Intelligent Decision-Making in Lane Detection Systems Featuring Dynamic Framework for Autonomous Vehicles

Author:

Blazevic RomanaORCID,Maaß Fynn LucaORCID,Veledar OmarORCID,Macher GeorgORCID

Publisher

Springer Nature Switzerland

Reference24 articles.

1. Almotairi, K.H.: Hybrid adaptive method for lane detection of degraded road surface condition. J. King Saud Univ.-Comput. Inf. Sci. 34(8), 5261–5272 (2022)

2. Arrieta, A.B., et al.: Explainable artificial intelligence (XAI): concepts, taxonomies, opportunities and challenges toward responsible AI. Inf. Fus. 58, 82–115 (2020)

3. Blazevic, R., Veledar, O., Macher, G.: Insides to trustworthy AI-based embedded systems. In: WCX SAE World Congress Experience. SAE International (2024). https://doi.org/10.4271/2024-01-2014

4. Cantzler, H.: Random sample consensus (ransac). Institute for Perception, Action and Behaviour, Division of Informatics, University of Edinburgh 3 (1981)

5. Chen, W., Wang, W., Wang, K., Li, Z., Li, H., Liu, S.: Lane departure warning systems and lane line detection methods based on image processing and semantic segmentation: A review. J. Traffic Transp. Eng. (Eng. Ed.) 7(6), 748–774 (2020)

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