statistical evaluation of the softening or hardening behaviour of metallic materials

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combined activation of braking and steering for automated driving systems adaptive intervention by injury risk based criteria

Abstract Increase in advanced driver assistance systems (ADAS) performances is a crucial step towards autonomous driving, allowing the design of increasingly reliable automated driving systems (ADS); ADAS devices play a key role in the enhancement of vehicle safety, which primarily results from the ability to avoid possible impacts. Nevertheless, inevitable collision states (ICS) can be triggered by obstacles as buildings and stationary vehicles interposing between the opponent and the working field of ADAS sensors, compromising their functions; therefore, the performance increase of ADAS devices on the market necessarily passes from the optimal handling of an ICS, which is not currently subject to evaluations. The work introduces ADAS intervention criteria which are based on the occupants' injury risk (IR): in a specific road scenario, the ADAS must primarily avoid the collision with maximum margin and minimize IR in the case of an ICS. Specifically, the ADAS must monitor the environment and intervene on braking and steering adapting to the scenario evolution, following an "adaptive" logic. The most critical aspect of the approach lies in reconstructing, for the specific intervention, the eventual impact: while being a time-consuming process, reconstruction of the impact phase is necessary to compute impact-related parameters (e.g., velocity change of the vehicle ∆V) which directly affect IR. To highlight the benefits offered by an adaptive ADAS compared to traditional ADASs, a special testing software has been developed: the best adaptive intervention to be applied at each instant is chosen in real-time through the criteria proposed, retrieving the required information from a pre-calculated database which collects the results of each braking and steering manoeuvre for a large variety of critical scenarios. Analyzing three ICS conditions, it is shown that the adaptive logic, differing from an autonomous emergency braking, aims at creating eccentrical impacts with minimum ∆V: the IR values associated with the ADAS adaptive intervention are consequently an order of magnitude lower than those obtained through traditional ADAS interventions

Vehicle Accident Databases: Correctness Checks for Accident Kinematic Data

(1) Background: Data collection procedures allow to obtain harmonization of in-depth road accident databases. Plausibility of calculable accident-related kinematic parameters depends on the constraints imposed on calculation, making their uncertainty degree higher than the one for measurable parameters (i.e., traces, airbag activation, etc.). Uncertainty translates in information loss, making the statistics based on databases analysis less consistent. Since kinematic parameters describe the global accident dynamics, their correctness assessment has a fundamental importance; (2) Methods: the paper takes as reference data collected in the Initiative for the GLobal harmonisation of Accident Data (IGLAD) database for vehicle-to-vehicle crashes. The procedure, however, has general nature and applies identically for other databases and multiple impacts between vehicles. To highlight issues which can arise in accident-related data collection, 3 different checks are proposed for parameters correctness assessment; (3) Results: by 4 examples, 1 with correct and 3 with incorrect parameters reported, the paper demonstrates that errors can go beyond simple calculation uncertainty, implying that a deeper analysis is desirable in data collection; (4) Conclusions: the step-by-step guidelines described in this paper will help in increasing goodness of collected data, providing for a methodology which can be used by each individual involved in accident data collection, both for collection itself and subsequent verification analysis

Optimal Rayleigh waves generation by continuous wave modulated laser

Laser-ultrasound technology is typically employed in case of non-destructive, non-contact inspection of mechanical components. In particular, low power laser sources (diodes) allow to contain implementation costs; on the other hand, identification of the ultrasonic peak is complex due to the low Signal-to-Noise Ratio (SNR), requiring the use of specific signal processing techniques. Features of the ultrasounds generated by the laser excitation, both in terms of frequencies and SNR, cannot be foreseen in advance, depending from the type of material and its thermo-elastic characteristics: it is thus fundamental to dispose of criteria to set in an optimal way the signal acquisition parameters to effectively apply a correct processing procedure and retrieve the useful information. In the work, surface R (Rayleigh) waves generated by a Continuous Wave (CW) low power laser are characterized, using a particular processing technique in the time domain. To identify the most influential input parameters on SNR, a Design Of Experiments (DOE) and a specific analysis are introduced: overall, the distance between source and receiver and the number of ensemble average applied before acquisition strongly affect SNR; the pulse duration results on the other hand influential at the same time on SNR and on the generated ultrasound frequency. Finally, analogies with longitudinal (L) waves generated by the same source are highlighted, allowing also for information on how to set up the investigation based on the type of wave and acquisition instruments employed

Performance Assessment in a “Lane Departure” Scenario of Impending Collision for an ADAS Logic Based on Injury Risk Minimisation

The current prioritisation of road safety enhancement in the automotive sector is leading toward the near future implementation of Advanced Driver Assistance Systems (ADASs), aiming at the simultaneous intervention of braking and steering for impact avoidance in case of an impending collision. However, it is partially unclear how new technologies for controlling the steering will actually behave in the case of inevitable collision states; the need consequently emerges to propose and tune efficient ADAS strategies to handle the complexity of critical road scenarios. An adaptive intervention logic on braking and steering for highly automated vehicles is applied in the context of a “lane departure”, two-vehicle critical road scenario; the ADAS implementing the logic activates to minimise the injury risk for the ego vehicle’s occupants at each time step, adapting to the eventual scenario evolution consequent to actions by other road users. The performance of the adaptive logic is investigated by a software-in-the-loop approach, varying the mutual position of the involved vehicles at the beginning of the criticality and comparing the injury risk outcomes of the eventual impacts with those connected to the Autonomous Emergency Braking (AEB). The results highlight a twofold benefit from the adaptive logic application in terms of road safety: (1) it decreases the frequency of impacts compared to the AEB function; (2) in inevitable collision states, it decreases injury risk for the vehicles’ occupants down to 40% compared to the AEB. This latter condition is achieved thanks to the possibility of reaching highly eccentric impact conditions (low impact forces and occupants’ injury risk as a consequence). The obtained highlights expand the literature regarding the adaptive logic by considering a diverse critical road scenario and investigating how fine variations on the vehicles’ mutual position at the beginning of the criticality reflect on the injury outcomes for different types of intervention logic