Suggested Citation:
Zhao, Jingyuan, Wenyi Zhao, Bo Deng, Zhenghong Wang, Feng Zhang, Wenxiang Zheng, Wanke Cao, Jinrui Nan, Yubo Lian, Andrew Burke (2023)

Autonomous Driving System: A Comprehensive Survey

Automation is increasingly at the forefront of transportation research, with the potential to bring fully autonomous vehicles to our roads in the coming years. This comprehensive survey provides a holistic look at the essential components and cutting-edge technologies that are driving the development and implementation of autonomous driving. It starts by evaluating two critical system architectures that are fundamental to the operation of autonomous vehicles: the layered and end-to-end structures. It then examines the critical areas of scene perception and localization, emphasizing the importance of sensor technologies. These technologies are vital for tasks such as object detection and semantic segmentation, which allow vehicles to understand and navigate their environment. A special focus is given to the complex topic of object detection, along with suggestions for how it can be enhanced. The survey then proceeds to provide detailed discussions on path planning, trajectory prediction, and decision-making processes. These elements are crucial for the smooth navigation of autonomous vehicles, and the survey highlights the role of artificial intelligence (AI) and machine learning in these processes. Overall, the survey presents the rapid progress in the field of autonomous driving, offering a comprehensive assessment of the technologies and innovations that are essential for moving toward a safe and efficient autonomous future.