Machine Learning Based ADAS Antenna Array Design and Optimization for V2V Communication
Advanced Driving Assistance Systems (ADAS) is an integral part of modern automobiles that are responsible for providing a safe and reliable driving experience. Over the last decade, automotive industries have invested significant resources in the development of reliable and efficient ADAS system. A key component of the ADAS system is the communication module that houses the ADAS antenna. A combination of series and parallel fed patch antenna array operating at 77 GHz is the most common ADAS antenna that is being widely used in the automotive industry. In the video below, workflow is presented for designing a 40 element patch antenna array operating at 77 GHz using machine learning techniques. For this purpose, a combination of Altair's tools, Feko (High Frequency Electromagnetics Tool) and HyperStudy (Multidisciplinary optimization tool) are used to realize the design. This is followed by a case study that uses the machine learning optimized antenna on a vehicle to show a V2V communication scenario in Altair's wave propagation tool WinProp.