An Investigation into C-NCAP AEB System Assessment Protocol

Guo, Kuiyuan; Yan, Yan; Shi, Juan; Guo, Runqing; Liu, Yuguang

doi:10.4271/2017-01-2009

Cited by 9 publications

(4 citation statements)

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“…Performance of the PPS across a range of survival times was examined using discrimination, a measure of a prognostic model’s ability to differentiate those who lived from those who died. We calculated time-specific area under the receiver operating characteristic curve (AUC) values at 1, 6, and 12 months, as well as integrated time-dependent AUC (iAUC) values, which average all available AUC statistics over time . We assessed internal validity via bootstrapping to quantify any optimism in model performance.…”

Section: Methodsmentioning

confidence: 99%

Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice

Bischoff,

Patel,

Boscardin

et al. 2024

JAMA Netw Open

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ImportanceThe Palliative Performance Scale (PPS) is one of the most widely used prognostic tools for patients with serious illness. However, current prognostic estimates associated with PPS scores are based on data that are over a decade old.ObjectiveTo generate updated prognostic estimates by PPS score, care setting, and illness category, and examine how well PPS predicts short- and longer-term survival.Design, Setting, and ParticipantsThis prognostic study was conducted at a large academic medical center with robust inpatient and outpatient palliative care practices using electronic health record data linked with data from California Vital Records. Eligible participants included patients who received a palliative care consultation between January 1, 2018, and December 31, 2020. Data analysis was conducted from November 2022 to February 2024.ExposurePalliative care consultation with a PPS score documented.Main Outcomes and MeasuresThe primary outcomes were predicted 1-, 6-, and 12-month mortality and median survival of patients by PPS score in the inpatient and outpatient settings, and performance of the PPS across a range of survival times. In subgroup analyses, mortality risk by PPS score was estimated in patients with cancer vs noncancer illnesses and those seen in-person vs by video telemedicine in the outpatient setting.ResultsOverall, 4779 patients (mean [SD] age, 63.5 [14.8] years; 2437 female [51.0%] and 2342 male [49.0%]) had a palliative care consultation with a PPS score documented. Of these patients, 2276 were seen in the inpatient setting and 3080 were seen in the outpatient setting. In both the inpatient and outpatient settings, 1-, 6-, and 12-month mortality were higher and median survival was shorter for patients with lower PPS scores. Prognostic estimates associated with PPS scores were substantially longer (2.3- to 11.7-fold) than previous estimates commonly used by clinicians. The PPS had good ability to discriminate between patients who lived and those who died in the inpatient setting (integrated time-dependent area under the curve [iAUC], 0.74) but its discriminative ability was lower in the outpatient setting (iAUC, 0.67). The PPS better predicted 1-month survival than longer-term survival. Mortality rates were higher for patients with cancer than other serious illnesses at most PPS levels.Conclusions and RelevanceIn this prognostic study, prognostic estimates associated with PPS scores were substantially longer than previous estimates commonly used by clinicians. Based on these findings, an online calculator was updated to assist clinicians in reaching prognostic estimates that are more consistent with modern palliative care practice and specific to the patient’s setting and diagnosis group.

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Section: Methodsmentioning

confidence: 99%

Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice

Bischoff,

Patel,

Boscardin

et al. 2024

JAMA Netw Open

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“…where E 0 is the initial kinetic energy of vehicle; E a is the energy absorbed during the collision; E r is the residual kinetic energy; M is the total mass of vehicle during the collision test; v 0 is the initial velocity, referencing China-New Car Assessment Programme (C-NCAP), 38 50 km/h as initial velocity; v r is the residual velocity.…”

Section: Methodology and Materialsmentioning

confidence: 99%

“…12,13,47 The static load cases are torsion and bending which contains two concentrated loads and one uniform load according to battery weight 12 to ensure the stiffness and stability of body structure. The dynamic load cases are specified by C-NCAP 38 for energy vehicles, which are 100% overlapping rigid wall collision condition, frontal 50% overlapping deformable barrier collision and side column collision. The two dynamic impact scenarios of 100% frontal collision and 50% offset collision are used to obtain longitudinal load paths, while column collision is used to obtain lateral loads paths.…”

Section: Body Frame Structure Designmentioning

confidence: 99%

Electric vehicles body frame structure design method: An approach to design electric vehicle body structure based on battery arrangement

Chen

Wang

Zhao

et al. 2021

Proceedings of the Institution of Mechanical Engineers, Part D:

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Although the electric vehicles (EVs) have become the main development of the automotive industry, there is still very limited knowledge about the design method of EVs’ body structure. This paper substantially increases this limited knowledge by developing an EV’s aluminum alloy body frame structure design (EVFD) method based on battery arrangements. The main concept of the EVFD approach is the development of the parametric knowledge base to facilitate performance driven design of body structure in concept design stage, including the battery sub-libraries designed by vehicle power performances and the modular body frame structure sub-libraries and cross section of profile sub-libraries designed by structure performances. The layout of vehicle is firstly determined based on battery volume which calculated on the basis of power performance of EVs. And then, the body frame structures are designed by multi-load topology optimization and multi-objective parametric optimization based on the body structure performance, considering the battery layout and its mass distribution. The developed body structure knowledge base is screened through comparing their structural mechanical properties. The feasibility and accuracy of selected EV’s aluminum alloy body frame structure is verified by experiment. In this paper, the case study demonstrates that the proposed EVFD method based on battery arrangement can be effectively used to design aluminum alloy body frame structure of EVs, which provides a reference to other EV’s body structure design. Due to the performance driven design concept employed, the designed body structure for EV meets the requirements of lightweight, dynamic performance, and structural mechanical properties.

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“…When traffic speeds are high, the braking distance may not be sufficient; so, new collision avoidance maneuvers are contemplated for the development of Advanced Driver Assistance Systems (ADASs) embedded in new-generation vehicles. Notably, the Automatic Emergency Steering (AES) system is placed within the Euro NCAP 2025 roadmap for primary safety [6].…”

Section: Introductionmentioning

confidence: 99%

Effectiveness of the Autonomous Braking and Evasive Steering System OPREVU-AES in Simulated Vehicle-to-Pedestrian Collisions

Losada,

Páez,

Luque

et al. 2023

Vehicles

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This paper proposes a combined system (OPREVU-AES) that integrates optimized AEB and Automatic Emergency Steering (AES) to generate evasive maneuvers, and it provides an assessment of its effectiveness when compared to a commercial AEB system. The optimized AEB system regulates the braking response through a collision prediction model. OPREVU is a research project in which INSIA-UPM and CEDINT-UPM cooperate to improve driving assistance systems and to characterize pedestrians’ behavior through virtual reality (VR) techniques. The kinematic and dynamic analysis of OPREVU-AES is conducted using CarSim© software v2020.1. The avoidance trajectories are predefined for speeds above 40 km/h, which controls the speed and lateral stability during the overtaking and lane re-entry process. In addition, the decision algorithm integrates information from the lane and the blind spot detectors. The effectiveness evaluation is based on the reconstruction of a sample of vehicle-to-pedestrian crashes (INSIA-UPM database), using PCCrash© software v. 2013, and it considers the probability of head injury severity (ISP) as an indicator. The incorporation of AEB can avoid 53.8% of accidents, with an additional 2.5–3.5% avoided by incorporating automatic steering. By increasing the lateral activation range, the total avoidance rate is increased to 61.8–69.8%. The average ISP reduction is 65%, with significant reductions achieved in most cases where avoidance is not possible.

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An Investigation into C-NCAP AEB System Assessment Protocol

Cited by 9 publications

References 0 publications

Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice

Prognoses Associated With Palliative Performance Scale Scores in Modern Palliative Care Practice

Electric vehicles body frame structure design method: An approach to design electric vehicle body structure based on battery arrangement

Effectiveness of the Autonomous Braking and Evasive Steering System OPREVU-AES in Simulated Vehicle-to-Pedestrian Collisions

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