Simone Piantini

Bio: Simone Piantini is an academic researcher from University of Florence. The author has contributed to research in topics: Poison control & Crash. The author has an hindex of 7, co-authored 24 publications receiving 174 citations.

Advanced accident research system based on a medical and engineering data in the metropolitan area of Florence

Abstract: Background: In the metropolitan area of Florence, 62% of major traumas involve powered two wheeler rider and pillion passengers, 10% cyclists, and 7% pedestrians. The urban and extra-urban areas are the most dangerous for the vulnerable road user. In-depth investigations are needed for assessing detailed information on road accidents. This type of study has been very limited in time frame in Italy, and completely absent in the Tuscan region. Consequently a study called “In-depth Study of road Accident in FlorencE” (In-SAFE) has been initiated. Methods: A network between the Department of Mechanics and Industrial Technologies (University of Florence) and the Intensive Care Unit of the Emergency Department (Careggi Teaching Hospital, Florence) was created with the aim of collecting information about the road accidents. The data collected includes: on-scene data, data coming from examination of the vehicles, kinematics and dynamic crash data, injuries, treatment, and injury mechanisms. Each injury is codified thorough the AIS score, localized by a three-dimensional human body model based on computer tomography slices, and the main scores are calculated. We then associate each injury with its cause and crash technical parameters. Finally, all the information is collected in the In-SAFE database. Results: Patient mean age at the time of the accident was 34.6 years, and 80% were males. The ISS mean is 24.2 (SD 8.7) and the NISS mean is 33.6 (SD 10.5). The main road accident configurations are the “car-to-PTW” (25%) and “pedestrian run over” (17,9%). For the former, the main collision configuration is “head-on crash” (57%). Cyclists and PTW riders-and-pillions-passengers suffer serious injuries (AIS3+) mainly to the head and the thorax. The head (56.4%) and the lower extremities (12.7%) are the most frequently injured pedestrian body regions. Conclusions: The aim of the project is to create an in-depth road accident study with special focus on the correlation between technical parameters and injuries. An in-depth investigation team was setup and is currently active in the metropolitan area of Florence. Twenty-eight serious road accidents involving twenty-nine ICU patients are studied. PTW users, cyclist and pedestrians are the most frequently involved in metropolitan accidents.

Proposal of a new motorcycle helmet test method for tangential impact

Abstract: Based on an existing in‐depth accident database available at Florence University, a total of 19 motorcycle accidents were selected for reconstruction using a multibody simulation approach. These computations give access to the head impact conditions in terms of initial head velocity vector. The real‐world accident simulation permitted the computation of the victim’s kinematics and demonstrated that the impact velocity vector presents an important tangential component. Typically, an impact angle of 40–50° is observed. Therefore, it is suggested to consider tangential helmet impacts in three different planes with an 8.5 m/s impact speed against an anvil inclined at 45°. Further, it has been demonstrated that the 6D HIII headform response under tangential impact is reliable and can be used in helmet testing. Finally, by driving a human head FE model with the 6D acceleration versus time history, it appears that the brain injury risk can be computed. The proposed test method suggests four tangential impacts leading to rotation among the three reference axes. For this combined linear and rotational head loading, the helmet can be evaluated against brain tissue level injury.

Motorcycles that See: Multifocal Stereo Vision Sensor for Advanced Safety Systems in Tilting Vehicles

Abstract: Advanced driver assistance systems, ADAS, have shown the possibility to anticipate crash accidents and effectively assist road users in critical traffic situations This is not the case for motorcyclists, in fact ADAS for motorcycles are still barely developed Our aim was to study a camera-based sensor for the application of preventive safety in tilting vehicles We identified two road conflict situations for which automotive remote sensors installed in a tilting vehicle are likely to fail in the identification of critical obstacles Accordingly, we set two experiments conducted in real traffic conditions to test our stereo vision sensor Our promising results support the application of this type of sensors for advanced motorcycle safety applications

Quantitative evaluation of matching methods and validity measures for stereo vision

Abstract: The authors present a qualitative and quantitative comparison of various similarity measures that form the kernel of common area-based stereo-matching systems. The authors compare classical difference and correlation measures as well as nonparametric measures based on the rank and census transforms for a number of outdoor images. For robotic applications, important considerations include robustness to image defects such as intensity variation and noise, the number of false matches, and computational complexity. In the absence of ground truth data, the authors compare the matching techniques based on the percentage of matches that pass the left-right consistency test. The authors also evaluate the discriminatory power of several match validity measures that are reported in the literature for eliminating false matches and for estimating match confidence. For guidance applications, it is essential to have and estimate of confidence in the three-dimensional points generated by stereo vision. Finally, a new validity measure, the rank constraint, is introduced that is capable of resolving ambiguous matches for rank transform-based matching.

Feasibility study on the use of a hierarchical lattice architecture for helmet liners

Abstract: Helmets are the most important piece of protective equipment for motorcyclists. The liner of the helmet is the main part of the helmet which dissipates the impact energy and mitigates the load transmitted to the head. Therefore, optimizing the material that absorbs most of the impact energy would improve the helmet’s protection capacity. It is known that the energy absorption of the helmet liner can be optimized by means of using liners with varying properties through the thickness, however currently the majority of used liners exhibit constant properties through the thickness. Advances in the field of topology optimization and additive manufacturing provide the ability of building complex geometries and tailoring mechanical properties. Along those lines, in the present work the feasibility of using a hierarchical lattice liner for helmets was studied. Finite element method was employed to study whether a hierarchical lattice liner could reduce the risk of head injuries in comparison to currently used liner materials. The results show that using a hierarchical lattice liner has the potential of significantly reducing the risk of head injury compared to a helmet with traditional EPS liner and could potentially be considered as the new generation of energy absorbing liners for helmets.