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School students having a discussion with their teacher School students having a discussion with their teacher
School students having a discussion with their teacher
Northampton Waterside Campus Northampton Waterside Campus
Northampton Waterside Campus
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People talking in a building under construction
A Starship Robot driving down a street A Starship Robot driving down a street
A Starship Robot driving down a street
East Northamptonshire Enterprise Centre East Northamptonshire Enterprise Centre
East Northamptonshire Enterprise Centre
Northampton College Advanced Engineering Centre Northampton College Advanced Engineering Centre
Northampton College Advanced Engineering Centre

Autonomous vehicle funding secured

4 May 2017

Cranfield University has been awarded £1.2 million for its role in testing and validating a new autonomous vehicle, which is being designed and built as part of the HumanDrive Connected and Autonomous Vehicle (CAV) project.

The project was won by the HumanDrive consortium, of which Cranfield is a core partner, as a grant awarded from Innovate UK under the Connected and Autonomous Vehicle (CAV2) programme.

This will be the inaugural project for the university’s new Multi-User Environment for Autonomous Vehicle Innovation (MUEAVI) research facility, which will become operational later this year. The vehicle will be tested on this road for its ability to safely operate in a variety of conditions, including in an environment with many moving and static objects and in a variety of weather-led conditions.

MUEAVI is a purpose-built, instrumented roadway created as a ‘living laboratory’ for research into connected and autonomous vehicles. MUEAVI enables autonomous vehicles to be researched and tested in diverse real-world situations and environments. This capability is essential to develop and gain confidence in exciting technological developments of autonomous vehicles. Cranfield’s contribution to HumanDrive is central to the project’s objective to build an autonomous vehicle with human-like, natural control and path planning, by 2020.

 

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