Machine Learning-Based Forward Collision Avoidance System: A Case Study for the Kayoola EVS
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-56576-2_13
Reference26 articles.
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2. Lajunen, T., & Sullman, M. J. M. (2021). Attitudes toward four levels of self-driving technology among elderly drivers. Frontiers in Psychology, 12, 682973. https://doi.org/10.3389/fpsyg.2021.682973
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4. Sanjana, T., Wahid, F., Habib, M. M., & Rumel, A. A. (2018). Design of an automatic forward and back collision avoidance system for automobiles. Advances in Science, Technology and Engineering Systems, 3(1), 205–212. https://doi.org/10.25046/aj030124
5. Koojo, I., Machuve, D., Mirau, S., & Miyingo, S. P. (2021, September). Design of a passenger security and safety system for the Kayoola EVs Bus. In IEEE AFRICON Conference (Vol. 2021). https://doi.org/10.1109/AFRICON51333.2021.9570932.
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