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Identifying bicycle...
Identifying bicycle trip impediments by data fusion
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- Knapen, Luk (author)
- Hasselt University, Martelarenlaan 42, Hasselt, 3500, Belgium; VU Amsterdam, De Boelelaan 1105, Amsterdam, 1081HV, Netherlands
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- Holmgren, Johan (author)
- Malmö universitet,Internet of Things and People (IOTAP),Institutionen för datavetenskap och medieteknik (DVMT)
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(creator_code:org_t)
- Elsevier, 2020
- 2020
- English.
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In: Procedia Computer Science. - : Elsevier. - 1877-0509. ; 170, s. 195-202
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Abstract
Subject headings
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- A set of GPS traces for bicyclists and a set of notifications by bicyclists of problematic situations (spots identified by GPS records) had been collected independently. The data collection periods did not coincide but overlapped and none was contained in the other one. The aim is to use both datasets to determine an optimal action plan for problem solving given a limited budget. First, problematic locations are clustered. Each cluster corresponds to an impediment. Impediments are then associated with trips using a distance function. The aim is to find out which impediments to solve under a given budget constraint in order to maximize the number of impediment free trips. Thereto the trip set is partitioned by matching each trip with the largest set of its affecting impediments. Solving all impediments in such set induces a cost and makes the associated part of trips impediment free. An optimizer is presented and evaluated. (C) 2020 The Authors. Published by Elsevier B.V.
Subject headings
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Keyword
- bicyclist
- GPS traces
- clustering
- data fusion
Publication and Content Type
- ref (subject category)
- art (subject category)
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