Aimsun enters partnership to develop tool for managing mixed-autonomy traffic

Aimsun has partnered with UC Berkeley’s Institute of Transportation Studies to develop Flow, a tool for managing large-scale traffic systems where human-driven and autonomous vehicles (AVs) operate together. Flow offers a suite of pre-built traffic scenarios and is now integrated with Aimsun Next mobility modelling software. The open source architecture knits together microsimulation tools with deep reinforcement learning libraries in the cloud. Launched last September, Flow allows users to build and
January 15, 2019 Read time: 2 mins

16 Aimsun has partnered with UC Berkeley’s Institute of Transportation Studies to develop Flow, a tool for managing large-scale traffic systems where human-driven and autonomous vehicles (AVs) operate together.

Flow offers a suite of pre-built traffic scenarios and is now integrated with Aimsun Next mobility modelling software. The open source architecture knits together microsimulation tools with deep reinforcement learning libraries in the cloud.

Launched last September, Flow allows users to build and combine modular traffic scenarios to tackle complex situations, the company says. For example, single-lane/multi-lane and merge building blocks can be used to study stop-and-go merging traffic behaviours along a highway.  

“In mixed-autonomy traffic control, evaluating machine learning methods is challenging due to the lack of standardised benchmarks,” says Alexandre Bayen, director, 8895 ITS Berkeley. “Systematic evaluation and comparison will not only further our understanding of the strengths of existing algorithms but also reveal their limitations and suggest directions for future research.”

Urban Traffic Control

Related Content

  • University research shows a few self-driving cars can improve traffic flow
    May 15, 2017
    The presence of just a few autonomous vehicles can eliminate the stop-and-go driving of the human drivers in traffic, along with the accident risk and fuel inefficiency it causes, according to new research by the University of Illinois at Urbana-Champaign. Funded by the National Science Foundation’s Cyber-Physical Systems program, the research was led by a multi-disciplinary team of researchers with expertise in traffic flow theory, control theory, robotics, cyber-physical systems, and transportation engine
    Read More
  • Here’s HD AV map prepared for 5G
    June 17, 2019
    The emergence of 5G may not be necessary to provide a high-definition map for autonomous driving, says Matt Preyss from Here Technologies. Ben Spencer asks why 5G is a hot topic worldwide, with the potential for faster transfer of information eagerly awaited by those convinced that it will be a game-changer for the ITS industry. High-definition (HD) maps are essential to allow autonomous vehicles (AVs) to understand their environment, and operate safely within it in relation to other road users and p
    Read More
  • Manchester seeks smart but not selective transport solutions
    January 25, 2018
    Smarter transport relies on better communications both with travellers and between transport providers. Andrew Williams reports. Inrix’s prediction that the cost of traffic congestion will rise by 63% to £21bn per year by 2030 clearly illustrates that, in addition to the ongoing inconvenience and inefficiency, ongoing gridlock is a significant drain on the economy. It is against this backdrop that a Cisco-led consortium has launched CitySpire, a smart transport programme that uses location-based services a
    Read More
  • Jenoptik uses sensor fusion to avoid monitoring confusion
    January 26, 2018
    Jenoptik’s Uwe Urban looks at the advantages of ‘sensor fusion’ for the ITS sector. When considering the ideal sensing and monitoring system to enable the ITS sector to deliver improvements in mobility and road safety, for general policing security and border protection, we have to think beyond radar-base systems or laser scanners. What is needed today are solutions for detecting and tracking vehicles while recording evidence to deacide if any action is necessary. There is no sole sensor capable of
    Read More

Highlighted Content