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Journal ArticleDOI

Improving Path Query Performance in Pgrouting Using a Map Generalization Approach

TL;DR: An in-depth analysis of the trade-offs between deviation in computed path and the performance gain in terms of space and time on road networks of varying sizes and topology is presented to get a better understanding of this approach and its applicability to large road networks.
Abstract: . pgRouting library provides functions to compute shortest path between any two points of a road network which is of great demand and also a topic of interest in the field of GIS, graph theory and transportation. To compute path in a road network, pgRouting functions process the entire road network which is a major bottleneck when it comes to routing in large road networks leading to the requirement of large server resources. A reduction/compression in the input network that is to be processed for path computation would improve the performance of pgRouting. In this study a map generalization based network model is proposed which extracts a significantly smaller subset of the road network aka skeleton which further used to divide the network into zones, that shall be selectively used in path computation. This results in processing a much smaller part of the network to compute path between any two points leading to an overall improvement in query performance of pgRouting when computing path, especially on large road networks. As part of assessment of this approach and its applicability to large road networks, the paper presents an in-depth analysis of the trade-offs between deviation in computed path and the performance gain in terms of space and time on road networks of varying sizes and topology to get a better understanding for both providing a sound proof of the utility of the proposed method and also to show its implementability within the current model of pgRouting or any other routing platforms.

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Book ChapterDOI
30 May 2008
TL;DR: CHs can be combined with many other route planning techniques, leading to improved performance for many-to-many routing, transit-node routing, goal-directed routing or mobile and dynamic scenarios, and a hierarchical query algorithm using bidirectional shortest-path search is obtained.
Abstract: We present a route planning technique solely based on the concept of node contraction. The nodes are first ordered by 'importance'. A hierarchy is then generated by iteratively contracting the least important node. Contracting a node υ means replacing shortest paths going through v by shortcuts. We obtain a hierarchical query algorithm using bidirectional shortest-path search. The forward search uses only edges leading to more important nodes and the backward search uses only edges coming from more important nodes. For fastest routes in road networks, the graph remains very sparse throughout the contraction process using rather simple heuristics for ordering the nodes. We have five times lower query times than the best previous hierarchical Dijkstra-based speedup techniques and a negative space overhead, i.e., the data structure for distance computation needs less space than the input graph. CHs can be combined with many other route planning techniques, leading to improved performance for many-to-many routing, transit-node routing, goal-directed routing or mobile and dynamic scenarios.

739 citations


"Improving Path Query Performance in..." refers background in this paper

  • ...(Geisberger et al., 2008) try to contract the graph by addition of shortcuts and store precomputed paths to achieve speedups in path computation....

    [...]

Journal ArticleDOI
TL;DR: This paper proposes a novel generalization model for selecting characteristic streets in an urban street network using graph principles where vertices represent named streets and links represent street intersections and centrality measures are introduced to qualify the status of each individual vertex within the graph.
Abstract: This paper proposes a novel generalization model for selecting characteristic streets in an urban street network. This model retains the central structure of a street network. It relies on a structural representation of a street network using graph principles where vertices represent named streets and links represent street intersections. Based on this representation, so-called connectivity graph, centrality measures are introduced to qualify the status of each individual vertex within the graph. We show that these measures can be used for characterizing the structural properties of an urban street network, and for the selection of important streets. The proposed approach is validated by a case study applied to a middle-sized Swedish city.

254 citations


"Improving Path Query Performance in..." refers background in this paper

  • ...(Thomson and Richardson, 1995, Mackaness and Beard, 1993, Jiang and Claramunt, 2004, Jiang and Harrie, 2004) propose graph theory based generalization methods....

    [...]

Book ChapterDOI
TL;DR: An experimental study that evaluates which partitioning methods are suited for Dijkstra's algorithm for the point-to-point shortest path problem in large and sparse graphs with a given layout and an extension of this speed-up technique to multiple levels of partitionings.
Abstract: In this paper, we consider Dijkstra's algorithm for the point-to-point shortest path problem in large and sparse graphs with a given layout. In [1], a method has been presented that uses a partitioning of the graph to perform a preprocessing which allows to speed-up Dijkstra's algorithm considerably. We present an experimental study that evaluates which partitioning methods are suited for this approach. In particular, we examine partitioning algorithms from computational geometry and compare their impact on the speed-up of the shortest-path algorithm. Using a suited partitioning algorithm speed-up factors of 500 and more were achieved. Furthermore, we present an extension of this speed-up technique to multiple levels of partitionings. With this multi-level variant, the same speed-up factors can be achieved with smaller space requirements. It can therefore be seen as a compression of the precomputed data that conserves the correctness of the computed shortest paths.

124 citations


"Improving Path Query Performance in..." refers background in this paper

  • ...(Möhring et al., 2005, Jung and Pramanik, 1996, Chondrogiannis and Gamper, 2016) try to partition the graph into clusters and store precomputed paths to reduce the search space and improve path computation....

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Journal ArticleDOI
01 Jan 1993
TL;DR: In this article, the essential characteristics and behavior of objects are preserved in the generalization of a concept, and the appropriate selection and application of procedures (such as procedure selection and procedure application) are discussed.
Abstract: In the generalization of a concept, we seek to preserve the essential characteristics and behavior of objects. In map generalization, the appropriate selection and application of procedures (such a...

123 citations


"Improving Path Query Performance in..." refers background in this paper

  • ...(Thomson and Richardson, 1995, Mackaness and Beard, 1993, Jiang and Claramunt, 2004, Jiang and Harrie, 2004) propose graph theory based generalization methods....

    [...]

Journal ArticleDOI
TL;DR: This work proposes a novel approach to selection of important streets from a network, based on the technique of a self‐organizing map (SOM), an artificial neural network algorithm for data clustering and visualization, providing a visual tool to cluster streets interactively.
Abstract: We propose a novel approach to selection of important streets from a network, based on the technique of a self-organizing map (SOM), an artificial neural network algorithm for data clustering and visualization. Using the SOM training process, the approach derives a set of neurons by considering multiple attributes including topological, geometric and semantic properties of streets. The set of neurons constitutes a SOM, with which each neuron corresponds to a set of streets with similar properties. Our approach creates an exploratory linkage between the SOM and a street network, thus providing a visual tool to cluster streets interactively. The approach is validated with a case study applied to the street network in Munich, Germany.

89 citations


"Improving Path Query Performance in..." refers background in this paper

  • ...(Thomson and Richardson, 1995, Mackaness and Beard, 1993, Jiang and Claramunt, 2004, Jiang and Harrie, 2004) propose graph theory based generalization methods....

    [...]