Crash model based on integrated design consistency with low traffic volumes (due to health disaster (COVID-19)/movement control order)

One year of COVID-19: Impacts on safe driving behavior and policy recommendations

INTRODUCTION

In the unprecedented year of 2020, the rapid spread of COVID-19 disrupted everyday activities worldwide, leading the majority of countries to impose lockdowns and confine citizens in order to minimize the exponential increase in cases and casualties. To date, very few studies have been concerned with the effect of the pandemic on driving behavior and road safety, and usually explore data from a limited time span.

METHOD

This study presents a descriptive overview of several driving behavior indicators as well as road crash data in correlation with the strictness of response measures in Greece and the Kingdom of Saudi Arabia (KSA). A k-means clustering approach was also employed to detect meaningful patterns.

RESULTS

Results indicated that during the lockdown periods, speeds were increased by up to 6%, while harsh events were increased by about 35% in the two countries, compared to the period after the confinement. However, the imposition of another lockdown did not cause radical changes in Greek driving behavior during the late months of 2020. Finally, the clustering algorithm identified a "baseline," a "restrictions," and a "lockdown" driving behavior cluster, and it was shown that harsh braking frequency was the most distinctive factor.

POLICY RECOMMENDATIONS

Based on these findings, policymakers should focus on the reduction and enforcement of speed limits, especially within urban areas, as well as the incorporation of active travelers in the current transport infrastructure.

Modeling Motorcyclists’ Aggressive Driving Behavior Using Computational and Statistical Analysis of Real-Time Driving Data to Improve Road Safety and Reduce Accidents

Driving behavior is considered one of the most important factors in all road crashes, accounting for 40% of all fatal and serious accidents. Moreover, aggressive driving is the leading cause of traffic accidents that jeopardize human life and property. By evaluating data collected by various collection devices, it is possible to detect dangerous and aggressive driving, which is a huge step toward altering the situation. The utilization of driving data, which has arisen as a new tool for assessing the style of driving, has lately moved the concentration of aggressive recognition research. The goal of this study is to detect dangerous and aggressive driving profiles utilizing data gathered from motorcyclists and smartphone APPs that run on the Android operating system. A two-stage method is used: first, determine driver profile thresholds (rules), then differentiate between non-aggressive and aggressive driving and show the harmful conduct for producing the needed outcome. The data were collected from motorcycles using -Speedometer GPS-, an application based on the Android system, supplemented with spatiotemporal information. After the completion of data collection, preprocessing of the raw data was conducted to make them ready for use. The next steps were extracting the relevant features and developing the classification model, which consists of the transformation of patterns into features that are considered a compressed representation. Lastly, this study discovered a collection of key characteristics which might be used to categorize driving behavior as aggressive, normal, or dangerous. The results also revealed major safety issues related to driving behavior while riding a motorcycle, providing valuable insight into improving road safety and reducing accidents.

Did the COVID-19 pandemic influence traffic fatalities in 2020? A presentation of first findings

The year 2020 was an extraordinary year due to the COVID-19 pandemic. This pandemic resulted in lockdowns and confinements globally and emptier streets and roads. Traffic patterns and traffic composition (modal split) changed considerably during the pandemic and as a consequence the number of people killed and injured in road crashes. The aim of this research is to present the number of road fatalities and the fatality rates (fatalities per kilometer driven) in 2020 and to compare these numbers and rates with the previous period (2017–2019), a baseline. An online questionnaire was distributed among the forty countries that are members of the International Safety Data and Analysis Group (IRTAD) in the International Transport Forum and 24 were in a position to submit the requested information before the 1st of June 2021. The questionnaire requested information on the monthly number of fatalities on a national level for four years, (2017–2020) and on kilometres driven. The number of fatalities in 2020 was 17.3% lower in the 24 participating countries compared with the baseline period and the reduction is almost seven times higher than annually in these countries in the period 2010–2019. The reduction took place in spring 2020 and not so much in the remainder of the year. The highest reduction were measured among young (0–17) and elderly people (75 and older), with public transport and on motorways. With the exception of one country, reductions in fatalities have been measured in all countries, however we observe major differences between countries. Regarding fatality rates (fatalities per vehicle kilometer travelled), we also observe major differences between countries and not a stable pattern over 2020 and a remarkable increase in April 2020, the month with the largest fatality reduction. Countries with severe COVID-19 restrictions do not necessarily demonstrate the greatest reductions in road fatalities. It is recommended to carry our further analysis to find explanations for the results and for the differences between the countries.