ELECTRICAL/ELECTRONICS AND ELECTRONIC SYSTEMS
• Operation / Functionality of Various HAV Capabilities −− Blind spot warning −− Backup assist / cross traffic warning −− Lane departure warning −− Lane keep assist −− Cruise control −− Adaptive cruise control −− Cooperative adaptive cruise control −− Forward collision warning −− Automatic emergency braking −− Pedestrian detection −− Collision imminent steering −− Do not pass warning −− Left turn assist −− Intersection movement assist −− Emergency electronic brake light −− Traffic sign recognition −− Traffic jam assist −− Auto park / park assist −− Platooning • SAE Level of Automation Corresponding to Each Application • Advantages and Limitations of Each Capability • Sensor(s) used in Each Capability • Technology Spread and Effects on Insurance Claims DAY TWO • Sensors: Active and Passive • Operating Principles, Performance, Advantages and Limitations of Various Sensors Used in HAV Capabilities −− GPS −− GLONASS −− IMU −− Gyros −− Cameras - monocular, stereo, monochrome (grayscale), color, CCD, CMOS −− Ultrasonic −− Radar −− Lidar −− Leddar −− Matrix TOF camera −− DSRC • Sensor Recalls • Sensor Fault Detection and Diagnostics • ECU Consolidation • Algorithms −− Types (classifications) of Algorithms −− Algorithm Examples - Haversine, Kalman filter, particle filter, neural net, SLAM −− Using ROC Analysis to Measure Algorithm Performance • Testing Processes Used in the Development of HAV Systems • Statistics Driving Vehicle Testing • Why Software Can Never be “Fully” Tested • Different Testing Approaches, and Their Strengths and Weaknesses
Learning Objectives By attending this seminar you will be able to: • Explain the SAE Levels of Automation and where different ADAS functions fit in the hierarchy • Explain the ADAS functions and articulate their limitations • Identify different sensors used in advanced driver assistance systems, how they operate, and their limitations • Analyze how different sensors can be combined to improve overall system performance • Describe the current and future methodologies used in developing ADAS algorithms • Articulate how ROC curves, DOE and Monte Carlo techniques can be used to measure and improve algorithm performance • Critically examine the proposed federal rules and validation methods for advanced driver assistance systems • Analyze how active safety systems may affect the performance of existing passive occupant safety systems and how integration of the systems might be accomplished • Describe liability and policy considerations for OEM’s and Tier suppliers Who Should Attend This course is designed for all professionals - technical or managerial - who are involved either directly or indirectly with vehicle safety performance. Professionals in legal and regulatory and compliance areas concerned with proposed NHTSA rulemaking, and insurance industry analysts developing coverage standards for vehicles with active safety technologies will also find this course useful. Prerequisites An engineering undergraduate degree in any discipline would be beneficial. Topical Outline DAY ONE • The Role of Vehicle Automation in Reducing Traffic Fatalities −− Passive safety highly optimized −− Recent increase in vehicle crash rates • Three Main Functions Provided by Highly Automated Vehicles (HAVs) −− Increase situational awareness −− Provide proactive driver warnings −− Intervene to prevent / mitigate crashes where driver response is late or non- existent (distracted driver) • Sensors Used in Highly Automated Vehicles • Current Development Efforts and Market Leaders • Levels of Automation −− BASt −− NHTSA −− SAE (Prior to September 2016) −− SAE (September 2016 Operational Driving Domain revision) −− Comparison of the Three Versions −− Level 3 Handoff Problem
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3 ways to get a no-obligation price quote to deliver a course to your company: Call SAE Corporate Learning at +1.724.772.8529 | Fill out the online quote request at sae.org/corplearning | Email us at corplearn@sae.org
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