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Automated Vehicles - cross modal learning in autonomy

IET factfile: Automated vehicles: cross-modal learning in autonomy

The Institution of Engineering and Technology has produced a report that looks at the value of cross-modal learning in autonomy. The report highlights the benefits and potential of autonomous vehicles and uses evidence from four modes of autonomy, road, rail, sea and air, to show the value of sharing best practice.

The report recommendations note that there is a great deal of value in cross-modal learning and makes the following recommendations:

  • Regulators of different modes of autonomy need to work together to develop a common approach to autonomous regulation and software standards across all transport sectors.
  • There are valuable lessons that can be learnt from different modes of autonomy that could challenge how software is being developed in autonomous cars currently. Professional bodies can bring together industry and regulators to encourage cross-modal learning.
  • Autonomous vehicles are not just about technical development. Before they can become part of our daily lives, we need to have a much better understanding of the behavioural and societal implications. This means there is a need for in-depth research and developing new skills within the autonomy industry.
  • An information campaign to help the public understand that automated transport already plays a major part in the UK transport system. Recommendations are laid out in the report of how to overcome key challenges in autonomous vehicles, such as linking autonomous vehicles to a traffic management system or remote ‘pilots’.

A detailed analysis of the latest autonomy in each mode of transportation (rail, road, sea, air) is also included.