A Comprehensive Overview of the Current State of Development in Autonomous Vehicle Driving
Abstract:
The 21st century has witnessed a rapid evolution in information technology, leading to significant transformations in the automotive industry. The focus has shifted from purely mechanical enhancements to the advent of a new generation of vehicles equipped with intelligent driving technology. These smart vehicles are capable of perceiving their surroundings and adapting to real-time conditions and traffic, enabling assisted or even fully autonomous driving. This advancement promises substantial improvements in safety, environmental sustainability, and comfort, enhancing the overall driving experience. This paper provides a comprehensive overview of the current state of autonomous vehicle technology, focusing on the fundamental principles of intelligent driving. It delves into three key areas: environmental perception, path planning, and the application of artificial intelligence in autonomous driving systems.
Keywords:
Intelligent Driving, Environmental Perception, Path Planning, Artificial Intelligence
APA Citation:
Jingzhou Sun (2024). A Comprehensive Overview of the Current State of Development in Autonomous Vehicle Driving. International Journal of Mechanical and Electrical Engineering, 2(2), 24-30. https://doi.org/10.62051/ijmee.v2n2.04
References
- Wang, S. (2018) Research on Vehicle Auxiliary Driving Technology based on Laser Radar and Camera. Thesis of Jilin University.
- Chen, Z. Y. (2020) Research on Multi-sensor Fusion Environment Perception Algorithm in Autonomous Driving.Thesis of Nanjing University of Posts and Telecommunications.
- Xiong, L., Yang, X., Zhuo, G. R., Leng, B., Zhang, R. X. (2020) Review on Motion Control of Autonomous Vehicles. Journal of Mechanical Engineering, 5(56):10.
- Guo, Y. S., Jiang Z. M., Bai, Y., Tang, J. Z. (2018) Investigation of Humanoid Level of Path Tracking Methods Based on Autonomous Vehicles. China Journal of Highway and Transport, 31(08):189-196.
- Zhang, H. (2022) Research on path planning and tracking control method of campus intelligent vehicle based on hybrid algorithm. Thesis of Taiyuan University of Technology.
- Pan, F., Pan, Z. H., Xiong, L., Pan, W. G. (2022) Application of Artificial Intelligence in Intelligent Driving Control. Journal of Beijing Union University, 7(36):129.
- Zhang, Y. S., Hua, G. D., Li, N., et al. (2022) A Review of Research on Intelligent Driving Based on Vehicle-Road Collaboration. Automotive Digest, (6):49-57.
- Fu, B., Zhu, X. H., Tu, N. N. (2022) Research on Lane Changing Decision of Intelligent Driving Vehicle Based on XGBoost. Automobile Technology, (11):10-15.