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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. Driving simulator is a key component of automotive interactive design, which can provide objective data to support both the effectiveness of design and user experience. On the other hand, driving simulator and the design of its experiments are major challenges, as improper experiment design will lead to consequences such as failure in identifying designing errors of the interactive design itself.

The ability to write concise and unambiguous reports, proposals, manuals, or other technical documents is a key skill for any high-functioning engineer or technical staff person in the mobility industries. Through a combination of class discussions, interactive workshop activities, assignments, checker teams (review teams) and job aids, this course delivers real-life technical writing techniques and tools that can be immediately applied. Participants discover the importance of knowing their audiences and how to communicate technical information in a 'user-friendly' style.

This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. This course serves a dual purpose: it delves into fundamental DFMEA principles and their practical applications while also offering guidance on leading DFMEA teams. Participants will be introduced to crucial FMEA concepts, along with the theoretical foundations before exploring how to implement these concepts in their DFMEA endeavors. Often, the FMEA process can become a mere replication of past efforts, which poses risks for both organizations developing the products under scrutiny and the end-users.

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 course will enable the learner to apply the fundamental principles behind safety of machine learning to a wide range of applications. The course guides learners through an appropriate selection of methods and tools tailored to the learner’s specific projects. With the acquired knowledge the learner will be able to shape the development and assessment of ML-based safety-related functions enabling their teams to leverage the power of advanced ML techniques without undermining safety.

This course highlights the technologies enabling ADAS and how they integrate with existing passive occupant crash protection systems, how ADAS functions perceive the world, make decisions, and either warn drivers or actively intervene in controlling the vehicle to avoid or mitigate crashes. Examples of current and future ADAS functions, and various sensors utilized in ADAS, including their operation and limitations, and sample algorithms, will be discussed and demonstrated. The course utilizes a combination of hands-on activities, including computer simulations, discussion and lecture.

Why a Management Academy? Why should you be interested in this Engineering Management Academy from SAE? The answer to these questions lies in the statistics highlighted by surveys of hiring managers. For example, are you aware that: 28% of internal leadership promotions fail On average, it takes six years before an individual receives any formal training after being promoted to a management position Individual contributors, who are technical experts, are usually natural candidates for  promotions to management positions.

"Spotlight on Design" features video interviews and case study segments, focusing on the latest technology breakthroughs. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing costs, improving quality, safety or environmental impact, and achieving regulatory compliance. Sensors are essential to the safety, efficiency, and dependability of modern vehicles. Crash sensors can anticipate a collision faster than humans would, and tire pressure sensors can alert the driver or pilot in case action is needed. In the episode "Sensors: Advanced Safety" (20:36) Continental engineers look at the evolution of passive safety systems, discuss the changes in sensors over the last ten years and what is coming next. Engineers at Meggitt demonstrate how tire pressure monitoring system sensors for aerospace are built and tested.

"Spotlight on Design" features video interviews and case study segments, focusing on the latest technology breakthroughs. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing cost, improving quality, safety or environmental impact, and achieving regulatory compliance. In the episode "Automated Vehicles: Sensors and Future Technologies" (24:31), highly automated driving is looked at in detail as the culmination of years of research in automotive technology, sensors, infrastructure, software, and systems integration. Real-life case studies show how organizations are actually developing solutions to the challenge of making cars safer with less driver intervention. IAV Automotive Engineering demonstrates how a highly automated vehicle capable of lane changing was created.

"Spotlight on Design: Insight" features an in-depth look at the latest technology breakthroughs impacting mobility. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing cost, improving quality, safety or environmental impact, and achieving regulatory compliance. Automated driving is made possible through the data acquisition and processing of many different kinds of sensors working in unison. Sensors, cameras, radar, and lidar must work cohesively together to safely provide automated features. In the episode "Automated Vehicles: Converging Sensor Data" (8:01), engineers from IAV Automotive Engineering discuss the challenges associated with the sensor data fusion, and one of Continental North America’s technical teams demonstrate how sensors, radars, and safety systems converge to enable higher levels of automated driving.

"Spotlight on Design" features video interviews and case study segments, focusing on the latest technology breakthroughs. Viewers are virtually taken to labs and research centers to learn how design engineers are enhancing product performance/reliability, reducing cost, improving quality, safety or environmental impact, and achieving regulatory compliance. In the episode "Diagnostics and Prognostics: Proactive Maintenance and Failure Prevention" (21:04), Delphi engineers explain how they leverage the growing number of sensors and computing power in vehicles to diagnose and proactively solve emerging mechanical or electronic problems, before a breakdown occurs. This video also looks at the next generation of automotive telematics, with HEM Data demonstrating how in-vehicle data acquisition is used to monitor the inner workings of vehicles.

Auto manufacturers have known and surveys confirm that consumers require short payback periods (2-4 years) for investments in fuel economy. Using societal discount rates, engineering-economic generally find substantial potential to increase fuel economy, cost-effectively. This phenomenon, often referred to as the ?energy paradox?, has been observed in nearly all consumers? choices of energy-using durable goods. Loss aversion, perhaps the most well established theory of behavioral economics, provides a compelling explanation. Engineering economic analyses generally overlook the fact that consumers? investments in fuel economy are not sure things but rather risky bets. Future energy prices, real world on-road fuel economy, and many other factors are uncertain. Loss aversion describes a fundamental human tendency to exaggerate the potential for loss relative to gain when faced with a risky bet. It provides a sufficient explanation for consumers?

When vehicles share certain information wirelessly via Dedicated Short Range Communications (DSRC), they enable a new layer of electronic vehicle safety that, when needed, can generate warnings to drivers and even initiate automatic preventive actions. Vehicle location and velocity provided by Global Navigation Systems (GNSS), including GPS, are key in allowing vehicle path estimation. GNSS is effective in accurately determining a vehicle's location coordinates in most driving environments, but its performance suffers from obstructions in dense urban environments. To combat this, augmentations to GNSS are being contemplated and tested. This testing has been typically done using a reference GNSS system complimented by expensive military-grade inertial sensors, which can still fail to provide adequate reference performance in certain environments.

Moir� method is useful to measure the shape and the whole-field distributions of displacement and strain of structures. There are many kinds of moir� methods such as geometric moir� method, sampling moir� method, Fourier transform moir� method, moir� interferometry, shadow moir� method and moir� topography. Grating method analyzing directly deformation of a grating without any moir� fringe pattern is considered as an extended technique of moire method. Phase analysis of the moire fringe patterns and the grating patterns provides accurate measurements of shapes or displacement and strain distributions. Some applications of these moir� methods and grating methods to dynamic shape and strain distribution measurements of a rotating tire, sub-millimeter displacement measurements from long distance for landslide prediction, real-time shape measurements with micro-meter order accuracy, etc. are shown. Presenter Yoshiharu Morimoto, Moire Institute Inc.

Nissan Motor Company has recently released the �Nissan Green Program 2016� which is a six-year action plan embodying the company�s environmental philosophy: Symbiosis of People, Vehicles and Nature. One of the key activities of this Program is the successful penetration of Zero-Emission Vehicles into the market which includes electric vehicle (EV) cumulative sales of 1.5M units with our Alliance partner Renault, introduction of a fuel cell electric vehicle (FCEV) into the market, taking a global leadership in supplying batteries for electric drive and creating zero-emission societies. This presentation will highlight some of these key activities. Presenter Kev Adjemian, Nissan Technical Center NA

These advanced checks have resulted in development of many new diagnostic monitors, of varying types, and a whole new internal software infrastructure to handle tracking, reporting, and self-verification of OBD related items. Due to this amplified complexity and the consequences surrounding a shortfall in meeting regulatory requirements, efficient and thorough validation of the OBD system in the powertrain control software is critical. Hardware-in-the-Loop (HIL) simulation provides the environment in which the needed efficiency and thoroughness for validating the OBD system can be achieved. A HIL simulation environment consisting of engine, aftertreatment, and basic vehicle models can be employed, providing the ability for software developers, calibration engineers, OBD experts, and test engineers to examine and validate both facets of OBD software: diagnostic monitors and diagnostic infrastructure (i.e., fault memory management).

Learn how the U.S. Department of Energy's Clean Cities Program can help with the deployment of alternative fuel and advanced technology school buses. Presenter Mark S. Smith, US Department of Energy

Propane autogas, the world?s third most-used engine fuel, powers vehicles, transit buses, and now school buses. Blue Bird has recently launched the Next Generation Vision type C school bus, powered by a ROUSH CleanTech liquid propane autogas fuel system and a Ford 6.8L V10 engine. The bus reduces operating costs by up to 40%, greenhouse gas emissions by up to 24%, and maintains the factory horsepower, torque, and towing capacity ratings. Learn about how school districts are saving over $.30 / mile using this clean, domestically-produced fuel. Presenter Brian Carney, Roush CleanTech.