Abstract
We present a methodology to extract points of interest (POIs) data from OpenStreetMap (OSM) for application in travel demand models. We use custom taglists to identify and assign POI elements to typical activities used in travel demand models. We then compare the extracted OSM data with official sources and point out that the OSM data quality depends on the type of POI and that it generally matches the quality of official sources. It can therefore be used in travel demand models. However, we recommend that plausibility checks should be done to ensure a certain quality. Further, we present a methodology for calculating attractiveness measures for typical activities from single POIs and national trip generation guidelines. We show that the quality of these calculated measures is good enough for them to be used in travel demand models. Using our approach, therefore, allows the quick, automated, and flexible generation of attractiveness measures for travel demand models.
Highlights
We present a methodology to extract points of interest (POIs) data from OpenStreetMap (OSM) for application in travel demand models
Following typical approaches in travel demand modeling, several decisions are made by individuals and are represented in the models, the most important being: which activities should be conducted; where should the activity happen; and which mode and which route should be used to move to the activity location [1]
People are looking for feasible destinations to satisfy a certain need: supermarkets allow people to take care of their weekly grocery purchases; local recreation areas serve as places for spending leisure time; and train stations are appropriate points for picking up or dropping off friends or relatives
Summary
We present a methodology to extract points of interest (POIs) data from OpenStreetMap (OSM) for application in travel demand models. We compare the extracted OSM data with official sources and point out that the OSM data quality depends on the type of POI and that it generally matches the quality of official sources It can be used in travel demand models. Travel demand models are usually created manually For this purpose, data from the network along with supply and structural data are collected from all participating offices and authorities. Travel demand models use attractiveness as a measure to model people’s destination choices by using spatial interaction models [2]. For this purpose, structural data, such as the sales area of retail facilities or the daily number of visitors to recreational facilities, are collected. The paper finishes with a conclusion and outlook for future research
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Transportation Research Record: Journal of the Transportation Research Board
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
