Introduction to Highly Automated Vehicles

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.