Artificial intelligence enabled participatory planning: a review

Figures & data

Table 1. Example of case studies with both AI and participatory planning (full table see appendix Table A).

Author (year)	Participatory planning procedure	AI methods	Key findings
Walisadeera et al. (2015)	Accessibility of scientific evidence for farmers	Crawler, ontology query system	Enabled knowledge gain for Sri Lankan farmers through a context-aware system.
Miranda et al. (2016)	Project cost prediction	Optimization	Provided initial cost-benefit insights for environmental protection plans in Porto and Brussels.
Shin et al. (2017)	Updating large-scale discussions	CNN, rule-based system, NER	Demonstrated the effectiveness of the eplamier map service in Singapore.
Yu et al. (2017)	Communication facilitation	Best-first Conflict-Directed Relaxation algorithm	Resolved over-subscribed scheduling problems in urban travel planning and transit system management.
Bakht et al. (2018)	Information collection	K-nearest neighbours, Naïve Bayes, Support Vector Machines	Detected community opinion evolution about urban projects through tweet analysis.
Kerebel et al. (2019)	Local knowledge collection	Bayesian networks	Designed a participatory methodology for evaluating landscape aesthetics.
Quan et al. (2019)	Auto-generation of plans	Genetic algorithms, Scientific performance simulation tools	Identified design solutions for sustainable city development in Seoul.
Austin et al. (2020)	Result prediction	Decision Tree	Predicted energy consumption in various scenarios in the Chicago Metropolitan Area.
Liu et al. (2020)	Idea generation	Word2vec	Validated the superiority of AI over wordnet in inspiring design ideas.
Lock & Pettit (2020)	Public opinion collection	IBM Watson Tone Analyzer, VADER, LDA	Found social media as a complementary tool to citizen surveys.
Pournaras (2020)	Witness presence verification	Blockchain consensus	Enhanced participant credibility by recording the decision process in Zurich.
Yang et al. (2020)	Expert identification and water quality monitoring	Adaboost	Developed a model for objective and automatic expert selection and opinion integration.
Haqbeen et al. (2021)	Communication facilitation	Recurrent neural network, Graph neural network	Achieved comparable response rates to human facilitators in an online urban planning forum in Afghanistan.
Kumar et al. (2021)	Communication facilitation	Random Forest	Identified redundant indicators for assessing community sustainability in Kolkata.
Li et al. (2021)	Local knowledge analysis	Decision trees, ensemble learning	Contributed to facilities adjustments and location selections in urban planning.
Lock et al. (2021)	Land value prediction	Xgboost	Found positive attitudes towards AI among planners and developers in Sydney.
Shin et al. (2021)	Communication facilitation	Boosted Classification Tree	Identified factors associated with dispute intensity in multi-owned buildings in Victoria.
Tian et al. (2021)	Satisfaction prediction	Long short term memory neural network	Predicted customer satisfaction for logistic service using simulated data.

Figure A. Summary of this review

Figure B. Systematic review workflow (after Page et al., 2021).

Table A. Full annotated bibliography of case studies with both AI and participatory planning in chronological order.

Author(year)	Participatory planning procedure	AI methods	Findings
Do and Gross (2001)	Designs at varying levels of abstraction and detail	Image processing algorithms	The paper identified requirements for computational support for the diagrams in design thinking.
Nijkamp et al. (2002)	Identify successful experience for participatory planning	Rough set analysis	Using an AI model to analyze nine Urban Land-use and Revitalization projects in Netherlands, the authors found a Public – Private Partnerships arrangement has a high chance of becoming successful, if it is designed based on joint-venture model.
Yasumoto et al. (2012)	Collecting local knowledge about building height	3D analysis	Aided by the building height information, building design and city planning can improve equity in the access to sunlight
Walisadeera et al. (2015)	Made scientific evidence more accessible for Sri Lankan farmers	Crawler, ontology query system	Sri Lankan farmers can gain knowledge in this context aware system.
Ai et al. (2016)	Selecting leaders to pass out the alert, Predicting the possible consequences of alternative emergency management plans	Optimization (heuristic algorithm)	The AI system has potential to support evacuation strategies and real-time guidance of communities at risk during disaster.
Miranda et al. (2016)	Predicting project costs on different scenarios	Optimization	In Porto Region and Brussels Capital Region, the models allowed stakeholders to have a first idea of the optimal investment costs and benefits in the environment protection plan. The author also found that the tools should be extended to allow their users to consider the implications of political and social acceptance in an early stage of the decision process.
Rodriguez-Soto et al. (2017)	Predicting stakeholder’s willingness to corporate	Artificial intelligence ensemble model	Agrarian communities that have coexisted for millennia with umbrella species can be regarded as allies in biodiversity conservation
Shin et al. (2017)	Keep everyone updated in a large-scale discussion by automatically enriching plan with geographical insights	CNN, rule-based system and NER	Results are presented on the eplamier, which is a map service on the GIS implemented by the urban redevelopment authority of Singapore.
P. Yu et al. (2017)	Facilitating communication by identifying temporal scheduling problems	Best-first Conflict-Directed Relaxation algorithm based on Conflict-Directed A* Algorithm	It has demonstrated its effectiveness in helping users resolve over-subscribed scheduling problems and evaluated the robustness of existing solutions for urban travel planning and transit system management.
Bakht et al. (2018)	Collecting information	K-nearest neighbours, Naïve Bayes and Support Vector Machines	Using AI to analyze tweets helped detect the evolution of community opinion about urban projects
Sharma et al. (2018)	Predict climate change	Integrated model of atmosphere, land, and lake	The authors stress the need to include input from diverse stakeholders in the development of tools to ensure the quality and usability of impact assessments.
Zhang, Grignard, Lyons, Aubuchon, and Larson (2018)	Predict the traffic based on different land-use patterns	Agent-based model	The result is a versatile, quick, accurate, and computationally efficient approach to provide real-time feedback and optimization for urban decision-making.
Barbosa et al. (2019)	Predicting results of alternative plans	Random Forest, Boosted Regression Trees and Maximum Entropy	Stakeholders define the problem and choose restoration and conservation plans in Andalusia (Spain) – Morocco based on results predicted by AI model
Elizalde-Ramirez et al. (2019)	Predicting results for alternatives transportation plans	Integer mathematical programming	The analysis identifies user preferences as the most critical factor that increases solution complexity for planning models.
Kaklauskas et al. (2019)	Collecting local knowledge to give tips for stakeholder groups.	Computer vision to detect emotions and demographical information	Can assist public spaces planning and a participation process by attendees by collecting and examining the emotional and physiological parameters of visitors.
Kerebel et al. (2019)	Collecting local knowledge about Landscape aesthetic	Bayesian networks	A participatory methodology for evaluating landscape aesthetics was designed to weigh indicators according to stakeholder preferences,
Martinez-Lopez et al. (2019)	Collecting ecosystem services of interest from stakeholders, then participants make plans with synthesized opinion	General linear models	The human-AI co-developed solutions can support adaptive management and the conservation of coastal ecosystems in Portugal.
Quan et al. (2019)	Auto-generate plans in a superblock based on participants input	Genetic algorithms, Scientific performance simulation tools	The case study in Seoul, South Korea illustrates how the framework identifies design solutions for sustainable city development in the process of participatory decision-making.
Zhao et al. (2019)	Explore nonlinear relationships between agent behaviours and decision-making environments and efficiently identify solutions to land use allocation in a spatially explicit way	Agent-based model and heuristic methods	The optimal allocation solutions obtained by the agent-based model are more applicable based on the support of the factual evidence than those obtained by the non-agent-based model. The proposed model can integrate the simulated local decision of stakeholders and global optimization of the specified objectives in land use planning, and thus provide a flexible theoretical framework to support the reform of China’s spatial planning system.
Y. Hu et al. (2019)	Collecting local knowledge	Sentiment analysis, topic modelling	This research was applied to New York City community reviews to support urban planning
Auerbach et al. (2020)	Budgeting	Random Forest	Data collected from residents can also correct and update the information, which would increase the accuracy of the programme estimates and validate the modelling, leading to a novel integration of AI and participatory planning
Austin et al. (2020)	Predicting results from alternative plans	Decision Tree	They used AI models to predict the energy consumption with several scenarios in the Chicago Metropolitan Area
Escobedo et al. (2020)	Assess the ability of different stakeholders	Classification and Regression Trees	This study used an AI model to identify and assess different stakeholder’s abilities in recognizing different processes from landscapes as well as their difficulty in accurately locating areas of interest. Low cost and participatory approaches can be used to design more context-relevant survey instruments for ecosystem service valuation research and assessments
Liu, Wang, Li, and Liu (2020)	Comparative analysis of recommended candidate warehouses.	Matrix-factorization and rule based algorithms for processing data	A case study in Shanghai, China, confirmed the efficacy of the system
Liu et al. (2020)	Inspire designers’ idea generation	Word2vec	Their demo validated that the AI method is better than wordnet for inspiring designers to generate design ideas.
Lock & Pettit (2020)	Ask people’s opinion on social media	The IBM Watson Tone Analyzer, VADER, LDA (Sentiment analysis and topic modelling)	Social media can be complementary to citizen surveys due to the sample and the techniques limitation
Nousdilis et al. (2020)	Assess the impact of various incentive policy schemes and operation strategies on the economic viability	Techno-economic modes based on an exhaustive optimization search	The results can be a valuable guide for policymakers and the market regulators to design new incentive schemes
Pournaras (2020)	Proving witness presence	Blockchain consensus.	The testnet scenario in Zurich showed that the model can enhance the credibility of participants by recording the decision process
van den Homberg et al. (2020)	Trigger the release of funds typically used for humanitarian response in advance of an impending typhoon to start up early actions to mitigate its potential impact.	Random forest and artificial neural networks	They highlighted emerging actors and fora in the accountability relationship of anticipatory humanitarian action as well as the consequences arising from actors’ (mis)conduct.
Yu et al. (2021)	Environmental planning, gathering local knowledge, garbage volume prediction, optimize waste collection	Multiple optimization algorithms	Their model helps collect information from multiple stakeholders and improving environmental planning and urban management performance, accuracy, and efficiency in Dongguan City, China.
Yang et al. (2020)	Identify experts. Monitoring water quality	Adaboost	A model was developed to select experts and integrate opinions objectively and automatically for governance alternatives in Yuyuantan Lake Beijing, China
Haqbeen et al. (2021)	Facilitating communication (content labelling, document summarization, and sentiment analysis in online forum)	BERT, recurrent neural network, Graph neural network,	The AI facilitator in online forum for urban planning in Afghanistan achieve almost the same response rate as human facilitators.
Kaklauskas et al. (2021)	Studies local knowledge such as emotional, affective, and physiological states, arousal and valence of the passersby.	Neuro decision matrix, which assisted in deriving a comprehensive analysis of the urban areas	The affective system for researching emotions was proven a helpful supplement to urban planning and public participation practice in the Vilnius city, Lithuania.
Kumar et al. (2021)	Facilitating communication	Random Forest	The participants first came up with many indicators for assessing the economic-socio-cultural sustainability of communities in Kolkata, India, then used AI model to identify the redundant indicators.
Li et al. (2021)	Analyzing local knowledge about human behaviour	Decision trees and ensemble learning	The proposed method and delineation results contribute to facilities adjustments and location selections in life circle planning, people-oriented transformation in urban planning.
Lock et al. (2021)	Predicting changes in land value based on different planning scenarios	Xgboost	In the workshops in Sydney, Australia, general attitudes towards artificial intelligence for planners and developers were positive, as they were seen as both potentially transformative but also as simply another technique to assist with workflows.
Shin et al. (2021)	Facilitating communications by understanding and predicting disputes	Boosted Classification Tree	Using the dispute cases in Victoria, Australia, this research confirms six factors highly associated with the dispute intensity in multi-owned buildings.
Shuler et al. (2021)	Predicting the change of water resources based on alternative land-use plans	Soil Water-Balance-2 model, dynamically downscaled general circulation climate model	Using future land use proposed by local stakeholder group, the model predicted future sustainability of essential resources in Tutuila Island, American Samoa.
Stamatiadou et al. (2021)	Collaborative collection and documentation of soundscapes and environmental sound semantics	A feature-based machine learning network and a convolutional deep learning architecture for sound classification	The AI models automatically labelled the crowdsourcing sound scape data for heritage protection, making the data management easier.
Tian et al. (2021)	Predicting satisfaction of alternative plans, making compensation to those unsatisfied customers	Long short term memory neural network	They used simulated data to predict customer satisfaction for logistic service. A smart contract based on block chain was designed to increase the transparency and protect sensitive information between logistics enterprises and the third authorities like banks and governments.
Ye et al. (2021)	Colorize master plans	GAN	The user cannot distinguish which master plan was generated by computer.

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