Optimizations in Dynamic Origin Technique for Efficient Lane Detection for Autonomous Vehicles

• Autorzy: Maya P. , Tharini C.

Identyfikatory

DOI

10.24425/ijet.2023.144377

• Języki publikacji: EN

Abstrakty

EN

Driver assistance systems have started becoming a key differentiator in automotive space and all major automotive manufacturers have such systems with various capabilities and stages of implementation. The main building blocks of such systems are similar in nature and one of the major building blocks is road lane detection. Even though lane detection technology has been around for decades, it is still an ongoing area of research and there are still several improvements and optimizations that are possible. This paper offers an Optimized Dynamic Origin Technique (Optimized DOT) for lane detection. The proposed optimization algorithm of optimized DOT gives better results in performance and accuracy compared to other methods of lane detection. Analysis of proposed optimized DOT with various edge detection techniques, various threshold levels, various sample dataset and various lane detection methods were done and the results are discussed in this paper. The proposed optimized DOT lane detection average processing time increases by 9.21 % when compared to previous Dynamic Origin Technique (DOT) and 59.09 % compared to traditional hough transform.

Słowa kluczowe

EN

lane detection; dynamic origin technique; partial hough transform; performance analysis; accuracy analysis; optimization; autonomous vehicles

• Wydawca: Polish Academy of Sciences, Committee of Electronics and Telecommunication
• Czasopismo: International Journal of Electronics and Telecommunications
• Rocznik: 2023
• Tom: Vol. 69, No. 2
• Strony: 407--413
• Opis fizyczny: Bibliogr. 14 poz., fot., rys., tab., wykr.

Twórcy

autor

Maya P.

• B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

autor

Tharini C.

• B S Abdur Rahman Crescent Institute of Science and Technology, Chennai, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).