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Computing the shortest path: A search meets graph theory

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TLDR
Experimental results show that the most efficient of the new shortest path algorithms outperforms previous algorithms, in particular A* search with Euclidean bounds, by a wide margin on road networks and on some synthetic problem families.
Abstract
We propose shortest path algorithms that use A* search in combination with a new graph-theoretic lower-bounding technique based on landmarks and the triangle inequality. Our algorithms compute optimal shortest paths and work on any directed graph. We give experimental results showing that the most efficient of our new algorithms outperforms previous algorithms, in particular A* search with Euclidean bounds, by a wide margin on road networks and on some synthetic problem families.

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Citations
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Journal ArticleDOI

A Survey of Motion Planning and Control Techniques for Self-Driving Urban Vehicles

TL;DR: In this article, the authors present a survey of the state of the art on planning and control algorithms with particular regard to the urban environment, along with a discussion of their effectiveness.
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A Survey of Motion Planning and Control Techniques for Self-driving Urban Vehicles

TL;DR: The objective of this paper is to survey the current state of the art on planning and control algorithms with particular regard to the urban setting and to gain insight into the strengths and limitations of the reviewed approaches.
Proceedings ArticleDOI

Map-matching for low-sampling-rate GPS trajectories

TL;DR: The results show that the ST-matching algorithm significantly outperform incremental algorithm in terms of matching accuracy for low-sampling trajectories and when compared with AFD-based global algorithm, ST-Matching also improves accuracy as well as running time.
Book ChapterDOI

Contraction hierarchies: faster and simpler hierarchical routing in road networks

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.
Book ChapterDOI

Route Planning in Transportation Networks

TL;DR: In this article, the authors survey recent advances in algorithms for route planning in transportation networks, and show that one can compute driving directions in milliseconds or less even at continental scale for road networks, while others can deal efficiently with real-time traffic.
References
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Journal ArticleDOI

A note on two problems in connexion with graphs

TL;DR: A tree is a graph with one and only one path between every two nodes, where at least one path exists between any two nodes and the length of each branch is given.
Book

Introduction to Algorithms

TL;DR: The updated new edition of the classic Introduction to Algorithms is intended primarily for use in undergraduate or graduate courses in algorithms or data structures and presents a rich variety of algorithms and covers them in considerable depth while making their design and analysis accessible to all levels of readers.
Journal ArticleDOI

A Formal Basis for the Heuristic Determination of Minimum Cost Paths

TL;DR: How heuristic information from the problem domain can be incorporated into a formal mathematical theory of graph searching is described and an optimality property of a class of search strategies is demonstrated.
Book

Linear Programming and Extensions

TL;DR: This classic book looks at a wealth of examples and develops linear programming methods for their solutions and begins by introducing the basic theory of linear inequalities and describes the powerful simplex method used to solve them.
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