Artificial Intelligence and Street Space Optimization in Green Cities: New Evidence from China

Author:

Liu Yuwei12,Qin Shan3,Li Jiamin4,Jin Ting5

Affiliation:

1. School of Urban Design, Wuhan University, Wuhan 430072, China

2. School of Arts and Communication, China University of Geosciences, Wuhan 430074, China

3. Huzhou University, Huzhou 313000, China

4. Westminster School of Arts, University of Westminster, London HA1 3TP, UK

5. School of Political Science and Public Administration, Wuhan University, Wuhan 430072, China

Abstract

In the context of the green economy and sustainable urban development, the rapid expansion of urban construction has given rise to pressing public health concerns, notably environmental pollution and the increased prevalence of chronic illnesses linked to swift urbanization. These urban health issues are escalating, prompting significant attention to the concept of creating “healthy cities”. Meanwhile, the planning and design of urban street space have a far-reaching impact on urban residents’ quality of life and health. Urban planners are facing challenges and need to follow the principle of a green economy while meeting the needs of residents for public activities and adapting to motor vehicle traffic. This study explores the optimization of urban street space to promote the harmonious coexistence between people and cars. This study actively explores the relationship between health, urban environment, and social background, focusing on promoting the harmonious coexistence between people and vehicles, especially the optimization goal of sharing urban streets. The study’s main goal is to design a road that can meet the needs of citizens’ public activities and accommodate motor vehicles, which conforms to the principle of a green economy. To achieve this, geographic information system (GIS) technology and a genetic algorithm (GA) are employed to optimize shared urban street spaces. Among them, GIS tools are used for spatial simulation to evaluate the effect of different shared street space configurations. The urban shared street space is gradually optimized through GA’s selection, crossover, and mutation operations. Simulation experiments are conducted to determine the relationship between street space utilization and the elements of a healthy city, ultimately striving to identify the optimal design parameters for shared street spaces. The research results reveal that the urban street space is optimized from the three aspects of shared allocation of facilities resources, replacement of land use functions, and mixed layout of facilities, and the utilization rate of urban streets is finally ensured to reach 53.43%, fully assuming the essential functions of urban streets. This innovative approach bridges the gap between urban development and public health, offering valuable insights for sustainable urban space planning and enhanced living environments within the framework of the green economy.

Publisher

MDPI AG

Subject

Management, Monitoring, Policy and Law,Renewable Energy, Sustainability and the Environment,Geography, Planning and Development,Building and Construction

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3