Realization of the penetration rate for autonomous vehicles in multi-vehicle assignment models

Growing development in technologies that can lead to fully automated driving is at pace. This can result in an enormous change in traffic operations and network properties. However, there are uncertainties about the full deployment time of these autonomous vehicles on road networks. The transition period from vehicles with drivers to driverless will result in a mutual environment with an interaction between traditional (that is, manual) vehicles, automated vehicles and infrastructure. In this context, this research attempts to focus on the various factors of land use, user demographics and road network affecting the percentage of autonomous vehicles into the multi-vehicle assignment models and their subsequent impacts on the traffic network properties. This research aims to use a realistic approach to evaluate the percentage of autonomous vehicles to be injected into the traffic models via an indicator matrix and seven decision indices. A macroscopic traffic model is formulated for mixed traffic flow to which demand is assigned following a stochastic user equilibrium approach using the Frank Wolfe algorithm. The formulated model is applied to a real-world city network for a small part of the Italian city of Genoa. Results showed an effective improvement in traffic network properties with increment in capacities and flow speeds against the saturation grade for the given network

Investigating the introduction of e-navigation and S-100 into bridge related operations: the impact over seafarers

The present work is focused on analyzing how e-navigation will affect the daily work of seafarers involved in bridge-related operations. Within e-navigation, the International Hydrographic Organization (IHO) is currently working in the development of the new standard (S-100) whose role is to guarantee a homogeneous management of the maritime domain data. S-100 is called to act as the Common Maritime Data Structure (CMDS), it represents the technical framework required to guarantee a wider and better use of maritime data. The mission of the standard is to create a common foundation that can be used for multiple purposes; meteorologists, physicists, and whoever is interested in developing maritime related products will refer to the same standard. Not having a homogeneous type of data processed with standardized procedures will allow a better combination and processing of maritime data. Considering the perspective of Hydrographic Offices, the objective of the present document is to analyze the impact which e-navigation will have over seafarers. The study is focused on the evaluation of the risks connected to S-100-based products and on the analysis of specific bridge operations. Considering that e-navigation products are still at their design phase, being aware of the consequences for the final users is essential to make S-100-based products more customer oriented and to allow seafarers who are involved in bridge operations to get familiar with this new technology

A Modal Choice Model for Evaluating the Impact of Increasing Automation in Container Terminals

The aim of this paper is to define a model for the modal choice between road and rail transport taking into account the increase of rail attractiveness resulting from the increasing of the number of container terminals equipped with automated handling systems. The considered automated handling system is the automated multilevel handling system developed within the RCMS EU project, that is, a multistory storage building, equipped with electric AGVs, remote controlled elevators and remote controlled ceiling cranes. This automated system makes possible to access to a specific container without the necessity of reshuffling and to load/unload containers to/from trucks and trains directly under the storage structure, allowing a significant reduction of the loading/unloading time. In order to define the modal choice model, the systematic utility and the perceived utility are provided and the flows of freight delivered via rail or via road are determined with a binomial Logit model. Moreover, the threshold distance between seaport and inland terminals beyond which automation has a significant impact on modal split is evaluated. As a case study, a European port hinterland network is considered and some scenarios are analyzed, assuming that an increasing number of terminals introduces automation. The paper shows that the introduction of automation in container terminals has significant consequences on modal split. In particular, as the number of automated terminals increases, the rail mode becomes more competitive and the threshold distance between seaport and inland terminals, at which the modal split is equally distributed between road and rail modes, significantly decreases

Traffic management system for smart road networks reserved for self-driving cars

A model of a smart road network consisting of unsignalised intersections and smart roads connecting them is considered in this work with the aim of presenting a traffic management system for self-driving cars (or, more generally, autonomous vehicles) which travel the network. The proposed system repeatedly solves a set of mathematical programming problems (each of them relative to a single intersection or to a single road stretch of the network) within a decentralised control scheme in which each local intersection controller and each local road controller communicates with the fully autonomous vehicles in order to receive travel data from vehicles and to provide speed profiles to them once determined the optimal solution of the problem. In order to reduce the computational effort required to provide the optimal solution, a discrete-time approach is adopted so that, in each time interval, a limited number of vehicles are taken into consideration; in this way, solutions can be determined in a very short time thus making the proposed model compatible with a practical application to real traffic systems. The proposed model is general enough, and can be adapted to different scenarios of smart road networks reserved for self-driving cars

On analyzing the vulnerabilities of a railway network with Petri nets

Petri nets are used in this paper to estimate the indirect consequences of accidents in a railway network, which belongs to the class of the so-called transportation Critical Infrastructures (CIs), that is, those assets consisting of systems, resources and/or processes whose total or partial destruction, or even temporarily unavailability, has the effect of significantly weakening the functioning of the system. In the proposed methodology, a timed Petri ne<t represents the railway network and the trains travelling over the rail lines; such a net also includes some places and some stochastically-timed transitions that are used to model the occurrence of unexpected events (accidents, disruptions, and so on) that make some resources of the network (tracks, blocks, crossovers, overhead line, electric power supply, etc.) temporarily unavailable. The overall Petri net is a live and bounded Generalized Stochastic Petri Net (GSPN) that can be analyzed by exploiting the steady-state probabilities of a continuous-time Markov chain (CTMC) that can be derived from the reachability graph of the GSPN. The final target of such an analysis is to determine and rank the levels of criticality of transportation facilities and assess the vulnerability of the whole railway network

Numerical and experimental verification of an inverse-direct approach for load and strain monitoring in aeronautical structures

n/

High-sensitivity C-reactive protein in HIV care: Tuberculosis diagnosis and short-term mortality in a cohort of Kenyan HIV patients in the DREAM programme.

Objective: Tuberculosis (TB) is the leading cause of death in HIV-positive people. In Kenya, 140 000 new TB cases occurred in 2019, and 13 000 HIV-positive patients died due to TB. The objective of this study was to investigate the role of high-sensitivity C-reactive protein (HS-CRP) in TB diagnosis and the prediction of mortality in HIV-positive patients. Methods: The IDEA-TB Study enrolled HIV-positive adult patients attending three DREAM centres in Kenya who were suspected of having TB. A lateral flow urine lipoarabinomannan assay (LF-LAM), serum HS-CRP, and GeneXpert MTB/RIF assay (Xpert MTB/RIF) were performed. Six-month survival was evaluated. Results: A total of 574 patients were enrolled. The median (interquartile range) age, body mass index, and CD4 count were 45 years (37–54 years), 20.5 kg/m2 (18.5–23.69 kg/m2), and 477 cells/mL (290–700 cells/mL), respectively. TB was confirmed in 87 (15.2%) patients. Concordance between the Xpert MTB/RIF and LF-LAM tests was 87.1%. HS-CRP was higher in TB patients (35.39 mg/l vs 9.21 mg/l). Malnutrition and elevated HS-CRP were associated with TB: odds ratio (OR) 2.5 (95% confidence interval (CI) 1.14–5.72) and OR 6.6 (95% CI 3.87–11.52), respectively. Nine (1.6%) patients died during follow-up. No single factor was associated with mortality. Only the combination of malnutrition and elevated HS-CRP was highly predictive of death (odds ratio (OR) 9.8, 95% CI 1.88–50.95); the association was stronger in TB patients (33.3% vs 1.0%; OR 47.6, 95% CI 7.03–322.23). Conclusion: TB diagnosis in HIV-positive patients remains challenging. HS-CRP could play a role in predicting early mortality in symptomatic patients