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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.

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.

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. 

FutureSteelVehicle's (FSV) objective is to develop detailed design concepts for a radically different steel body structure for a compact Battery Electric Vehicle (BEV). It also will identify structure changes to accommodate larger Plug-In Hybrid (PHEV) and Fuel Cell (FCEV) vehicle variants. The presentation will demonstrate seven optimized structural sub-systems that contribute to the program's 35 percent mass reduction goals and meet its safety and life cycle emissions targets. It will explain the advanced design optimization process used and the resulting aggressive steel concepts. Presenter Jody R. Shaw, US Steel

Trans Tech recently debuted the all-electric eTrans school bus providing a total zero emission school bus. The presentation will demonstrate Smith Electric Vehicles and their history with electric vehicles. The presentation will help ensure that everybody has an idea of what the electric school bus will do and to dispel any rumors about the vehicle. Presenter Brian S. Barrington, Trans Tech. Bus

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.

Micro-pitting is a fatigue effect that occurs in geared transmission systems due to high contact stress, and monitoring its progression is vital to prevent the eventual failure of the tooth flank. Parameter signature analysis has been successfully used to monitor bending fatigue failure and advanced phases of gear surface fatigue failure such as macro-pitting and scuffing. However, due to modern improvements in steel production the main cause of gear contact fatigue failure can be attributed to surface micro-pitting rather than sub-surface phenomena. Responding to the consequent demand to detect and monitor the progression of micro-pitting, this study experimentally evaluated the development of micro-pitting in spur gears using vibration and oil debris analysis. The paper presents the development of an online health monitoring system for use with back-to-back gear test rigs.

A significant step is achieved on the flight control actuation system toward the more electrical aircraft through the Airbus A380, A400M and the A350 development phase ongoing. The A380/A400M/A350 features a mixed flight control actuation power source distribution, associating electrically powered actuators with conventional FlyByWire hydraulic servocontrols. In the scope of the preparation of the future Airbus Aircraft, this paper presents the perspectives of the use of the EMA technologies for the flight control systems in the more electrical aircraft highlighting the main technical challenges need to treat: jamming susceptibility, ?on board? maintenance reduction, Operational reliability increase, power electronics and power management optimization, and regarding the environmental constraints, the predicted performances; the benefits associated to the optimized utilization of on-board power sources.

TERBAN® hydrogenated nitrile rubber (HNBR) is a specialty elastomer used in demanding engineering applications such as the automotive, heavy duty, and industrial markets. It has excellent combination of heat, oil and abrasion resistance in addition to its high mechanical strength, very good dynamic and sealing properties. This paper will present data on aging HNBR for five thousand hours in an aggressive and un-stabilized B30A biodiesel fuel blend (70% ULSD, 30% SME, and an aggressive additive package) and explore the effect of HNBR polymer properties and vulcanizate composition on the performance in such fuel blends. Presenter Victor Nasreddine

Exatec� PC glazing technology team, has developed advanced weathering and abrasion resistant coatings technology that can be applied to protect polycarbonate. It is of particular interest to quantify and understand the factors that determine the surface abrasion performance of coated PC in rear window and backlight applications that have a wiper system. In the present study we describe Exatec's lab scale wiper testing equipment and test protocols. We also describe adaptation of optical imaging system to measure contrast and nano-profiling using nano-indenter, as post wiper surface characterization methods. These methods are more sensitive to fine scratches on glazing surface than standard haze measurement and mechanical profilometry. Three coating systems were investigated; Siloxane wetcoat (A), Siloxane wetcoat (B), and Siloxane wetcoat (B) plus plasma coat (Exatec� E900 coating). The performance comparisons were made using all these surface characterization methods.

This technical paper collection discusses optical techniques; digital correlation; holography; shearography; nondestructive testing.

Abstract Based on the characteristics of high strength and modulus of carbon fiber-reinforced composite (CFRP), in this article, the CFRP material was used to replace the steel material of the automobile’s B-pillar inner and outer plates, and the three-stage optimization design of the lamination structure was carried out. Firstly, this article used the principle of equal stiffness replacement to determine the thickness of the carbon fiber B-pillar inner and outer plates, and the structural design of the replaced B-pillar was also carried out. Secondly, on the basis of the vehicle collision model, the B-pillar subsystem model was extracted, and the material replacement and collision simulation were carried out.

Abstract Real-time reconstruction of 3D environment attributed with semantic information is significant for a variety of applications, such as obstacle detection, traffic scene comprehension and autonomous navigation. The current approaches to achieve it are mainly using stereo vision, Structure from Motion (SfM) or mobile LiDAR sensors. Each of these approaches has its own limitation, stereo vision has high computational cost, SfM needs accurate calibration between a sequences of images, and the onboard LiDAR sensor can only provide sparse points without color information. This paper describes a novel method for traffic scene semantic segmentation by combining sparse LiDAR point cloud (e.g. from Velodyne scans), with monocular color image. The key novelty of the method is the semantic coupling of stereoscopic point cloud with color lattice from camera image labelled through a Convolutional Neural Network (CNN).

Abstract In this paper, an efficient lane detection using deep feature extraction method is proposed to achieve real-time lane detection in diverse road environment. The method contains three main stages: 1) pre-processing, 2) deep lane feature extraction and 3) lane fitting. In pre-processing stage, the inverse perspective mapping (IPM) is used to obtain a bird's eye view of the road image, and then an edge image is generated using the canny operator. In deep lane feature extraction stage, an advanced lane extraction method is proposed. Firstly, line segment detector (LSD) is applied to achieve the fast line segment detection in the IPM image. After that, a proposed adaptive lane clustering algorithm is employed to gather the adjacent line segments generated by the LSD method. Finally, a proposed local gray value maximum cascaded spatial correlation filter (GMSF) algorithm is used to extract the target lane lines among the multiple lines.

Abstract The high-frequency noise issue is one of the most significant noise, vibration, and harshness problems, particularly in battery electric vehicles (BEVs). The sound package treatment is one of the most important approaches toward solving this problem. Owing to the limitations imposed by manufacturing error, assembly error, and the operating conditions, there is often a big difference between the actual values and the design values of the sound package components. Therefore, the sound package parameters include greater uncertainties. In this article, an uncertainty analysis method for BEV interior noise was developed based on an interval model to investigate the effect of sound package uncertainty on the interior noise of a BEV. An interval perturbation method was formulated to compute the uncertainty of the BEV’s interior noise.

Abstract The dynamic characteristics of tires are critical in the overall vibrations of vehicles because the tire-road interface is the only medium of energy transfer between the vehicle and the road surface. Obtaining the natural frequencies and mode shapes of the tire helps in improving the comfort of the passengers. The vibrational characteristics of structures are usually obtained by performing conventional impact hammer modal testing, in which the structure is excited with an impact hammer and the response of the structure under excitation is captured using accelerometers. However, this approach only provides the response of the structure at a few discrete locations, and it is challenging to use this procedure for rotating structures. Digital Image Correlation (DIC) helps in overcoming these challenges by providing the full-field response of the structure.