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Ruttbaserade simulerade trafikdata för högupplöst analys av tunga godstransporter på det svenska vägnätet
RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.ORCID iD: 0000-0001-8029-4528
RISE Research Institutes of Sweden, Digital Systems, Mobility and Systems.ORCID iD: 0000-0003-2661-1064
2022 (Swedish)Report (Other academic)
Abstract [en]

Route-based simulated traffic data for high-resolution analysis of heavy goods transport on the Swedish road network In this report, a national database has been created regarding freight transport with heavy road vehicles. The primary purpose of the work is to serve as input for further analysis of what appropriate charging infrastructure planning and placement should look like given the knowledge of the transport work. It has thus been no ambition to give any recommendations in this report about, for example, expansion of charging infrastructure, but rather to collect and process information/data as well as develop methods and finally generate a data set that is useful and well representative of the traffic on the national road network. By the time of this publication, a dataset is available based on data from the Swedish Transport Administration’s Samgods-model with its simulations of transport connections based on transport demand between producer and consumer zones. In addition, all transport connections have been translated into routes (how trucks drive from A to B) on the road network, to enable analysis of electrification of/at specific road segments. Finally, the dataset has also been calibrated in various ways to better match statistics and actual measurements, as some major differences/deviations compared to some of them were identified. What the data set now consists of can be summarized as the number of truck movements and tons of goods that annually pass each road segment of the Swedish road network (and on some foreign roads). Furthermore, these totals can be easily divided into subsets and linked to specific routes, types of trucks (weight classes), origin, etcetera. Some shortcomings/limitations have been noticed during the production of this data set, such as the fact that the Samgods-model seems to miss a lot of transport in metropolitan areas, that the routing carried out by all flows is not completely perfect (which has partly to do with requests from OpenStreetMap), that the methods for generating new routes based on population density within municipalities are unlikely to be fully representative of where the transport is going, or that the data itself is based on a simulation model that tries to optimize which type of transport should be used to meet which demand. A couple of additional things may be worth clarifying: (1) The data only tells the number of transports or shipped goods between start and end nodes. Thus, there is no way to determine what the movement pattern of individual vehicle individuals looks like between routes, nor when in time each transport is performed. (2) The data only includes freight transport, and thus "misses" for example all passenger car traffic, which should also be seen as potential users of the charging infrastructure and thus be included in the calculations in the future. It would therefore be interesting to include these in some way in the next step.

Place, publisher, year, edition, pages
2022.
Series
RISE Rapport ; 2022:112
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:ri:diva-60209ISBN: 978-91-89711-63-1 (electronic)OAI: oai:DiVA.org:ri-60209DiVA, id: diva2:1699119
Note

2202-11-28: byte av fulltext pga mindre ändring. (71 nedladdningar)

Available from: 2022-09-27 Created: 2022-09-27 Last updated: 2023-06-30Bibliographically approved

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Alfredsson, HampusRogstadius, Jakob

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