Research on the Optimization Design of Intersections for Safe Operation of Large Trucks

When big trucks are running at urban road intersections,they are easy to interfere with other motor vehicles,and the turning big trucks are easy to have conflicts with non-motor vehicles and pedestrians,which will affect the safety of intersections.This paper first studied the intersection of trucks to the running trajectory,on this basis,through the establishment of mathematical model analysis of large truck steering conditions inside the wheel,and the influence of blind area to the driver.In the research of intersection safety design,the safety design is divided into three parts:Entrance road,internal operation and signal control.At the same time,the design method of the entrance road,the interior of the intersection and the signal control is given,which improves the safety of the truck driving at the intersection.Finally,the intersection of Jungong road and Zhoujiazui road in Yangpu district of Shanghai was selected as a case,and the optimal design of the intersection for large trucks was carried out through the investigation and analysis of actual data.The evaluation and analysis were carried out by using the multi-index matter-element model.The results show that the comprehensive safety correlation degree of the intersection is reduced to 0.42,and the safety level of is improved by one level.

Excessive Drowsiness among Truck Drivers in Benin in 2023: Associated Factors and Risk of Crashes Occurrence

Introduction: Over-drowsiness is a condition with serious consequences, including road accidents. The condition, however, is often ignored both by carers as well as victims themselves. The aim of the present study was to investigate the factors associated with excessive drowsiness in Cotonou, Benin 2023, along with its influence on the occurrence of crashes among truck drivers. Methods: This was a descriptive and analytical cross-sectional study, held from March 13 to April 10, 2023, focusing on large truck drivers over 18 years of age, selected by convenience from parking lots in and around the city of Cotonou. Data collected using questionnaires on socio-demographic and behavioral factors, sleeping habits and working conditions were processed using Stata 15.0 software. Excessive drowsiness was defined by a score above 10 on the Epworth scale. Associated factors were found by multiple logistic regression, at a threshold of 0.05. Results: Altogether 304 drivers, all male and aged 35.98 ± 8.42 years, were surveyed. The prevalence of excessive drowsiness was 29.2%. The associated factors identified were not practicing sport OR = 2.27, CI95% = [1.33;3.86], p = 0,002;sleep duration per working day OR = 1.82;CI95% = [1.06;3.11], p = 0,027 and average distance travelled per day OR = 3.40;CI95% = [1.53;7.56], p = 0,003. Excessive drowsiness was associated with a 1.73-fold increased risk of road accidents (CI95% [1.04;2.87];p = 0.03). Conclusion: Communicating excessive drowsiness and its associated factors to all the stakeholders in the haulage chain is essential to help prevent road accidents.