The effect of adverse weather conditions on the safety of vehicles moving on different types of roads and measuring its margin of safety have always been a major research issue of highways. Determining the exact value of friction coefficient between the wheels of the vehicle and the surface of the pavement (usually Asphalt Concrete) in different weather conditions is assumed as a major factor in design process. An appropriate method is analyzing the dynamic motion of the vehicle and its interactions with geometrical elements of road using dynamic simulation of vehicles. In this paper the effect of changes of friction coefficient caused by the weather conditions on the dynamic responses of three types of vehicles: including Sedan, Bus, and Truck based on the results of Adams/car Simulator are investigated. The studies conducted on this issue for different weather conditions suggest values ranging from 0.04 to 1.25. The results obtained from simulation based on Adams/car represent that the friction coefficient in values of 0.9, 0.8, 0.7, 0.6 do not effect on braking distance significantly and it is possible to attribute them all to dry weather condition. However, as it was anticipated the values of 0.5, 0.4, 0.28 and 0.18 have significant differences in braking distance. Hence, the values of 0.5, 0.4, 0.28 and 0.18 can be attributed to wet, rainy, snowy and icy conditions respectively.

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The color and brightness of pedestrian clothing are among the factors that could increase the severity of their accidents due to the lack of visibility, especially at night. Today, as most Iranian females tend to wear hijab or dark clothing, the necessity of investigating female pedestrian accidents influenced by clothing color is important. Many studies have been performed to analyze the severity of pedestrian accidents, but a study has not yet been conducted to determine the effect of the dark clothing color of female pedestrians on the severity of accidents. Therefore, in this study, 12 independent variables affecting the severity of female pedestrian accidents such as clothing color, age, accident time, day, weather condition, education, pedestrian action, crossing facilities, crossing permit, job, road classification, and fault status were studied. Frequency analysis, Friedman test (FT), and Factor Analysis (FA) methods, as well as modeling methods of Multiple Logistic Regression (MLR) and Artificial Neural Networks (ANNs) using Multilayer Perceptron (MLP) and Radius Basis Function (RBF), were used. Results indicated that clothing color had a significant influence on pedestrian accidents, and chador and dark clothing color increased the probability of accidents, especially at night. The MLP model had a better prediction percentage than the rest, the prediction accuracy of which was 94.6%. Finally, safety solutions were presented according to the results to reduce pedestrian accidents and increase road safety.

Rural highway crash analyses have shown that the majority of accidents occur on horizontal curves where the vehicle is exposed to lateral forces, which increase the probability of skidding. Moreover, in cases of compound alignments where curves from the road's horizontal alignment are overlaid with constant grades or vertical curves, the probability of skidding increases due to the increase of the longitudinal force on the vehicle. In this research, by utilising vehicle multi-body simulation modelling, several scenarios are defined to assess the impact when horizontal curves are combined with vertical sag curves for three different kinds of vehicles (sedan, sports utility vehicle and truck). For various speed values, the maximum lateral friction demand between the road surface and vehicle tyres is calculated. Finally, by using regression analysis, a model is presented according to the inputs and outputs of the simulation modelling to determine the maximum lateral friction demand created in various conditions. The results of this research indicate that the maximum lateral friction between the road surface and vehicle occurs when the lower part of the sag vertical alignment is located in the middle of horizontal curve.

Rollover crash is a type of dangerous crash that occurs often in two-lane highways. Therefore, this study evaluates the effect of road shoulder and weather condition on rollover crashes. Crash data show that 8,609 crashes were recorded from 2006 to 2009 on six two-lane highways located at the center of Iran. This data contains 1860 rollover crashes. Rollover crash in this paper not included the head on crashes and fixed object crashes. Therefore the rollover crashes are only single vehicle crashes. Binary logit was selected for modelling since there were two possible outcomes: rollover crashes and other crash types. The variables of the final model include highway class, road shoulder width, as well as rainy, snowy, foggy and night conditions. The modeling results show that rainy and foggy variables, with coefficients of 0.731 and 0.719 respectively, had the greatest effects on rollover crash occurrence. Also, road shoulder width and night conditions, with coefficients of 0.221 and 0.184 respectively, had the least effects on rollover crash occurrence. Afterward, sensitivity analysis was performed on all the independent variables, and the results show variable variation and indicate that the probability of rollover crash occurrence is 21.29 % on the mentioned highway.