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Advanced Driver Assist System (ADAS) and autonomous vehicle technologies have disrupted the traditional automotive industry with potential to increase safety and optimize the cost of car ownership. Among the challenges are those of sensing the environment in and around the vehicle. Infrared camera sensing is seeing a rapid growth and adoption in the industry. The applications and illumination architecture options continue to evolve. This course will provide the foundation on which to build near infrared camera technologies for automotive applications.

Many technical projects, most vehicle and component testing, and all accident reconstructions, product failure analyses, and other forensic investigations, require photographic documentation. Roadway evidence disappears, tested or wrecked vehicles are repaired, disassembled, or scrapped, and components can be tested for failure. Photographs are frequently the only evidence that remains of a wreck, or the only records of subjects before or during tests. Making consistently good images during any inspection is a critical part of the evaluation process. 

This two-day course will begin with a discussion of commercial off the shelf (COTS) test requirements.  The instructor will then guide participants through the various cabin interior emergency provisions and their requirements such as supplemental passenger oxygen, emergency equipment, seats, flammability, emergency exits, emergency lighting and escape path markings, and various other cabin interior systems.  

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.

Finite Element Analysis (FEA) is a powerful and well recognized tool used in the analysis of heat transfer problems. However, FEA can only analyze solid bodies and, by necessity thermal analysis with FEA is limited to conductive heat transfer. The other two types of heat transfer: convection and radiation must by approximated by boundary conditions. Modeling all three mechanisms of heat transfer without arbitrary assumption requires a combined use of FEA and Computational Fluid Dynamics (CFD).

From lenses to composition, these videos cover everything you need to know when photographing accident reconstruction. Join accident reconstruction expert Tom Vadnais as he demonstrates how to photograph trucks, passenger vehicles, and accident sites, as well as a looks at must-have photography equipment.

Participants learn what a drone is and how this tool can aid them in producing an orthomosaic map of an accident scene/location. Participants will learn basic drone safety, operations, and best practices, and will understand how to address airspace basic steps to achieve their Part 107 federal aviation administration (FAA) certification.

Engineers and managers involved with product development are continually challenged to reduce time to market, minimize warranty costs, and increase product quality. This results in less time for testing, which means the need for effective accelerated test procedures has never been greater. Accelerating your testing program sounds great, but how do you begin? This course starts by taking a look at statistical models for reliability testing. It looks specifically at how sample size and testing timeframe affect what you’re able to do versus what you'd ideally do with more time and money.