On the Effect of COVID-19 on Drivers' Behavior: A Survey Study

Multigroup invariance of measure for angry drivers (MAD) scale using a representative sample of drivers in Australia

INTRODUCTION

Driver anger and aggression have been linked to crash involvement and injury outcomes. Improved road safety outcomes may be achieved through understanding the causes of driver anger, and interventions designed to reduce this anger or prevent it from becoming aggression. Scales to measure anger propensities will be an important tool in this work. The measure for angry drivers (MAD; Stephens et al., 2019) is a contemporary scale designed to measure tendencies for anger across three types of driving scenarios: perceived danger from others, travel delays, and hostility or aggression from other drivers.

METHOD

This study aimed to validate MAD using a representative sample of Australian drivers, stratified across age, gender, and location. Participants completed a 10-minute online survey that included MAD, sought demographic information (age, gender, driving purpose, crash history), as well as the frequency of aggressive driving. Multigroup confirmatory factor analyses (MGCFA) assessed how stable the structure of the MAD was across drivers of different ages, gender, purposes for driving and those who do or do not display anger aggressively. MAD was invariant across all groups, showing that all drivers interpreted and responded to MAD in the same way.

RESULTS

A comparison of latent means showed anger tendencies were higher for men compared to women, for younger drivers compared to older drivers, and for those who drive mainly for work compared to those who mainly drive for other reasons. When controlling for driver factors, driving anger was associated with increased odds of being aggressive while driving.

PRACTICAL APPLICATIONS

Overall, this study demonstrated that MAD is an appropriate scale to measure anger tendencies and can be used to support interventions, and evaluation of interventions, to reduce anger and aggressive driving.

Driving under the influence of cannabis, alcohol, and illicit drugs among adults in the United States from 2016 to 2020

OBJECTIVE

Driving under the influence (DUI) of substances increases motor vehicle crash risk. Understanding current national trends of driving under the influence of alcohol (DUIA), cannabis (DUIC), and drugs other than cannabis (DUID) can inform public health efforts. Herein, we provide updated trends among United States (US) adults regarding DUIA, DUIC, DUID, and DUI of any substance.

METHOD

We used nationally-representative National Survey on Drug Use and Health (2016-2020) data to derive prevalence estimates of past-year DUIC, DUIA, DUID, and DUI of any substance among non-institutionalized US adults and among those reporting respective past-year  substance use. Prevalence estimates and adjusted logistic regressions characterized temporal trends of these behaviors among US adults, among those with respective past-year substance use, and among stratified demographic subpopulations.

RESULTS

Over 1 in 10 US adults reported DUI of any substance annually from 2016 to 2020.DUIA was most prevalent among all US adults (8.7% in 2017); however, this behavior is decreasing (AOR:0.96; 95%CI:0.94,0.98). No change in DUIC among the US adult population was found, but a decrease was found among those with past-year cannabis use (AOR:0.95; 95%CI:0.93,0.98), which coincided with a 29.1% increase in past-year cannabis use. There were no significant changes in overall DUID; however, females, those ages 26-34 and 65 or older with past-year use displayed increasing trends. DUI of any substance decreased among the US adult population.

CONCLUSIONS

DUI remains a salient public health concern in the US and results indicate population subgroups who may benefit from impaired driving prevention interventions.

Investigating the Effect of COVID-19 on Driver Behavior and Road Safety: A Naturalistic Driving Study in Malaysia

The spread of the novel coronavirus COVID-19 resulted in unprecedented worldwide countermeasures such as lockdowns and suspensions of all retail, recreational, and religious activities for the majority of 2020. Nonetheless, no adequate scientific data have been provided thus far about the impact of COVID-19 on driving behavior and road safety, especially in Malaysia. This study examined the effect of COVID-19 on driving behavior using naturalistic driving data. This was accomplished by comparing the driving behaviors of the same drivers in three periods: before COVID-19 lockdown, during COVID-19 lockdown, and after COVID-19 lockdown. Thirty people were previously recruited in 2019 to drive an instrumental vehicle on a 25 km route while recording their driving data such as speed, acceleration, deceleration, distance to vehicle ahead, and steering. The data acquisition system incorporated various sensors such as an OBDII reader, a lidar, two ultrasonic sensors, an IMU, and a GPS. The same individuals were contacted again in 2020 to drive the same vehicle on the same route in order to capture their driving behavior during the COVID-19 lockdown. Participants were approached once again in 2022 to repeat the procedure in order to capture their driving behavior after the COVID-19 lockdown. Such valuable and trustworthy data enable the assessment of changes in driving behavior throughout the three time periods. Results showed that drivers committed more violations during the COVID-19 lockdown, with young drivers in particular being most affected by the traffic restrictions, driving significantly faster and performing more aggressive steering behaviors during the COVID-19 lockdown than any other time. Furthermore, the locations where the most speeding offenses were committed are highlighted in order to provide lawmakers with guidance on how to improve traffic safety in those areas, in addition to various recommendations on how to manage traffic during future lockdowns.