StarLine autonomous car is equipped with the latest hardware that enables locating the car in space, detecting objects and laying driving routes. In order to determine the vehicle location we use the RTK GNSS high-precision satellite receiver, the inertial navigation module, and wheel speed data obtained from the vehicle digital bus. Cameras, lidars, and radars are used to detect static and dynamic objects, including road infrastructure elements. Data received from the equipment is processed by several calculators and controlled by a certified computer.

Nowadays StarLine engineers are working hard to develop a digital model of Russian roads which enables the autonomous car to set the route between the given points and to dynamically modify it if any obstacles arise.

In 2018, StarLine became a participant of the autonomous cars’ trial drive which was held on Novorossiysk — Kerch section of А-290 Federal Russian highway. Later on, there were organized test drives in other 24 Russian cities as well as a large-scale trial drive of StarLine autonomous car from St. Petersburg to Kazan. Most of the route was driven in the automated mode.

In early 2019, StarLine autonomous car successfully passed the qualification stage of the technological competition “Winter city”. In December 2019 during the final tests it showed the best result out of other participants — 50 km in 2 hours 47 minutes.

ScPA StarLine cooperates with most of the world’s leading car manufacturers and fulfills contract orders.
One of the directions of contract manufacturing is the development of a ready-made autonomous solution for logistics operators:

ScPA StarLine is ready to provide the contract development of a training platform for the Russian and foreign universities which are preparing the qualified specialists for the future market of autonomous vehicles. Such a platform helps the young engineers to be focused on the development of autonomous control algorithms. StarLine provides both the platform itself and its integration into the car as well as technical support.

Implemented features:

  1. Interaction with the car through the digital CAN bus.
  2. Control of the linear and angular car velocity.
  3. Precise car localization in space.
  4. 360 degree detection of static obstacles (buildings, road signs, traffic lights).
  5. 360 degree detection of dynamic obstacles (people, cars, bicycles, motor vehicles), pedestrians pass.
  6. Detection of traffic signals.
  7. Distributed computing system to enhance the functional safety of the autonomous vehicle.
  8. Laying a global route to the point set on a digital road model.
  9. Movement in the lane based on the set route and the existing speed limit.
  10. Dynamic updating of the route, changing lanes and avoiding obstacles according to the traffic rules as well as informing other road participants about changing the route.
  11. Keeping the distance to the objects moving in front (people, cars, bicycles, motor vehicles).

In the near future:

  1. Development of the localization system through the introduction of visual and laser odometry algorithms.
  2. Development of the route setting system.
  3. Development of car control algorithms.
  4. Development of the object detection system adapted for various conditions, including poor visibility and lighting.
  5. Further development of the digital road model for autonomous vehicles, and digitization of roads in Russian cities.
  6. Development of the tool for creating digital road model.
  7. Upgrading and updating of the installed equipment.
  8. Passing certification of the autonomous car, performing trial drives on public roads in various regions of Russia.