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| Fältnamn | Indikatorer | Metadata |
|---|---|---|
| 000 | 03606naa a2200373 4500 | |
| 001 | oai:DiVA.org:kth-344060 | |
| 003 | SwePub | |
| 008 | 240229s2023 | |||||||||||000 ||eng| | |
| 009 | oai:DiVA.org:liu-205197 | |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-3440602 URI |
| 024 | 7 | a https://doi.org/10.1109/ITSC57777.2023.104221992 DOI |
| 024 | 7 | a https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2051972 URI |
| 040 | a (SwePub)kthd (SwePub)liu | |
| 041 | a engb eng | |
| 042 | 9 SwePub | |
| 072 | 7 | a ref2 swepub-contenttype |
| 072 | 7 | a kon2 swepub-publicationtype |
| 100 | 1 | a Cebecauer, Mateju KTH,Transportplanering,KTH Royal Inst Technol, Sweden4 aut0 (Swepub:kth)u1nb1u4p |
| 245 | 1 0 | a Spatio-Temporal Public Transport Mode Share Estimation and Analysis Using Mobile Network and Smart Card Data |
| 264 | 1 | b Institute of Electrical and Electronics Engineers (IEEE),c 2023 |
| 338 | a print2 rdacarrier | |
| 500 | a QC 20240301Part of ISBN 979-8-3503-9946-2 | |
| 500 | a Funding Agencies|Swedish Transport Administration through the Multimodal traffic management project [TRV 2020/118663] | |
| 520 | a Public transport plays a vital role in society and the urban environment. However, knowledge of its spatial and temporal shares is often limited to traditional travel surveys. Recently, there has been substantial progress in mobility data collection, including data from traffic, public transport, and mobile phones. Especially mobile network data is a large-scale and affordable source of high-level mobility records. Similarly, public transport smart cards or ticket validation data are being collected and made available in major cities. The contribution of this study is to unveil the potential of estimating public transport shares, by merging mobile and smart card data. Stockholm, Sweden, is used as a case study. We analyze and discuss spatio-temporal patterns of estimated public transport shares for Stockholm, using descriptive and cluster analysis. The typical representative day-types are revealed and analyzed. Finally, a regression analysis considering the weather and socioeconomic context is conducted. It provides a highly explanatory and predictive understanding of which factors impact the share of public transport in Stockholm. To conclude, combined mobile and smart card data offers a cost-efficient, large-scale, low spatio-temporal aggregation (capturing daily and hourly variations) alternative to traditional travel surveys for analyzing PT shares. | |
| 650 | 7 | a TEKNIK OCH TEKNOLOGIERx Samhällsbyggnadsteknikx Transportteknik och logistik0 (SwePub)201052 hsv//swe |
| 650 | 7 | a ENGINEERING AND TECHNOLOGYx Civil Engineeringx Transport Systems and Logistics0 (SwePub)201052 hsv//eng |
| 700 | 1 | a Gundlegård, Davidu Linköpings universitet,Kommunikations- och transportsystem,Tekniska fakulteten4 aut0 (Swepub:liu)davgu33 |
| 700 | 1 | a Jenelius, Erik,c Docent,d 1980-u KTH,Transportplanering,KTH Royal Inst Technol, Sweden4 aut0 (Swepub:kth)u1x5t81f |
| 700 | 1 | a Burghout, Wilcou KTH,Transportplanering,KTH Royal Inst Technol, Sweden4 aut0 (Swepub:kth)u1x8efdz |
| 710 | 2 | a KTHb Transportplanering4 org |
| 773 | 0 | t 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)d : Institute of Electrical and Electronics Engineers (IEEE)g , s. 2543-2548q <2543-2548z 9798350399462z 9798350399479 |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-344060 |
| 856 | 4 8 | u https://doi.org/10.1109/ITSC57777.2023.10422199 |
| 856 | 4 8 | u https://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-205197 |
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