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

Abstract

AbstractThe 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%.KeywordsCovid-19Fuzzy logicPublic transportation