Ahmad Kamil Arshad

A good asphalt mixture is very important to maintain the triangle of sustainability. Many accidents occur due to pavement damage such as permanent deformation caused by the external loads induced by heavy traffic. Stone Mastic Asphalt (SMA) has a low resistance to moisture and other performances. Many researchers have conducted on SMA using various types of fiber. However, not much research has been done using steel fiber in the SMA mixture and has analyzed the result obtained using a statistical approach. The objective of this research was to identify the optimum amount of steel fiber in a modified asphalt mixture and characterize the performance of steel fiber in the SMA mixture using the statistical approach of Response Surface Methodology (RSM) in Design Expert Software. In this study, various steel fiber proportions of 0 percent, 0.3 percent, 0.5 percent, and 0.7 percent by the total weight of the SMA mixture were used. The Marshall stability and flow test, dynamic creep and moisture susceptibility test, and ultimately, RSM analysis were used to evaluate the properties and performance of the steel fiber-modified SMA, which contained 6.2 percent of PEN 60/70 asphalt binder content. The testing findings unmistakably demonstrated that the addition of steel fiber greatly improves the SMA mixture’s resistance to moisture and permanent deformation. An amount of 0.3 percent was found to be the most optimum steel fiber content from the optimization by using Response Surface Methodology, thus proven with additional steel fiber in the SMA mixture enhancing the performance of the mixture. As a result, it can be determined that the addition of steel fiber to SMA asphalt mixtures has improved the properties and performance in the construction of asphalt pavements, and the RSM method is an efficient statistical method for producing an appropriate empirical model for relating parameters and predicting the best performance of an asphaltic mixture.

The chances of a road user getting involved in a crash increase with an increased number of vehicles. Because of the rise in mobility, especially Heavy Goods Vehicle (HGV), a comprehensive study of the causes of a road crash involving HGV is required. Univariate binary logistic Regression was applied to HGV crash data collected from police records to examine the contribution of several road elements factors to accident severity. A total of 3,663 crash cases involving HGV were analyzed for three years (2015-2017). Accident severity (the dependent variable) in this study is a dichotomous variable with two categories, fatal and non-fatal. Therefore, the subjects sampled were classified as either fatal or non-fatal crashes. As a result, from eight independent variables of road elements obtained from police crash reports, five were most significantly associated with accident severity: road geometry, road defect, shoulder type, quality of surface and lane markings. A statistical interpretation is estimated in terms of the odds ratio concept. In conclusion, the significant factors identified in this study can be used as a guide to mitigate the probability of severe injuries and deaths. The significant factors can also help relevant authorities plan and design a sufficient and safe road element, especially for HGV safety.

The pedestrian-related concerns receive a substantial amount of attention among researchers around the world in order to primarily understand the situation and the associated factors. In fact, the most prominent pedestrian behaviour engaged in pedestrian casualties was reckless crossing while displayed a distracted activity. The purpose of this study is to determine the prevalence of distracted walking at unsignalized intersection through observation and empirical method. The field observation was conducted at selected unsignalized intersection around Subang Jaya, Selangor and the distracted walking activities were observed along with their cautionary crossing behaviour. This empirical study observed over 931 pedestrians and revealed that a substantial minority of pedestrians (30.4%) are distracted. Male pedestrians (55.7%) are more likely to display distracted activity compared to female pedestrians (44.3%). The findings of this study found that the most often distraction was social distraction (talking with friends) of 34.4%, followed by technological distraction (texting) of 33% respectively. Gender variables are found to be significantly (p<0.05) associated with “conversing on the phone” distraction during both time observations. Furthermore, group size variables are noticed to be significantly (p<0.05) associated with at least one cautionary behaviour in which crosswalk utilization during peak hour. Distracted walking by “texting” and “listening to music” are found to be significantly (p<0.05) associated with looking left or right while crossing behaviour. Meanwhile, distracted walking by “conversing on the phone” are significantly associated with observe both ways prior to crossing behaviour. Based on the findings, it is essential that enforcement efforts should be stepped it up and oriented toward safer pedestrian behaviour.

Road accident cases involving motorcyclists in Malaysia are on the rise where the latest recorded at 113,288 cases in 2018. It was also found that motorcyclists

Hot mix asphalt (HMA) is the most prevalent technique that used road pavements as surfacing. However, recently, the quality of the conventional flexible road surface has been questionable as a number of road surfacing deteriorated extensively. Researchers are aggressively looking up for new solutions to improve existing conventional asphalt mixtures. One of the possible solutions to improve the mixes is to use polymer s as modifier/additive in the mixture. The goal of this study was to see how natural rubber latex (NRL) affected the modified asphalt binder on the performance of hot mix asphalt mixture. Commercially produced bitumen PEN 50/70 modified with 5% NRL by weight of bitumen was used for the asphalt mixes. Dense asphaltic concrete AC14 specimens were then prepared using the modified bitumen. After that, the moisture susceptibility, resilience modulus, and rutting resistance of the asphaltic concrete specimens were assessed. The moisture susceptibility was evaluated using the Indirect Tensile Strength (ITS) test, the resilient modulus of the asphaltic specimens was evaluated using the Universal Testing Machine (UTM), and the rutting resistance was assessed using the asphalt Pavement Analyzer (APA). The results revealed that adding NRL to dense asphaltic concrete mixes improved the resilience modulus value and decreased the rutting depth while maintaining the required moisture resistance. According to the findings, the addition of NRL to bitumen upgrade the performance of dense asphaltic concrete mixtures.

Pavement evaluations provide crucial information regarding the performance and service life of asphalt concrete (HMA). They examine the structure of an existing pavement before deciding on different maintenance alternatives. The Klang Valley, as part of one of the developing areas in the state of Selangor, generates a high volume of traffic every day due to the increasing number of vehicles crossing the area. Every day, the impact of axle loads caused by vehicles has a negative impact on flexible pavement, resulting in road deterioration due to extreme distress. Pothole failures are one of the most common causes of distress. Five research areas in the Klang Valley area that have deteriorated owing to pothole failures were chosen as case studies. The objective of the study is to investigate the existing flexible pavement conditions by means of laboratory testing consisting of physical, volumetric, and performance tests using collected core samples. As a result, the data collected was compared to the Malaysian Public Work Department’s (PWD) standard. Data from laboratory tests was analyzed using Response Surface Methodology (RSM) to determine correlations with parameters influencing distress. Historical data design was carried out between test components and responses, which consisted of laboratory parameters. Axial strain, tensile strength ratio, and stability were the responses measured in the RSM. The created models between the independent variables and responses revealed a high level of correlation. The binder content, degree of compaction, and stiffness were the most significant operating parameters from the 3D plots. Optimized performance due to asphaltic pavement failure was observed at binder content (5.1%), degree of compaction (97%), and stiffness (3.1 kN/mm) to achieve ultimate axial strain (5000 microstrains), tensile strength ratio (80%), and stability (9.2 kN). The study showed that the response surface methodology (RSM) is an effective statistical method for providing an appropriate empirical model for relating parameters and predicting the best performance of an asphaltic mixture to reduce flexible pavement failure.