Analyzing Safe Epidemic Distancing in Public Transport Buses: A Simulation Study on Passenger Flow

Abstract

During the COVID-19 pandemic, public transport played a crucial role in maintaining essential services while ensuring the safety of both passengers and staff. As the world gradually resumes operations, the impact of the pandemic is expected to persist for some time. Existing studies focus on virus transmission in vehicles, with limited knowledge about post-pandemic passenger flow, safety, and satisfaction. This paper presents a model of passenger movement in public transport, considering factors like boarding times, movement within stops, and the impact of crowding and delays. To reduce transmission at bus stops, we developed a simulation-based passenger flow model using PTV Vissim. The program was used to simulate passenger exchange scenarios, using data collected from real data. The goal was to create a model that minimizes the risk of infection. By understanding passenger flow and interactions with the public transport system, effective measures can be implemented to mitigate the spread of COVID-19 and other infectious diseases.