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.

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.

Safety by design: production of engineering surface modified nanomaterials

This PhD thesis focused on nanomaterial (NM) engineering for occupational health and safety, in the frame of the EU project “Safe Nano Worker Exposure Scenarios (SANOWORK)”. Following a safety by design approach, surface engineering (surface coating, purification process, colloidal force control, wet milling, film coating deposition and granulation) were proposed as risk remediation strategies (RRS) to decrease toxicity and emission potential of NMs within real processing lines. In the first case investigated, the PlasmaChem ZrO2 manufacturing, the colloidal force control applied to the washing of synthesis rector, allowed to reduce ZrO2 contamination in wastewater, performing an efficient recycling procedure of ZrO2 recovered. Furthermore, ZrO2 NM was investigated in the ceramic process owned by CNR-ISTEC and GEA-Niro; the spray drying and freeze drying techniques were employed decreasing NM emissivity, but maintaining a reactive surface in dried NM. Considering the handling operation of nanofibers (NFs) obtained through Elmarco electrospinning procedure, the film coating deposition was applied on polyamide non-woven to avoid free fiber release. For TiO2 NF the wet milling was applied to reduce and homogenize the aspect ratio, leading to a significant mitigation of fiber toxicity. In the Colorobbia spray coating line, Ag and TiO2 nanosols, employed to transfer respectively antibacterial or depolluting properties to different substrates, were investigated. Ag was subjected to surface coating and purification, decreasing NM toxicity. TiO2 was modified by surface coating, spray drying and blending with colloidal SiO2, improving its technological performance. In the extrusion of polymeric matrix charged with carbon nanotube (CNTs) owned by Leitat, the CNTs used as filler were granulated by spray drying and freeze spray drying techniques, allowing to reduce their exposure potential. Engineered NMs tested by biologists were further investigated in relevant biological conditions, to improve the knowledge of structure/toxicity mechanisms and obtain new insights for the design of safest NMs.