Topics: Advanced Technologies
Every year, the U.S. on average, experiences more than 34,000 traffic deaths and over 5 million vehicle crashes. While the trend in traffic deaths has been generally downward for the past decade, most of this reduction has been the result of optimizing passive occupant crash protection systems such as seatbelts and airbags. Highly automated vehicle's (HAV's) offer the potential to significantly reduce vehicle crashes by perceiving a dangerous situation before the crash has occurred and supporting the human driver with proactive warnings and in some cases active interventions to avoid or mitigate the crash. Fully autonomous vehicles promise even greater benefits, such as increased mobility for elderly, visually-impaired, and other physically challenged individuals, reduced public infrastructure needs such as parking decks, and reduced environmental impact.
This course is designed to familiarize participants with the technologies enabling highly automated vehicles, and how they integrate with existing passive occupant crash protection systems. You will learn how HAV's 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 HAV functions, various sensors used, including their operation and limitations, and sample algorithms, will be discussed and demonstrated. The course also looks at the ethics driving HAV behavior, liability considerations and reviews the current and future regulatory landscape. The course uses a combination of lectures, class discussions, computer simulations, and videos.
By attending this class, you will be able to:
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.
An engineering undergraduate degree in any discipline would be beneficial.
You must complete all course contact hours and successfully pass the learning assessment to obtain CEUs.
Registration for the web seminar (live, online) is available on a per-person basis, similar to purchasing a seat in a classroom. The fee includes one connection to WebEx training center, using a PC with internet access and VoIP or a telephone,* and access to a secure course in the SAE Learning Center for presentations, supplemental materials, assignments, and learning assessment. To enjoy a more personalized experience, use of a webcam is encouraged.
*Global toll-free telephone numbers are provided for many countries outside the U.S., but are limited to those on the WebEx call-in toll-free number list. Check here to see if your country has a global call-in toll free telephone number for this web seminar. If your country is not listed, you may still connect using the US/Canada Call-in toll number or VoIP.
Although WebEx will automatically launch when you join the web seminar, you are encouraged to test your setup in advance of the course start date. Click here, then follow the onscreen instructions.
Jeff Blackburn is the Senior Product Sales Manager for Ansys Autonomy, the world’s largest supplier of simulation software. Prior to joining Ansys, Jeff worked on developing autonomous vehicle research platforms at Dataspeed, was a founding member of Metamoto who developed a massively scalable cloud-based simulation platform, and was the North American ADAS and Autonomous Vehicle subject matter expert for Siemens / Tass PLM Software, Inc. He has also held positions in controls and systems engineering with National Instruments, Takata, Fanuc Robotics, and Rockwell Automation. Jeff has organized and presented at numerous technical forums. He has been issued twenty-one U.S patents, primarily in the area of occupant safety. Jeff holds a B.S. in Engineering and a J.D. from the University of Akron.