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The challenges of driverless technology

The challenges of driverless technology

Associate professor at University College London and author of ‘Who’s Driving Innovation’ Jack Stilgoerecently commented on the unmet driverless car deadlines promised by various car brands.

Both Ford and Nissan, for example, were set to release self-driving vehicles in 2020 – a deadline that has since been pushed to 2022. 

Jack Stilgoe said, “I think we’re starting to see a correction.

“The paradoxical thing is that the earlier a technology is, the more hype there is. The more work people actually do into the technology, the more they realise how hard it is to bring it into the real world.

“Obviously, we shouldn’t listen only to what the companies say. They’re trying to sell stuff. But that isn’t to say that the technology won’t have enormous value in the years to come.”

This said, there has been some development in self-driving technology. Tesla drivers are now able to engage autopilot mode and Waymo, formerly the Google self-driving car project, is using cars without a human safety driver at the wheel for taxi services. Instead of a driver, Waymo engineers operate remotely to override the artificial intelligence (AI) in the event that it does not react appropriately to a situation. 

Apple also has plans to introduce its own driverless car by 2024.

So, the question remains, why is driverless technology not yet operational and available to consumers? 

Artificial intelligence is still relatively new and driverless vehicles, like humans, require extensive training and practice to be able to learn how to make decisions. 

Using three vision systems - radar, cameras and light detection and ranging (LiDar) - driverless vehicles can ‘see’ the world around them, detecting road signs, other vehicles, pedestrians and more. One example of a potential complication with decision-making, is graffiti. If a ‘stop’ road sign is covered by graffiti, the artificial intelligence may be unable to recognise the road sign itself and therefore may not make the correct decision to stop. 

A driverless vehicle also needs to be able to recognise factors such as weather conditions and make decisions accordingly. For example, if there is snow on the road, the vehicle must decide to slow down and create a larger gap between itself and the car in front. 

On top of this, each vision system has its own weakness. Radar, for example, is hindered by wet weather conditions. 

At the earliest, as announced by the government in April 2021, we could see some self-driving technology on UK roads by the end of 2021 using automated lane keeping systems (ALKS). This will be limited to motorway use in slow traffic – speeds of up to 37 MPH – in the hopes of easing congestion, cutting emissions and reducing human error. 

Transport Minister Rachel Maclean said, “This is a major step for the safe use of self-driving vehicles in the UK, making future journeys greener, easier and more reliable while also helping the nation to build back better.

“But we must ensure that this exciting new tech is deployed safely, which is why we are consulting on what the rules to enable this should look like. In doing so, we can improve transport for all, securing the UK’s place as a global science superpower.”

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