Community-based programmes to prevent pedestrian injuries in children 0-14 years: A systematic review

Community-based models for injury prevention have become an accepted part of the overall injury control strategy. This systematic review of the scientific literature examines the evidence for their effectiveness in reducing pedestrian injury in children 0-14 years of age. A comprehensive search of the literature was performed using the following study selection criteria: community-based intervention study; target population was children under 14 years; outcome measure is either pedestrian injury rates or observed child pedestrian or vehicle driver behaviour; and use of a community control or an historical control in the study design. Quality assessment and data abstraction was guided by a standardized procedure and performed independently by two authors. Data synthesis was in tabular and text form with meta-analysis not being possible due to the discrepancy in methods and measures between the studies.

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.

Sviluppo di un modello Simulink per la gestione termica di un veicolo elettrico a batteria

Obiettivo di questo progetto di tesi è la realizzazione di un modello per la gestione termica di un veicolo elettrico a batteria: l’elettrificazione in ambito automotive richiede un approfondito studio delle problematiche termiche allo scopo di incrementare l’efficienza del veicolo, le performance e la vita della batteria. In particolare, l’oggetto di ricerca consiste nella modellazione di una pompa di calore. Partendo dalla definizione dei requisiti e degli obiettivi del sistema di gestione termica, ogni componente della pompa di calore viene analizzato modellato e connesso all’intero sistema. La modellazione è stata affrontata mediante l’utilizzo dell’ambiente MATLAB/Simulink. Il primo passo è stato avanzato nell’analisi del ciclo termodinamico ideale, analizzando il comportamento di vari fluidi frigorigeni, la funzionalità dei singoli componenti e l’interazione di quest’ultimi al variare delle condizioni di funzionamento, principalmente potenze scambiate, pressioni, temperature e portata massica di refrigerante. Il principale lavoro di simulazione è legato alla realizzazione di un modello configurabile dell’intero apparato di gestione termica della batteria per un veicolo elettrico. Per mezzo dello studio delle relazioni termodinamiche dei componenti principali del ciclo frigorifero sono state valutate tutte le grandezze che variano durante le trasformazioni che compie il fluido refrigerante all’interno del ciclo frigorifero. L’attività di validazione del modello implementato è stata svolta mediante il confronto tra le condizioni del fluido refrigerante determinate mediante le relazioni termodinamiche e quelle ottenute valutando le trasformazioni sui diagrammi di stato dei fluidi frigorigeni trattati. Il modello implementato è da ritenersi primordiale nel contesto legato alla modellazione e controllo dei sistemi di gestione termica per i sistemi propulsivi dei veicoli elettrici a batteria.

A review of the driver-vehicle effectiveness (DRIVEM) model. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Analytical modeling of driver response in crash avoidance maneuvering. Volume II: an interactive tire model for driver/vehicle simulation. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Analytical modeling of driver response in crash avoidance maneuvering. Volume III: a trim model and computer program for determining ground vehicle steady state operating conditions and quasilinear stability coefficients. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Model Predictive Control for Vehicle Stabilization at the Limits of Handling

Recent developments in vehicle steering systems offer new opportunities to measure the steering torque and reliably estimate the vehicle sideslip and the tire-road friction coefficient. This paper presents an approach to vehicle stabilization that leverages these estimates to define state boundaries that exclude unstable vehicle dynamics and utilizes a model predictive envelope controller to bound the vehicle motion within this stable region of the state space. This approach provides a large operating region accessible by the driver and smooth interventions at the stability boundaries. Experimental results obtained with a steer-by-wire vehicle and a proof of envelope invariance demonstrate the efficacy of the envelope controller in controlling the vehicle at the limits of handling.

A model state classified licensing program. Guidelines for motor vehicle administrators.

Mode of access: Internet.

Highway-vehicle-object simulation model - 1976. Volume 2: programmers manual. Final report.

Federal Highway Administration, Washington, D.C.

Highway-vehicle-object simulation model - 1976. Volume 3: engineering manual - analysis. Final report.

Federal Highway Administration, Washington, D.C.

Highway-vehicle-object simulation model - 1976. Volume 4: engineering manual - validation. Final report.

Federal Highway Administration, Washington, D.C.

Driver and vehicle characteristics as related to the precipitation of accidents. Final report.

National Highway Traffic Safety Administration, Washington, D.C.

Highway-vehicle-object simulation model - 1976. Volume 1: users manual. Final report.

Federal Highway Administration, Washington, D.C.

Model-Based validation of Driver Drowsiness Detection System for ADAS

The work described in this Master’s Degree thesis was born after the collaboration with the company Maserati S.p.a, an Italian luxury car maker with its headquarters located in Modena, in the heart of the Italian Motor Valley, where I worked as a stagiaire in the Virtual Engineering team between September 2021 and February 2022. This work proposes the validation using real-world ECUs of a Driver Drowsiness Detection (DDD) system prototype based on different detection methods with the goal to overcome input signal losses and system failures. Detection methods of different categories have been chosen from literature and merged with the goal of utilizing the benefits of each of them, overcoming their limitations and limiting as much as possible their degree of intrusiveness to prevent any kind of driving distraction: an image processing-based technique for human physical signals detection as well as methods based on driver-vehicle interaction are used. A Driver-In-the-Loop simulator is used to gather real data on which a Machine Learning-based algorithm will be trained and validated. These data come from the tests that the company conducts in its daily activities so confidential information about the simulator and the drivers will be omitted. Although the impact of the proposed system is not remarkable and there is still work to do in all its elements, the results indicate the main advantages of the system in terms of robustness against subsystem failures and signal losses.

Vehicle and driver attributes affecting distance from the steering wheel in motor vehicles

The current study was designed to confirm that female drivers sit closer to the steering wheel than do male drivers and to investigate whether this expected difference in sitting position is attributable to differences in the physical dimensions of men and women. Driver body dimensions and multiple measures of sitting distance from the steering wheel were collected from a sample of 150 men and 150 women. The results confirmed that on average, women sit closer to the steering wheel than men do and that this difference is accounted for by variations in body dimensions, especially height. This result suggests that driver height may provide a good surrogate for sitting distance from the steering wheel when investigating the role of driver position in real-world crash outcomes. The potential applications of this research include change to vehicle design that allows independent adjustment of the relative distance among the driver's seat, the steering wheel, and the floor pedals.