A new approach for resource allocation for black spot treatment (case study: The road network of Iran)

Hot spot analysis and evaluation of influencing factors on regional road crash safety and severity indices: insights from Iran

Inadequate regional road safety studies have been conducted in developing countries like Iran. Regarding regional road safety indices (RSIs), a significant disparity between Iranian provinces was observed. Thus, it was aimed to evaluate the regional RSIs in Iran and identify their influencing factors and potential hot spots. Data on regional road crashes, fatalities, demographics, transportation, health institutions, economics, education, and fuel consumption rates were collected. The association between the variables was evaluated using correlation analysis. Using Moran's I and local Moran indices, provinces' spatial distributions were evaluated. Hot spot analysis was used to identify factors influencing RSIs. Significant correlations between the variables were detected. A vast local cluster in terms of fatality per injury (as a crash severity index) was identified in the country's southeast. The distribution patterns of provinces in terms of seven RSIs were cluster-like. Variable groups, including road length, demographic, income, education, and geographic, influence RSIs in hot or cold spot regions. Crashes were severe in underdeveloped and remote provinces. Increasing income and education levels make it possible to reduce crash severity indices in this country. A positive Moran's I index does not guarantee the existence of significant local cluster cores in a country.

Impact of COVID-19 spread on road safety indices of Turkey

Little is known about the effect of the COVID-19 on road safety indicators (RSIs) in developing countries, and conducted studies provide limited information regarding this impact. These prompted the author to evaluate the impact of COVID-19 on RSIs in Turkey. RSIs and related indices of Turkey between 2016 and 2020 were collected. For evaluating the impact, RSIs whose 2020 measures differed significantly from the pre-COVID era were identified using the outlier detection technique and Regression analysis. K-means clustering was used to group RSIs according to their variation patterns in the study period. Results show that COVID-19 led to significant decreases in 26 RSIs, especially ones related to non-fatal road traffic injuries. COVID-19 resulted in a significant drop in road traffic crashes and related indices. Also, considerable changes in monthly and daily fatalities and injuries in 2020 were observed. Clustering results revealed that COVID-19 significantly impacts variation patterns of studied RSIs, especially ones related to non-fatal injuries. Clustering aided in identifying affected RSIs by COVID-19, which other used methods were unable to detect. COVID-19 led to significant changes in road safety indices in Turkey. Road authorities and researchers should be aware of these significant fluctuations in road safety data.