Abstract:COVID-19 has generated significant mobility impacts in Santiago de Chile: mandatory and nonmandatory trips have declined by an average of 38% over the last year. Despite such a drop, a high share of low-income groups still relies on public transport for their daily activities. Thus, the decline is far from being homogeneous across socioeconomic groups. And due to the strong urban segregation observed in the city some flows have diminished significantly more than others. Thus, some services at certain periods present a quite high demand. In this scenario managing travel demand and public transport supply becomes key to keeping the number of people circulating in the system safe.

Our work develops a simulation tool of the operations of a public transport system to evaluate the impacts of different intervention scenarios in a pandemic context. Using a baseline scenario that severely violates safety and social distance recommendations, we study the impact of several travel demand and public transport supply measures, focusing the analysis on waiting times and crowding conditions inside vehicles and platforms. As a result, we generate easy-to-analyze visual outputs that can assist prioritizing actions at the metropolitan and district level.

Keywords: Public transport, Passive data, Discrete-event simulation, COVID-19

Note:Available online at: https://sochitran.cl/wp-content/uploads/2021/10/2021-99b-A-discrete-event-public-transportation-simulation-model-to-evaluate-the-impacts-of-social-distancing-and...-Soza-Parra-Tiznado-Aitken-Munoz.pdf