Management of Road Infrastructure Safety

Road Infrastructure Safety Management (RISM) refers to a set of procedures that support a road authority in decision making related to the improvement of safety on a road network. Some of these procedures can be applied to existing infrastructure, thus enabling a reactive approach; and other procedures are used in early stages of a project's life-cycle allowing a proactive approach. The objective of this paper is to provide an overview of the most well-known procedures and present a series of recommendations for successful road infrastructure safety management. The work described in the paper was completed by the IRTAD sub-working group on Road Infrastructure Safety Management and presented in detail in the respective Report. The methodology followed on this purpose included the description of the most consolidated RISM procedures, the analysis of the use of RISM procedures worldwide and the identification of possible weaknesses and barriers to their implementation, the provision of good practice examples and the contribution to the scientific assessment of procedures. Specifically, the following RISM procedures were considered: Road Safety Impact Assessment (RIA), Efficiency Assessment Tools (EAT), Road Safety Audit (RSA), Network Operation (NO), Road Infrastructure Safety Performance Indicators (SPI), Network Safety Ranking (NSR), Road Assessment Programs (RAP), Road Safety Inspection (RSI), High Risk Sites (HRS) and In-depth Investigation. Each procedure was described along with tools and data needed for its implementation as well as relevant common practices worldwide. A synthesis summarizing the key information for each procedure was also drafted. Based on a survey on 23 IRTAD member countries from worldwide, the lack of resources or tools is the most commonly stated reason for not applying a RISM procedure. This has been frequently found mainly in European countries. Another common reason is the absence of recommendations/guidelines, especially for SPI, RAP, RSI and RSA. This highlights the importance of the presence of some legislation regulating the application of the procedures. Lack of data was found important mainly for SPI, HRS and EAT. Good practices of road infrastructure safety management have been explored in order to find solutions to the issues highlighted by the survey and provide examples about how these issues have been overcome in some countries. Specifically, issues related to data, legal framework, funding, knowledge, tools and dealing with more RISM procedures were addressed. Finally, nine key messages and six recommendations for better Road Infrastructure Safety Management were developed based on the conclusions made

A Process to Implement an Artificial Neural Network and Association Rules Techniques to Improve Asset Performance and Energy Efficiency

In this paper, we address the problem of asset performance monitoring, with the intention of both detecting any potential reliability problem and predicting any loss of energy consumption e ciency. This is an important concern for many industries and utilities with very intensive capitalization in very long-lasting assets. To overcome this problem, in this paper we propose an approach to combine an Artificial Neural Network (ANN) with Data Mining (DM) tools, specifically with Association Rule (AR) Mining. The combination of these two techniques can now be done using software which can handle large volumes of data (big data), but the process still needs to ensure that the required amount of data will be available during the assets’ life cycle and that its quality is acceptable. The combination of these two techniques in the proposed sequence di ers from previous works found in the literature, giving researchers new options to face the problem. Practical implementation of the proposed approach may lead to novel predictive maintenance models (emerging predictive analytics) that may detect with unprecedented precision any asset’s lack of performance and help manage assets’ O&M accordingly. The approach is illustrated using specific examples where asset performance monitoring is rather complex under normal operational conditions.Ministerio de Economía y Competitividad DPI2015-70842-

A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone