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For highway construction or any superstructure, on dune sand, designers and construction teams must ensure that the foundation soil is stable enough to provide support for the applied loads. Sand dunes are stretched across Libyan deserts that make road construction a challenge because of the poor soil base. Replacement of such a weak soil is very expensive and not economically feasible, and, in many cases, there is no alternative soil nearby. This study used two different mix designs aimed at stabilizing the existing base course using a mix of dune sand and manufactured sand with a small percentage of Portland cement. Compaction, unconfined compressive strength and California bearing ratio tests were conducted on the treated sample with a varying cement proportion of 0%, 3%, 5% and 7% by weight. The first tests were done with a mix of 50% dune sand and 50% crushed sand that is shown to have excellent results. For a more economic design, this study also included testing of another mix design with 70% dune sand and 30% crushed sand; laboratory results show this 70%/30% mixture was appropriate to use as a base-treated material for road construction material. This mix resulted in overall superior performance. Its use will reduce the cost of road construction by saving materials and time, and it will also have lower environmental impacts in desert areas. This study has shown that the stabilization of weak material (desert sand) by using cement improves the strength characteristics of the treated soil.

Soil characteristics are paramount to design pavements and to assess the economic viability of a road. In the desert, such as that found in southern Libya, the very poor quality of soils leads to important pavement distress such as cracks, rutting, potholes, and lateral shear failure on the edges. To improve the strength of desert sand, an innovative approach is proposed, consisting of adding manufactured sand, ordinary Portland cement (OPC), and fly ash (FA) as a binder. OPC and FA improve the characteristics of mixes of crushed fine aggregate (CFA) and natural desert sand (NDS). These results are based on a gradation of two sand sources to determine the particle distribution and X-ray fluorescence (XRF) to determine their chemical and physical properties, respectively. This research assesses the effect of cement and fly ash on the geotechnical behavior of two mixtures of fine desert and manufactured sands (30:70% and 50:50%). The mix composed of 26% of CFA, 62% of NDS, 5% of OPC, and 7% of FA shows optimal results in terms of strength, compaction, and bearing capacity characteristics.

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Pavement maintenance plays a significant role in megacities. Managing complaints and scheduling road reviews are the two maintenance concerns under the intelligent pavement management system (PMS) plan. In contrast, if the damages are not treated immediately, they will increase over time. By leveraging accurate data from sensors, smart PMS will improve management capability, support sustainability, and drive economic growth in the road network. This research aimed to elaborate on the different modules of an intelligent city pavement network to advance to a sustainable city. First, a 3D mobile light detection and ranging (LiDAR) sensor, accompanied by a camera, was applied as the data collection tool. Although 3D mobile LiDAR data have gained popularity, they lack precise detection of pavement distresses, including cracks. As a result, utilizing RGB imaging may help to detect distresses properly. Two approaches were integrated alongside conducting the data analysis in this paper: (1) ArcGIS pro, developed by Esri Inc., which includes noise removal, digital elevation model (DEM) generation, and pavement and building footprint extraction; (2) the Mechanistic-Empirical Pavement Design Guide (AASHTOWare PMED), which was used to assess site specifications such as traffic, weather, subbase, and current pavement conditions in an effort to design the most appropriate pavement for each road section. For the 3D visualization module, CityEngine (a software from Esri) was used to provide the 3D city model. After implementing the research methodology, we drew the following conclusions: (1) using the AASHTOWare PMED method to make decisions about road maintenance and rehabilitation(M&R) actions can significantly speed up the decision-making process, essentially saving time and money and shortening the project’s duration; and (2) if the road conditions are similar, the smart geographical information system (GIS)-based PMS can make consistent decisions about road M&R strategies, i.e., the interference from human factors is less significant.

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