The Dott-See.Sense London trial took place in 2021, following Dott’s successful tender bid to operate e-scooters in the city. A key priority for Dott in securing and conducting the trial was e-scooter safety. As such, Dott sought to show how its e-scooters and e-bikes could be used to improve road safety for all micro-mobility users. See.Sense SUMMIT trackers were integrated into a group of Dott e-scooters to monitor rider behaviour on the vehicles to help better understand the users experience on the road. These trackers utilise patented See.Sense AI-sensor technology, enabling See.Sense to gather granular insights into the experience of the rider.
See.Sense and Dott had two core objectives for the trial. Firstly, the trial aimed to identify areas around the city where extreme braking / swerving may be indicative of potential collision areas. These data insights would be shared with the authorities to suggest improvements, helping make the streets safer for all micro-mobility users. Secondly; pavement detection through monitoring changes in road surface.
After the successful 10 week trial, in which over 1800 rides and 18 million sensor readings were recorded, several key results were achieved.
Results: Safety Analysis
By using the data collected, a detailed safety analysis into e-scooters usage was conducted. As seen from the images below, a vivid picture of Dott e-scooter use across central London was created. Braking, swerving and road surface conditions were mapped, and from this, areas that witnessed high levels of braking and swerving - as well as areas of poor road surface conditions - were identified.
Once these areas of concern were identified, closer analysis was then undertaken. In many cases, the data analysis found strong correlations between high levels of braking and swerving, and poor road surface conditions. This could occur in areas with potholes or poor infrastructure, causing riders to swerve or brake to avoid crashes, as well in roads with rough surfaces - such as cobbled streets - resulting in reduced control of the e-scooter. Other problematic areas were found in densely populated areas such as Trafalgar Square, with heavy braking and swerving resulting from conflict with pedestrians in busy streets.
In the data, we saw the same patterns as we saw on bikes, indicating that swerve and brake behaviour can be used to identify more dangerous areas.
Results: Pavement Detection
The trial was also successful in its aim of successfully detecting pavement riding and distinguishing between various types of road surface. In a test conducted along London’s Victoria Embankment, Dott e-scooters were used on three different types of road surface; road, cycle path and pavement. Using the data collected, See.Sense analysts could consistently distinguish between scooters riding on the road, cycle path or footpath based on road surface characteristics. As a result of these findings, it is possible to operationalise this technology in conjunction with e-scooters to consistently identify footpath riding.
These results highlight the potential for data-driven approaches to inform micromobility safety across cities. The data collected through this project not only helps to ensure the safety of individual users, but on a wider scale this data can create cities which are smarter, safer and better suited to a future in which active travel takes precedence. Our work with Dott on this project ultimately demonstrates a scalable solution that provides cities with powerful data driven insights that will help cities unlock the true potential of micro-mobility.
Maxim Romain, Co-Founder and COO, Dott, stated: “Quality infrastructure is key to helping users of micro-mobility feel safe whilst on the road. The results of this new trial, in partnership with See.Sense, reveal that Dott’s vehicles can do more than provide efficient, reliable and sustainable transport for its riders – they can also deliver valuable learnings to create smart cities which are safer and more pleasant for all residents.”
The results of the trial were also presented at the annual POLIS Conference in Gothenburg, Sweden in December 2021 by See.Sense Co-founder Irene McAleese. This well received presentation was given as part of the ‘Going Beyond Crash Data’ segment of POLIS 2021.