Utilization of a Digital Twin in Autonomous Vehicles
One of our accounts of this time was creation of a digital twin for vehicle’s autonomous movement verification, from the end of production line through testing system to its arrival at the parking lot. There were autonomous systems used in these vehicles, eventually the systems were temporarily set in them.
What was the assignment?
The contracting authority needed to test the impact of increasing the production capacity, do an analysis of the current infrastructure and then take action towards support of autonomous vehicle movement implementation. The goal of the project was reducing the need for resources, damage elimination and space requirements optimization. This goal was fulfilled without exception.
What to imagine under the term of autonomous vehicle?
An autonomous vehicle is able to capture a complex picture of its surroundings and work without human intervention. It’s not necessary for the human to take over the vehicle control and it’s also not necessary for them to be physically present in there. An autonomous vehicle can go anywhere where traditional cars go and do everything like an experienced driver does.
How does it all work?
Autonomous vehicles rely on a lot of technologies in time of their operation. Sensors, complex algorithms, machine learning and powerful processors belong to the most mentioned.
What job do specific technologies do?
Based on the data from sensors, vehicles create and constantly update the map of their surroundings. Radars monitor the location of other vehicles. For traffic lights, other vehicles and pedestrians detection, there are video cameras. Lidar sensors, using light pulses, measure distances, detect road edges and identify lanes. Ultrasound sensors in wheels are used especially for parking and they detect curbs and other vehicles or obstacles.
All data from these sensors are processed through sophisticated software. Based on them, an optimal route is rendered and instructions are sent to individual functional vehicle parts for correction of acceleration, braking and steering. Exactly given algorithms secure avoiding obstacles, predictive modeling and object recognition. The vehicle is then navigated in accordance with external conditions of traffic, as well as general rules of road transport.
We won’t see them in regular traffic yet, but they already show their benefits
Despite optimistic scenarios and estimates, autonomous vehicles are not common participants of regular transport yet, however some elements of autonomous movement are already successfully used today. And even in this limited use, their implementation leads to cost reduction, minimum error rate and subsequent lower damage rate of vehicles and their surroundings, better organization and lower space requirements.
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