Autonomous vehicles and their impact on road infrastructure and user safety

Skarbek-Żabkin, Anna; Szczepanek, Marcin

doi:10.1109/autosafe.2018.8373343

Cited by 13 publications

(1 citation statement)

References 4 publications

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“…This level-based roadmap is visualized in Figure 2. Level 0 vehicles are those which are under the full control of drivers [12]. Level 1 allows performing minor tasks of acceleration or steering by car and This work is licensed under a Creative Commons Attribution 4.0 License.…”

Section: Introductionmentioning

confidence: 99%

Deep Learning for Safe Autonomous Driving: Current Challenges and Future Directions

Muhammad

Ullah

Lloret

et al. 2021

IEEE Trans. Intell. Transport. Syst.

261

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Advances in information and signal processing technologies have a significant impact on autonomous driving (AD), improving driving safety while minimizing the efforts of human drivers with the help of advanced artificial intelligence (AI) techniques. Recently, deep learning (DL) approaches have solved several real-world problems of complex nature. However, their strengths in terms of control processes for AD have not been deeply investigated and highlighted yet. This survey highlights the power of DL architectures in terms of reliability and efficient real-time performance and overviews state-of-theart strategies for safe AD, with their major achievements and limitations. Furthermore, it covers major embodiments of DL along the AD pipeline including measurement, analysis, and execution, with a focus on road, lane, vehicle, pedestrian, drowsiness detection, collision avoidance, and traffic sign detection through sensing and vision-based DL methods. In addition, we discuss on the performance of several reviewed methods by using different evaluation metrics, with critics on their pros and cons. Finally, this survey highlights the current issues of safe DL-based AD with a prospect of recommendations for future research, rounding up a reference material for newcomers and researchers willing to join this vibrant area of Intelligent Transportation Systems.

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Section: Introductionmentioning

confidence: 99%