The Planning Process of Transport Tasks for Autonomous Vans-Case Study
Artykuł w czasopiśmie
MNiSW
100
Lista 2021
Status: | |
Autorzy: | Caban Jacek, Nieoczym Aleksander, Dudziak Andrzej, Krajka Tomasz, Stopková Mária |
Dyscypliny: | |
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Rok wydania: | 2022 |
Wersja dokumentu: | Drukowana | Elektroniczna |
Język: | angielski |
Numer czasopisma: | 6 |
Wolumen/Tom: | 12 |
Numer artykułu: | 2993 |
Strony: | 1 - 18 |
Impact Factor: | 2,7 |
Web of Science® Times Cited: | 14 |
Scopus® Cytowania: | 15 |
Bazy: | Web of Science | Scopus |
Efekt badań statutowych | NIE |
Finansowanie: | The project/research was financed in the framework of the project Lublin University of Technology - Regional Excellence Initiative, funded by the Polish Ministry of Science and Higher Education (contract no. 030/RID/2018/19). |
Materiał konferencyjny: | NIE |
Publikacja OA: | TAK |
Licencja: | |
Sposób udostępnienia: | Witryna wydawcy |
Wersja tekstu: | Ostateczna wersja opublikowana |
Czas opublikowania: | W momencie opublikowania |
Data opublikowania w OA: | 15 marca 2022 |
Abstrakty: | angielski |
Transport is an area that is developing at a tremendous pace. This development applies not only to electric and hybrid cars appearing more and more often on the road but also to those of an autonomous or semi-autonomous nature. This applies to both passenger cars and vans. In many different publications, you can find a description of a number of benefits of using automated guided vehicles (AGV) for logistics and technical tasks, e.g., in the workplace. An important aspect is the use of knowledge management and machine learning, i.e., artificial intelligence (AI), to design these types of processes. An important issue in the construction of autonomous vehicles is the IT connection of sensors receiving signals from the environment. These signals are data for deep learning algorithms. The data after IT processing enable the decision-making by AI systems, while the used machine learning algorithms and neural networks are also needed for video image analysis in order to identify and classify registered objects. The purpose of this article is to present and verify a mathematical model used to respond to vehicles’ demand for a transport service under set conditions. The optimal conditions of the system to perform the transport task were simulated, and the efficiency of this system and benefits of this choice were determined. |