Mario De Luca

Indirect Skid Resistance Measurement for Porous Asphalt Pavement Management

This paper focuses on developing a method for road managers to assess the sideways-force coefficient (SFC) in porous asphalt with low-cost standard tests. SFC can be used as a component in road surface condition surveys and asset management decisions. A standard piece of equipment for determining SFC is the sideways-force coefficient routine investigation machine (SCRIM), which can be truck or trailer mounted. This equipment is often beyond the budget of most small, low-volume road agencies. An empirical model for the indirect estimation of SFC for porous road surfaces was developed as a result of this study. With handheld equipment—the portable skid resistance tester [to derive the British pendulum number (BPN)] and the sand patch method [height in sand (HS) test]—a correlation of these test results can be made, and a reasonable approximation to SFC with the use of the SCRIM method can be attained. BPN, the unit of measurement of the skid tester, is a representation of the microroughness of the wearing surface, and the sand patch method (HS test) results yield the macroroughness of the pavement. The study was conducted over 20-km segments of low-volume roadway in southern Italy. The initial results are promising, with a maximum percentage of error of less than 15.2%. Further study is needed to adapt the model to other road surface conditions.

Aircraft safety analysis using clustering algorithms

In recent years, there have been many cost-benefit studies on aviation safety, which deal mainly with economic issues, omitting some strictly technical aspects. This study compares aircraft accidents in relation to the characteristics of the aircraft, environmental conditions, route, and traffic type. The study was conducted using a database of over 1500 aircraft accidents worldwide, occurring between 1985 and 2010. The data were processed and then aggregated into groups, using cluster analysis based on an algorithm of partition binary ‘Hard c means.’ For each cluster, the ‘cluster representative’ accident was identified as the average of all the different characteristics of the accident. Moreover, a ‘hazard index’ was defined for each cluster (according to annual movements); using this index, it was possible to establish the dangerousness of each ‘cluster’ in terms of aviation accidents. Obtained results allowed the construction of an easy-to-use predictive model for accidents using multivariate analysis.

Procedure for Making Paving Decisions with Cluster and Multicriteria Analysis

For many years, much research has been carried out to assess the affordability of paving a road. Now, increased construction and maintenance costs for traditional asphalt pavement systems have persuaded many civil administrations, regional councils, and agencies to replace pavement with gravel surfaces. Low-volume roads (LVRs), as they are presented in this paper, constitute a significant proportion of the total road network in Italy (around 80%) and in many other countries. Such infrastructures are vital parts of the road network, but their construction can have significant adverse effects on the environment. As a result, these roads must be well planned, well designed, well constructed, and properly maintained to create minimal adverse effects, to be cost-effective in the long term, and to have acceptable maintenance and repair costs. Limited resources often exist for LVRs, and a frequent question is whether to use paved or gravel surfaces. In many cases, the choice depends only on economic considerations, which must take maintenance costs into account. A complete procedure that applies cluster analysis and multicriteria analysis is presented for deciding whether to pave gravel road surfaces on the basis of different geometric, traffic, and environmental layouts.

Calibrating the passenger car equivalent on Italian two line highways: a case study

AbstractThe Level of Service (LOS) of a road infrastructure, a concept introduced for the first time in the Highway Capacity Manual (second edition), is defined as the ‘qualitative measure of traffic conditions and their perception by users’. The Highway Capacity Manual, developed in the U.S., is still the most highly internationally credited reference text in the study of vehicular traffic. The method proposed by the Highway Capacity Manual is based mainly on studies and research compiled in the U.S., so in order to apply this method to other realities (e.g. Italy), research needs to be carried out at a local level. In this study, a series of studies were carried out to verify the transferability of these procedures to two roads classified as ‘two-lane highways’. Two fixed RTMS (Remote Traffic Microwave Sensor) were used to record traffic data for two sections located at 3100 km on the SP30 and at 8900 km on the SP175 from 1 January to 31 December 2010. From the data, it was possible to determine not onl...

Field measurements on runway friction decay related to rubber deposits

Surfaces of airport pavements are subject to contamination that can be very dangerous for the movement of aircraft particularly on the runway. A recurrent problem is represented by the deposits of vulcanized rubber of aircraft tires in the touchdown area during landings and lesser during take-offs. This causes a loss of grip that compromises the safety of aircraft movements in take-off and landing operations. This study deals with the surface characteristics decay phenomenon related to contamination from rubber deposits. The experiment was conducted by correlating the pavement surface characteristics, as detected by Grip Tester, to air traffic before and after de-rubberizing operation and two models were constructed for the assessment of functional capacity of the runway before and after the operations de-rubberizing.

A comparison between prediction power of artificial neural networks and multivariate analysis in road safety management

AbstractThis paper presents a methodology for the management of road safety on two-lane highways. The methodology is based on an experimental investigation carried out on a stretch of road located in southern Italy (the two-lane highway SS106). The study analyses accidents occurring between 2000 and 2005 and the data concerning the accidents that were acquired from police reports. The geometric data were acquired from the official cartography, while the traffic and environmental data were provided by the regional agency for roadway management. The data, organized and stored in a specific designed Geographic Information System (GIS), were processed using a series of statistical procedures, in particular, the results took out the following two models: Model 1 was produced by MultiVariate Analysis (MVA) and the Model 2 was obtained using the Artificial Neural Network (ANN) technique. Comparing the two models, it emerged that Model 2 is better than Model 1 because the total sum of the residual is lower. Howev...

Using artificial neural network and multivariate analysis techniques to evaluate road operating conditions

Regional paved roads are low volume roads with a prevalence of heavy traffic. In the world, these roads concern about 80% of the total road network; however, the traffic that affects these roads is about 20%. Since regional roads are characterized by weak demand, budget for their management/maintenance is very low. This produces considerable difficulties in the choice of strategies for maintenance planning and scheduling. For this reason, the recurring topics of research in this field deal with typical roads issues and aim to develop low cost tools and methods. The study proposes a decision support system to evaluate regional paved roads operating condition in relation to the hydrogeological situation. In particular, the system allows to evaluate in a quick and easy manner, the operating conditions of the road, through low-cost tools (i.e. using low economic resources). This is very useful in the case of LVRs because administrations for these roads have a limited budget. The procedure is developed on a regional paved roads network based on more than 80 roads located in Southern Italy. Data is collected by direct surveys in the field and is integrated with cartography and information available in road agency records. From data analysis, obtained using two different techniques, an easy and quick use procedure is made. In particular, Model 1 is built through multivariate analysis and Model 2 using the artificial neural network (ANN) technique. The results show the validity of the two models in Regional paved roads operating conditions estimation in relation to hydrogeological situations of sites. Both models show good reliability. In particular, the first model (Model 1) is characterized by a high level of significance (p < 0.01) and by a coefficient of determination equal to 0.82. Comparative tests between the second model (Model 2) on which standard tests cannot be performed for obvious reasons, and the first model (Model 1). The results show that the ANN model (model 2), characterized by lower residual, simulates more accurately than the second (Model 1).