Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/26214
Title: GTFS Bus Stop Mapping to the OSM Network
Authors: VUURSTAEK, Jan 
CICH, Glenn 
KNAPEN, Luk 
ECTORS, Wim 
YASAR, Ansar 
BELLEMANS, Tom 
JANSSENS, Davy 
Issue Date: 2020
Publisher: ELSEVIER
Source: Future generation computer systems, 110, p. 393-406
Abstract: Due to budget constraints public transportation (PT) can no longer be deployed in regions where it attractsinsufficient customers. Novel techniques such as demand-responsive collective transportation (DRT) areevaluated to cut costs. This requires detailed simulations that are able to predict travel demand andinclude trip execution. Simulating facilities acting as feeder services to time-table based PT servicesrequires detailed and accurate information about the PT infrastructure on a network. However, there areno public data sources that combine network and PT infrastructure data with the preferred level of detail.This led to the development of a new bus stop mapping technique that combines the OpenStreetMap (OSM)and General Transit Feed Specification (GTFS) open data sources, which are maintained independently.Merging the data into a single database requires alignment. Developing bus stop mapping algorithmsis challenging due to (i) inaccurate location data, (ii) inconsistent data sources and (iii) the vastlyinterconnected PT network and services. Due to the inaccuracy in the GTFS stop locations and in the OSMnetwork, pure geometric considerations might lead to multiple candidate solutions to map a stop to thenetwork. The new technique handles all GTFS trips at once and operates under the assumption that PToperators minimize the total distance driven to complete all trips.
Keywords: OpenStreetMap (OSM);General Transit Feed Specification (GTFS);Micro-simulation;Public transport;Mapping algorithm
Document URI: http://hdl.handle.net/1942/26214
ISSN: 0167-739X
e-ISSN: 1872-7115
DOI: 10.1016/j.future.2018.02.020
ISI #: WOS:000541153400036
Rights: © 2018 Elsevier B.V. All rights reserved.
Category: A1
Type: Journal Contribution
Validations: ecoom 2021
Appears in Collections:Research publications

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