Research Status of Autonomous Vehicle Path Planning

Shangzhe Shi

doi:10.1051/shsconf/202214402019

All issues

Volume 144 (2022)

SHS Web Conf., 144 (2022) 02019

References

Open Access

Issue		SHS Web Conf. Volume 144, 2022 2022 International Conference on Science and Technology Ethics and Human Future (STEHF 2022)


Article Number		02019
Number of page(s)		4
Section		Mobile Communication Technology and Prospects of Frontier Technology
DOI		https://doi.org/10.1051/shsconf/202214402019
Published online		26 August 2022

H.Q Sang, Y.s You, X.J Sun, Y. Zhou, F. Liu. (2021) The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations, Ocean Engineering, vol. 223, 2021, Article 108709. [Google Scholar]
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Q. Luo, H.B Wang, Y. Zheng, J.C He. (2019) Research on path planning of mobile robot based on improved ant colony algorithm, Neural Computing and Applications, vol. 32, pp. 1555-1566. [Google Scholar]
L.F Wu, H.S Zha, C.J Xiu, Q.J He. (2017) Local Path Planning for Intelligent Vehicle Obstacle Avoidance Based on Dubins Curve and Tentacle Algorithm. In: Intelligent and Connected Vehicles Symposium. https://doi.org/10.4271/2017-01-1951. [Google Scholar]
V.N Sichkar. (2019) Reinforcement Learning Algorithms in Global Path Planning for Mobile Robot. In: 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Sochi. [Google Scholar]
A. Maoudj, A. Hentout. (2020) Optimal path planning approach based on Q-learning algorithm for mobile robots, Applied Soft Computing, vol. 97, Part. A, Article 106796. [CrossRef] [Google Scholar]
T.W Zhang, G.H Xu, X.S Zhan, T. Han. (2021) A new hybrid algorithm for path planning of mobile robot. The Journal of Supercomputing, vol. 78, pp. 4158-4181. [Google Scholar]
X.H, Liu, D.G Zhang, T. Zhang, J. Zhang, J.X Wang. (2022) A new path plan method based on hybrid algorithm of reinforcement learning and particle swarm optimization, Engineering Computations, vol. 39, pp. 993-1019. [CrossRef] [Google Scholar]
S. Ansari, J. Ahmad, S.A Shah, A.K Bashir, T. Boutaleb, S. Sinanovic. (2020) Chaos-based privacy preserving vehicle safety protocol for 5G Connected Autonomous Vehicle networks, Future Internet of Vehicles, vol. 31, https://doi.org/10.1002/ett.3966 [Google Scholar]
S. Lee, D. Park. (2021) Efficient Power Control Using Variable Resolution Algorithm for LiDAR Sensorbased Autonomous Vehicle, In: 2021 18th International SoC Design Conference (ISOCC), Jeju Island. [Google Scholar]
J.D Choi, M.Y Kim. (2022) A sensor fusion system with thermal infrared camera and LiDAR for autonomous vehicles and deep learning based object detection, ICT Express, https://doi.org/10.1016/j.icte.2021.12.016 [Google Scholar]

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[1] H.Q Sang, Y.s You, X.J Sun, Y. Zhou, F. Liu. (2021) The hybrid path planning algorithm based on improved A* and artificial potential field for unmanned surface vehicle formations, Ocean Engineering, vol. 223, 2021, Article 108709. [Google Scholar]

[2] Y. Zhou, E.D Zhang, H.L Guo, Y.H Fang, H. Li (2021) Lifting path planning of mobile cranes based on an improved RRT algorithm. Advanced Engineering Informatics, vol. 50, Article 101376. [Google Scholar]

[3] Q. Luo, H.B Wang, Y. Zheng, J.C He. (2019) Research on path planning of mobile robot based on improved ant colony algorithm, Neural Computing and Applications, vol. 32, pp. 1555-1566. [Google Scholar]

[4] L.F Wu, H.S Zha, C.J Xiu, Q.J He. (2017) Local Path Planning for Intelligent Vehicle Obstacle Avoidance Based on Dubins Curve and Tentacle Algorithm. In: Intelligent and Connected Vehicles Symposium. https://doi.org/10.4271/2017-01-1951. [Google Scholar]

[5] V.N Sichkar. (2019) Reinforcement Learning Algorithms in Global Path Planning for Mobile Robot. In: 2019 International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM), Sochi. [Google Scholar]

[6] A. Maoudj, A. Hentout. (2020) Optimal path planning approach based on Q-learning algorithm for mobile robots, Applied Soft Computing, vol. 97, Part. A, Article 106796. [CrossRef] [Google Scholar]

[7] T.W Zhang, G.H Xu, X.S Zhan, T. Han. (2021) A new hybrid algorithm for path planning of mobile robot. The Journal of Supercomputing, vol. 78, pp. 4158-4181. [Google Scholar]

[8] X.H, Liu, D.G Zhang, T. Zhang, J. Zhang, J.X Wang. (2022) A new path plan method based on hybrid algorithm of reinforcement learning and particle swarm optimization, Engineering Computations, vol. 39, pp. 993-1019. [CrossRef] [Google Scholar]

[9] S. Ansari, J. Ahmad, S.A Shah, A.K Bashir, T. Boutaleb, S. Sinanovic. (2020) Chaos-based privacy preserving vehicle safety protocol for 5G Connected Autonomous Vehicle networks, Future Internet of Vehicles, vol. 31, https://doi.org/10.1002/ett.3966 [Google Scholar]

[10] S. Lee, D. Park. (2021) Efficient Power Control Using Variable Resolution Algorithm for LiDAR Sensorbased Autonomous Vehicle, In: 2021 18th International SoC Design Conference (ISOCC), Jeju Island. [Google Scholar]

[11] J.D Choi, M.Y Kim. (2022) A sensor fusion system with thermal infrared camera and LiDAR for autonomous vehicles and deep learning based object detection, ICT Express, https://doi.org/10.1016/j.icte.2021.12.016 [Google Scholar]