Calibration and Validation of a Dynamic Assignment Model in Emergency Conditions from Real-world Experimentation

AbstractCalibration and validation of dynamic assignment models to simulate urban road transport systems in ordinary conditions are still an open issue. This problem is further emphasized in the case of transport systems analysis in emergency conditions, as there are no standardised methods and there is a lack of experience of real-world applications.The paper presents a DA model and a procedure able to simulate transport supply and transport supply – travel demand interaction of an urban road transport system in emergency conditions. The transport supply models are calibrated and validated through traffic data observed during a real-world evacuation experiment conducted in the town of Melito di Porto Salvo (Italy). The DA model has been applied in order to reproduce the observed real-world evacuation experiment and a set of indicators for testing the performance of a road network in emergency conditions is estimated.We think that the findings reported in the paper represent a contribution in the field of transportation systems analysis in emergency conditions at urban scale. The specified and calibrated DA model and the applied set of indicators can be a useful tool to support the planning and management of road networks and mobility in emergency conditions

Shape Localization and Recognition using a Magnetorheological-fluid Haptic Display

Smart materials such as magnetorheological fluids (MRF) offer an interesting technology for use in haptic displays as changes in the magnetic field are rapid, reversible, and controllable. These interfaces have been evaluated in a number of medical and surgical simulators where they can provide cues regarding the viscoelastic properties of tissues. The objective of the present set of experiments was first to determine whether a shape embedded in the MRF could be precisely localized and second whether 10 shapes rendered in a MRF haptic display could be accurately identified. It was also of interest to determine how the information transfer associated with this type of haptic display compares to that achieved using other haptic channels of communication. The overall performance of participants at identifying the shapes rendered in the MRF was good with a mean score of 73 percent correct and an Information Transfer (IT) of 2.2 bits. Participants could also localize a rigid object in the display accurately. These findings indicate that this technology has potential for use in training manual palpation skills and in exploring haptic shape perception in dynamic environments

Passengers and freight mobility with electric vehicles: A methodology to plan green transport and logistic services near port areas

Abstract The paper describes a research, named GRE.ENE.LOG. (from GREen ENErgy to green LOGistic: from the port of Roccella Jonica to the Locride area), which aims to integrate the production of green-energy inside port areas and its consumption to feed Electric Vehicles (EVs) for transport and logistic services. The system is composed by: (i) a "sea-to-grid" technological component harvesting and producing electrical energy from sea waves; (ii) a "green" logistic services based on the use of EVs. This paper is relative to part (ii). One of the main challenge is to promote the use of green-energy resources for freight and people mobility planning involved in the port area. The main task concerns the location of a parking area/distribution center and the optimal design of mobility services, operated by means of EVs, connecting a port with a closer extended (sub)urban area. The mobility services by EV bikes and cars are oriented to the port users; the freight services are oriented to the extended port area. In this context, the paper presents a methodology for the definition of freight logistics and passenger transport services in order to pursue sustainability goals, and a data analysis in the pilot study of Roccella Jonica port, South of Italy

Stated locational preferences of entrepreneurs in Italy

The objective of the thesis is to study and analyse the stated locational preferences of entrepreneurs in Italy: that is, their mental maps, their characteristics (pattern, shape, etc.), and their explanatory factors. The research was undertaken following the conceptual, theoretical and methodological approach of a long line of research started by Pellenbarg and Meester (1983). The thesis in particular presents and discusses the outcomes of the quantitative and qualitative analyses of the findings from: a questionnaire survey conducted in Italy in which entrepreneurs were asked to rate Italian regions and provinces as hypothetical locations for their firm; a set of verbal semi-structured interviews conducted with key economic actors. The evidence gained from the surveys and from the analyses indicates that the North-South divide emerges as the spatial pattern which most clearly characterises the mental maps of Italian entrepreneurs. The other very important pattern which characterises the entrepreneurs’ mental maps, although less predictable, is the centre-periphery dichotomy. The range of explanatory elements that emerged from the analyses includes both objective and subjective factors, and strictly economic and clearly non-economic factors. For example, the questions of accessibility and centrality, together with the agglomeration economies, turned out to be key location factors for the high attractiveness of the Padana region. At the same time, the lack of these factors contributes to explaining the low attractiveness of Southern Italy, which is also related to the presence and the influence of organised crime

A semi-anaytical model for the analysis of a Permanent Magnet Tubular Linear Generator

In this paper the authors introduce a semi-analytical model for the analysis and the design of a Permanent Magnet (PM) tubular linear generator intended for electrical energy generation from sea waves. The translator of the analyzed machine is constituted by axially magnetized ferrite PMs with alternating polarity and soft-magnetic pole-pieces in between; a two poles, double layer three-phase winding is located in the slots of the stator. The presented model, based on use of the Carter coefficient and of the Fourier transform in the direction of the motion, is able to take into account the end effects due to the finite length of the stator. The presence of slots and teeth is subsequently considered by some post processing calculation carried on the results of the semi-analytical model. Comparison with a Finite Element analysis and with measurements taken on a prototype has been performed to validate the presented model. The model can be easily extended to other translator typologies, e.g. to air core translator with Halbach array of NdFeB PMs

The AMLEV technology applied to low speed urban transportation systems

The American version of Maglev (AMLEV) was developed in the USA since 1992. It is based on the interaction between a system of permanent magnets (PMs) installed on the vehicle, and steel cores positioned along the guideway. By using an analytical model, the inventor demonstrated that the system was able to produce levitating and stabilizing forces, allowing to safely reach a speed up to 150 m/s. In the present paper, the AMLEV technology is firstly simulated by using a FEM model; then its possible application in a low speed urban transportation system is verified. Finally, a comparison in terms of energy consumption and braking energy recovery efficiency is performed

Optimal design of EMALS based on a double-sided tubular linear induction motor

A novel evolutionary algorithm is used for the optimization of the thrust force of the stages of an electromagnetic aircraft launch system, based on a double-sided tubular linear induction motor. A semianalytical model allows for a fast and accurate prediction of all the electromagnetic quantities in the device, including the thrust force, the back electromotive force, the distribution of the induced current density, and the average magnetic flux density in the teeth. Using the semianalytical formulation, the characterization of the machine is greatly facilitated, so allowing a fast evaluation of the cost function and of the design constraint

Energy consumption of electric vehicles: models' estimation using big data (FCD)

Abstract The paper presents a framework to estimate energy consumption of Electric Vehicles (EVs) by combining: (a) the use of models derived from traffic flow theory and from mechanics of locomotion and (b) the great amount of Floating Cara Data (FCD) from available Information and Communications Technology (ICT) devices. Existing energy consumption models may be classified into aggregate vs. disaggregate, according to the level of aggregation of variables related to driver, vehicle, and infrastructure. The proposed models have a hybrid nature: the aggregate component allows to estimating the values of vehicular speed and acceleration on a road link; the disaggregate one allows to estimating the discrete variability of EVs' energy consumption inside a spatial-temporal domain. The energy consumption models are estimated using traffic data extracted from FCD. The proposed framework is structured into four steps: FCD processing, estimation of vehicular speeds and accelerations, estimation of resistance/energy consumption. The framework is applied in a pilot study area, composed by the backward (sub-)urban area of the port of "Porto delle Grazie" of Roccella Jonica (South of Italy). The preliminary results show that the methodology allows relative inexpensive and accurate calculation of EVs' energy consumption and that it can be integrated into Intelligent Transportation System (ITS) applications

Estimation of Travel Demand Models with Limited Information: Floating Car Data for Parameters' Calibration

This paper attempts to integrate data from models, traditional surveys and big data in a situation of limited information. The goal is to increase the capacity of transport planners to analyze, forecast, and plan passenger mobility. (Big) data are a precious source of information and substantial effort is necessary to filter, integrate, and convert big data into travel demand estimates. Moreover, data analytics approaches without demand models are limited because they allow: (a) the analysis of historical and/or real-time transport system configurations, and (b) the forecasting of transport system configurations in ordinary conditions. Without the support of travel demand models, the mere use of (big) data does not allow the forecasting of mobility patterns. The paper attempts to support traditional methods of transport systems engineering with new data sources from ICTs. By combining traditional data and floating car data (FCD), the proposed framework allows the estimation of travel demand models (e.g., trip generation and destination). The proposed method can be applied in a specific case of an area where FCD are available, and other sources of information are not available. The results of an application of the proposed framework in a sub-regional area (Calabria, southern Italy) are presented