Long COVID in the context of driving styles: An empirical study employing connected vehicle trajectory data
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Abstract
This manuscript examines the "long-COVID" phenomenon, defined for this study as lasting changes in driving behavior stemming from pandemic-induced travel restrictions, particularly statewide stay-at-home orders that limited trips to curb virus transmission.
Two tailored studies analyzed paneled connected vehicle (CV) data over four years to understand driving style changes and identify susceptible individuals.
Study one employed mixed-effects logistic regression to find that drivers active on freeways are more likely to change their driving style than those on arterials. Additionally, drivers aged 56 and over are more likely to experience changes to driving styles as compared to other age groups.
Study two utilized random intercept hierarchical modeling and reveals significant increases in volatility measures, derived from speed, acceleration, jerk, and yaw rate, associated with more aggressive driving on both arterial and freeway segments in the post-lockdown period. The analysis suggests that driving styles have not fully returned to pre-pandemic levels.
The rise in risky and aggressive driving behaviors during and post COVID-19 can be mainly attributed to the observed drastic changes in traffic conditions, such as shifts in trip patterns and volumes over a short period, requiring drivers to rapidly adjust their driving style to the evolving dynamics.
Web | DOI | PDF | Journal of Traffic and Transportation Engineering (English Edition) | Open Access
Kummetha, Vishal C.; Mohammadnazar, Amin; Concas, Sisinnio; Kourtellis, Achilleas
[Line breaks added]
Abstract
This manuscript examines the "long-COVID" phenomenon, defined for this study as lasting changes in driving behavior stemming from pandemic-induced travel restrictions, particularly statewide stay-at-home orders that limited trips to curb virus transmission.
Two tailored studies analyzed paneled connected vehicle (CV) data over four years to understand driving style changes and identify susceptible individuals.
Study one employed mixed-effects logistic regression to find that drivers active on freeways are more likely to change their driving style than those on arterials. Additionally, drivers aged 56 and over are more likely to experience changes to driving styles as compared to other age groups.
Study two utilized random intercept hierarchical modeling and reveals significant increases in volatility measures, derived from speed, acceleration, jerk, and yaw rate, associated with more aggressive driving on both arterial and freeway segments in the post-lockdown period. The analysis suggests that driving styles have not fully returned to pre-pandemic levels.
The rise in risky and aggressive driving behaviors during and post COVID-19 can be mainly attributed to the observed drastic changes in traffic conditions, such as shifts in trip patterns and volumes over a short period, requiring drivers to rapidly adjust their driving style to the evolving dynamics.
Web | DOI | PDF | Journal of Traffic and Transportation Engineering (English Edition) | Open Access