Abstract
The relationship between walking and people's health has been scientifically demonstrated. In the 1970s, doctors managed and succeeded in jogging for heart disease patients in the United States. In addition, there are reports in Germany that very few cases of cancer among joggers. Under its influence, Japan also rose extremely popular jogging fever from top to bottom. Because of the great individual differences and some disadvantages of sports, people's interest has gradually shifted to walking in recent years. From both physical and mental point of view, walking is a safe, effective and easy way of exercise, which is conducive to cultivating people's positive and optimistic attitude and healthy lifestyle. Modern urban development only pays attention to function and efficiency, ignoring the health problems caused by lack of physical activity. After the 21st century, with the rapid development of China's economy, the width of urban roads has been increasing and the scale of cities has been expanding. On the contrary, the demand for pedestrian travel in cities has not been taken seriously, such as the lack of necessary pedestrian facilities, poor street connectivity, and insufficient guarantee of walking safety. As a result, the share rate of pedestrian trips is gradually reduced, and the amount of physical activity of the population is greatly reduced. It has become an important reason for the gradual increase in the proportion of chronic diseases in China. Therefore, it is of great significance to study the optimal design of pedestrian space in urban streets. The development of Internet technology and information and communication technology under the new data model not only provides technical and data support for intuitive quantitative analysis method, but also provides data support for the research of urban pedestrian system. The emergence of "open data" and "big data" has changed the data base of the study, and the enhancement of the data environment has provided a new opportunity for the study of urban pedestrian space. This paper combines the innovative artificial intelligence research method "deep learning" with the traditional research method, and makes a more comprehensive analysis of the present situation and existing problems of urban pedestrian space, and puts forward the corresponding optimization design method. Urban pedestrian space is an important component of the overall urban environment, which is closely related to the lives of residents. The study of urban pedestrian space has practical significance for creating a better living and working environment for the majority of urban residents. It mainly includes: Firstly, a good urban pedestrian space environment can improve the comfort and safety of walking, and provide the basic needs and guarantees for walking activities; Secondly, through the optimization of urban pedestrian space, it not only improves the quality of pedestrian space, facilities and landscape, microclimate, but also provides a more humanized and diversified activity space for the majority of urban residents, and increases the humanistic feelings of the city; Thirdly, the reasonable planning and design of urban pedestrian system is conducive to improving urban traffic, beautify the environment and guide people to travel green, which is of great significance to the construction of eco-healthy cities.
