The fields of autonomous ground and aerial vehicles are a young, dynamically expanding field of industry. The current traffic management solutions are inadequate to support the predicted high volume of operations efficiently ...

In recent years, artificial intelligence, deep learning, and computer vision systems have paved the way for the development of various self-driving vehicles. The risk of testing these vehicles is not negligible, given the ...

Autonomous industrial transport vehicles are already in operation in the industry, but the area is very rich in further development topics. Collaboration among these vehicles makes up a special problem. First, this paper ...

The development and adjustment process of a race car consists of countless steps that require a lot of decisions to be made. These decisions can only be effective if we have the right amount and quality of information. A ...

One of the state-of-the-art trends in intelligent transportation systems research is the development of real-time digital twin technologies and their applications for increased safety and autonomy on the roads. The areas ...

This paper describes a simulation of a specific accident reconstructed in PreScan software. Through this, we show that the PreScan software can be efficiently applied in accident reconstruction, particularly the operation ...

For modern scientific results, it is increasingly challenging to present them in a form that the general public can understand. This is particularly true in the field of collaborative intelligent transportation services ...

Sensor fusion-based detector utilizes camera sensors to solve the problem of recognizing objects and their classifications accurately. This has been proven to increase accuracy compared to single sensor detectors and can ...

The ZalaZONE Automotive Proving Ground can provide multiple controlled and safe test environments which becomes essential when various measurements and field tests are required for different vehicle-related scientific ...

Robust sensing of the environment is an essential and safety-critical part of self-driving vehicles. Most of the algorithms used for this problem employ sensor fusion to increase the reliability of sensing. The most common ...