The Application of Artificial Intelligence Technology in Road Traffic Management

YANG Jianping

(Beijing Zhongke Soft Technology Co., Ltd., Beijing 100090, China)

Abstract: With the continuous acceleration of urbanization, road traffic management is facing increasing challenges. In order to solve problems such as traffic congestion, frequent accidents, and environmental pollution, the application of artificial intelligence technology in road traffic management has become increasingly important. Artificial intelligence technology can optimize road traffic management, improve traffic efficiency and safety through data analysis, intelligent control, and predictive models. By collecting road traffic data, such as traffic flow, speed, and driving routes, artificial intelligence can quickly analyze the data and predict traffic conditions. Based on the prediction results, the traffic management department can take targeted measures, such as adjusting the timing of traffic lights, guiding traffic flow, etc., in order to reasonably allocate traffic resources and reduce traffic congestion. The article will conduct corresponding analysis on the application of artificial intelligence technology in road traffic management for reference.

Key words: manual labor; intelligent technology; road traffic; management; application

0 引言

随着人工智能技术的不断发展和应用，道路交通管理可借助其进一步提升效率、提高安全性、优化资源配置，为城市的可持续发展贡献力量。因此，进一步研究和推广人工智能技术在道路交通管理中的应用是非常必要的。

1 人工智能技术原理

人工智能技术的原理涉及深度学习、机器学习和自然语言处理等多个领域。

（1）深度学习是一种机器学习的方法，通过建立人工神经网络模型来模拟人类大脑和神经机能。深度学习使用多个层次的神经元连接来处理和学习数据。这些层次结构可以自动地从数据中提取特征，并构建复杂的模型来执行任务，如图像识别、语音识别

和自然语言处理等。

（2）机器学习是一种让计算机系统自动地从经

验数据中学习和改进性能的方法。在机器学习中，算法通过建立数学模型从数据中学习，而不是直接进行编程。机器学习主要分为监督学习、无监督学习和强化学习。监督学习通过已标记的数据进行学习，无监督学习通过未标记的数据进行学习，而强化学习则通过与环境的互动学习来进行决策。

（3）自然语言处理（NLP）是指计算机与人类自然语言之间的交互与沟通。NLP使用机器学习和深度学习的方法来理解、分析和生成自然语言。NLP涵盖

多个任务，如文本分类、语义分析、语言生成和机器翻译等。通过构建自然语言处理模型，计算机可以理解和处理语言的语义、语法和语境，从而实现与人类的有效沟通。