Skip to main content

Aimsun unveils test platform for AVs in digital cities

Aimsun has released a software platform for the large-scale design and validation of path planning algorithms for autonomous vehicles (AV). The company says Aimsun Auto allows test vehicles to drive inside digital cities - virtual copies of transportation networks, where users can safely explore the limits of AV technology. Paolo Rinelli, global head of product management at Aimsun, says Auto removes the need to drive around seeking conditions that users want to test or to “script each actor’s behaviour
May 24, 2019 Read time: 2 mins
16 Aimsun has released a software platform for the large-scale design and validation of path planning algorithms for autonomous vehicles (AV).


The company says Aimsun Auto allows test vehicles to drive inside digital cities - virtual copies of transportation networks, where users can safely explore the limits of AV technology.

Paolo Rinelli, global head of product management at Aimsun, says Auto removes the need to drive around seeking conditions that users want to test or to “script each actor’s behaviour frame-by-frame”.

“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,” he adds.

The solution is expected to complement sensor testing tools and driving simulation software, being able to integrate into a test environment and providing a scenario generation engine ordinary and non-compliant solutions.

It can be used analyse traffic violations such as rolling stops, running red lights, jaywalking or speeding as well as the dilemma of an AV ‘choosing’ who to spare in a fatal accident, the company adds.

Artificial intelligence start-ups can use Auto to validate the development of the AV stack – domain controllers which handle perception, decision and control. Government regulators can use the platform to test and authorise the deployment of AVs on public roads while AV test tracks can utilise Auto to generate synthetic traffic for testing AVs in an augmented reality environment.

According to Rinelli, Auto allows users to “run wide-area regression tests t ensure that a new release of autonomy stack continues to meet prior safety standards”.

The platform also provides estimates on overall journey time, emissions profile, energy consumption and smoothness of ride for door-to-door trips, Rinelli concludes.

Related Content

  • August 7, 2019
    Aimsun unveils test platform for AVs in digital cities
    Aimsun has released a software platform for the large-scale design and validation of path-planning algorithms for autonomous vehicles (AVs). The company says Aimsun Auto allows test vehicles to drive inside digital cities - virtual copies of transportation networks, where users can safely explore the limits of AV technology. Paolo Rinelli, global head of product management at Aimsun, says Auto removes the need to drive around seeking conditions that users want to test or to “script each actor’s behaviou
  • May 10, 2023
    Scaling up road safety analysis with Aimsun cloud simulation
    Synthetic generation, execution, and analysis of thousands of road safety scenarios is exponentially more efficient and wider ranging than any methodology based on field data. Marcel Sala & Jordi Casas of Aimsun examine the benefits of cloud simulation for safety testing
  • December 14, 2021
    AWS enhances Aurora AV system 
    AWS supports millions of virtual tests to validate the capabilities of the Aurora Driver 
  • June 17, 2019
    How MaaS and AVs can cut Oslo traffic
    A new study shows that on-demand AVs and MaaS together could make a significant difference to traffic in Oslo, Norway – but only if ride-share is involved too If you replace today’s traditional private car ownership with a mixture of Mobility as a Service (MaaS) and on-demand autonomous vehicles (AVs) running door-to-door, you could make dramatic cuts in city traffic. That, at least, is the view of researchers from COWI and PTV, who have modelled a variety of future scenarios based on the morning rush h