Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting. (September 2021)
- Record Type:
- Journal Article
- Title:
- Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting. (September 2021)
- Main Title:
- Identifying the impact of the COVID-19 pandemic on driving behavior using naturalistic driving data and time series forecasting
- Authors:
- Katrakazas, Christos
Michelaraki, Eva
Sekadakis, Marios
Ziakopoulos, Apostolos
Kontaxi, Armira
Yannis, George - Abstract:
- Highlights: The impact of COVID-19 on speed, speeding and harsh braking is evaluated. SARIMA time-series modelling is used for quantifying the pandemic effect. Naturalistic driving data captured from a novel smartphone applications are used. Speeds and harsh brakings were found to have the highest increase. Abstract: Introduction: COVID-19 has disrupted daily life and societal flow globally since December 2019; it introduced measures such as lockdown and suspension of all non-essential movements. As a result, driving activity was also significantly affected. Still, to-date, a quantitative assessment of the effect of COVID-19 on driving behavior during the lockdown is yet to be provided. This gap forms the motivation for this paper, which aims at comparing observed values concerning three indicators (average speed, speeding, and harsh braking), with forecasts based on their corresponding observations before the lockdown in Greece. Method: Time series of the three indicators were extracted using a specially developed smartphone application and transmitted to a back-end platform between 01/01/2020 and 09/05/2020, a time period containing normal operations, COVID-19 spreading, and the full lockdown period in Greece. Based on the collected data, XGBoost was employed to identify the most influential COVID-19 indicators, and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models were developed for obtaining forecasts on driving behavior. Results: Results revealed theHighlights: The impact of COVID-19 on speed, speeding and harsh braking is evaluated. SARIMA time-series modelling is used for quantifying the pandemic effect. Naturalistic driving data captured from a novel smartphone applications are used. Speeds and harsh brakings were found to have the highest increase. Abstract: Introduction: COVID-19 has disrupted daily life and societal flow globally since December 2019; it introduced measures such as lockdown and suspension of all non-essential movements. As a result, driving activity was also significantly affected. Still, to-date, a quantitative assessment of the effect of COVID-19 on driving behavior during the lockdown is yet to be provided. This gap forms the motivation for this paper, which aims at comparing observed values concerning three indicators (average speed, speeding, and harsh braking), with forecasts based on their corresponding observations before the lockdown in Greece. Method: Time series of the three indicators were extracted using a specially developed smartphone application and transmitted to a back-end platform between 01/01/2020 and 09/05/2020, a time period containing normal operations, COVID-19 spreading, and the full lockdown period in Greece. Based on the collected data, XGBoost was employed to identify the most influential COVID-19 indicators, and Seasonal AutoRegressive Integrated Moving Average (SARIMA) models were developed for obtaining forecasts on driving behavior. Results: Results revealed the intensity of the impact of COVID-19 on driving, especially on average speed, speeding, and harsh braking per 100 km. More specifically, speeds were found to increase by 2.27 km/h on average compared to the forecasted evolution, while harsh braking/100 km increased to almost 1.51 on average. On the bright side, road crashes in Greece were reduced by 49% during the months of COVID-19 compared to the non-COVID-19 period. … (more)
- Is Part Of:
- Journal of safety research. Volume 78(2021)
- Journal:
- Journal of safety research
- Issue:
- Volume 78(2021)
- Issue Display:
- Volume 78, Issue 2021 (2021)
- Year:
- 2021
- Volume:
- 78
- Issue:
- 2021
- Issue Sort Value:
- 2021-0078-2021-0000
- Page Start:
- 189
- Page End:
- 202
- Publication Date:
- 2021-09
- Subjects:
- COVID-19 -- Driving behavior -- Time-series forecasting -- SARIMA -- XGBoost
Industrial safety -- Periodicals
Accidents -- Prevention -- Periodicals
Safety -- Periodicals
Accidents, Occupational -- Periodicals
Sécurité du travail -- Périodiques
Accidents -- Prévention -- Périodiques
Accidents -- Prevention
Industrial safety
Periodicals
363.1 - Journal URLs:
- http://www.sciencedirect.com/science/journal/00224375 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.jsr.2021.04.007 ↗
- Languages:
- English
- ISSNs:
- 0022-4375
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5052.130000
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