Driving Behavior and Its Correlation with COVID-19 Response Measures: A Neural Network Forecasting Analysis
Publication: Journal of Transportation Engineering, Part A: Systems
Volume 148, Issue 10
Abstract
The pandemic of COVID-19 has affected human patterns since December 2019. Since the very beginning, most countries imposed strict measures such as lockdowns and the suspension of all nonessential movements to reduce the spread of the pandemic. Therefore, mobility, road safety, and travel behavior were also significantly affected. At present, many studies tried to investigate travel or mobility behavior changes taking into account all possible transportation modes, but very few studies investigated driving behavior. This study aims to investigate driving behavior and its correlation with the strictness of COVID-19 response measures. Four neural network autoregression (NNAR) models with an external regressor were developed in order to forecast three different future stringency scenarios. NNAR models were employed as the forecasting performance was superior when comparing with statistical autoregressive integrated moving average (ARIMA) models. The NNAR models were developed using driving behavior-related variables (i.e., driving speed, speeding, speeding duration percentage, and mobile use percentage), derived from a smartphone application that has been developed by OSeven Telematics. The NNAR models were trained on 2020 data and three different scenarios were predicted for 2021 by providing three different constant stringency indices (i.e., 0, 55, 85). In particular, normal conditions without restrictions were simulated with zero stringency index, whereas moderate restrictions were simulated with 55 and finally, fully restrictions were simulated with 85. The NNAR modeling results showed that with higher stringency index, mobile use and driving speed tend to increase, whereas speeding duration demonstrates higher peaks. Interestingly, with stricter response measures, lower values were forecasted for speeding. Taking into account the modeling outcomes, there is a direct effect of the COVID-19 response measures on driving behavior. Nevertheless, a wider time frame for data collection as well as the use of more sophisticated techniques to control for the interrelationship between COVID-19 spread and driving behavior might be useful for future studies.
Practical Applications
Interested stakeholders could exploit the study findings and the lessons learned during the pandemic in order to mitigate road safety implications. The COVID-19 pandemic demonstrated the vulnerability of mobility, travel behavior, road safety, and driving behavior patterns throughout health or societal crises. For example, driving speed, peaks of speeding duration percentage, as well as mobile use were found to be higher for an increased stringency index (i.e., during measures imposition) which lower traffic volumes imply. As a direct effect between response measures and driving behavior was observed, measures that promote safety and equity could be tested using the modeling approach followed in this paper. In this direction, road safety administrations have already proposed lowering speed limits inside cities to 20 or . Lower speeds could reduce the chance of road crashes, serious injuries, fatalities, and harsh events. Active traveling such as walking, cycling, or e-scooters could also be promoted by policymakers as a step towards safer and environmentally friendly mobility.
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Data Availability Statement
All data used during the study are confidential in nature and may only be provided with restrictions (e.g., anonymized data) by OSeven Telematics, London (OSeven 2022).
Acknowledgments
The authors would like to thank OSeven Telematics, London (OSeven 2022) for providing all driving data exploited to accomplish this study. All data provided by OSeven follow strict information security procedures and privacy policies, which are fully compliant with the general data protection regulation (GDPR) of the European Parliament and the council of the European Union (EU 2016). Therefore, all data have been provided in a fully anonymized format and no geolocation information for the trips is provided, apart from the country. The authors declare that the current study was conducted according to the ethical principles of the Declaration of Helsinki since no one was harmed, or physically or mentally affected during the driving measurements, and the drivers participated voluntarily. The OSeven application is open-access and does not affect the drivers during the driving task. The OSeven application intends to record and evaluate the drivers’ performance and improve road safety and eco-driving towards self-improvement. Application users have the ability at the end of the route to witness their hazardous and environmentally harmful actions and events. These randomly chosen measurements were exploited in this study. The ethics guidelines were also approved by the director of the Department of Transportation Planning and Engineering of the School of Civil Engineering at the National Technical University of Athens.
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Journal of Transportation Engineering, Part A: Systems
Volume 148 • Issue 10 • October 2022
Copyright
© 2022 American Society of Civil Engineers.
History
Received: Apr 16, 2021
Accepted: May 20, 2022
Published online: Aug 9, 2022
Published in print: Oct 1, 2022
Discussion open until: Jan 9, 2023
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