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The following results are related to COVID-19. Are you interested to view more results? Visit OpenAIRE - Explore.
3 Research products, page 1 of 1

  • COVID-19
  • Research data
  • Research software
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  • Transport Research

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  • Open Access
    Authors: 
    van de Wiel, Thijs; Shelat, Sanmay; Molin, Eric; van Lint, Hans; Cats, Oded;
    Publisher: 4TU.ResearchData
    Country: Netherlands

    Stated preference data for analysing the impact of COVID-19 risk perceptions on route choice behaviour in train networks

  • Open Access Dutch; Flemish
    Authors: 
    Shelat, Sanmay; Cats, Oded; van Cranenburgh, Sander;
    Publisher: 4TU.ResearchData
    Country: Netherlands
    Project: EC | My-TRAC (777640)

    Data for the paper "Traveller behaviour in public transport in the early stages of COVID-19 pandemic in the Netherlands". Includes, respondents' rankings between two train options and an opt-out option for different choice situations with varying COVID-19 contexts and travel time attributes. Personal characteristics related to mobility, socio-economic status, and COVID-19 perception are also included. A data dictionary is included in the data file. Further information can be found in the linked paper.

  • Open Source
    Authors: 
    Gkiotsalitis, Konstantinos;
    Country: Netherlands

    Description:This repository contains the software code related to deriving dynamic service patterns in order to comply with the pandemic-imposed vehicle capacity limits in public transport operations.Currently, this repository contains:The model_case_study.py script which is the source code of the devised dynamic service pattern model introduced in the paper "A model for modifying the public transport service patterns to account for the imposed COVID-19 capacity", which is currently under scientific review. This script contains all necessary functions to calculate the solution of the mathematical program for the scenario described in the case study of the scientific paper.The model_demonstration.py script that contains the implementation of the demonstration scenario in the aforementioned scientific paper.Referencing:In case you use this code for scientific purposes, you can cite the paper "A model for modifying the public transport service patterns to account for the imposed COVID-19 capacity" once it is publicly available.License:MIT LicenseDependencies:Note that the script model_case_study.py is written in Python. Running or modifying this script requires an installed version of Python 3.6. In addition, the mathematical model is solved with the use of Gurobi 9.0.3. You would need a Gurobi license to obtain an optimal solution.Research Project:This software code is developed in the research programme 'COVID 19 Wetenschap voor de Praktijk', project number:10430042010018. The project is funded by the Dutch Research Organization for Health Research and Development (ZonMw)