Automatic driving vehicle implementation method based on hybrid enhanced intelligence

Abstract

The invention provides an automatic driving vehicle implementation method based on hybrid enhanced intelligence. Wherein the automatic driving vehicle is provided with a vehicle-mounted sensor and a navigation positioning map device so as to realize sensing, navigation, decision planning and control technologies on a road environment; an edge computing server and a roadside intelligent sensor areinstalled at the position, close to the automatic driving vehicle, of the roadside. According to the intelligent characteristics of the automatic driving vehicle, real-time perception of the road environment is mainly achieved through a vehicle-mounted sensor and a roadside sensor, data understanding and extracting work is conducted on perceived data information, and driving decision making and path planning work of the automatic driving vehicle is conducted; the hybrid enhanced intelligence makes full use of the respective advantages of the two kinds of intelligence, comprehensively realizesa relatively strong pushing function for the automatic driving vehicle, can realize perception in a complex road environment, and further realizes high-efficiency driving safety of the automatic driving vehicle.

Description

technical field [0001] The invention relates to a method for realizing a self-driving vehicle based on hybrid enhanced intelligence, which belongs to the field of artificial intelligence hybrid enhanced intelligence cognition. Background technique [0002] With the development of artificial intelligence technology, breakthroughs have been made in autonomous vehicle technology, which will become the main development direction of the future automotive industry. The current self-driving vehicles generally drive in relatively simple traffic scenes at relatively low speeds, and cannot be universally applied to most actual road environments. Although artificial intelligence algorithms such as machine learning and deep learning assist self-driving vehicles to better perceive environment, but artificial intelligence algorithms such as deep learning cannot effectively reason and infer the road environment, so they cannot perceive and make decisions about the complex road environment,...

AI Technical Summary

Problems solved by technology

The current self-driving vehicles generally drive in relatively simple traffic scenes at relatively low speeds, and cannot be universally applied to most actual road environments. Although artificial intelligence algorithms such as machine learning and deep learning assist self-driving vehicles to better perceive environment, but artificial intelligence algorithms such as deep learning cannot effectively reason and infer the road environment, so they cannot perceive and make decisions about the complex road environment, which limits the development of autonomous vehicle technology to some extent

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