Abstract
The COVID-19 pandemic has a direct impact on public transport operations. In this paper, impacts on transit operations of the physical distancing measures deployed to slow the spread of the virus are analyzed and recommendations are provided. At first, two social distancing optimization solutions are provided in order to keep riders at a safe distance. The first is a discrete optimization that can be used in buses with fixed seats, while the second is a continuous optimization that can be used to distribute riders on a grid and be applied on a bus or subway platform. Assuming that the ridership will eventually go back to its level before the pandemic, the second objective of this research is to address the transit operation parameters that need to be changed in order to serve the pre-COVID ridership level, while respecting the social distancing measures. An O-D distribution has been developed in this paper for New York City (NYC) subway line 1, based on the 2018 NYC Travel Survey conducted by the Metropolitan Transportation Authority. Five scenarios of physical distancing are simulated and analyzed in this paper: 3ft, 4ft, 5ft, 5.4ft, and 6ft of separation between passengers. The results show the number of additional trains required to accommodate the hypothetical pre-COVID ridership demand while maintaining social distancing. An interesting key finding is that, by decreasing the minimum distance from 6ft to 5.4ft, the number of additional trains required to serve the transit demand drastically decreases and hence more resources are saved.