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

Demand and routing models for urban goods movement simulation

This paper presents a macro-architecture for simulating goods movements in an urban area. Urban goods supply is analysed when the retailer is the decision-maker and chooses to supply his/her shop. Two components are considered: demand in terms of goods supply and vehicle routing with constraints to simulate goods movements. To analyse demand we consider a multi-step model, while to analyse goods movements a Vehicle Routing Problem with Time Windows (VRPTW) is formalized. We examine the distribution process for a VRPTW in which the optimum paths between all the customers are combined to determine the best vehicle trip chain. As regard optimum path search, a multipath approach is proposed that entails the generation of more than one path between two delivery points. Some procedures (traffic assignment, real time system measurement, reverse assignment) to estimate system performance are also proposed. Finally, heuristics to solve the proposed problem are reported and their results are compared with those exact

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

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

Residential Location, Mobility, and Travel Time: A Pilot Study in a Small-Size Italian Metropolitan Area

This research concerns the topic of Land Use and Transport Interaction (LUTI) models. In particular, the patterns between residential households' location and mobility choices are analyzed and simulated. The attributes that influence household residential location choices belong to four categories: socioeconomic and mobility attributes of households and/or of their components; land use; real-estate market; transport system. The paper presents the results of a pilot study on households' location and mobility patterns in the metropolitan area of Reggio Calabria (Southern Italy). The pilot study is divided into two stages. In the first stage, a survey allowed to collect information and identify existing patterns about residential and mobility choices of a sample of households. In the second stage, a residential location model is proposed and some preliminary calibrations are presented in a prototypal way. The pilot study could be extended and improved in terms of spatial extension and sample dimension in order to allow a complete specification-calibration-validation process of the model. The model development can support the land use-transport planning process in the Metropolitan City of Reggio Calabria

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

From green-energy to green-logistics: a pilot study in an Italian port area

Abstract An ongoing two-year research is performing with the general objective to assess the feasibility of a system integrating the production of green-energy and its consumption inside and close to port areas for mobility services. The system is composed by two elements: (a) a "sea-to-grid" technological component harvesting and producing electrical energy from sea waves; and (b) a "green" logistic service based on the use of Fully Electric Vehicles (FEVs). A pilot study will be conducted near an Italian port area supporting passengers and freight mobility between a port and a backward (sub)-urban area. The proposed system is within the environmental goals set by the EU (Europe 2020 Strategy) and the Italian Government (National Energy Masterplan). Indeed, the energy-producing technology reduces dependence from traditional energy sources (coal, gas, oil) and consequently reduces their negative effects (greenhouse gases, air pollution, etc.). Considering that the energy is produced by sea waves, the system transfers the entire amount of produced (green) energy to the electric vehicles. The system will be experimented in a medium size urbanized area and the energy will be produced in a small size port

Transport System Models and Big Data: Zoning and Graph Building with Traditional Surveys, FCD and GIS

The paper deals with the integration of data provided from traditional transport surveys (small data) with big data, provided from Information and Communication Technology (ICT), in building Transport System Models (TSMs). Big data are used to observe historical mobility patterns and transport facilities and services, but they are not able to assess ex-ante effects of planned interventions and policies. To overcome these limitations, TSMs can be specified, calibrated and validated with small data, but they are expensive to obtain. The paper proposes a procedure to increase the benefits of TSMs’ building in forecasting capabilities, on one side; and limiting the costs connected to traditional surveys thanks to the availability of big data, on the other side. Small data (e.g., census data) are enriched with Floating Car Data (FCD). At the current stage, the procedure focuses on two specific elements of TSMs: zoning and graph building. These processes are both executed considering the estimated values of an intensity function of FCDs, consistently with traditional methods based on small data. The data-fusion of small and big data, operated with a Geographic Information System (GIS) tool, in a real extra-urban context is presented in order to validate the proposed procedure. Document type: Articl

DALLA GREEN-ENERGY ALLA GREEN-LOGISTIC: UNA METODOLOGIA PER LA PROGETTAZIONE DEI SERVIZI DI TRASPORTO SOSTENIBILI CON VEICOLI ELETTRICI

The paper outlines the main actions of a research project concerning: (a) the energy production from sea waves; (b) the design of transport services for passenger and freight mobility with electric vehicles. The idea is to transfer the energy produced from sea waves to electric vehicles for passenger and freight services near port area The paper, in particular, presents a methodology related to part (b) of the research project. The objective of the methodology is to support the decision-making process regarding the optimization of transport services for people and freight in an effort to minimise renewable energy resources. Transport system models are the core of the methodology, adopted to design transport services operated with electric vehicles. The methodology and the transport system models are validated in a practical scenario, represented by the touristic port “Porto delle Grazie”, located in the Città Metropolitana of Reggio Calabria, south of Italy. Clean energy is produced from maritime waves. Transport services are designed to fulfil people mobility requirements while optimising the use of energy resources (green transport services). The research was developed within the GRE.ENE.LOG. project, financed by Calabria Region (Italy)

International Society of Sports Nutrition Position Stand: Probiotics.

Position statement: The International Society of Sports Nutrition (ISSN) provides an objective and critical review of the mechanisms and use of probiotic supplementation to optimize the health, performance, and recovery of athletes. Based on the current available literature, the conclusions of the ISSN are as follows: 1)Probiotics are live microorganisms that, when administered in adequate amounts, confer a health benefit on the host (FAO/WHO).2)Probiotic administration has been linked to a multitude of health benefits, with gut and immune health being the most researched applications.3)Despite the existence of shared, core mechanisms for probiotic function, health benefits of probiotics are strain- and dose-dependent.4)Athletes have varying gut microbiota compositions that appear to reflect the activity level of the host in comparison to sedentary people, with the differences linked primarily to the volume of exercise and amount of protein consumption. Whether differences in gut microbiota composition affect probiotic efficacy is unknown.5)The main function of the gut is to digest food and absorb nutrients. In athletic populations, certain probiotics strains can increase absorption of key nutrients such as amino acids from protein, and affect the pharmacology and physiological properties of multiple food components.6)Immune depression in athletes worsens with excessive training load, psychological stress, disturbed sleep, and environmental extremes, all of which can contribute to an increased risk of respiratory tract infections. In certain situations, including exposure to crowds, foreign travel and poor hygiene at home, and training or competition venues, athletes' exposure to pathogens may be elevated leading to increased rates of infections. Approximately 70% of the immune system is located in the gut and probiotic supplementation has been shown to promote a healthy immune response. In an athletic population, specific probiotic strains can reduce the number of episodes, severity and duration of upper respiratory tract infections.7)Intense, prolonged exercise, especially in the heat, has been shown to increase gut permeability which potentially can result in systemic toxemia. Specific probiotic strains can improve the integrity of the gut-barrier function in athletes.8)Administration of selected anti-inflammatory probiotic strains have been linked to improved recovery from muscle-damaging exercise.9)The minimal effective dose and method of administration (potency per serving, single vs. split dose, delivery form) of a specific probiotic strain depends on validation studies for this particular strain. Products that contain probiotics must include the genus, species, and strain of each live microorganism on its label as well as the total estimated quantity of each probiotic strain at the end of the product's shelf life, as measured by colony forming units (CFU) or live cells.10)Preclinical and early human research has shown potential probiotic benefits relevant to an athletic population that include improved body composition and lean body mass, normalizing age-related declines in testosterone levels, reductions in cortisol levels indicating improved responses to a physical or mental stressor, reduction of exercise-induced lactate, and increased neurotransmitter synthesis, cognition and mood. However, these potential benefits require validation in more rigorous human studies and in an athletic population