New sim helps car makers understand how we will interact with autonomous cars
Latest Ansible Motion simulator generates millions of scenarios that allow real people to experience new automotive driver assistance technologies
A new simulator to help car makers better understand how drivers will cope with and respond to the rising number of driver assistance (ADAS) and autonomous (AI) automotive technologies has been revealed by Ansible Motion, an established provider to the automotive industry. The latest iteration of Ansible Motion’s multi-million-pound Delta Driver-in-the-Loop (DIL) simulator provides a safe and repeatable laboratory environment to test and validate the myriad ADAS systems that are increasingly being fitted (or proposed) to new cars.
With the driver assistance systems market set to grow to 70 billion USD by 2024, fuelled by vehicle manufacturers pushing toward increasing levels of autonomy to address emerging legislation, the issue of how real people might react to a car receiving more notifications – or even taking control – is one that car makers are investigating seriously.
To create the most immersive human simulation experiences - and therefore the most meaningful pre-validation results – Ansible Motion’s simulator lab in Hethel, Norfolk, has now added a number of new features, such as new cabin environments that reflect OEM styling and human interaction features and new software connectivity that allows deeper environment and sensor simulation, coupled with Ansible Motion’s proprietary motion, vision, and audio environment that ‘tricks’ drivers and occupants into believing they are experiencing a real vehicle and its ADAS or autonomous technologies.
This special type of driving simulator technology, pioneered by Ansible Motion, is far-removed from gaming “simulation” endeavours, and has been trusted for nearly a decade by top vehicle constructors in the US, Europe and Japan (Ford, GM and Honda, to name a few).
Cutting evaluation times from hundreds of years to months
With the ability to create and explore an incredible number of scenarios in a short amount of time, Ansible Motion’s simulator means engineers can conduct experimental variations that might consume a hundred years’ of testing time in the real world, within a few months. Examples include the validation of Autonomous Emergency Braking (AEB) systems that rely upon multiple sensor feeds and vehicle piloting logic algorithms to respond (in some cases, faster that human response capability!) to various situations such as traffic and pedestrian intrusions.
The need to validate international driver's expectations
Other system validation examples include lane departure warnings and assistance, intelligent speed adaption and driver monitoring for drowsiness and distraction. Ansible Motion's Kia Cammaerts cites a recent example of how drivers in the Chinese market expect different intervention cues for lane departure warning compared to their US counterparts. “There are cultural differences and expectations to respond to audible or visual warnings. Validating this in our simulator prevents frustration, dissatisfaction or confusion when vehicles deployed in different markets are required to interact in critical situations. With the burgeoning need to validate more and more driver assistance systems and autonomous functions, the number of possible scenarios grows every day,” says Cammaerts. “It’s, of course, impossible to validate every situation on a proving ground test track or in the real world: there simply isn’t time. And in the case of real-world testing, well, some experiments may be quite dangerous, putting people and equipment at risk.”