Autodiscovery’s primary objective is to supply up-to-date information on the state of road infrastructure objects, and a history of their changes. The system operates in real time, locating objects with up to a 10 cm accuracy level.
The system contains information on 28 object classes, including traffic lights, traffic signs, and road paving. Various attributes are available for each class: coordinates, geometric parameters, grouping with other objects, etc. Object recognition is facilitated by developments in such areas as machine vision, neural network-based deep machine learning, and 3D analysis based on LiDAR technologies.
As the result, the customer receives complete information on objects and their current state. The data so supplied may be used to identify defects in, and departures from, road traffic management plans, to plan road infrastructure development, and to follow up on road maintenance, repairs, and upgrade work performed by contractors.
The Accelerator provides a forum for networking and draws the attention of innovation centers and state-owned companies to domestic innovation. As part of the Accelerator, the Digital Roads' team succeeded in starting a dialog on technological partnership with ROSDORNII (Russia's National Road Research Institute).