Browse Topic: Bodies and Structures
Dooring accidents occur when a vehicle door is opened into the path of an approaching cyclist, motorcyclist, or other road user, often causing serious collisions and injuries. These incidents are a major road safety concern, particularly in densely populated urban areas where heavy traffic, narrow roads, and inattentive behavior increase the likelihood of such events. To address this challenge, this project presents an intelligent computer vision based warning system designed to detect approaching vehicles and alert occupants before they open a door. The system can operate using either the existing rear parking camera in a vehicle or a USB webcam in vehicles without such a feature. The captured live video stream is processed by a Raspberry Pi 4 microprocessor, chosen for its compact size, low power consumption, and ability to support machine learning frameworks. The video feed is analyzed in real time using MobileNetSSD, a lightweight deep learning object detection model optimized
This SAE Recommended Practice is intended as a guide toward standard practice and is subject to change to keep pace with experience and technical advances. This document establishes additional performance requirements and provides test methods and requirements to evaluate the suitability of materials intended for optical applications in motor vehicles. The tests are intended to determine physical and optical characteristics of the materials only. Performance expectations of finished assemblies, including plastic components, are to be based on tests for lighting devices, as specified in SAE Standards and Recommended Practices for motor vehicle lighting equipment. Glass and materials inclusive to the light source are not in scope for this method.
The objective of this study was to examine the effect of Correlated Colour Temperature (CCT) of automotive LED headlamps on driver’s visibility and comfort during night driving. The experiment was conducted on different headlamps having different correlated colour temperatures ranging from 5000K to 6500K in laboratory. Further study was conducted involving participants of different age group and genders for understanding their perception to identify objects when observed in light of different LED headlamps with different CCTs. Studies have shown that both Correlated Colour Temperature and illumination level affect driver’s alertness and performance. Further study required on headlamps with automatically varying CCT to get better solution on driver’s visibility and safety.
The present work demonstrates a transient Fluid-Structure-Interaction (FSI) based numerical methodology for estimation of aerodynamic-induced flutter of the rear bumper of a Sports Utility Vehicle (SUV). Finite Volume Method (FVM) based High-fidelity transient full vehicle aerodynamic simulations were conducted for the estimation of the transient aerodynamic load. Subsequently, by mapping this transient aero load onto the surface of the rear bumper, Finite Element Method (FEM) based dynamic structural simulations were performed to predict its response. The results obtained through simulations were then compared against experimental wind tunnel test data of a prototype car with modified bumper for the specific test-case. The pressure and the time series data of rear bumper deflection were captured at multiple probe locations from wind tunnel experiments at 140 and 200 kmph. The distribution of pressure on the rear surfaces of the car was well captured by the aerodynamic simulation at
The rising importance of sustainability in the automotive sector has led to increased interest in circular and environmentally responsible materials, particularly for plastic trims parts, both interior and exterior. This study focuses on developing textile solutions using recycled polyethylene terephthalate (r-PET) sourced from post-consumer plastic waste, along with bio-based fibres such as bamboo. These materials made into woven and knitted fabrics are studied to suit different vehicle interior applications. r-PET textiles show promising strength, aesthetic appeal, and durability performance. Bamboo fabrics are known for their natural antimicrobial properties and enhanced breathability. Extensive testing is performed to validate explored sustainable materials performance against key automotive requirements. With this study, we gain an understanding of the performance of variedly sourced sustainable raw materials for automotive specific textile applications by different manufacturing
A passenger vehicle's front-end structure's structural integrity and crashworthiness are crucial to ensure compliance with various frontal impact safety standards (such as those set by Euro NCAP & IIHS). For a new front-end architecture, design targets must be defined at a component level for crush cans, longitudinal, bumper beam, subframe, suspension tower and backup structure. The traditional process of defining these targets involves multiple sensitivity studies in CAE. This paper explores the implementation of Physics-Informed Neural Networks (PINNs) in component-level target setting. PINNs integrate the governing equations into neural network training, enabling data-driven models to adhere to fundamental mechanical principles. The underlying physics in our model is based upon a force scheme of a full-frontal impact. A force scheme is a one-dimensional representation of the front-end structure components that simplifies a crash event's complex physics. It uses the dimensional and
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