Enhancing participatory planning with ChatGPT-assisted planning support systems: a hypothetical case study in Seoul

参与式规划 公民新闻 过程管理 环境规划 计算机科学 业务 地理 万维网
作者
Steven Jige Quan,Seojung Lee
出处
期刊:The International Journal of Urban Sciences [Taylor & Francis]
卷期号:29 (1): 89-122 被引量:12
标识
DOI:10.1080/12265934.2025.2462823
摘要

Recent advancements in technology for planning support have led to increased interest in participatory planning support systems (PPSSs). However, existing PPSSs often struggle to facilitate higher levels of public participation due to limitations in their practical usefulness. Emerging large language models (LLMs) like ChatGPT, along with artificial intelligence (AI) technologies such as deep generative methods, offer new opportunities to enhance PPSS, though this potential has yet to be fully explored. This study aims to address these gaps by integrating LLMs, specifically ChatGPT, into a new web-based PPSS platform. The platform operates as a multi-agent system with five key components: users, process, agents, knowledge, and tools. Stakeholders engage with ChatGPT-enabled personalized agents that are supported by a project-specific knowledge base. These agents understand user preferences, concerns, and needs, and call upon task agents, also powered by ChatGPT, to execute tasks, including applying deep generative tools that enable stakeholders to create their own designs. A workflow agent coordinates the overall process, facilitating the sharing of information, data, opinions, and designs to promote communication and build consensus among stakeholders. The platform was tested in a hypothetical sustainable urban regeneration case, the New Seollo Project in Seoul. Compared to the actual Seoullo project, which faced substantial criticism, the simulated results suggest the platform’s potential to significantly improve participation and generate better design solutions. This new PPSS platform enhances usefulness by improving stakeholder communication and empowering the public to contribute comprehensive, inclusive, and creative solutions for sustainable urban development.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
星辰大海应助儒雅的夏山采纳,获得10
刚刚
xinqisusu发布了新的文献求助10
刚刚
盐焗小崔发布了新的文献求助10
刚刚
搜集达人应助莫弃采纳,获得10
1秒前
贾硕士发布了新的文献求助10
1秒前
情怀应助lsabelie采纳,获得10
1秒前
Juan发布了新的文献求助10
2秒前
2秒前
2秒前
NexusExplorer应助不安的雪萍采纳,获得10
3秒前
4秒前
星点点发布了新的文献求助10
4秒前
4秒前
NexusExplorer应助禹宛白采纳,获得10
5秒前
生动的凝蕊完成签到,获得积分10
5秒前
派大星完成签到 ,获得积分10
5秒前
明天发布了新的文献求助10
5秒前
搜集达人应助wwb采纳,获得10
5秒前
5秒前
安南应助lilili采纳,获得10
6秒前
万能图书馆应助lilili采纳,获得10
6秒前
风趣的凡完成签到 ,获得积分10
7秒前
传统的孤丝完成签到 ,获得积分10
7秒前
kuiuLinvk完成签到,获得积分10
7秒前
慕夏发布了新的文献求助10
7秒前
7秒前
Manuela完成签到,获得积分10
8秒前
biyy完成签到,获得积分10
8秒前
8秒前
9秒前
keji发布了新的文献求助10
9秒前
xinqisusu完成签到,获得积分10
9秒前
完美亦竹给完美亦竹的求助进行了留言
9秒前
10秒前
大海发布了新的文献求助10
11秒前
Weimiao关注了科研通微信公众号
11秒前
CodeCraft应助暗回采纳,获得10
11秒前
满意曼寒发布了新的文献求助10
12秒前
zhezhe发布了新的文献求助10
13秒前
13秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Organic Reactions, Volume 116 1500
VALIDATION OF THE TAYLOR, ALAMEL AND VPSC MODELS FOR PLASTIC ANISOTROPY MODELING OF SHEET METALS 1000
Geist der Kunst und Kultur 1000
Resistance Spot Welding Dataset for Automobile Body-in-White Quality Analysis 748
悉尼大学博士学位论文,题目:Modelling and testing of one-sided stitched laminated composites. 作者:Kristopher P. Plain 700
Machine Learning for Asset Management and Pricing 600
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7404809
求助须知:如何正确求助?哪些是违规求助? 9009511
关于积分的说明 19185860
捐赠科研通 7038269
什么是DOI,文献DOI怎么找? 3231887
关于科研通互助平台的介绍 2394147
邀请新用户注册赠送积分活动 2213858