Improvement of The Driver Simulator Control and Comparison Between Driver-Road-Vehicle Interaction in Real and Simulated Environment

The present doctoral thesis discusses the ways to improve the performance of driving simulator, provide objective measures for the road safety evaluation methodology based on driver’s behavior and response and investigates the drivers' adaptation to the driving assistant systems. The activities are divided into two macro areas; the driving simulation studies and on-road experiments. During the driving simulation experimentation, the classical motion cueing algorithm with logarithmic scale was implemented in the 2DOF motion cueing simulator and the motion cues were found desirable by the participants. In addition, it found out that motion stimuli could change the behaviour of the drivers in terms of depth/distance perception. During the on-road experimentations, The driver gaze behaviour was investigated to find the objective measures on the visibility of the road signs and reaction time of the drivers. The sensor infusion and the vehicle monitoring instruments were found useful for an objective assessment of the pavement condition and the drivers’ performance. In the last chapter of the thesis, the safety assessment during the use of level 1 automated driving “ACC” is discussed with the simulator and on-road experiment. The drivers’ visual behaviour was investigated in both studies with innovative classification method to find the epochs of the distraction of the drivers. The behavioural adaptation to ACC showed that drivers may divert their attention away from the driving task to engage in secondary, non-driving-related tasks.

Sensitivity of the Top quark mass measurement with the CMS experiment at LHC using t-tbar multijet simulated events

This thesis comes after a strong contribution on the realization of the CMS computing system, which can be seen as a relevant part of the experiment itself. A physics analysis completes the road from Monte Carlo production and analysis tools realization to the final physics study which is the actual goal of the experiment. The topic of physics work of this thesis is the study of tt events fully hadronic decay in the CMS experiment. A multi-jet trigger has been provided to fix a reasonable starting point, reducing the multi-jet sample to the nominal trigger rate. An offline selection has been provided to reduce the S/B ratio. The b-tag is applied to provide a further S/B improvement. The selection is applied to the background sample and to the samples generated at different top quark masses. The top quark mass candidate is reconstructed for all those samples using a kinematic fitter. The resulting distributions are used to build p.d.f.’s, interpolating them with a continuous arbitrary curve. These curves are used to perform the top mass measurement through a likelihood comparison

Criteri di valutazione medico-legale della narcolessia

Impairment due to narcolepsy strongly limits job performance, but there are no standard criteria to assess disability in people with narcolepsy and a scale of disease severity is still lacking. We explored: 1. the interobserver reliability among Italian Medical Commissions making disability and handicap benefit decisions for people with narcolepsy, searching for correlations between the recognized disability degree and patients’ features; 2. the willingness to report patients to the driving licence authority; 3. possible sources of variance in judgement. Fifteen narcoleptic patients were examined by four Medical Commissions in simulated sessions. Raw agreement and interobserver reliability among Commissions were calculated for disability and handicap benefit decisions and for driving licence decisions. Levels of judgement differed on percentage of disability (p<0.001), severity of handicap (p=0.0007) and the need to inform the driving licence authority (p=0.032). Interobserver reliability ranged from Kappa = - 0.10 to Kappa = 0.35 for disability benefit decision and from Kappa = - 0.26 to Kappa = 0.36 for handicap benefit decision. The raw agreement on driving licence decision ranged from 73% to 100% (Kappa not calculable). Spearman’s correlation between percentages of disability and patients’ features showed correlations with age, daytime naps, sleepiness, cataplexy and quality of life. This first interobserver reliability study on social benefit decisions for narcolepsy shows the difficulty of reaching an agreement in this field, mainly due to variance in interpretation of the assessment criteria. The minimum set of indicators of disease severity correlating with patients’ self assessments encourages a disability classification of narcolepsy.

The assessment of change in rural landscape and the analysis of the driving forces. Proposal of a spatial model for the rural built environment

The presented study carried out an analysis on rural landscape changes. In particular the study focuses on the understanding of driving forces acting on the rural built environment using a statistical spatial model implemented through GIS techniques. It is well known that the study of landscape changes is essential for a conscious decision making in land planning. From a bibliography review results a general lack of studies dealing with the modeling of rural built environment and hence a theoretical modelling approach for such purpose is needed. The advancement in technology and modernity in building construction and agriculture have gradually changed the rural built environment. In addition, the phenomenon of urbanization of a determined the construction of new volumes that occurred beside abandoned or derelict rural buildings. Consequently there are two types of transformation dynamics affecting mainly the rural built environment that can be observed: the conversion of rural buildings and the increasing of building numbers. It is the specific aim of the presented study to propose a methodology for the development of a spatial model that allows the identification of driving forces that acted on the behaviours of the building allocation. In fact one of the most concerning dynamic nowadays is related to an irrational expansion of buildings sprawl across landscape. The proposed methodology is composed by some conceptual steps that cover different aspects related to the development of a spatial model: the selection of a response variable that better describe the phenomenon under study, the identification of possible driving forces, the sampling methodology concerning the collection of data, the most suitable algorithm to be adopted in relation to statistical theory and method used, the calibration process and evaluation of the model. A different combination of factors in various parts of the territory generated favourable or less favourable conditions for the building allocation and the existence of buildings represents the evidence of such optimum. Conversely the absence of buildings expresses a combination of agents which is not suitable for building allocation. Presence or absence of buildings can be adopted as indicators of such driving conditions, since they represent the expression of the action of driving forces in the land suitability sorting process. The existence of correlation between site selection and hypothetical driving forces, evaluated by means of modeling techniques, provides an evidence of which driving forces are involved in the allocation dynamic and an insight on their level of influence into the process. GIS software by means of spatial analysis tools allows to associate the concept of presence and absence with point futures generating a point process. Presence or absence of buildings at some site locations represent the expression of these driving factors interaction. In case of presences, points represent locations of real existing buildings, conversely absences represent locations were buildings are not existent and so they are generated by a stochastic mechanism. Possible driving forces are selected and the existence of a causal relationship with building allocations is assessed through a spatial model. The adoption of empirical statistical models provides a mechanism for the explanatory variable analysis and for the identification of key driving variables behind the site selection process for new building allocation. The model developed by following the methodology is applied to a case study to test the validity of the methodology. In particular the study area for the testing of the methodology is represented by the New District of Imola characterized by a prevailing agricultural production vocation and were transformation dynamic intensively occurred. The development of the model involved the identification of predictive variables (related to geomorphologic, socio-economic, structural and infrastructural systems of landscape) capable of representing the driving forces responsible for landscape changes.. The calibration of the model is carried out referring to spatial data regarding the periurban and rural area of the study area within the 1975-2005 time period by means of Generalised linear model. The resulting output from the model fit is continuous grid surface where cells assume values ranged from 0 to 1 of probability of building occurrences along the rural and periurban area of the study area. Hence the response variable assesses the changes in the rural built environment occurred in such time interval and is correlated to the selected explanatory variables by means of a generalized linear model using logistic regression. Comparing the probability map obtained from the model to the actual rural building distribution in 2005, the interpretation capability of the model can be evaluated. The proposed model can be also applied to the interpretation of trends which occurred in other study areas, and also referring to different time intervals, depending on the availability of data. The use of suitable data in terms of time, information, and spatial resolution and the costs related to data acquisition, pre-processing, and survey are among the most critical aspects of model implementation. Future in-depth studies can focus on using the proposed model to predict short/medium-range future scenarios for the rural built environment distribution in the study area. In order to predict future scenarios it is necessary to assume that the driving forces do not change and that their levels of influence within the model are not far from those assessed for the time interval used for the calibration.

Analisi della dinamica e composizione chimica del particolato atmosferico mediante un modello alla mesoscala

The vertical profile of aerosol in the planetary boundary layer of the Milan urban area is studied in terms of its development and chemical composition in a high-resolution modelling framework. The period of study spans a week in summer of 2007 (12-18 July), when continuous LIDAR measurements and a limited set of balloon profiles were collected in the frame of the ASI/QUITSAT project. LIDAR observations show a diurnal development of an aerosol plume that lifts early morning surface emissions to the top of the boundary layer, reaching maximum concentration around midday. Mountain breeze from Alps clean the bottom of the aerosol layer, typically leaving a residual layer at around 1500-2000 m which may survive for several days. During the last two days under analysis, a dust layer transported from Sahara reaches the upper layers of Milan area and affects the aerosol vertical distribution in the boundary layer. Simulation from the MM5/CHIMERE modelling system, carried out at 1 km horizontal resolution, qualitatively reproduced the general features of the Milan aerosol layer observed with LIDAR, including the rise and fall of the aersol plume, the residual layer in altitude and the Saharan dust event. The simulation highlighted the importance of nitrates and secondary organics in its composition. Several sensitivity tests showed that main driving factors leading to the dominance of nitrates in the plume are temperature and gas absorption process. A modelling study turn to the analysis of the vertical aerosol profiles distribution and knowledge of the characterization of the PM at a site near the city of Milan is performed using a model system composed by a meteorological model MM5 (V3-6), the mesoscale model from PSU/NCAR and a Chemical Transport Model (CTM) CHIMERE to simulate the vertical aerosol profile. LiDAR continuous observations and balloon profiles collected during two intensive campaigns in summer 2007 and in winter 2008 in the frame of the ASI/QUITSAT project have been used to perform comparisons in order to evaluate the ability of the aerosol chemistry transport model CHIMERE to simulate the aerosols dynamics and compositions in this area. The comparisons of model aerosols with measurements are carried out over a full time period between 12 July 2007 and 18 July 2007. The comparisons demonstrate the ability of the model to reproduce correctly the aerosol vertical distributions and their temporal variability. As detected by the LiDAR, the model during the period considered, predicts a diurnal development of a plume during the morning and a clearing during the afternoon, typically the plume reaches the top of the boundary layer around mid day, in this time CHIMERE produces highest concentrations in the upper levels as detected by LiDAR. The model, moreover can reproduce LiDAR observes enhancement aerosols concentrations above the boundary layer, attributing the phenomena to dust out intrusion. Another important information from the model analysis regard the composition , it predicts that a large part of the plume is composed by nitrate, in particular during 13 and 16 July 2007 , pointing to the model tendency to overestimates the nitrous component in the particular matter vertical structure . Sensitivity study carried out in this work show that there are a combination of different factor which determine the major nitrous composition of the “plume” observed and in particular humidity temperature and the absorption phenomena are the mainly candidate to explain the principal difference in composition simulated in the period object of this study , in particular , the CHIMERE model seems to be mostly sensitive to the absorption process.

Background minimization issues for next generation hard X-ray focusing telescopes

The hard X-ray band (10 - 100 keV) has been only observed so far by collimated and coded aperture mask instruments, with a sensitivity and an angular resolution lower than two orders of magnitude as respects the current X-ray focusing telescopes operating below 10 - 15 keV. The technological advance in X-ray mirrors and detection systems is now able to extend the X-ray focusing technique to the hard X-ray domain, filling the gap in terms of observational performances and providing a totally new deep view on some of the most energetic phenomena of the Universe. In order to reach a sensitivity of 1 muCrab in the 10 - 40 keV energy range, a great care in the background minimization is required, a common issue for all the hard X-ray focusing telescopes. In the present PhD thesis, a comprehensive analysis of the space radiation environment, the payload design and the resulting prompt X-ray background level is presented, with the aim of driving the feasibility study of the shielding system and assessing the scientific requirements of the future hard X-ray missions. A Geant4 based multi-mission background simulator, BoGEMMS, is developed to be applied to any high energy mission for which the shielding and instruments performances are required. It allows to interactively create a virtual model of the telescope and expose it to the space radiation environment, tracking the particles along their path and filtering the simulated background counts as a real observation in space. Its flexibility is exploited to evaluate the background spectra of the Simbol-X and NHXM mission, as well as the soft proton scattering by the X-ray optics and the selection of the best shielding configuration. Altough the Simbol-X and NHXM missions are the case studies of the background analysis, the obtained results can be generalized to any future hard X-ray telescope. For this reason, a simplified, ideal payload model is also used to select the major sources of background in LEO. All the results are original contributions to the assessment studies of the cited missions, as part of the background groups activities.

Dynamic analysis of the motorcycle chattering behaviour by means of symbolic multibody modelling

Aim of this research is the development and validation of a comprehensive multibody motorcycle model featuring rigid-ring tires, taking into account both slope and roughness of road surfaces. A novel parametrization for the general kinematics of the motorcycle is proposed, using a mixed reference-point and relative-coordinates approach. The resulting description, developed in terms of dependent coordinates, makes it possible to efficiently include rigid-ring kinematics as well as road elevation and slope. The equations of motion for the multibody system are derived symbolically and the constraint equations arising from the dependent-coordinate formulation are handled using a projection technique. Therefore the resulting system of equations can be integrated in time domain using a standard ODE algorithm. The model is validated with respect to maneuvers experimentally measured on the race track, showing consistent results and excellent computational efficiency. More in detail, it is also capable of reproducing the chatter vibration of racing motorcycles. The chatter phenomenon, appearing during high speed cornering maneuvers, consists of a self-excited vertical oscillation of both the front and rear unsprung masses in the range of frequency between 17 and 22 Hz. A critical maneuver is numerically simulated, and a self-excited vibration appears, consistent with the experimentally measured chatter vibration. Finally, the driving mechanism for the self-excitation is highlighted and a physical interpretation is proposed.

Towards the 3D attenuation imaging of active volcanoes: methods and tests on real and simulated data

The purpose of my PhD thesis has been to face the issue of retrieving a three dimensional attenuation model in volcanic areas. To this purpose, I first elaborated a robust strategy for the analysis of seismic data. This was done by performing several synthetic tests to assess the applicability of spectral ratio method to our purposes. The results of the tests allowed us to conclude that: 1) spectral ratio method gives reliable differential attenuation (dt*) measurements in smooth velocity models; 2) short signal time window has to be chosen to perform spectral analysis; 3) the frequency range over which to compute spectral ratios greatly affects dt* measurements. Furthermore, a refined approach for the application of spectral ratio method has been developed and tested. Through this procedure, the effects caused by heterogeneities of propagation medium on the seismic signals may be removed. The tested data analysis technique was applied to the real active seismic SERAPIS database. It provided a dataset of dt* measurements which was used to obtain a three dimensional attenuation model of the shallowest part of Campi Flegrei caldera. Then, a linearized, iterative, damped attenuation tomography technique has been tested and applied to the selected dataset. The tomography, with a resolution of 0.5 km in the horizontal directions and 0.25 km in the vertical direction, allowed to image important features in the off-shore part of Campi Flegrei caldera. High QP bodies are immersed in a high attenuation body (Qp=30). The latter is well correlated with low Vp and high Vp/Vs values and it is interpreted as a saturated marine and volcanic sediments layer. High Qp anomalies, instead, are interpreted as the effects either of cooled lava bodies or of a CO2 reservoir. A pseudo-circular high Qp anomaly was detected and interpreted as the buried rim of NYT caldera.

1° level of automation: the effectiveness of adaptive cruise control on driving and visual behaviour

The research activities have allowed the analysis of the driver assistance systems, called Advanced Driver Assistance Systems (ADAS) in relation to road safety. The study is structured according to several evaluation steps, related to definite on-site tests that have been carried out with different samples of users, according to their driving experience with the ACC. The evaluation steps concern: •The testing mode and the choice of suitable instrumentation to detect the driver’s behaviour in relation to the ACC. •The analysis modes and outputs to be obtained, i.e.: - Distribution of attention and inattention; - Mental workload; - The Perception-Reaction Time (PRT), the Time To Collision (TTC) and the Time Headway (TH). The main purpose is to assess the interaction between vehicle drivers and ADAS, highlighting the inattention and variation of the workloads they induce regarding the driving task. The research project considered the use of a system for monitoring visual behavior (ASL Mobile Eye-XG - ME), a powerful GPS that allowed to record the kinematic data of the vehicle (Racelogic Video V-BOX) and a tool for reading brain activity (Electroencephalographic System - EEG). Just during the analytical phase, a second and important research objective was born: the creation of a graphical interface that would allow exceeding the frame count limit, making faster and more effective the labeling of the driver’s points of view. The results show a complete and exhaustive picture of the vehicle-driver interaction. It has been possible to highlight the main sources of criticalities related to the user and the vehicle, in order to concretely reduce the accident rate. In addition, the use of mathematical-computational methodologies for the analysis of experimental data has allowed the optimization and verification of analytical processes with neural networks that have made an effective comparison between the manual and automatic methodology.

Thermal and air quality modeling of an electric vehicle cabin with low-cost sensors and reinforcement learning

The design process of any electric vehicle system has to be oriented towards the best energy efficiency, together with the constraint of maintaining comfort in the vehicle cabin. Main aim of this study is to research the best thermal management solution in terms of HVAC efficiency without compromising occupant’s comfort and internal air quality. An Arduino controlled Low Cost System of Sensors was developed and compared against reference instrumentation (average R-squared of 0.92) and then used to characterise the vehicle cabin in real parking and driving conditions trials. Data on the energy use of the HVAC was retrieved from the car On-Board Diagnostic port. Energy savings using recirculation can reach 30 %, but pollutants concentration in the cabin builds up in this operating mode. Moreover, the temperature profile appeared strongly nonuniform with air temperature differences up to 10° C. Optimisation methods often require a high number of runs to find the optimal configuration of the system. Fast models proved to be beneficial for these task, while CFD-1D model are usually slower despite the higher level of detail provided. In this work, the collected dataset was used to train a fast ML model of both cabin and HVAC using linear regression. Average scaled RMSE over all trials is 0.4 %, while computation time is 0.0077 ms for each second of simulated time on a laptop computer. Finally, a reinforcement learning environment was built in OpenAI and Stable-Baselines3 using the built-in Proximal Policy Optimisation algorithm to update the policy and seek for the best compromise between comfort, air quality and energy reward terms. The learning curves show an oscillating behaviour overall, with only 2 experiments behaving as expected even if too slow. This result leaves large room for improvement, ranging from the reward function engineering to the expansion of the ML model.