grantmakers and funders working with impoverished communities in applying a PoC lens to their practice

Poor Philanthropist III: A Practice Relevant Guide to Community Philanthropy

This guide has its origins in a research study carried out between 2003 and 2005, the purpose of which was to explore the local ethos of caring and sharing in poor African communities. Focus groups carried out by national research teams in Namibia, Mozambique, South Africa and Zimbabwe generated rich narrative text revealing what the term 'help' means to the poor, who helps and is helped in poor communities, the forms help takes and, finally, why people help each other. This knowledge informed the first systematic understanding of 'indigenous philanthropy' in southern Africa. To emphasise the local ethos of caring and sharing and make it more visible to development organisations, it was named. The term 'horizontal philanthropy' or 'philanthropy of community' (PoC) was coined and the research findings documented in a 2005 monograph entitled, The Poor Philanthropist: How and Why the Poor Help Each Other (Wilkinson-Maposa, Fowler, Oliver-Evans & Mulenga 2005). The findings published in 2005 sparked the interest of the development community

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

Grenoble Traffic Lab: An experimental platform for advanced traffic monitoring and forecasting

International audienceThis paper describes the main features of the "Grenoble Traffic Lab" (GTL), a new experimental platform for the collection of traffic data coming from a dense network of wireless sensors installed in the south ring of Grenoble, in France. The main challenges related to the configuration of the platform and data validation are discussed, and two relevant traffic monitoring and forecasting applications are presented to illustrate the operation of GTL

Congestion Avoidance on Road Networks through Adaptive Routing on Contracted Graphs

We have developed a method of integrating live traffic information into preprocessed graphs of large road networks in order to adaptively route autonomous vehicles. Our intent is to reduce congestion caused by fleets of centrally-routed vehicles being assigned overlapping routes and to help those vehicles avoid already congested areas. Recent developments in shortest-path routing, namely Contraction Hierarchies, are used in conjunction with a modified bidirectional Dijkstra search algorithm to ensure fast route computations despite frequent graph updates. We introduce a novel heuristic for graph reprocessing that enables quick updates alongside a simple approach to computing appropriate edge weights based on substantial amounts of feedback received from vehicles on the road. Our approach is tested on a developed simulation platform using real road data and a Nagel-Schreckenberg traffic model. Results show that vehicles experience an overall speedup in travel time and adeptly react to unforeseen conditions by using alternative routes to avoid further congestion.Bachelor of Scienc