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Giuseppe Sollazzo
Department of Engineering, University of Messina, Messina, Italy

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Research article
Published: 12 April 2021 in International Journal of Pavement Engineering
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This paper proposes an ensemble learning model that deploys a Gradient Boosting Decision Tree (GBDT) to predict two relevant functional indices, the International roughness index (IRI) and the rut depth (RD), considering multiple influence factors. To train and validate the proposed models, more than 1600 different records were extracted from Long-Term Pavement Performance database. The most suitable hyper parameters for the GBDT model are determined through a grid search and 5-fold cross-validation. Then, a sensitivity analysis is performed to determine the final input variables among the initial considered factors. Further, the optimized models utilise SHAP (Shapley Additive explanation) to interpret the results and analyse the importance of influencing factors. Finally, a comparison experiment with reference artificial intelligence approaches demonstrates that, the GBDT model can outperform the artificial neural network (ANN) and the random forest regression (RFR) methods in terms of quality of prediction results, reaching a coefficient of determination (R2) equal to 0.9. The proposed model can provide more precise pavement performance values and may be useful for providing accurate reference for pavement maintenance and optimising the available budget for road administrations.

ACS Style

Runhua Guo; Donglei Fu; Giuseppe Sollazzo. An ensemble learning model for asphalt pavement performance prediction based on gradient boosting decision tree. International Journal of Pavement Engineering 2021, 1 -14.

AMA Style

Runhua Guo, Donglei Fu, Giuseppe Sollazzo. An ensemble learning model for asphalt pavement performance prediction based on gradient boosting decision tree. International Journal of Pavement Engineering. 2021; ():1-14.

Chicago/Turabian Style

Runhua Guo; Donglei Fu; Giuseppe Sollazzo. 2021. "An ensemble learning model for asphalt pavement performance prediction based on gradient boosting decision tree." International Journal of Pavement Engineering , no. : 1-14.

Journal article
Published: 09 December 2020 in Sustainability
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Road construction and maintenance have a great impact on the environment, owing to the huge volumes of resources involved. Consequently, current production procedures and technologies must be properly investigated, for identifying and quantifying the life cycle environmental impacts produced. In this paper, primary data, i.e., site-specific data directly collected or measured on a reference plant, are analyzed for calculating the impact of the production of a hot mix asphalt. The analysis is performed in a from “cradle to gate” approach to estimate the environmental burdens of the production process in an average plant, representative of the existing technology in Italy and Southern Europe. The research outcomes are useful to increase reliability in quantification of asphalt production impacts and the contribution of each component. The results represent a reference basis for producers, designers, and contractors in the decisional phases, identifying the most critical aspects in the current practice and the possible improvements for reducing impacts of road industries. In this regard, efficient energy technologies for reducing the production temperature (such as warm mix asphalt) and burned fuels are proven to assure relevant improvements in the environmental performance.

ACS Style

Giuseppe Sollazzo; Sonia Longo; Maurizio Cellura; Clara Celauro. Impact Analysis Using Life Cycle Assessment of Asphalt Production from Primary Data. Sustainability 2020, 12, 10171 .

AMA Style

Giuseppe Sollazzo, Sonia Longo, Maurizio Cellura, Clara Celauro. Impact Analysis Using Life Cycle Assessment of Asphalt Production from Primary Data. Sustainability. 2020; 12 (24):10171.

Chicago/Turabian Style

Giuseppe Sollazzo; Sonia Longo; Maurizio Cellura; Clara Celauro. 2020. "Impact Analysis Using Life Cycle Assessment of Asphalt Production from Primary Data." Sustainability 12, no. 24: 10171.

Corrigendum
Published: 11 September 2020 in Journal of Advanced Transportation
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In the article titled “Automatic Segmentation and Enhancement of Pavement Cracks Based on 3D Pavement Images” [1], the author Dr. Giuseppe Sollazzo was omitted from the authorship list in error. The authorship list is, therefore, being updated to add this author due to his contribution to the ideas and analysis of the study. The final authors’ list is Baoxian Li, Kelvin C. P. Wang, Allen Zhang, Yue Fei, and Giuseppe Sollazzo. Copyright © 2020 Baoxian Li et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

ACS Style

Baoxian Li; Kelvin C. P. Wang; Allen Zhang; Yue Fei; Giuseppe Sollazzo. Corrigendum to “Automatic Segmentation and Enhancement of Pavement Cracks Based on 3D Pavement Images”. Journal of Advanced Transportation 2020, 2020, 1 -1.

AMA Style

Baoxian Li, Kelvin C. P. Wang, Allen Zhang, Yue Fei, Giuseppe Sollazzo. Corrigendum to “Automatic Segmentation and Enhancement of Pavement Cracks Based on 3D Pavement Images”. Journal of Advanced Transportation. 2020; 2020 ():1-1.

Chicago/Turabian Style

Baoxian Li; Kelvin C. P. Wang; Allen Zhang; Yue Fei; Giuseppe Sollazzo. 2020. "Corrigendum to “Automatic Segmentation and Enhancement of Pavement Cracks Based on 3D Pavement Images”." Journal of Advanced Transportation 2020, no. : 1-1.

Journal article
Published: 20 April 2020 in Energies
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The development of the road construction sector determines the consequences on consumption of non-renewable resources, energy expenditure and environmental pollution. Recent sustainability issues have highlighted the importance of efficient design and quality-oriented techniques in this sector, due to the huge amount of materials involved in construction and maintenance activities. Thus, it is necessary to properly quantify the environmental impacts of asphalt mixtures used for pavement construction, considering the whole life cycle of the products. Life cycle assessment (LCA) represents the most appropriate methodological framework for assessing the environmental burdens of a product, from raw material acquisition to final disposal. A common problem for LCA is the lack of primary data useful to calculate the product eco-profile, for a specific production process. In this context, there is generally limited reliable and accurate data regarding the asphalt plant production phase, which represents the most critical phase. Consequently, the aim of this paper is to perform an environmental/energy audit of an asphalt plant and, further, to collect and analyze primary data useful for the definition of the eco-profile of 1 metric ton of hot mix asphalt (HMA), following a “gate to gate” approach, including transport. The asphalt production is examined in a Sicilian batch-mix plant, representing one of the most commonly used for asphalt production in the Italian context. The results are of interest for asphalt mixture producers, contractors, transportation agencies and researchers seeking to quantify asphalt pavement environmental impacts in Italy, based on context-related foreground data.

ACS Style

Vincenzo Franzitta; Sonia Longo; Giuseppe Sollazzo; Maurizio Cellura; Clara Celauro. Primary Data Collection and Environmental/Energy Audit of Hot Mix Asphalt Production. Energies 2020, 13, 2045 .

AMA Style

Vincenzo Franzitta, Sonia Longo, Giuseppe Sollazzo, Maurizio Cellura, Clara Celauro. Primary Data Collection and Environmental/Energy Audit of Hot Mix Asphalt Production. Energies. 2020; 13 (8):2045.

Chicago/Turabian Style

Vincenzo Franzitta; Sonia Longo; Giuseppe Sollazzo; Maurizio Cellura; Clara Celauro. 2020. "Primary Data Collection and Environmental/Energy Audit of Hot Mix Asphalt Production." Energies 13, no. 8: 2045.

Journal article
Published: 26 September 2019 in The Baltic Journal of Road and Bridge Engineering
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The existing international standards suggest a methodology to assign a specific functional class to a road, by the values of some features, both geometrical and use-related. Sometimes, these characteristics are in contrast with each other and direct the analyst towards conflicting classes for a road or, worse, one or more of these features vary heterogeneously along the road. In these conditions, the analyst assigns the class that, by his capability and experience, he retains the most appropriate, in a very subjective way. On the contrary, the definition of an automatic procedure assuring an objective identification of the most appropriate functional class for each road would be desirable. Such a solution would be useful, especially when the road belongs to the existing infrastructure network or when it was not realised by out of date standards. The proposed procedure regards the definition of a classification model based on Pattern Recognition techniques, considering 13 input variables that, depending on their assumed value, direct the analyst towards one of the four functional classes defined by the Italian standards. In this way, it is possible to classify a road even when its characteristics are heterogeneous and conflicting. Moreover, the authors analysed the model limitations, in terms of errors and dataset size, considering observation and variable numbers. This approach, representing a beneficial decision support tool for the decision-maker, is exploitable for both planned and existing roads and becomes particularly advantageous for road agencies aiming to optimally allocate their limited funds for specific interventions assuring the achievement of a fixed functional class.

ACS Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. Road Functional Classification Using Pattern Recognition Techniques. The Baltic Journal of Road and Bridge Engineering 2019, 14, 360 -383.

AMA Style

Gaetano Bosurgi, Orazio Pellegrino, Giuseppe Sollazzo. Road Functional Classification Using Pattern Recognition Techniques. The Baltic Journal of Road and Bridge Engineering. 2019; 14 (3):360-383.

Chicago/Turabian Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. 2019. "Road Functional Classification Using Pattern Recognition Techniques." The Baltic Journal of Road and Bridge Engineering 14, no. 3: 360-383.

Journal article
Published: 28 March 2019 in The Baltic Journal of Road and Bridge Engineering
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Artificial Neural Networks represent useful tools for several engineering issues. Although they were adopted in several pavement-engineering problems for performance evaluation, their application on pavement structural performance evaluation appears to be remarkable. It is conceivable that defining a proper Artificial Neural Network for estimating structural performance in asphalt pavements from measurements performed through quick and economic surveys produces significant savings for road agencies and improves maintenance planning. However, the architecture of such an Artificial Neural Network must be optimised, to improve the final accuracy and provide a reliable technique for enriching decision-making tools. In this paper, the influence on the final quality of different features conditioning the network architecture has been examined, for maximising the resulting quality and, consequently, the final benefits of the methodology. In particular, input factor quality (structural, traffic, climatic), “homogeneity” of training data records and the actual net topology have been investigated. Finally, these results further prove the approach efficiency, for improving Pavement Management Systems and reducing deflection survey frequency, with remarkable savings for road agencies.

ACS Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. Optimizing Artificial Neural Networks For The Evaluation Of Asphalt Pavement Structural Performance. The Baltic Journal of Road and Bridge Engineering 2019, 14, 58 -79.

AMA Style

Gaetano Bosurgi, Orazio Pellegrino, Giuseppe Sollazzo. Optimizing Artificial Neural Networks For The Evaluation Of Asphalt Pavement Structural Performance. The Baltic Journal of Road and Bridge Engineering. 2019; 14 (1):58-79.

Chicago/Turabian Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. 2019. "Optimizing Artificial Neural Networks For The Evaluation Of Asphalt Pavement Structural Performance." The Baltic Journal of Road and Bridge Engineering 14, no. 1: 58-79.

Journal article
Published: 12 March 2019 in Periodica Polytechnica Civil Engineering
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The BIM (Building Information Modeling) approach potential in the civil engineering field opened novel scenarios in the design idea concept, from planning to executive and constructive phases. The related advantages are numerous and not only limited to a real-time interaction among the involved subjects, that can actually operate in an optimized 3D shared environment. Owing to the sharing information philosophy and to the features of various "smart objects" combined in the project, this innovation reduces potential errors and increases the effectiveness of the design solution in terms of both functionality and cost. Despite these advantages, the highway alignment design problem remains very complicated and not easy to solve without appropriate supporting tools. In recent years, several efforts have been spent in defining highway optimization procedures for helping designers in the selection of an optimal solution in compliance with numerous different constraints. Introducing these procedures in a BIM environment may represent a crucial step in the improvement of the highway design procedures, exploiting the full representation and modelling potential of the approach. In this paper, the authors present the advantages of a 3D highway alignment optimization algorithm, based on the Particle Swarm Optimization method, and its possible implementation in a BIM platform. A proper I-BIM environment can exploit the potential of the alignment optimization algorithms, simplifying the analysis of the different solutions, the final representation and the eventual manual modifications.

ACS Style

Nicola Bongiorno; Gaetano Bosurgi; Federico Carbone; Orazio Pellegrino; Giuseppe Sollazzo. Potentialities of a Highway Alignment Optimization Method in an I-BIM Environment. Periodica Polytechnica Civil Engineering 2019, 1 .

AMA Style

Nicola Bongiorno, Gaetano Bosurgi, Federico Carbone, Orazio Pellegrino, Giuseppe Sollazzo. Potentialities of a Highway Alignment Optimization Method in an I-BIM Environment. Periodica Polytechnica Civil Engineering. 2019; ():1.

Chicago/Turabian Style

Nicola Bongiorno; Gaetano Bosurgi; Federico Carbone; Orazio Pellegrino; Giuseppe Sollazzo. 2019. "Potentialities of a Highway Alignment Optimization Method in an I-BIM Environment." Periodica Polytechnica Civil Engineering , no. : 1.

Journal article
Published: 10 July 2018 in Transport
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This paper analyses the driver’ visual behaviour in the different conditions of ‘isolated vehicle’ and ‘disturbed vehicle’. If the meaning of the former is clear, the latter condition considers the influence on the driving behaviour of various objects that could be encountered along the road. These can be classified in static (signage, stationary vehicles at the roadside, etc.) and dynamic objects (cars, motorcycles, bicycles). The aim of this paper is to propose a proper analysis regarding the driver’s visual behaviour. In particular, the authors examined the quality of the visually informa-tion acquired from the entire road environment, useful for detecting any critical safety condition. In order to guaran-tee a deep examination of the various possible behaviours, the authors combined the several test outcomes with other variables related to the road geometry and with the dynamic variables involved while driving. The results of this study are very interesting. As expected, they obviously confirmed better performances for the ‘isolated vehicle’ in a rural two-lane road with different traffic flows. Moreover, analysing the various scenarios in the disturbed condition, the proposed indices allow the authors to quantitatively describe the different influence on the visual field and effects on the visual behaviour, favouring critical analysis of the road characteristics. Potential applications of these results may contribute to improve the choice of the best maintenance strategies for a road, to select the optimal signage location, to define forecasting models for the driving behaviour and to develop useful instruments for intelligent transportation systems.

ACS Style

Nicola Bongiorno; Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. ANALYSIS OF DIFFERENT VISUAL STRATEGIES OF ‘ISOLATED VEHICLE’ AND ‘DISTURBED VEHICLE’. Transport 2018, 33, 853 -860.

AMA Style

Nicola Bongiorno, Gaetano Bosurgi, Orazio Pellegrino, Giuseppe Sollazzo. ANALYSIS OF DIFFERENT VISUAL STRATEGIES OF ‘ISOLATED VEHICLE’ AND ‘DISTURBED VEHICLE’. Transport. 2018; 33 (3):853-860.

Chicago/Turabian Style

Nicola Bongiorno; Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. 2018. "ANALYSIS OF DIFFERENT VISUAL STRATEGIES OF ‘ISOLATED VEHICLE’ AND ‘DISTURBED VEHICLE’." Transport 33, no. 3: 853-860.

Journal article
Published: 09 February 2017 in Periodica Polytechnica Transportation Engineering
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In the civil engineering field, there are usually unexpected troubles that can cause delays during execution. This situation involves numerous variables (resource number, execution time, costs, working area availability, etc.), mutually dependent, that complicate the definition of the problem analytical model and the related resolution. Consequently, the decision-maker may avoid rational methods to define the activities that could be conveniently modified, relying only on his personal experience or experts’ advices. In order to improve this kind of decision from an objective point of view, the authors analysed the operation correction using a data mining technique, called Fuzzy Clustering. This allows the analysts to represent complex real scenarios and classify the various activities according to their influence on the reduction of the total execution time. The proposed procedure provides positive results that are also in compliance with significant operational constraints, such as the control of costs and areas needed by the workers to perform the tasks. Finally, it is possible to increase the input variable number preserving the algorithm simplicity and avoiding lacks of accuracy in the final numerical outcomes.

ACS Style

Gaetano Bosurgi; Federico Carbone; Orazio Pellegrino; Giuseppe Sollazzo. Time Reduction for Completion of a Civil Engineering Construction Using Fuzzy Clustering Techniques. Periodica Polytechnica Transportation Engineering 2017, 45, 25 -34.

AMA Style

Gaetano Bosurgi, Federico Carbone, Orazio Pellegrino, Giuseppe Sollazzo. Time Reduction for Completion of a Civil Engineering Construction Using Fuzzy Clustering Techniques. Periodica Polytechnica Transportation Engineering. 2017; 45 (1):25-34.

Chicago/Turabian Style

Gaetano Bosurgi; Federico Carbone; Orazio Pellegrino; Giuseppe Sollazzo. 2017. "Time Reduction for Completion of a Civil Engineering Construction Using Fuzzy Clustering Techniques." Periodica Polytechnica Transportation Engineering 45, no. 1: 25-34.

Journal article
Published: 01 January 2017 in Procedia Engineering
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ACS Style

Nicola Bongiorno; Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. How is the Driver's Workload Influenced by the Road Environment? Procedia Engineering 2017, 187, 5 -13.

AMA Style

Nicola Bongiorno, Gaetano Bosurgi, Orazio Pellegrino, Giuseppe Sollazzo. How is the Driver's Workload Influenced by the Road Environment? Procedia Engineering. 2017; 187 ():5-13.

Chicago/Turabian Style

Nicola Bongiorno; Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. 2017. "How is the Driver's Workload Influenced by the Road Environment?" Procedia Engineering 187, no. : 5-13.

Journal article
Published: 19 December 2016 in Periodica Polytechnica Civil Engineering
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A civil engineering work can be performed by organizing theavailable resources (manpower, equipment and materials) inmany different ways. Each different configuration results in arealization time and a cost that a building company has to bear.To produce reliable duration forecasts and money savings, itis essential to take into account all the uncertainties involvedin the project operations. Generally, since it is impractical toprocess numerous uncertain variables - also undefined froma statistical point of view -, traditional probabilistic methodsinvolve application difficulties for complex environmentssuch as construction sites. To properly handle this issue, theauthors propose in this paper the application of the AffineArithmetic technique. This method treats the variables as intervalsand returns reliable results, even when the variables aremutually dependent. The numerical example presented in thepaper proves the efficiency of the procedure, even if some analyticalcomplications are included in the analysis (dependencybetween variables, non-linear functions, etc.). Comparisonswith Interval Analysis and traditional procedures are also provided.Adopting Affine Arithmetic, the results are reported interms of intervals, avoiding the definition of unrealistic deterministicvalues that can strongly affect the operation organization.Furthermore, without increasing the problem complexity,the model admits continuous modifications (interval amplitudes,new variable dependencies, etc.) to correct and optimizethe durations.

ACS Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. Project Duration Evaluated Using Affine Arithmetic. Periodica Polytechnica Civil Engineering 2016, 61, 412 -420.

AMA Style

Gaetano Bosurgi, Orazio Pellegrino, Giuseppe Sollazzo. Project Duration Evaluated Using Affine Arithmetic. Periodica Polytechnica Civil Engineering. 2016; 61 (3):412-420.

Chicago/Turabian Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. 2016. "Project Duration Evaluated Using Affine Arithmetic." Periodica Polytechnica Civil Engineering 61, no. 3: 412-420.

Journal article
Published: 01 January 2016 in Journal of Computing in Civil Engineering
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ACS Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design. Journal of Computing in Civil Engineering 2016, 30, 04014114 .

AMA Style

Gaetano Bosurgi, Orazio Pellegrino, Giuseppe Sollazzo. Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design. Journal of Computing in Civil Engineering. 2016; 30 (1):04014114.

Chicago/Turabian Style

Gaetano Bosurgi; Orazio Pellegrino; Giuseppe Sollazzo. 2016. "Using Genetic Algorithms for Optimizing the PPC in the Highway Horizontal Alignment Design." Journal of Computing in Civil Engineering 30, no. 1: 04014114.