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Development and application of Aimsun to the assessment of autonomous and connected vehicles.
Research projects Cooperative, connected and automated mobility (CCAM)
The HumanDrive project team successfully completed a 230-mile AV journey across the UK, setting a national precedent for the successful deployment of an autonomous, human-like vehicle undergoing a complex journey through real-world driving conditions.
The project aided the national development of R&D in the domain of AVs to aid understanding of the user needs for automated vehicles, increase public awareness of and confidence in autonomous vehicles, and enable authorities responsible for the road network and safety to benefit from developments in automated transport system technologies.
The project will build an autonomous vehicle with human like, natural control / path planning, by 2019, that 1) is able to be fully autonomous on country roads, when overtaking, on roundabouts and/ or motorways 2) mimics the driving behaviour of human beings, to provide an enhanced experiences for the occupants. Nissan and Hitachi will use their global automotive, artificial intelligence/ machine learning and communication technology expertise to build vehicles and AI models that are fit for purpose, and use the expertise of Horiba MIRA, Cranfield University and the University of Leeds to ensure the system is validated and end-user acceptance is evaluated. Atkins and SBD will address protective security, making the vehicle digitally and physically secure. The Transport Systems Catapult will be responsible for project management and development of safety aspects of the project. The impact of L4 vehicles on the Strategic Road Network will be explored through work by Highways England and TSS. Highways England and Milton Keynes Council will provide support to the demonstration route of the vehicle.
Aimsun sought to assess the impact of AVs on the Strategic Road Network (SRN – Motorways and ‘A’ roads) with the buy-in of an Original Equipment Manufacturer (OEM) and National Highways. The project produced assessments of the effects of differing levels and types of AVs in terms of indicators such as delay times and queuing at junctions which indicated the level of improvement that could be expected. These were assessed on two models of the SRN and also showed (for comparison) the effects of cooperative vehicles, using Vehicle-to-vehicle (V2V) systems, as well and conventional roadside, and Vehicle-to-infrastructure (V2I), speed control systems.
Development and application of Aimsun to the assessment of autonomous and connected vehicles.
Processing existing datasets to understand the parameters for modelling human drivers and how to extend them to create vehicle rules for CAVs.
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