Mohamed Hanafy Sayed Radwan, Chief Software Engineer and P2/P3 System Engineering Pre-Expert at Valeo Egypt. PhD, MSc, and BSc in Computer and Systems Engineering from Faculty of Engineering, Ain-Shams University in 2006, 2012, and 2015, respectively. My research is mainly focusing on Artificial Intelligence, Automotive Embedded Systems, and Digital Design Verification Methodologies. This is my research track regarding intelligent solutions for both Automotive and ASIC industry.
About the Talk
Advanced Driver-Assistance Systems – The Greatly Competitive Challenging Industry
Advanced driver-assistance systems, or ADAS, are systems to help the driver in the driving process. When designed with a safe human-machine interface, they should increase car safety and more generally road safety. Most road accidents occurred due to the human error. Advanced driver-assistance systems are systems developed to automate, adapt and enhance vehicle systems for safety and better driving. The automated system which is provided by ADAS to the vehicle is proven to reduce road fatalities, by minimizing the human error. Safety features are designed to avoid collisions and accidents by offering technologies that alert the driver to potential problems, or to avoid collisions by implementing safeguards and taking over control of the vehicle. Adaptive features may automate lighting, provide adaptive cruise control and collision avoidance, incorporate traffic warnings, connect to smart-phones, alert driver to other cars or dangers, lane departure warning system, automatic lane centering, or show what is in blind spots.
An increasing number of modern vehicles have advanced driver-assistance systems such as electronic stability control, anti-lock brakes, lane departure warning, adaptive cruise control and traction control. These systems can be affected by mechanical alignment adjustments. This has led many manufacturers to require electronic resets for these systems, after a mechanical alignment is performed, ensure the wheel aligner you are considering to allow you to meet these safety requirements.
There are many forms of ADAS available; some features are built into cars or are available as an add-on package. Also, there are aftermarket solutions available. ADAS relies on inputs from multiple data sources, including automotive imaging, LiDAR, radar, image processing, computer vision, and in-car networking. Additional inputs are possible from other sources separate from the primary vehicle platform, such as other vehicles, referred to as Vehicle-to-vehicle (V2V), or Vehicle-to- Infrastructure (such as mobile telephony or wifi data network) systems.
Advanced driver-assistance systems are one of the fastest-growing segments in automotive electronics, with steadily increasing rates of adoption of industry-wide quality standards, in vehicular safety systems ISO 26262, developing technology specific standards, such as IEEE 2020 for Image Sensor quality and communications protocols such as the Vehicle Information API.
Next-generation ADAS will increasingly leverage wireless network connectivity to offer improved value by using car-to-car (also known as Vehicle to Vehicle, or V2V) and car-to-infrastructure (also known as Vehicle to Infrastructure, or V2X) data.