Visteon Corporation’s (NYSE: VC) new technical center in Silicon Valley will lead the company’s development of artificial intelligence for autonomous vehicles. Visteon’s breakthrough autonomous vehicle program will apply machine learning technology for accurately detecting and classifying objects in a vehicle’s path and planning the vehicle’s movements, resulting in fully trained driving control systems.
The recently opened facility in Santa Clara, California, will work closely with global Visteon tech centers to develop excellence in artificial intelligence software, advanced driver awareness systems (ADAS) and deep machine learning. These efforts will support Visteon’s approach to autonomous driving, which encompasses three key elements:
* Creating fail-safe, centralized domain controller hardware leveraging Visteon’s industry-first cockpit domain controller, Smartcore™.
* Unlocking the innovation potential of algorithm developers through an easy-to-access open framework and test/simulation environment.
* Applying artificial intelligence for object detection, classification, perception and decision-making in future autonomous vehicles.
“Most current advanced driver assistance systems based on radar and cameras are not capable of accurately detecting and classifying objects – such as cars, pedestrians or bicycles – at a level required for autonomous driving,” said Sachin Lawande, president and CEO of Visteon, a leading global cockpit electronics supplier. “We need to achieve virtually 100 percent accuracy for autonomous driving, which will require innovative solutions based on deep machine learning technology. Our Silicon Valley team, with its focus on machine learning software development, will be a critical part of our autonomous driving technology initiative.”
Visteon’s recently opened facility in the heart of Silicon Valley will house a team of engineers specializing in artificial intelligence and machine learning. The center is located close to the West Coast offices of various automakers and tech companies, as well as Stanford University and the University of California, Berkeley – two of the leading universities for artificial intelligence and deep learning in the U.S.
In addition to leading Visteon’s artificial intelligence efforts, the Silicon Valley office will play a key role in delivering control systems, localization and vision processing – interpreting live camera data and converting it to information required for autonomous driving. Visteon is targeting launching its first autonomous driving domain controller platform in 2018.
Leading Visteon’s artificial intelligence effort based in Silicon Valley is Vijay Nadkarni, who joined Visteon earlier this year from Chalkzen, Inc., where he developed and launched a revolutionary SaaS (software as a service) and connected car services platform.
Visteon has been continually expanding its resources to support development of next-generation ADAS development and autonomous driving. On April 1, Markus Schupfner joined the company as chief technology officer, bringing more than 20 years of experience leading software development for global automotive suppliers. Visteon recently announced that Matthias Schulze will join the company in January 2017 from Daimler AG; he will lead Visteon’s ADAS development, including overseeing the Silicon Valley facility.
Visteon is a global company that designs, engineers and manufactures innovative cockpit electronics products and connected car solutions for most of the world’s major vehicle manufacturers. Visteon is a leading provider of instrument clusters, head-up displays, information displays, infotainment, audio systems, telematics solutions and SmartCore™ cockpit domain controllers. Visteon also supplies embedded multimedia and smartphone connectivity software solutions to the global automotive industry. Headquartered in Van Buren Township, Michigan, Visteon has approximately 10,000 employees at more than 40 facilities in 18 countries. Visteon had sales of $3.25 billion in 2015. Learn more at www.visteon.com <http://www.visteon.com/> .