Prof. Dr. Adnan Shaout
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ACIT'2024 will be held in Zarqa University, December 10-12, 2024 -Zarqa, Jordan
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Full professor in the Electrical and Computer Engineering Department, he will address the title:
Real-Time Advanced Driver Assistance Systems.
Professor A. Shaout received his B. S., M. S. and Ph. D. degrees in 1982, 1983, and 1987 from Syracuse University respectively. Since 1987, he has been with the University of Michigan - Dearborn, where he is currently a full professor in the Electrical and Computer Engineering Department. His current research interests are in the areas of applications of fuzzy set theory, computer design (hardware & software), intelligent Systems, image processing and pattern recognition.
Abstract
Every year, automobile manufactures spend millions in funding development of cutting edge technologies to keep drivers safe and accident free while operating their vehicles. Number of cars sold each year is more than 60 million and continues to grow. Active safety systems are increasingly attracting the attention within the automotive industry because more and more people realize the importance of the driving safety. Passive safety elements (seat belt, air-bags etc.) can only reduce the injuries and fatalities caused by the accidents but not avoid them. Active safety systems will help the driver control the vehicle to avoid accidents and enhance the driving experience under various road conditions and traffic patterns. This presentation will present the following:
• Multiple forms of Advanced Driver Assistance Systems and will give detailed overviews of past, present and future designs of each variant.
• A technology survey on the state of the art fuzzy control applications for automotive active safety systems will also be presented focusing on the fuzzy technique used within the modern active safety systems. We will show how the fuzzy control is applied to those systems and the advantage of using the fuzzy comparing to the classic control methods.
• A fuzzy logic based prediction algorithm is also developed which predicts when a driver will use cruise control in their automobile. The fuzzy system reads vehicle speed, the smoothness of vehicle speed, the delta speed from the current speed limit and estimates likelihood of cruise control usage. Over 1700 km of real world driving data was recorded.