The Data Mining applied for the prediction of highway roughness due to overloaded trucks

Currently, the quality of the Indonesian national road network is inadequate due to several constraints, including overcapacity and overloaded trucks. The high deterioration rate of the road infrastructure in developing countries along with major budgetary restrictions and high growth in traffic have led to an emerging need for improving the performance of the highway maintenance system. However, the high number of intervening factors and their complex effects require advanced tools to successfully solve this problem. The high learning capabilities of Data Mining (DM) are a powerful solution to this problem. In the past, these tools have been successfully applied to solve complex and multi-dimensional problems in various scientific fields. Therefore, it is expected that DM can be used to analyze the large amount of data regarding the pavement and traffic, identify the relationship between variables, and provide information regarding the prediction of the data. In this paper, we present a new approach to predict the International Roughness Index (IRI) of pavement based on DM techniques. DM was used to analyze the initial IRI data, including age, Equivalent Single Axle Load (ESAL), crack, potholes, rutting, and long cracks. This model was developed and verified using data from an Integrated Indonesia Road Management System (IIRMS) that was measured with the National Association of Australian State Road Authorities (NAASRA) roughness meter. The results of the proposed approach are compared with the IIRMS analytical model adapted to the IRI, and the advantages of the new approach are highlighted. We show that the novel data-driven model is able to learn (with high accuracy) the complex relationships between the IRI and the contributing factors of overloaded trucks

Earthwork optimization system for sustainable highway construction

In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

Geotechnical engineering for sustainable transportation infrastructure

This paper highlights how transportation geotechnics can interact with transportation infrastructures and how through the planning, design, construction and maintenance can contribute to ensure solutions more safe, reliable and resilient in the future. In this context sustainable concepts are discussed and applied as best practices to preserve natural resources and assuring socio-economic and environment benefits for the society

A review of sustainable approaches in transport infrastructure geotechnics

Transportation geotechnics associated with constructing and maintaining properly functioning transportation infrastructure is a very resource intensive activity. Large amounts of materials and natural resources are required, consuming proportionately large amounts of energy and fuel. Thus, the implementation of the principles of sustainability is important to reduce energy consumption, carbon footprint, greenhouse gas emissions, and to increase material reuse/recycling, for example. This paper focusses on some issues and activities relevant to sustainable earthwork construction aimed at minimising the use of energy and the production of CO2 while improving the in-situ ground to enable its use as a foundation without the consumption of large amounts of primary aggregate as additional foundation layers. The use of recycled materials is discussed, including steel slag and tyre bales, alongside a conceptual framework for evaluating the utility of applications for recycled materials in transportation infrastructure.