Ranking and Determining the Factors Affecting the Road Freight Accidents Model

Abstract

The tremendous growth of population, particularly in developing countries, has led to increased number of travels, especially those with load and freight specifications. Hence, expanding the present facilities or developing new networks or systems concerning freight and transportation is an essential issue. Among the various transportation systems, road freight has secured a significant place in sub-urban transportation, as it is responsible for transporting loads, decreasing transportation costs, and increasing the safety of highway users. Besides these advantages, poor and nonstandard design and performance of sub-urban highways and transport fleet and equipment leads to the increased number of accidents and inefficiency of these facilities. Based on these facts, the primary aim of the present study is to probe into the factors affecting road freight accident severity. For this purpose, the data obtained from road freight accidents occurring in 2016, 2017, and 2018 in Gilan Province, Iran, were used for analyzing the frequency, ranking and determining the factors, and creating models for accident severity. The results indicated that in accordance with the accident severity model in 2016, several factors such as the season of autumn, daytime light, drivers aged from 18 to 60, and pickup trucks have impacted the on-road freight accident severity. While, in 2017 the severity was affected by factors like rural road, freight trucks, non-faulty passenger cars, motorcycles, and pedestrians. When considering the effective variables in 2018, it was found that such factors as the accident time (usually occurring between 12 p.m. to 6 p.m)., rural and major roads, freight trucks, non-faulty motorcycles, and the careless driving without due care and attention to the front were the variables affecting road freight accidents. Moreover, not following safety guidelines during freighting is the most effective variable in road freight accidents.

Public acceptance of driver state monitoring for automated vehicles: Applying the UTAUT framework

“…It was shown that being inattentive to the road ahead and noncompliance with road safety rules were the main variables in road freight collisions. (Bagheri and Shirazian, 2020). Since 'human error' is the main cause of road traffic collisions, there have been attempts to minimize unfavorable driver behaviour in vehicles.…”

Road Traffic Accident Analysis and Identification of Black Spot Locations on Highway

“…The results indicated that in accordance with the accident severity model in 2016, Several factors such as the season of autumn, daytime light, drivers aged from 18 to 60, and pickup trucks have impacted the on-road freight accident severity. While, in 2017 the severity was affected by factors like rural road, freight trucks, non-faulty passenger cars, motorcycles, and pedestrians [27]. With the above information and data assessment, very little study has been carried out yet in Pakistan.…”

Investigating what makes people walk or cycle using a socio-ecological approach in seven European cities

“…The timing (e.g. flexible working hours vs. morning rush hour trips (Shove, 2002) may influence mode choice from a reliability perspective, and daytime/nighttime travel and lighting also has an impact on accident rates, which may in turn influence the psychosocial attitudes towards the safety of a mode (Ramiani and Shirazian, 2020;Uttley et al, 2020). Depending on location, warmer weather may increase active travel (Børrestad et al, 2011), or conversely, decrease it (Wang et al, 2020), although adverse conditions tend to decrease active travel in general.…”