Kicksharing Whoosh shared test results of scooters with a computer vision module and a large dashboard. According to the survey results, more than 65% of users will prefer a device with a large control panel, as they are more comfortable.
In summer, the company launched a pilot operation of scooters with new technologies. Advanced computer vision modules and control panels were installed on the latest model scooters. This pilot is part of the development and assembly project of the Whoosh scooter, the company clarifies.
The module reads and analyzes data around the device and the larger screen makes operation easier. The technologies were introduced on several hundred scooters in Moscow and the Moscow region, and during the pilot test 7.5 thousand people managed to use them.
As the survey showed, more than 65% appreciated the new control panel and, if possible, would choose devices with this configuration.
Test results
- The devices recognized people and read types of road markings. The service also studied tenants’ reaction to obstacles and the environment around the scooter;
- Road surface recognition makes it easy to identify restricted areas. Thus, the scooter will be able to distinguish between the sidewalk, the road and the intersection, and the service will be able to limit traffic where traffic regulations prohibit it;
- Computer vision allows you to adjust the speed of movement according to the surrounding situation. Whoosh currently uses “slow zones” where the speed is automatically reduced.
The tests also allowed us to identify aspects that still need improvement. According to Dmitry Chuiko, CEO of Whoosh, the strength of the structure will need to be reinforced to mount the phone.
In early September, Whoosh, together with the Neiry biotechnology laboratory, carried out an experiment on how to control a scooter with the power of thought. The speed of the device was controlled without the use of hands using brain wave activity.
This was made possible by the Neiry neural interface. The development analyzes EEG indicators of the brain.
Author:
Natalia Gormaleva
Source: RB
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