The effectiveness of passenger attraction policies designed to induce a modal shift from private mode of transport to public mode of transport is tested frequently as a solution to the constantly dropping ridership rates in public transportation (PT). However, with COVID-19 pandemic in the picture, will the policies that were previously tested effective stand the test of time? Using the work-trip data collected from employees working in Thiruvananthapuram City, this study compares the effectiveness of six passenger attraction policies, aimed at decreasing the travel time and travel cost parameters, in a pre-COVID-19 and a post-lockdown scenario. Fuzzy logic-based mode choice models are developed to perform policy sensitivity analysis. The policies such as improving PT coverage and supply, introducing parking prohibition on major streets, operating non-stop bus services, reducing return-trip fares, early bird pre-peak hour discounts, and providing monthly PT season tickets are tested. The results show that, compared to the pre-COVID-19 model, the effectiveness of two out of the six policies reduces for the post-lockdown model, and the two policies being related to the travel cost parameter. The six policies are found to induce a private to public modal shift ranging from 5.8 to 7.9% for the pre-COVID-19 scenario, while the post-lockdown model gives a shift ranging from 5.8 to 7.1%.


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    Titel :

    Effectiveness of Passenger Attraction Policies: A Pre-COVID-19 and Post-lockdown Comparison


    Weitere Titelangaben:

    Lecture Notes in Civil Engineering


    Beteiligte:
    Anjaneyulu, M. V. L. R. (Herausgeber:in) / Harikrishna, M. (Herausgeber:in) / Arkatkar, Shriniwas S. (Herausgeber:in) / Veeraragavan, A. (Herausgeber:in) / Kamar, Sandra (Autor:in) / Shaheem, S. (Autor:in) / Vinayaka, B. (Autor:in) / Mathew, Samson (Autor:in)


    Erscheinungsdatum :

    2022-11-11


    Format / Umfang :

    13 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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