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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.

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. Light detection and ranging (LIDAR) sensing, a sensing method that detects objects and maps their distances, is seeing rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve. This course will provide the foundation to build LIDAR technologies in automotive applications.

This course is offered in China only and presented in Mandarin Chinese. The course materials are bilingual (English and Chinese). The course introduces the basic knowledge of vehicle noise and vibration, provides the analysis and control methods for noise and vibration sources, and transfer paths, and describes the occupants' responses and control. The course is specially designed for NVH engineer and related graduate participants. The course combines the NVH theory and engineering practices. After finishing the course, the students will deeply understand the mechanism of NVH and promote their capacity to solve engineering problems. 

This course is offered in China only and presented in Mandarin Chinese. Sound quality is one of the most important desired attributes for the customers, and road noise is one of the most vital factors influencing sound quality. Road noise is the major interior noise source, especially for EVs, and it is a common customer complaint. In order to improve the customers’ satisfaction and market share, almost all the OEMs have spent lots of sources on the road noise attenuation.

This course examines ADAS and autonomous vehicle technologies that offer the potential to increase safety while attempting to optimize the cost of car ownership. LIDAR (light detection ranging) and Infrared camera sensing are seeing a rapid growth and adoption in the industry. However, the sensor requirements and system architecture options continue to evolve almost every six months. This course will provide the foundation to build on for these two technologies in automotive applications. It will include a demonstration model for LIDAR and Infrared camera.

The Vehicle Noise Control Engineering Academy covers a variety of vehicle noise control engineering principles and practices. There are two concurrent, specialty tracks (with some common sessions): Vehicle Interior Noise and Powertrain Noise. Participants should choose and register for the appropriate track they wish to attend. The Vehicle Interior Noise track focuses on understanding the characteristics of noise produced by different propulsion systems, including internal combustion, hybrid and electric powered vehicles and how these noises affect the sound quality of a vehicle’s interior.  

The Vehicle Noise Control Engineering Academy covers a variety of vehicle noise control engineering principles and practices. There are two concurrent, specialty tracks (with some common sessions): Powertrain Noise and Vehicle Interior Noise. Participants should choose and register for the appropriate Academy they wish to attend. The Powertrain Noise track focuses on noise and vibration control issues associated with internal combustion, hybrid and electric powered vehicles. The vehicle in this case includes passenger cars, SUVs, light trucks, off-highway vehicles, and heavy trucks.

Photographs and video recordings of vehicle crashes and accident sites are more prevalent than ever, with dash mounted cameras, surveillance footage, and personal cell phones now ubiquitous. The information contained in these pictures and videos provide critical information to understanding how crashes occurred, and  analyze physical evidence. This course teaches the theory and techniques for getting the most out of digital media, including correctly processing raw video and photographs, correcting for lens distortion, and using photogrammetric techniques to convert the information in digital media to usable scaled three-dimensional data.

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.

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. 

Optical fiber has begun replacing copper in avionic networks. So far, however, it has been mainly restricted to non-critical applications (video transmission to the flight deck, IFE?). In order to take advantage of the high-bandwidth, low weight, no EMI properties of optical fibers in all data transmission networks, it will be necessary to improve the testing. One part of the puzzle, which is still missing, is the self-test button: the possibility to check the network and detect potential failures before they occur. The typical testing tool of a technician involved in optical fiber cables is the ?light source ? optical power meter? pair. With this tool, one can measure the insertion loss of the fiber link. A second important parameter, the return loss at each optical connector, is not analysed. In addition, this is only a global measurement, which does not allow the detection of possible weak points.

This article characterizes the special features of drilling of CFRP/Titanium and -Aluminium stacks. Simplified theoretic models will show how CFRP/Titanium stacks should be machined without scratches and burn marks contacting carbon. Low axial forces and smart chip removal technology are the main characteristics of the drilling tool technology, optimized to reach H8 quality in one shot operation. Presenter Peter Mueller-Hummel, Cutting Tools Inc.

The aerospace industry has long sought a solution for storing maintenance history information directly on aircraft parts. In 2005 leading airframe manufacturers determined that passive Radio Frequency Identification (RFID) technology presented a unique opportunity to address this industry need. Through the efforts of the Air Transport Association (ATA) RFID on Parts Committee and SAE International testing standards and data specifications are in place to support the broad adoption of passive RFID for storing parts history information directly on aircraft parts. The primary focus of the paper will be on the SAE AS-5678 environmental testing standard for passive RFID tags intended for aircraft use. Detail will be provided to help aerospace manufacturers understand their role and responsibilities for current programs and understand how this may impact their parts certification process.