Driving forward with autonomous vehicle trials

The MOVE_UK consortium, led by Bosch, has completed the first phase in its three-year research programme, designed to accelerate the development of automated driving systems and make them intelligent and safe enough for the UK’s roads.

Taking place in the Royal Borough of Greenwich – one of the UK’s leading ‘smart cities’ and a global reference point for mobility innovation – the project has enabled the MOVE_UK consortium to develop a validation method that will reduce the time taken to test automated driving systems and bring them to market.

The project’s data is gathered from sensors installed on a fleet of Land Rover vehicles that have so far completed more than 30,000 miles of driving on public roads in Greenwich by council workers from their fleet services department. As part of the validation method, data is selected and recorded intelligently which helps to reduce the total volume of data collected and speed up validation of the automated driving functions in the real world. The data is then automatically transferred to a central cloud, allowing researchers to analyse it remotely. As a result, the consortium partners can analyse how automated driving functions respond in the real world, helping to ensure that future autonomous vehicles drive in a natural way, retaining the positive driving characteristics of a good driver.

The next two phases of the project will see additional sensors added to the test vehicles, so by the end of the project the data gathered will be from full 360-degree surround sensing.

Arun Srinivasan, executive vice president and head of mobility solutions, Bosch UK said: “This ground-breaking project is a major step for the UK in becoming a world leader in automated and connected vehicle technology. The data collected is particularly valuable, as it is being generated through ‘real world’ driving, rather than from the test track.”

The MOVE_UK research programme is also allowing Direct Line and The Floow to start developing more accurate insurance models associated with automated driving technology. This has only been possible due to the unprecedented volume of ‘real world’ data available which will help towards providing insurance products and pricing that is more closely linked to risk.