Aimsun unveils new platform for simulating a driverless future
ITS (UK) member Aimsun has unveilled a new product: Aimsun Auto, a software platform for large-scale design and validation of path planning algorithms for self-driving vehicles.
When used in combination with sensor testing tools and vehicle dynamics simulation tools, Auto provides a test harness that is full-stack, highly automated and infinitely scalable.
Auto allows test vehicles to drive inside entire digital cities — perfect virtual copies of our transportation networks — where users can safely explore the limits of autonomous vehicle technology. In Auto, you can synthetically generate, execute, and analyse tens of thousands of scenarios, making it exponentially more efficient and wider-ranging than any methodology based on field data.
“With Auto there is no need to drive around seeking the conditions that you want to test, or to laboriously script each actor’s behaviour frame-by-frame. Scale and speed are of the essence,” said Paolo Rinelli, Global Head of Product Management at Aimsun. “Auto can execute thousands of concurrent instances much faster than real time on private or commercial cloud infrastructure, effectively covering the equivalent of millions of autonomous miles overnight. It’s fast, it’s infinitely scalable and, most importantly, it’s safe.”
Auto is a perfect complement to sensor testing tools and driving simulation software, being able to integrate seamlessly into a testing environment and providing a scenario generation engine to cater for both ordinary and non-compliant situations.
“Path planning design and validation is a key element of autonomous vehicle testing,” says Rinelli. “You can run all the sensor tests in the world, but that won’t make your AV any better at, say, merging onto a highway.”
Unlike trajectory analysis and scripted scenario creation, Aimsun Auto is the perfect tool for analysing edge cases: traffic violations such as rolling stops, running red lights, jaywalking or speeding – even the often cited moral dilemma of an autonomous car ‘choosing’ who to spare in a fatal accident.