Since automated emergency braking (AEB) was first introduced, initially to prevent a collision with a slower or stopped vehicle ahead, it has been enhanced in many cases to recognise much more - pedestrians and cyclists, for example.

Ansible Motion's director, Kia Cammaerts, believes that while the technology has a number of convenience benefits, mandating automated emergency braking on all vehicles could eliminate the majority of road accidents. "If it were standard on all new vehicles, we would probably eliminate 80% of all road accidents without any further advances towards fully autonomous vehicles," he said.

There’s a uniquely human aspect to testing and developing new cars. Despite the quantifiable data available, a human driver is arguably the ultimate arbiter of how well a car handles and performs. Beyond subjective appeal, cars also have to be robust to withstand the unpredictable nature of human drivers. That’s a challenging element to model in a virtual world.

Among the numerous possibilities a fully autonomous vehicle will promise, maybe the most attractive selling point for the general public is the ability to turn on, tune in, and drop out.  However, the exciting prospect of reading, working or watching TV as the car transports occupants without the requirement of human control comes with one caveat: the issue of motion sickness. 

Steve, an ace apprentice, spent time with Ansible Motion, helping to design and build driving simulators while traveling the world. This is no ordinary apprenticeship. So, how is it possible? 

A Driver in the Loop (DIL) simulator is a mechanism for creating an immersive automotive environment for real people. If a simulator can create an illusion that is so convincing that a driver responds as if they were in a real car, then it an be a very useful and cost-effective tool for human factor studies, vehicle engineering work and/or fundamental research. 

Phil Morse from Ansible Motion explains why humans will still have a significant role to play in the development of autonomous and ADAS technologies

With the costs to develop any new vehicle easily reaching a billion dollars, car makers are naturally keen to uncover savings in their R&D budgets. With increasing emissions and safety regulations, the sheer diversity of legislation across the globe, and autonomous cars just around the corner in development terms, the cost problem isn’t going away anytime soon.

Paul Bray explains the key differences between visualisation and simulation and how AV technology is allowing an industry sector to design and test solutions to the highest standards.

The introduction of autonomous vehicles will bring a lot of uncertainty for drivers, workshop engineers and automotive manufacturers alike - and time is soon running out, as car makers are promising full hands-off SAE Level-4 autonomy as soon as 2021. 

With the costs to develop any new vehicle easily reaching a billion dollars, car makers are keen to uncover savings in R&D budgets. With increasing emissions and safety regulations, the diversity of legislation across the globe, and autonomous cars just around the corner in car development terms, the cost problem isn’t going away anytime soon.

In response to the costs of testing, OEMs and tier ones are increasing their use of simulation tools to undertake an ever increasing amount of the validation. Simulation, at first glance, offers obvious benefits; producing fewer development cars – typically costing $1m for a first prototype – and shaving this from a programme by introducing virtual sign-offs naturally appeals to programme managers.

Over the past two decades increasingly powerful simulators have revolutionised car design and development. Now, tools built to hone circuit performance are being utilised to spearhead the design of the automated road cars of the future.