Public invited to test driverless pods in Greenwich

GATEway Project on automated vehicles in ‘last mile’ mobility moves into next phase

The team behind the GATEway Project has invited members of the public to take part in the next stage of testing the fleet of driverless pods around the Greenwich Peninsula in south-east London.

Driverless pod with doors open at riversideIt has announced the four-week trial as the latest stage in a series of tests in which unoccupied pods have been travelling the area for the past five months.

The project is aimed at understanding public attitudes towards driverless vehicles and demonstrating their use for ‘last mile’ mobility. It involves a handful of companies, the London Borough of Greenwich and the University of Greenwich, and has received Government backing under the Intelligent Mobility Fund.

Transport Research Laboratory (TRL), one of the organisations involved in the project, said that more than 5,000 people have already registered an interest in taking part, but that there is still a chance for others to do so.

Understanding perceptions

Richard Cuerden, academy director at TRL, said: “As we explore the future of mobility solutions, it is essential that we consider the experience and benefits delivered to the consumer. This is why understanding and exploring the public perception of automated services has always been at the heart of the GATEway Project.

“The project is enabling us to discover how potential users of automated vehicles respond to them in a real world environment, so that the anticipated benefits to mobility can be maximised. We see driverless vehicles as a practical solution to delivering safe, clean, accessible and affordable mobility.”

The pods have been developed by UK companies Westfield Sportscars and Heathrow Enterprises, and are controlled by an automation system created by Fusion Processing. They have no steering wheels or typical controls, but use Fusion’s CAVstar software with GPS, radar and LiDAR (light detection and ranging) sensing to detect and negotiate objects in their path.

Image from TRL