Road Conditions & Driving Patterns during the COVID-19 Pandemic as Predictors of Distracted Driving Behaviors
Standing
Graduate (Masters)
Type of Proposal
Oral Research Presentation
Faculty Sponsor
Dr. Francesco Biondi
Proposal
Erika Lopetrone (lopetroe@uwindsor.ca), University of Windsor, MHK
Road Conditions & Driving Patterns during the COVID-19 Pandemic as Predictors of Distracted Driving Behaviors:
Background: Understanding driving patterns and behaviors is important in transportation and road safety research. However, little evidence is available on how drivers are behaving on the roads during a global pandemic when remote working is prevalent and stay-at-home restrictions are in place. With less traffic on the roadways, recent studies have reported an uptick in high-risk taking behaviors such as speeding, stunt driving, and cellphone use (ZenDrive, 2020). The aim of the proposed study is to investigate how driving behaviors may have changed following the stay-at-home restrictions beginning in March, 2020.
Methods: To achieve our objectives, several questions of distracted driving behaviors (speeding, stunt driving, use of conferencing apps ect.) were asked during an online retrospective survey administered through Qualtrics, an online platform. Further analysis will be conducted to understand the associations between gender and age and each distracted driving behavior. A logistic regression will be run for each distracted behavior separately to see the relationship them and between fewer vehicles on the road after controlling for demographic variables. In using a logistic regression, I can predict if age, gender, or encountering fewer vehicles on the roads are associated with the risk of increased distracted driving behaviors.
Results: A total of 103 respondents with complete data sets will be included for final statistical analysis. This sample consisted of 52 Males and 51 females. Of these participants, 82.5% agreed to encountering fewer vehicles on the road and 76.7% reported a diminished total number of driving hours per week since March, 2020.
Conclusions: This research will help fill the gaps in the literature with regard to driver behavior characteristics during a global pandemic, and help to predict driving patterns for our ‘new-normal’ post-pandemic.
Availability
March 29th 12-2pm, March 30th 12-1pm, March 31st, 2-3pm, April 1st Not available
Road Conditions & Driving Patterns during the COVID-19 Pandemic as Predictors of Distracted Driving Behaviors
Erika Lopetrone (lopetroe@uwindsor.ca), University of Windsor, MHK
Road Conditions & Driving Patterns during the COVID-19 Pandemic as Predictors of Distracted Driving Behaviors:
Background: Understanding driving patterns and behaviors is important in transportation and road safety research. However, little evidence is available on how drivers are behaving on the roads during a global pandemic when remote working is prevalent and stay-at-home restrictions are in place. With less traffic on the roadways, recent studies have reported an uptick in high-risk taking behaviors such as speeding, stunt driving, and cellphone use (ZenDrive, 2020). The aim of the proposed study is to investigate how driving behaviors may have changed following the stay-at-home restrictions beginning in March, 2020.
Methods: To achieve our objectives, several questions of distracted driving behaviors (speeding, stunt driving, use of conferencing apps ect.) were asked during an online retrospective survey administered through Qualtrics, an online platform. Further analysis will be conducted to understand the associations between gender and age and each distracted driving behavior. A logistic regression will be run for each distracted behavior separately to see the relationship them and between fewer vehicles on the road after controlling for demographic variables. In using a logistic regression, I can predict if age, gender, or encountering fewer vehicles on the roads are associated with the risk of increased distracted driving behaviors.
Results: A total of 103 respondents with complete data sets will be included for final statistical analysis. This sample consisted of 52 Males and 51 females. Of these participants, 82.5% agreed to encountering fewer vehicles on the road and 76.7% reported a diminished total number of driving hours per week since March, 2020.
Conclusions: This research will help fill the gaps in the literature with regard to driver behavior characteristics during a global pandemic, and help to predict driving patterns for our ‘new-normal’ post-pandemic.