摘 要
本文旨在探讨自动驾驶中的避障问题，并提出一种综合考虑车辆和环境信息的避障算法。首先，论文概述了智能算法的发展历程和分类，特别介绍了多层感知器神经网络模型的基本结构和原理。随后，针对自动驾驶中的避障问题，论文详细分析了其定义和特点，以及车辆信息与环境信息之间的相互作用。在此基础上，论文设计了一种基于多层感知器神经网络模型的避障算法，该算法能够充分利用传感器获取的车辆和环境信息，通过构建合适的数据结构，实现对周围环境的准确感知和有效避障。算法的设计思路包括数据预处理、特征提取、模型训练和实时避障决策等步骤，其中多层感知器神经网络模型的构建是算法的核心部分。通过该算法，自动驾驶车辆能够在复杂多变的道路环境中，实现对障碍物的实时检测和避让，提高自动驾驶的安全性和可靠性。本文的研究为自动驾驶技术的发展提供了新的思路和方法，具有重要的理论意义和应用价值。
关键词：自动驾驶；智能算法；避障
Abstract
This paper aims to explore the problem of obstacle avoidance in autonomous driving and propose an obstacle avoidance algorithm that considers vehicle and environmental information. First, the paper gives an overview of the development process and classification of intelligent algorithms, and especially introduces the basic structure and principle of the multi-layer perceptron neural network model. Subsequently, in view of obstacle avoidance in autonomous driving, the paper analyzes its definition and characteristics, as well as the interaction between vehicle information and environmental information. On this basis, the paper designs an obstacle avoidance algorithm based on the multi-layer perceptron neural network model. The algorithm can make full use of the vehicle and environment information obtained by the sensor, and realize the accurate perception and effective obstacle avoidance of the surrounding environment by constructing an appropriate data structure. The design idea of the algorithm includes the steps of data preprocessing, feature extraction, model training and real-time obstacle avoidance decision, among which the construction of multi-layer perceptron neural network model is the core part of the algorithm. Through this algorithm, the autonomous vehicles can realize the real-time detection and avoidance of obstacles in the complex and changeable road environment, and improve the safety and reliability of the autonomous driving. The research in this paper provides new ideas and methods for the development of autonomous driving technology, which has important theoretical significance and application value.
Keywords: Autonomous driving; intelligent algorithm; obstacle avoidance
目 录
1 引言 1
2 智能算法概述 1
2.1 智能算法的发展和分类 1
2.2 多层感知器神经网络模型介绍 1
3 自动驾驶避障问题分析 2
3.1 避障问题的定义和特点 2
3.2 车辆信息与环境信息的相互作用 3
4 综合考虑车辆和环境信息的避障算法 3
4.1 算法设计思路 3
4.2 基于传感器获取车辆和环境信息的数据结构 5
4.3 多层感知器神经网络模型的构建 5
5 结论 6
致 谢 7
参考文献 8
本文旨在探讨自动驾驶中的避障问题，并提出一种综合考虑车辆和环境信息的避障算法。首先，论文概述了智能算法的发展历程和分类，特别介绍了多层感知器神经网络模型的基本结构和原理。随后，针对自动驾驶中的避障问题，论文详细分析了其定义和特点，以及车辆信息与环境信息之间的相互作用。在此基础上，论文设计了一种基于多层感知器神经网络模型的避障算法，该算法能够充分利用传感器获取的车辆和环境信息，通过构建合适的数据结构，实现对周围环境的准确感知和有效避障。算法的设计思路包括数据预处理、特征提取、模型训练和实时避障决策等步骤，其中多层感知器神经网络模型的构建是算法的核心部分。通过该算法，自动驾驶车辆能够在复杂多变的道路环境中，实现对障碍物的实时检测和避让，提高自动驾驶的安全性和可靠性。本文的研究为自动驾驶技术的发展提供了新的思路和方法，具有重要的理论意义和应用价值。
关键词：自动驾驶；智能算法；避障
Abstract
This paper aims to explore the problem of obstacle avoidance in autonomous driving and propose an obstacle avoidance algorithm that considers vehicle and environmental information. First, the paper gives an overview of the development process and classification of intelligent algorithms, and especially introduces the basic structure and principle of the multi-layer perceptron neural network model. Subsequently, in view of obstacle avoidance in autonomous driving, the paper analyzes its definition and characteristics, as well as the interaction between vehicle information and environmental information. On this basis, the paper designs an obstacle avoidance algorithm based on the multi-layer perceptron neural network model. The algorithm can make full use of the vehicle and environment information obtained by the sensor, and realize the accurate perception and effective obstacle avoidance of the surrounding environment by constructing an appropriate data structure. The design idea of the algorithm includes the steps of data preprocessing, feature extraction, model training and real-time obstacle avoidance decision, among which the construction of multi-layer perceptron neural network model is the core part of the algorithm. Through this algorithm, the autonomous vehicles can realize the real-time detection and avoidance of obstacles in the complex and changeable road environment, and improve the safety and reliability of the autonomous driving. The research in this paper provides new ideas and methods for the development of autonomous driving technology, which has important theoretical significance and application value.
Keywords: Autonomous driving; intelligent algorithm; obstacle avoidance
目 录
1 引言 1
2 智能算法概述 1
2.1 智能算法的发展和分类 1
2.2 多层感知器神经网络模型介绍 1
3 自动驾驶避障问题分析 2
3.1 避障问题的定义和特点 2
3.2 车辆信息与环境信息的相互作用 3
4 综合考虑车辆和环境信息的避障算法 3
4.1 算法设计思路 3
4.2 基于传感器获取车辆和环境信息的数据结构 5
4.3 多层感知器神经网络模型的构建 5
5 结论 6
致 谢 7
参考文献 8
