Fast travel-distance estimation using overhead graph

Shortest path can be computed in real-time for single navigational instructions. However, in complex optimisation tasks, lots of travel-distances (lengths of shortest paths) are needed and the total workload becomes a burden. We present a fast method for estimating the travel-distance from one locat...

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Published in:Journal of Location Based Services
Main Authors: Mariescu-Istodor, Radu, Fränti, Pasi
Other Authors: School of Computing, activities
Format: Article in Journal/Newspaper
Language:unknown
Published: Informa UK Limited 2021
Subjects:
Online Access:https://erepo.uef.fi/handle/123456789/26390
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spelling ftuniveasternfin:oai:erepo.uef.fi:123456789/26390 2023-05-15T17:00:19+02:00 Fast travel-distance estimation using overhead graph Mariescu-Istodor, Radu Fränti, Pasi School of Computing, activities 2021-11-08T07:26:11Z 261-279 https://erepo.uef.fi/handle/123456789/26390 englanti unknown Informa UK Limited Journal of location based services http://dx.doi.org/10.1080/17489725.2021.1889058 10.1080/17489725.2021.1889058 1748-9725 4 15 https://erepo.uef.fi/handle/123456789/26390 CC BY 4.0 openAccess © 2021 The Authors https://creativecommons.org/licenses/by/4.0/ CC-BY travel-time estimation travel-distance estimation road network graph Tieteelliset aikakauslehtiartikkelit A1 article artikkeli 2021 ftuniveasternfin https://doi.org/10.1080/17489725.2021.1889058 2022-12-11T06:55:05Z Shortest path can be computed in real-time for single navigational instructions. However, in complex optimisation tasks, lots of travel-distances (lengths of shortest paths) are needed and the total workload becomes a burden. We present a fast method for estimating the travel-distance from one location to another by using an overhead graph that stores the ratio between the bird-distance and the travel-distance for few representative locations. The travel-distance is then estimated for any two locations using the corresponding value between their nearest nodes in the graph. We test the method within an optimization setting where the goal is to relocate health services so that the travel-distance of patients is minimised. We build the overhead graph using road network information from Open Street Map and experiment with real-world data in the region of North Karelia, Finland as a part of the ongoing IMPRO project. The results show that the average estimation error is 0.5 km with a graph of 512 nodes, and the total processing time reduces from 1.2 hours to 2.9 seconds per iteration in the optimisation process. The error in the estimated travel-distances is 2%, on average, which is significantly smaller than 8% of the second best estimation method. published version peerReviewed Article in Journal/Newspaper karelia* UEF eRepository (University of Eastern Finland) Journal of Location Based Services 15 4 261 279
institution Open Polar
collection UEF eRepository (University of Eastern Finland)
op_collection_id ftuniveasternfin
language unknown
topic travel-time estimation
travel-distance estimation
road network
graph
spellingShingle travel-time estimation
travel-distance estimation
road network
graph
Mariescu-Istodor, Radu
Fränti, Pasi
Fast travel-distance estimation using overhead graph
topic_facet travel-time estimation
travel-distance estimation
road network
graph
description Shortest path can be computed in real-time for single navigational instructions. However, in complex optimisation tasks, lots of travel-distances (lengths of shortest paths) are needed and the total workload becomes a burden. We present a fast method for estimating the travel-distance from one location to another by using an overhead graph that stores the ratio between the bird-distance and the travel-distance for few representative locations. The travel-distance is then estimated for any two locations using the corresponding value between their nearest nodes in the graph. We test the method within an optimization setting where the goal is to relocate health services so that the travel-distance of patients is minimised. We build the overhead graph using road network information from Open Street Map and experiment with real-world data in the region of North Karelia, Finland as a part of the ongoing IMPRO project. The results show that the average estimation error is 0.5 km with a graph of 512 nodes, and the total processing time reduces from 1.2 hours to 2.9 seconds per iteration in the optimisation process. The error in the estimated travel-distances is 2%, on average, which is significantly smaller than 8% of the second best estimation method. published version peerReviewed
author2 School of Computing, activities
format Article in Journal/Newspaper
author Mariescu-Istodor, Radu
Fränti, Pasi
author_facet Mariescu-Istodor, Radu
Fränti, Pasi
author_sort Mariescu-Istodor, Radu
title Fast travel-distance estimation using overhead graph
title_short Fast travel-distance estimation using overhead graph
title_full Fast travel-distance estimation using overhead graph
title_fullStr Fast travel-distance estimation using overhead graph
title_full_unstemmed Fast travel-distance estimation using overhead graph
title_sort fast travel-distance estimation using overhead graph
publisher Informa UK Limited
publishDate 2021
url https://erepo.uef.fi/handle/123456789/26390
genre karelia*
genre_facet karelia*
op_relation Journal of location based services
http://dx.doi.org/10.1080/17489725.2021.1889058
10.1080/17489725.2021.1889058
1748-9725
4
15
https://erepo.uef.fi/handle/123456789/26390
op_rights CC BY 4.0
openAccess
© 2021 The Authors
https://creativecommons.org/licenses/by/4.0/
op_rightsnorm CC-BY
op_doi https://doi.org/10.1080/17489725.2021.1889058
container_title Journal of Location Based Services
container_volume 15
container_issue 4
container_start_page 261
op_container_end_page 279
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