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研究通过多传感器动态映射技术的集成来提高自动驾驶汽车的性能。

Investigating the Improvement of Autonomous Vehicle Performance through the Integration of Multi-Sensor Dynamic Mapping Techniques.

机构信息

College of Electronics & Information, Kyunghee University, 1732 Deogyeong-daero, Giheung-gu, Yongin-si 17104, Gyeonggi-do, Republic of Korea.

Department of Electronic Engineering, Semyung University, 65 Semyung-ro, Jecheon-si 27136, Chungcheongbuk-do, Republic of Korea.

出版信息

Sensors (Basel). 2023 Feb 21;23(5):2369. doi: 10.3390/s23052369.

Abstract

The emergence of autonomous vehicles marks a shift in mobility. Conventional vehicles have been designed to prioritize the safety of drivers and passengers and increase fuel efficiency, while autonomous vehicles are developing as convergence technologies with a focus on more than just transportation. With the potential for autonomous vehicles to serve as an office or leisure space, the accuracy and stability of their driving technology is of utmost importance. However, commercializing autonomous vehicles has been challenging due to the limitations of current technology. This paper proposes a method to build a precision map for multi-sensor-based autonomous driving to improve the accuracy and stability of autonomous vehicle technology. The proposed method leverages dynamic high-definition maps to enhance the recognition rates and autonomous driving path recognition of objects in the vicinity of the vehicle, utilizing multiple sensors such as cameras, LIDAR, and RADAR. The goal is to improve the accuracy and stability of autonomous driving technology.

摘要

自动驾驶汽车的出现标志着交通方式的转变。传统汽车的设计优先考虑驾驶员和乘客的安全,并提高燃油效率,而自动驾驶汽车则作为融合技术发展,不仅仅关注交通。自动驾驶汽车有可能成为办公或休闲空间,因此其驾驶技术的准确性和稳定性至关重要。然而,由于当前技术的限制,自动驾驶汽车的商业化一直具有挑战性。本文提出了一种基于多传感器的自动驾驶精密地图构建方法,以提高自动驾驶技术的准确性和稳定性。该方法利用动态高清地图提高车辆附近物体的识别率和自动驾驶路径识别率,同时使用摄像头、激光雷达和雷达等多种传感器。目标是提高自动驾驶技术的准确性和稳定性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/1b66/10007208/65a294d33ebc/sensors-23-02369-g001.jpg

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