Bus safety during COVID-19: analyzing bus-involved crashes and economic harm

Abstract

The COVID-19 pandemic has certainly been disrupting human mobility. The impact of COVID-19 on the diverse urban transport modes varies. It has greatly influenced bus ridership and service provision. At the same time, major concerns have been raised regarding road safety during COVID-19 in the US, as the crash fatality rate has shown a surge despite the substantial reduction in the traffic flow. Therefore, it is important to know how buses are involved in these situations. Typically, drivers’ behaviors such as violations (speeding, hit-and-run, and alcohol), vehicle, and roadway characteristics contribute to bus-involved crashes and fatalities. This study aims to investigate the role of these factors in bus-involved crashes and associated monetary harm during COVID-19. A unique and comprehensive county-level time-series dataset (2019–2020) is harnessed by linking Tennessee’s Integrated Traffic Analysis Network (TITAN) crash database with the COVID-19 travel behavior database. The adopted feasible generalised least square (FGLS) models using the first differences of pre-COVID-19 and during-COVID-19 periods analyze the factors associated with bus-involved crashes and crash harm. Results suggest that bus-involved crashes and economic harm are associated with more violations (alcohol, speeding, and hit-and-run) and more trips per person (not staying home during COVID-19) in 2020. Besides bad weather, slope and curve roads, interstate-related crashes are more frequent in 2020 compared to 2019. These results may inform policymakers to strengthen traffic law enforcement through appropriate countermeasures, such as the placement of warning signs and the reduction of the speed limit in hotspots.

Keywords:

• Bus-involved crash
• fatality
• crash harm
• COVID-19 pandemic

Acknowledgments

The author thanks the Department of Civil and Environmental Engineering, UTK for providing the TITAN crash database. The author also would like to acknowledge the University of Maryland’s advanced transportation laboratory for making their human mobility dataset available publicly.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The authors do not have permission to share data.

Additional information

Funding

This research does not have any associated funding.