PL EN
PRACA ORYGINALNA
Current Approaches in Traffic Lane Detection: a minireview
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Więcej
Ukryj
1
Automotive Engineering and Transportation, Technical University of Cluj-Napoca, Romania
 
2
EMARC Research Centre, Technical University of Cluj-Napoca, Romania
 
 
Data nadesłania: 30-01-2024
 
 
Data ostatniej rewizji: 14-06-2024
 
 
Data akceptacji: 17-06-2024
 
 
Data publikacji: 26-06-2024
 
 
Autor do korespondencji
MARIASIU Florin   

EMARC Research Centre, Technical University of Cluj-Napoca, Bdul.Muncii 103-105, Cluj-Napoca, Romania
 
 
The Archives of Automotive Engineering – Archiwum Motoryzacji 2024;104(2):19-47
 
SŁOWA KLUCZOWE
DZIEDZINY
STRESZCZENIE
The continuous development and importance of the field of road transport these days make it necessary to design, develop and implement technological solutions that reduce (eliminate as much as possible) the risk of road accidents. Such a technological solution is also represented by advanced driver assistance systems (ADAS), systems that assist drivers in various ways, such as collision avoidance, automatic parking, adaptive cruise control, attention and lane departure warnings. Over the next ten years, there will likely be a rise in the need for ADAS system deployment in automobile construction, driven by consumer and regulatory interest in safety applications that protect drivers and lower accident rates. At the moment, autonomous emergency braking and forward collision warning systems are mandated for all cars in the US and the EU. Additionally, advanced driver assistance systems (ADAS) may soon distinguish automobile brands and have a significant impact on consumer preference. The present work aims to provide a general picture related to the current research and development of ADAS systems that refer to the detection of the traffic lane and lane markings. The approaches are presented regarding: the current development directions of ADAS systems, current traffic lane detection techniques, traffic lane detection methods and the use of artificial intelligence techniques in this field. The general conclusion is that further research is needed in the field, research to increase the performance of traffic lane detective systems by using advanced algorithms and easy-to-implement methods that do not require large hardware resources.
 
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