Can AI shape the future of micromobility?

How AI will shape the future of micromobility

By Steve Pyer, Country Manager UK&I, Spin

Now established in many UK communities, e-scooter rental schemes have quickly become a popular, reliable, inexpensive, accessible and environmentally-friendly alternative to cars and public transport for short journeys.

With so many positives, it would be easy to see the world through rose tinted glasses, but the reality is that local communities (including riders, pedestrians and authorities) are still learning to adapt to this new form of micromobility, which inevitably creates points of friction — the most common of which are inappropriate parking and pavement riding.

The good news is that new technology integrating AI (artificial intelligence) into e-scooters will play a huge role in overcoming these concerns in the very near future.

Making roads safer by addressing rider behaviour

Integration of cameras and AI within e-scooters effectively allows scooters to “see” their rider’s surroundings and make decisions for them in real-time. These cameras can identify city infrastructure such as pavements, bike lanes and kerbs, and in the future will also identify pedestrians or obstacles in a rider’s path. Augmenting contextual awareness in this way brings obvious safety benefits.

As camera-based AI algorithms advance, future generations of the technology could conceivably be able to prevent collisions before they happen, similar to advanced driver-assistance systems in cars.

Off the back of these AI safety advancements, there will also be new ways to use the data gathered by on-board cameras to better understand how and why safety incidents happen. This kind of data is extremely valuable to operators to better understand fleet behaviour, to cities to help inform micromobility-friendly infrastructure planning, and to insurance companies to better assess risk and pricing.

Educating riders on e-scooter parking etiquette

Beyond safety and real-time vehicle awareness AI technology has a role to play in verifying appropriate parking and reporting this to ground operations for seamless retrieval and relocation of e-scooters before they become a nuisance to pedestrians and local residents.

Where traditional GPS lacks the level of accuracy required to implement precise parking management (especially in dense urban areas where tall buildings result in location inaccuracies) the use of AI can also dramatically enhance scooter positioning capabilities.

The beauty of this technology is that while it may seem futuristic, through our exclusive partnership with Drover AI, PathPilot technology is already being incorporated into the latest Spin e-scooters and its Insight monitoring platform.

E-scooters that come to you

As well as leveraging AI technology to mitigate pavement riding and incorrect parking, perhaps most exciting of all is the idea of remotely operated e-scooters which remotely re-park themselves out of the pathway of pedestrians. In collaboration with software company Tortoise, this will become a reality for our e-scooters in 2022. Going forward it is anticipated that this technology will enable users to ‘hail’ a nearby e-scooter in a similar way to taxi ride hailing currently does.

Read more: HumanForest sets sustainability and fitness challenges for its users 

For micromobility to flourish we must develop technologies that drive positive change in rider behaviour. By eliminating the industry’s biggest barriers — illegal pavement riding and improper parking — communities around the UK can continue to embrace e-scooters as a valuable part of the transport network.

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