The use of recycled crumb rubber (CR) in asphalt pavements could be an essential step towards ensuring a more sustainable future in addition to opening a new investment opportunity for global investors. Asphalt modifiers have the ability to enhance the performance of flexible pavements and contribute towards ensuring a more sustainable environment. The utilization of CR produced from end-of-life tires (ELTs) as an asphalt modifier has been shown to enhance asphalt performance with regard to high-temperature rutting and low-temperature thermal cracking due to the remarkable characteristics of the CR. This paper presents the findings of previous studies, including the grinding of ELTs to obtain crumb rubber, the technology employed in the process, and the physical and mechanical properties of the asphalt modifiers. Even though the present study focuses on the application of hot-mix asphalt (HMA), there are other methods, for instance, warm-mix asphalt (WMA), reclaimed asphalt pavement (RAP), and porous asphalt, that used CR as a modifier or as an additive in asphalt binders. A review of the literature suggests that most CR have a good performance and are suitable for use in the top paving layer to reduce noise as well as for other applications.

One of the most frequently used waste materials is reclaimed asphalt pavement (RAP). The use of RAP can help reduce the cost of a project and ensure that the project is eco-friendly. Therefore, the aim of this study is to give a detailed description of the production of RAP to ensure that the rehabilitation and maintenance of pavements as well as the construction of pavements are environmentally friendly and cost effective. Previous works have shown the benefits of using RAP with regard to its ability to produce equally good or even superior results compared to the use of virgin or original mixes if they are properly produced and applied. Among the benefits of RAP mixes are good moisture resistance and higher density. This review also demonstrate the critical importance of using RAP in asphalt mixtures.

Public bus transit travel time is affected by many factors, including traffic signals and traffic condition. Transit agencies have implemented transit signal priority (TSP) strategies to reduce transit travel time and improve service reliability. However, due to the lack of empirical data, these factors' collective impact and bus travel time strategies have not been studied at the stop-to-stop segment level. This research focuses on the factors affecting travel time reliability, emphasising the variability between operators and the policy implications of such differences. One-way analysis of variance (ANOVA) statistical methods have been used to assess the quality implications of public bus transportation time reliability. This research seeks to investigate the factors affecting the travel time (TT) reliability of bus transport. Studies were conducted along three bus routes serving different areas. Factors strongly related to TT reliability include route length, number of signalised intersections, day of the week, bus stops, departure delays, bus lane, passenger boarding and alighting, weather condition, and fare structure. Based on the proposed model factors affecting TT reliability, it was found that TT is strongly affected by the number of bus stoppings and also the length of the route. The reliability of all three routes during the weekday is low because of delays in departure. The number of signalised intersections along the route affects reliability. Meanwhile, more passengers boarding and paying cash increased the travel time reliability of buses.

Rheology can be defined as the primary measurement associated with bitumen flow and deformation characteristics. In the long term, DSR testing consumes a long time, expensive cost and skilled labour to operate equipment or machines in the laboratory. The complex modulus, G* and phase angle, δ, are essential parameters for characterising and predicting the rheological behaviour of unaged bitumen (UB) and polymer-modified bitumen (PMB) in the model. This study developed three regression models using Azure machine learning (AML) to predict the rheological behaviour of UB and PMB. There are three types of data used as input data to develop the regression model: temperature, frequency, and modified material content. Regression models were developed with three processes or steps that need to be prioritised: data collection, model preparation, and model validation. Algorithms used in model development are decision tree regression (DFR), boosted decision tree regression (BDTR) and linear regression (LR). The results show G* and δ values. The R² values in the G* and <em>δ</em> predictions obtained from the DFR models are 0.8199 and 0.9480, respectively. Moreover, the R² values in the G* and <em>δ</em> predictions obtained from the LR models are 0.4219 and 0.7836, respectively.

The feasibility of utilizing waste material for road construction is encouraging as it can decrease waste material harmful to the environment. Hence, a more sustainable method and a meticulous study of the available admixtures utilized to substitute standard asphalt binders with waste material must be conducted. However, there are several concerns and doubts about the real situation arising from the chemical and physical traits, as well as the mechanical performance issuing from the integration of waste material within the asphalt pavement to alleviate roads surface's permanent deformation. This investigation was carried out to study physical improvements made on ACW-14 bitumen by adding waste Polyethylene Terephthalate (PET) to serve as a partial replacement for bitumen content compared to normal, conventional 80/100 bitumen physical and rheological behavior. PET percentage added to the bitumen content was 10%, 8%, 6%, 4% and 2% of optimum bitumen content weight. The outcomes concluded that the best performance of bitumen on its density, VTM, VFB, flow, stability, and stiffness was achieved when 5.8% of Optimum Modified-Bitumen Content using PET. All the results obtained have been compared according to JKR Standards results, and the conclusion has fulfilled these requirements.