Publikationer av Matej Cebecauer
Refereegranskade
Artiklar
[1]
A. Skoufas et al., "Assessing contributions of passenger groups to public transportation crowding," Journal of Public Transportation, vol. 26, 2024.
[2]
M. Cebecauer et al., "Revealing representative day-types in transport networks using traffic data clustering," Journal of Intelligent Transportation Systems / Taylor & Francis, vol. 8, no. 5, s. 695-718, 2024.
[3]
L. Kolkowski et al., "Measuring activity-based social segregation using public transport smart card data," Journal of Transport Geography, vol. 110, 2023.
[4]
J. Y. Lin et al., "The equity of public transport crowding exposure," Journal of Transport Geography, vol. 110, 2023.
[5]
M. Cebecauer et al., "Integrating Demand Responsive Services into Public Transport Disruption Management," IEEE Open Journal of Intelligent Transportation Systems, vol. 2, s. 24-36, 2021.
[6]
Y. Kholodov et al., "Public transport fare elasticities from smartcard data: Evidence from a natural experiment," Transport Policy, vol. 105, s. 35-43, 2021.
[7]
E. Almlöf et al., "Who continued travelling by public transport during COVID-19? : Socioeconomic factors explaining travel behaviour in Stockholm 2020 based on smart card data," European Transport Research Review, vol. 13, no. 1, 2021.
[8]
E. Jenelius och M. Cebecauer, "Impacts of COVID-19 on public transport ridership in Sweden: Analysis of ticket validations, sales and passenger counts," Transportation Research Interdisciplinary Perspectives, vol. 8, 2020.
[9]
J. H. M. Langbroek et al., "Electric vehicle rental and electric vehicle adoption," Research in Transportation Economics, vol. 73, s. 72-82, 2019.
[10]
A. Tympakianaki et al., "Impact analysis of transport network disruptions using multimodal data : A case study for tunnel closures in Stockholm," Case Studies on Transport Policy, vol. 6, no. 2, s. 179-189, 2018.
[11]
M. Cebecauer, E. Jenelius och W. Burghout, "Integrated framework for real-time urban network travel time prediction on sparse probe data," IET Intelligent Transport Systems, vol. 12, no. 1, s. 66-74, 2018.
[12]
M. Cebecauer och Ľ. Buzna, "Large-scale test data set for location problems," Data in Brief, vol. 17, s. 267-274, 2018.
[13]
M. Cebecauer och Ľ. Buzna, "A versatile adaptive aggregation framework for spatially large discrete location-allocation problems," Computers & industrial engineering, vol. 111, s. 364-380, 2017.
[14]
K. Rosina, P. Hurbánek och M. Cebecauer, "Using OpenStreetMap to improve population grids in Europe," Cartography and Geographic Information Science, s. 1-13, 2016.
Konferensbidrag
[15]
A. Skoufas et al., "Assessing school students' contributions to public transport crowding," i Transit Data 2024: 9th International Workshop and Symposium on the Use of Passive Data from Public Transport Systems, London, UK, 1-4 July 2024, 2024.
[16]
J. Y. Lin et al., "Equity of public transport crowding exposure: Stockholm before, during and after the pandemic," i Transit Data 2024: 9th International Workshop and Symposium on the Use of Passive Data from Public Transport Systems, London, UK, 1-4 July 2024, 2024.
[17]
A. Skoufas et al., "Ex-post assessment of public transport on-board crowding induced by new urban development," i Transportation Research Board (TRB) 103rd Annual Meeting, Washington DC, USA, 7-11 January 2024, 2024.
[18]
M. A. Khan et al., "Feasibility study for deployment of mobile autonomous charging pods (MAPs) for charging operations," i MFTS 2024: The 5th Symposium on Management of Future Motorway and Urban Traffic Systems, 4-6 September, 2024, Heraklion, Crete, Greece, 2024.
[19]
A. Skoufas et al., "Understanding the impact of crowding in public transport route choice using longitudinal data: A case study for Stockholm Region," i Transit Data 2024: 9th International Workshop and Symposium on the Use of Passive Data from Public Transport Systems, London, UK, 1-4 July 2024, 2024.
[20]
H. N. Ngo et al., "Considering Multi-Scale Data for Continuous Traffic Prediction Using Adaptive Multi-Agent System," i Proceedings 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023, s. 1835-1842.
[21]
A. Skoufas et al., "Generating and Evaluating Route Choice Sets for Large Multimodal Public Transport Networks : A Case Study for Stockholm Region," i 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023, s. 2926-2931.
[22]
M. Cebecauer et al., "Spatio-Temporal Public Transport Mode Share Estimation and Analysis Using Mobile Network and Smart Card Data," i 2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC), 2023, s. 2543-2548.
[23]
E. Jenelius et al., "Public transport fare elasticities from smartcard data : A natural experiment in Stockholm," i 9th Symposium of the European Association for Research in Transportation (hEART), Lyon, France, 3-4 February 2021, 2021.
[24]
Y. Kholodov et al., "Transport fare elasticities from smartcard data : A natural experiment in Stockholm," i Transportation Research Board (TRB) 100th Annual Meeting, 2021.
[25]
E. Almlöf et al., "Who is still travelling by public transport during COVID-19? : Socioeconomic factors explaining travel behaviour in Stockholm based on smart card data," i Transportation Research Board (TRB) 100th Annual Meeting, 2021.
[26]
M. Cebecauer et al., "Public transport disruption management by collaboration with demand responsive services," i Transportation Research Board (TRB) 99th Annual Meeting, January 12–16, 2020, Washington, DC, USA, 2020.
[27]
M. Cebecauer et al., "3D Speed Maps and Mean Observations Vectors for Short-Term Urban Traffic Prediction," i TRB Annual Meeting Online, 2019, s. 1-20.
[28]
O. Cats et al., "Generating network-wide travel diaries using smartcard data," i Transit Data 2019: 5th International Workshop and Symposium, Paris, France, 8-10 July 2019, 2019.
[29]
M. Koháni et al., "Location-scheduling optimization problem to design private charging infrastructure for electric vehicles," i 6th International Conference on Operations Research and Enterprise Systems, ICORES 2017, 2018, s. 151-169.
[30]
M. Cebecauer, E. Jenelius och W. Burghout, "Spatio-Temporal Partitioning of Large Urban Networks for Travel Time Prediction," i 2018 21ST INTERNATIONAL CONFERENCE ON INTELLIGENT TRANSPORTATION SYSTEMS (ITSC), 2018, s. 1390-1395.
[31]
M. Koháni et al., "Designing charging infrastructure for a fleet of electric vehicles operating in large urban areas," i ICORES 2017 - Proceedings of the 6th International Conference on Operations Research and Enterprise Systems, 2017, s. 360-368.
Icke refereegranskade
Konferensbidrag
[32]
M. A. Khan et al., "Feasibility study for deployment of mobile autonomous charging pods (MAPs) for charging operations," i 13th Annual Swedish Transport Research Conference (STRC 2024), Gothenburg, Sweden, 16-17 October 2024, 2024.
[33]
M. A. Khan et al., "A comprehensive review of viability and operability of dynamic charging solutions for autonomous electric vehicles," i 12th Annual Swedish Transport Research Conference, Stockholm, Sweden, 16-17 October 2023, 2023.
[34]
A. Skoufas et al., "Generating and evaluating route choice sets for large multimodal public transport networks: A case study for Stockholm Region," i 12th Annual Swedish Transport Research Conference, Stockholm, Sweden, 16-17 October 2023, 2023.
[35]
M. Cebecauer et al., "High-resolution public transport mode share estimation from mobile network and smart card data," i 12th Annual Swedish Transport Research Conference, Stockholm, Sweden, 16-17 October 2023, 2023.
[36]
Z. Dong, M. Cebecauer och E. Jenelius, "Pattern recognition in dynamic origin-destination matrices using dimensionality reduction and short-term prediction," i 11th Swedish Transport Research Conference, 18-19 October 2022, Lund, Sweden, 2022.
[37]
J. Lin et al., "The equity of public transport crowding exposure," i 11th Swedish National Transport Conference, 18-19 October 2022, Sweden, 2022.
[38]
M. Cebecauer et al., "Using flows or speeds in traffic pattern clustering and prediction : does the data type matter?," i Transportforum, Linköping, 16–17 juni 2022, 2022.
[39]
M. Cebecauer et al., "Generating Network-Wide Travel Diaries and OD Matrices Using Stockholm County Smartcard Data," i Transportforum, Linköping, 8-9 januari 2020, 2020.
[40]
I. Rubensson et al., "Resmönster och fördelningseffekter av taxeförändringanalyserat med hjälp av biljettvalideringsdata," i Transportforum, 8-9 januari 2020, Linköping, 2020.
[41]
M. Cebecauer et al., "Real-time city-level traffic prediction in the context of Stockholm City," i Transportforum, Linköping, Sweden, 10-11 January 2019, 2019.
[42]
D. Gundlegård et al., "Travel time estimation and prediction for traffic management in Stockholm," i Transportforum, Linköping, Sweden, 10-11 January 2018, 2018.
Avhandlingar
[43]
M. Cebecauer, "Enhancing Short-Term Traffic Prediction for Large-Scale Transport Networks by Spatio-Temporal Clustering," Doktorsavhandling Stockholm, Sweden : KTH Royal Institute of Technology, TRITA-ABE-DLT, 2143, 2021.
[44]
M. Cebecauer, "Short-Term Traffic Prediction in Large-Scale Urban Networks," Licentiatavhandling Stockholm : KTH Royal Institute of Technology, TRITA-ABE-DLT, 1915, 2019.
Rapporter
[45]
[46]
O. Cats et al., "Unravelling Mobility Patterns using Longitudinal Smart Card Data : Final report for Trafik och Region 2019SLL-KTH research project," KTH Royal Institute of Technology, 2021.
[47]
E. Jenelius et al., "Bilrestider i storstad: Variationsmönster och upplevd osäkerhet (VARIA) : Slutrapport för projekt som genomförts på uppdrag av Trafikverket," KTH Royal Institute of Technology, 2020.
[48]
O. Cats et al., "How fair is the fare? Estimating travel patterns and the impacts of fare schemes for different user groups in Stockholm based on smartcard data : Final report for Trafik och Region 2018 SLL-KTH research project," KTH Royal Institute of Technology, 2019.
[49]
E. Jenelius och M. Cebecauer, "SHARP: Pre-study of Data Sharing for Demand-Responsive and Public Transport System-of-Systems : Public report," Fordonsstrategisk forskning och innovation, 2019.
Övriga
[50]
[51]
M. Cebecauer et al., "Revealing representative day-types in transport networks using traffic data clustering," (Manuskript).
Senaste synkning med DiVA:
2024-11-22 00:26:01