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This course is verified by Probitas as meeting the AS9104/3A requirements for Continuing Professional Development. Problems arise in all facets of life. This is particularly true in the business world. Problems impact all aspects of an organization’s operations such as; product development, product quality, process efficiency, marketing efforts, human relations, leadership efforts, financial execution and ultimate profitability. If these problems are not addressed, they inhibit the operation of the business and can eventually result in total failure.

There is a growing interest in the concept of a smart city and how these advanced technologies will improve the quality of living and make a city more attractive to visitors, commerce and industry. This course fills an unmet need for defining and explaining the relationship between connected and autonomous vehicles (CAVs) and smart city transportation. It is apparent that CAVs will achieve the best results when integrated with current and emerging urban infrastructure for transportation. This course addresses such integration from technology, organizational, policy and business model perspectives.

This course provides an overview of state-of-the-art intelligent vehicles, presents a systematic framework for intelligent technologies and vehicle-level architecture, and introduces testing methodologies to evaluate individual and integrated intelligent functions. Considering the increasing demand for vehicle intelligence, it is critical to gain an understanding of the growing variety of intelligent vehicle technologies and how they must function together effectively as a system.

There is been tremendous progress in the application of technology and artificial intelligence to connected and autonomous vehicles. At the same time, there have been considerable advances in data science and data analysis that allows large data sets to be managed for results. This course introduces big data and analytics, focusing on how these will be applied to data generated by autonomous and connected vehicles. These technologies will be explained within the context of a smart city.

Vehicle cybersecurity vulnerabilities could impact a vehicle's safe operation. Therefore, engineers should ensure that systems are designed free of unreasonable risks to motor vehicle safety, including those that may result due to existence of potential cybersecurity vulnerabilities. The automotive industry is making vehicle cybersecurity an organizational priority.

Crash reconstruction is a scientific process that utilizes principles of physics and empirical data to analyze the physical, electronic, video, audio, and testimonial evidence from a crash to determine how and why the crash occurred. This course will introduce this reconstruction process as it gets applied to various crash types - in-line and intersection collisions, pedestrian collisions, motorcycle crashes, rollover crashes, and heavy truck crashes. Methods of evidence documentation will be covered. Analysis methods will also be presented for electronic data from event data recorders and for video.

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.

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 has been developed in cooperation with TÜV SÜD. The certification concept behind the training comprises a multi-stage qualification and is characterized by a high level of practical bearing. The focus of this training is on the cybersecurity lifecycle for automotive products. In addition to a brief refresher on the content of the standard, important aspects of ISO/SAE 21434 that play an important role along the automotive lifecycle are discussed in detail. Starting with the topic "Culture & Competence", through cybersecurity planning to audits and assessments and post-development activities.

The ever-increasing networking and automation of vehicles make cybersecurity a core requirement for future vehicles and their components. Automobile manufacturers and suppliers are confronted with new requirements that address the cybersecurity of vehicle IT/OT. This certification, created in partnership between SAE International and TÜV SÜD, provides the necessary basic knowledge for people who work in the field of automotive cybersecurity, management, engineering, and auditing. Course participants will gain an understanding of the current challenges in the automotive industry and the relevance and importance of cybersecurity.

"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. Fuel efficiency, or simply put, how to get more mileage out of the same amount of fuel has become one of the main goals to be achieved by new automotive technologies in the future, thanks in part to new government regulations. In the episode "Fuel Efficiency: Racing toward CAFE 2025" (21:24) AVL engineers show simulation and testing being used to design more fuel efficient vehicles, including the equipment that actually analyzes fuel economy.

"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. As global concerns about the negative consequences of greenhouse gases on the environment increase, regulatory agencies around the world are taking serious steps to address the issue of tailpipe emissions In the episode "Fuel Efficiency: Fuel Economy Testing" (12:01), engineers at the EPA’s National Vehicle and Fuel Emissions Laboratory demonstrate how different vehicles are tested for emissions, and AVL’s technical team shows how accurate tailpipe emissions can be measured and reported.

"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.

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).

ECOtality North America, in partnership with the Idaho National Laboratory (INL), Nissan North America, General Motors, and over 40 government, electric utility, and private organizations, has launched a large-scale demonstration of electric vehicle charging infrastructure. This demonstration, called The EV Project, will deploy more than 15,000 level 2 and DC fast chargers in private residence, commercial, and public locations in seven market areas in Arizona, California, Oregon, Tennessee, Texas, Washington state, and Washington, D.C. The EV Project will also include a total of 5,700 Nissan Leaf battery electric vehicles and 2,600 Chevrolet Volt extended range electric vehicles, operated by consumers and fleets in each of the market areas. This demonstration, which is funded by the U.S. Department of Energy�s (DOE) Vehicle Technologies Program, represents the largest ever deployment of electric vehicles and charging infrastructure.

There are many macro drivers that are creating opportunities for transportation electrification. They include the environment, dependence on foreign oil, national security, battery technology and government incentives to name a few. In light of this growing momentum consumers will have choices to where they can charge ? at home, workplace or publicly. Electrical vehicle supply equipment will drive value throughout the supply chain ? installer, building owner, automaker, suppliers, utilities and consumers. Market acceptance will occur when consumer?s needs and wants are met. To meet these needs access to products through multiple channels will be required. Presenter Manoj Karwa, Leviton Manufacturing Co. Inc.

Career development is no longer something you focus on in your twenties and are set for life, it is ongoing and constant. New technologies, globalization and the world-wide competition for jobs demand that we continue to grow our skills and knowledge throughout our life. This session will provide you with tools to help you meet this demand as an engineering professional. Participants will create a personal mission statement and set career goals, identify the best way to research new opportunities and build their network while also crafting a personal brand with consistent messaging. Organizer Martha Schanno, SAE International Panelist Caryn Mateer, Transformational Leaders Intl. Kathleen Riley, Transformational Leaders Intl.

Edgewater Computer Systems Inc. product RTEdge Platform 1.2 is a software toolset supporting proof based engineering, implementation and deployment of software components, built using the RTEdge AADL Microkernel modeling subset. This is a small subset of the AADL component model and execution semantics, covering threads and thread-groups communicating solely through asynchronous event ports and through explicitly shared data ports. Threads behavior is expressed as state machines and dispatch run time semantics is encoded in a Run-time Executive, enforcing pre-emptive priority dispatch based on statically assigned event priorities, with ceiling priority protocol access to shared data. This simple AADL microkernel semantic core can support all dispatch policies, communication and synchronization mechanisms of a fully fledged AADL run time environment, permitting the systematic use of the RTEdge static analysis tools for AADL compliant software components.