A Hybrid Link-Node Approach for Finding Shortest Paths in Road Networks with Turn Restrictions

AbstractShortest path planning is a fundamental building block in many applications. Hence developing efficient methods for computing shortest paths in, e.g., road or grid networks is an important challenge. The most successful techniques for fast query answering rely on preprocessing. However, for many of these techniques it is not fully understood why they perform so remarkably well, and theoretical justification for the empirical results is missing. An attempt to explain the excellent practical performance of preprocessing based techniques on road networks (as transit nodes, hub labels, or contraction hierarchies) in a sound theoretical way are parametrized analyses, e.g., considering the highway dimension or skeleton dimension of a graph. Still, these parameters may be large in case the network contains grid-like substructures—which inarguably is the case for real-world road networks around the globe. In this paper, we use the very intuitive notion of bounded growth graphs to describe road networks and also grid graphs. We show that this model suffices to prove sublinear search spaces for the three above mentioned state-of-the-art shortest path planning techniques. Furthermore, our preprocessing methods are close to the ones used in practice and only require expected polynomial time.

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Space-Efficient, Fast and Exact Routing in Time-Dependent Road Networks

Algorithms ◽

10.3390/a14030090 ◽

2021 ◽

Vol 14 (3) ◽

pp. 90

Author(s):

Ben Strasser ◽

Dorothea Wagner ◽

Tim Zeitz

Keyword(s):

Shortest Paths ◽

Road Networks ◽

Time Dependent ◽

Travel Times ◽

Traffic Patterns ◽

Two Phase ◽

The Road ◽

On The Road ◽

Core Idea ◽

Point To Point

We study the problem of quickly computing point-to-point shortest paths in massive road networks with traffic predictions. Incorporating traffic predictions into routing allows, for example, to avoid commuter traffic congestions. Existing techniques follow a two-phase approach: In a preprocessing step, an index is built. The index depends on the road network and the traffic patterns but not on the path start and end. The latter are the input of the query phase, in which shortest paths are computed. All existing techniques have large index size, slow query running times or may compute suboptimal paths. In this work, we introduce CATCHUp (Customizable Approximated Time-dependent Contraction Hierarchies through Unpacking), the first algorithm that simultaneously achieves all three objectives. The core idea of CATCHUp is to store paths instead of travel times at shortcuts. Shortcut travel times are derived lazily from the stored paths. We perform an experimental study on a set of real world instances and compare our approach with state-of-the-art techniques. Our approach achieves the fastest preprocessing, competitive query running times and up to 38 times smaller indexes than competing approaches.

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Finding Shortest Path for Road Network Using Dijkstra’s Algorithm

Bangladesh Journal of Multidisciplinary Scientific Research ◽

10.46281/bjmsr.v1i2.366 ◽

2019 ◽

Vol 1 (2) ◽

pp. 41-45

Author(s):

Md. Almash Alam ◽

Md. Omar Faruq

Keyword(s):

Shortest Path ◽

Road Network ◽

Shortest Paths ◽

Road Networks ◽

Transportation Systems ◽

Shortest Path Problem ◽

Dijkstra’S Algorithm ◽

Traffic Condition ◽

Shortest Path Problems ◽

Dijkstra's Algorithm

Roads play a Major role to the people live in various states, cities, town and villages, from each and every day they travel to work, to schools, to business meetings, and to transport their goods. Even in this modern era whole world used roads, remain one of the most useful mediums used most frequently for transportation and travel. The manipulation of shortest paths between various locations appears to be a major problem in the road networks. The large range of applications and product was introduced to solve or overcome the difficulties by developing different shortest path algorithms. Even now the problem still exists to find the shortest path for road networks. Shortest Path problems are inevitable in road network applications such as city emergency handling and drive guiding system. Basic concepts of network analysis in connection with traffic issues are explored. The traffic condition among a city changes from time to time and there are usually huge amounts of requests occur, it needs to find the solution quickly. The above problems can be rectified through shortest paths by using the Dijkstra’s Algorithm. The main objective is the low cost of the implementation. The shortest path problem is to find a path between two vertices (nodes) on a given graph, such that the sum of the weights on its constituent edges is minimized. This problem has been intensively investigated over years, due to its extensive applications in graph theory, artificial intelligence, computer network and the design of transportation systems. The classic Dijkstra’s algorithm was designed to solve the single source shortest path problem for a static graph. It works starting from the source node and calculating the shortest path on the whole network. Noting that an upper bound of the distance between two nodes can be evaluated in advance on the given transportation network.

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Continuously monitoring alternative shortest paths on road networks

Proceedings of the VLDB Endowment ◽

10.14778/3407790.3407822 ◽

2020 ◽

Vol 13 (12) ◽

pp. 2243-2255

Author(s):

Lingxiao Li ◽

Muhammad Aamir Cheema ◽

Mohammed Eunus Ali ◽

Hua Lu ◽

David Taniar

Keyword(s):

Shortest Paths ◽

Road Networks

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Querying shortest paths on time dependent road networks

Proceedings of the VLDB Endowment ◽

10.14778/3342263.3342265 ◽

2019 ◽

Vol 12 (11) ◽

pp. 1249-1261 ◽

Cited By ~ 2

Author(s):

Yong Wang ◽

Guoliang Li ◽

Nan Tang

Keyword(s):

Shortest Paths ◽

Road Networks ◽

Time Dependent

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