Convolutional neural networks are the de facto method of processing camera, radar, and lidar data for use in perception in ADAS and L4 vehicles, yet their operation is a black box to many engineers. Unlike traditional rules-based approaches to coding intelligent systems, networks are trained and the internal structure created during the training process is too complex to be understood by humans, yet in operation networks are able to classify objects of interest at error rates better than rates achieved by humans viewing the same input data.
The manner in which a motor vehicle fire is initiated and subsequently spreads is dependent on a number of complex, interdependent, phenomena including combustion kinetics, heat transfer and fluid dynamics. Because the damage caused by a fire is coupled to these phenomena, damage patterns can sometimes be used to understand certain characteristics about the fire. In many cases, the goal is to determine the cause and origin of the fire.
The design and development of vehicle suspensions significantly influences vehicle handling and ride comfort. Suspension system design excellence follows the basic laws of physics using design synthesis techniques, a methodical process for suspension geometry development. Suspension geometry is the foundation of vehicle performance from which high-confidence suspension components and tunings can be developed. Suspension component design continues to move toward mass and cost efficient designs with high levels of stiffness being essential to achieving design requirements.