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Impact of Driver, Vehicle, and Environment on Rural Road Crash Rate

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There is an abundance of research on road-crash-influencing factors; however, it often relies on a limited subset of variables. The aim of this work was to analyze the significance of road-crash-influencing variables on rural roads and to estimate the crash frequencies during different conditions by introducing a holistic approach and analyzing a wide range of driver–vehicle–road–environment variables. The input data comprised long-term vehicle speed data, obtained using inductive loop traffic counters, and short-term data, obtained using a calibrated police radar. A combination of both was augmented with driver traits and meteorological conditions, gender, age, years possessing a driver’s license, crashes, vehicle, and environmental data. The crash data used for the analysis was based on police records. The results indicate that crash frequencies and driving speed have strong daily and weekly seasonality. The average hourly crash frequencies per kilometer driven during the week varied between 0.2 and 2.2 crashes per million km; the major cause was speeding, which contributed to nearly 32% of fatal crashes. Speed choice could be affected by alcohol-consuming drivers involved in crashes, as the percentage of drivers with any level of alcohol detected expressed daily and weekly patterns similar to those of crash frequencies per kilometer. Contrary to the highest relative crash frequency, which occurred during nighttime, the majority of daily crashes occurred during the afternoon peak hours; thus, the societal impact of crashes is the highest during the day.
Title: Impact of Driver, Vehicle, and Environment on Rural Road Crash Rate
Description:
There is an abundance of research on road-crash-influencing factors; however, it often relies on a limited subset of variables.
The aim of this work was to analyze the significance of road-crash-influencing variables on rural roads and to estimate the crash frequencies during different conditions by introducing a holistic approach and analyzing a wide range of driver–vehicle–road–environment variables.
The input data comprised long-term vehicle speed data, obtained using inductive loop traffic counters, and short-term data, obtained using a calibrated police radar.
A combination of both was augmented with driver traits and meteorological conditions, gender, age, years possessing a driver’s license, crashes, vehicle, and environmental data.
The crash data used for the analysis was based on police records.
The results indicate that crash frequencies and driving speed have strong daily and weekly seasonality.
The average hourly crash frequencies per kilometer driven during the week varied between 0.
2 and 2.
2 crashes per million km; the major cause was speeding, which contributed to nearly 32% of fatal crashes.
Speed choice could be affected by alcohol-consuming drivers involved in crashes, as the percentage of drivers with any level of alcohol detected expressed daily and weekly patterns similar to those of crash frequencies per kilometer.
Contrary to the highest relative crash frequency, which occurred during nighttime, the majority of daily crashes occurred during the afternoon peak hours; thus, the societal impact of crashes is the highest during the day.

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