Feature: Software
Avionics successes at the heart of autonomous vehicles
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By Ian Ferguson, Vice President, Marketing and Strategic Alliances, Lynx Software System architectures are being re-
e are seeing exciting and innovative work in autonomous cars, especially around Level
4, where the car is in complete control of certain parts of the driving. It is helpful to think about convergence between automotive systems and avionics: autonomous vehicles can combine the extraordinarily successful safety culture of aviation, where even one accident is unacceptable, and the extraordinary fl exibility and aff ordability of the automobile.
System architecture Achieving this fl exibility demands a major focus on driving down costs, vehicle weight and the volume of electronics on board cars. Aſt er the engine, the electronics and wiring harness are the most expensive and heaviest parts of a vehicle.
evaluated to deliver a tenfold reduction of cabling lengths, from the current 1.5+ kilometres. Instead of the traditional approach of creating diff erent domains for various data networking protocols, we are seeing zonal architectures, where high- performance controllers manage many functions in sections of the vehicle. Hence, we are seeing: a) Ethernet to connect subsystems inside the vehicle – some are even evaluating 10Gb technology here;
b) A consolidation of processing functionality into fewer, very high- performance electric control units (ECUs). T e range of networks inside the car
includes the controller area network (CAN) – which takes care of the powertrain and related functions; local interconnect network (LIN) – for passenger/driver comfort functions like climate control, lighting, seat adjustment; media-oriented system transport (MOST),
48 September/October 2020
www.electronicsworld.co.uk
developed for infotainment; and FlexRay for anti-lock braking (ABS), electronic power steering (EPS) and vehicle stability functions. Each network must be highly secure, to reduce the “attack surface” for potential hackers. Attack surface of a soſt ware environment is the sum of diff erent points where a hacker could extract or insert data. For example, simple sensors that send encrypted information to a centralised node need their security improved locally and at the central point. It is obvious that these nodes are processing traffi c with very diff erent response requirements. T e challenge is how to implement this in
a vehicle where certain systems are mission- critical and need addressing in microseconds. T e self-driving vehicles on the road today are eff ectively servers on wheels. Intel Xeon + nVidia platforms deployed in prototypes will most likely be ousted in favour of solutions that fi t signifi cantly smaller footprints, costs and power envelopes – and that race is on between companies!
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