TRANS-FORM

The TRANS-FORM project develops, implements and tests real-time traffic management strategies to support proactive and adaptive operations. The tool will integrate new concepts and methods of behavioural modelling, passenger flow forecasting and network state predictions into real-time operations. New empirical knowledge and modelling foundations are developed by undertaking a multi-level approach for monitoring, mapping, analysing and managing dynamics of interchanging travel flows. Analysis of pedestrian and traveler flows at the hub, urban and regional networks is facilitated by data secured from case studies in Switzerland, the Netherlands and Sweden, respectively. The outcomes will help improve coordination between travel modes, in particular in cases of disturbances and disruptions.

TRANS-FORM is funded by NWO as part of its Joint Programming Initiative ‘Urban Europe’. It runs from 2016 to 2019. The consortium consists of universities in the Netherlands (TU Delft), Sweden (LiU and BTH) and Switzerland (EPFL), as well as IBM Research and ETRA.


For more information please visit: http://www.trans-form-project.org

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Publications

2019

Yap M. and Cats O. (2019).  “Predicting and Clustering Station Vulnerability in Urban Networks”. TransitData2019, Paris. July 2019.

Yap M., Luo D., Cats O., van Oort N. and Hoogendoorn S. (2019). Where Shall We Sync? Clustering Passenger Flows to Identify Urban Public Transport Hubs and Their Key Synchronization Priorities. Transportation Research Part C, 98, 433-448.

Yap, M.D., Cats, O. (2019). Analysis and Prediction of Disruptions in Metro Networks. 6th International Conference on Models and Technologies for Intelligent Transportation Systems (MT-ITS), Krakow, Poland.

2018

Bellver Munoz P., Cats O., Törnquist Krasemann J., Rydergren C., Scarinci R., Laumanns M. (2018). Unravelling Travel Flow Dynamics: A Multi-Level Analysis of Public Transport Demand and Passenger Reliability. Transport Research Arena, Vienna.

Gavriilidou A. and Cats O. (2018). Reconciling Transfer Synchronization and Service Regularity: Real-time Control Strategies using Passenger Data. Transportmetrica A, Accepted.

Roelofsen D., Cats O., van Oort N. and Hoogendoorn S. (2018). Assessing Disruption Management Strategies in Rail-bound Urban Public Transport from a Passenger Perspective. Proceedings of the Conference on Advanced Systems in Public Transport (CASPT), Brisbane, Australia.

Roelofsen D., Cats O., van Oort N. and Hoogendoorn S. (2018). Assessing Disruption Management Strategies in Rail-Bound Urban Public Transport from a Passenger Perspective”. Conference on Advanced Systems in Public Transport and TransitData (CASPT), Brisbane, Australia. July 2018.

Yap M., Cats O. and van Arem B. (2018). Crowding Valuation in Urban Tram and Bus Transportation based on Smart Card Data. Transportmetrica A. In press.

Yap M., Cats O., van Oort N. and Hoogendoorn S. “Controlling the propagation of passenger disruption impacts in multi-level public transport networks”. OR 2018: International Conference on Operations Research, Brussels, Belgium. September 2018.

Yap M., Cats O., van Oort N. and Hoogendoorn S. “Controlling the Propagation of Passenger Disruption Impacts in Multi-level Public Transport Networks”. 7th European Symposium on Quantitative Methods in Transportation Systems (hEART), Athens, Greece, September 2018.

Yap M., Luo D. and Cats O. (2018). Using Passenger Flows to Determine Key Interchange Connections. Conference on Advanced Systems in Public Transport (CASPT), Brisbane, Australia. Proceedings of the Conference on Advanced Systems in Public Transport and TransitData (CASPT), Brisbane, Australia.

Yap M., Luo D. and Cats O. “Where Shall We Sync? Using Passenger Flows to Determine Key Interchange Connections”. Conference on Advanced Systems in Public Transport and TransitData (CASPT), Brisbane, Australia. July 2018.

Yap, M.D., Nijenstein, S. & Van Oort, N. (2018). Improving predictions of public transport usage during disturbances based on smart card data. Transport Policy, 61, pp. 84-95.

Yap, M.D., Van Oort, N., Van Nes, N., Van Arem, B. (2018). Identification and quantification of link vulnerability in multi-level public transport networks: a passenger perspective. Transportation. https://doi.org/10.1007/s11116-018-9892-5

2017

Van Oort, N., A. de Koning, S. van der Drift, M.D. Yap. (2017). Insights into door-to-door dynamics of public transport riders by app, survey and AVL data; case of Amsterdam metropolitan area. TransitData, 3rd Internatonal workshop and symposium, Santiago de Chile.

Yap M., Cats O., van Oort N. and Hoogendoorn S. (2017). Data-driven Transfer Inference for Public Transport Journeys during Disruptions. EWGT2017 (20th Euro Working Group on Transportation), Budapest, Hungary.

Yap M., Cats O., Yu S. and van Arem B. (2017). Crowding Valuation in Urban Tram and Bus Transportation based on Smart Card Data. The 5th International Conference Series on Competition and Ownership in Land Passenger Transport (Thredbo17), Sweden.

Yap, M.D., Cats, O., Van Oort, N. & Hoogendoorn, S.P. (2017). Robust transfer inference: a transfer inference algorithm for public transport journeys during disruptions. Transportation Research Procedia, 27, pp. 1042-1049.

Yap, M.D., Cats, O., Yu, S. & Van Arem, B. (2017). Crowding valuation in urban tram and bus transportation based on smart card data. Thredbo 15: Competition and Ownership in Land Passenger Transport, Vol.15, Stockholm: Sweden.

Yap, M.D., O. Cats, N. van Oort, S.P. Hoogendoorn. (2017). A data-driven approach to infer spatial characteristics and service reliability of public transport hubs. TransitData, 3rd Internatonal workshop and symposium, Santiago de Chile

Yap, M.D., S. Nijensteijn, N. van Oort (2017). Improving predictions of the impact of disturbances on public transport usage based on smart card data. Proceedings of the Transportation Research Board 96th annual meeting. Washington DC.

2016

Cats, O., M. Yap, N. van Oort (2016) Exposing the role of exposure: Public transport network risk analysis, Transportation Research Part A: Policy and Practice, Volume 88, pp. 1-14,

Scheltes, A.F., M.D. Yap, N. van Oort (2016). Het verbeteren van de last-mile in een OV reis met automatische voertuigen; Een Delftse case studie en stated preference onderzoek gecombineerd. In s.n. (Ed.), Colloquium vervoersplanologisch speurwerk, Zwolle.

Van Oort, N., T. Brands, E. de Romph, M. Yap (2016), Ridership Evaluation and Prediction in Public Transport by Processing Smart Card Data: A Dutch Approach and Example, Chapter 11, Public Transport Planning with Smart Card Data, eds. Kurauchi F., Schmöcker, J.D., CRC Press.

Smart Public Transport Lab

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Contact:
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 E-mail: smartptlab@tudelft.nl

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