The Siemens Mustang Will Compete at the Goodwood Festival of Speed
Justin Lam — July 13, 2018 — Autos
References: cnet & digitaltrends
Autonomous vehicles are becoming more and more impressive, especially in the realm of racing, and a new Siemens Mustang will now be competing at the 2018 Goodwood Festival of Speed. This custom-built 1965 Ford Mustang was designed in collaboration with Cranfield University, a science and engineering school in England, and is completely retrofitted with a suite of autonomous technology. Siemens has not stated what type of hardware or software is powering the Siemens Mustang but it has noted that the location-scanning tech was provided by Bentley Systems.
Unlike other autonomous vehicle offerings, such as models from Waymo and Uber, the Siemens Mustang lacks any bulky radars, cameras and sensors. Instead, the autonomous Mustang features coaster-sized sensors on the hood and lid of the trunk.
Image Credit: Siemens
Unlike other autonomous vehicle offerings, such as models from Waymo and Uber, the Siemens Mustang lacks any bulky radars, cameras and sensors. Instead, the autonomous Mustang features coaster-sized sensors on the hood and lid of the trunk.
Image Credit: Siemens
Trend Themes
1. Retrofit Autonomous Vehicles - The development of retrofitting autonomous technology onto existing vehicles creates new opportunities for the automotive industry.
2. Autonomous Racing - The use of autonomous technology in racing presents opportunities for innovation and advancement.
3. Locational Scanning Technology - The use of locational scanning technology in autonomous vehicles creates potential for improved accuracy and safety.
Industry Implications
1. Automotive - The automotive industry can benefit from developing retrofit autonomous technology for existing vehicles.
2. Education - Educational institutions, such as Cranfield University, can play a role in developing and promoting advancements in autonomous technology.
3. Engineering - The engineering industry has opportunities to develop and implement locational scanning technology into various applications, including autonomous vehicles.
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