Public participation is crucial for designing livable cities and accelerating planning procedures. A key challenge is the complexity of planning documents, which are often difficult for non-experts to understand. Digital participation and techniques like 3D visualizations and Building Information Modeling (BIM) offer promising solutions to enhance the comprehensibility and acceptance of construction projects. This study aims to develop an assessment matrix for participation procedures that enables the quality and effectiveness of such processes to be comprehensively evaluated. A systematic literature analysis is first used to identify success factors and challenges of public participation as well as specific success factors and challenges for digital forms of participation (e-participation). These success factors are divided into the categories of resources, communication and process-related aspects, while challenges are categorized into stakeholder-specific and overarching aspects. Based on these findings, an assessment matrix is created to evaluate public participation in the context of planning and approval procedures. The assessment matrix includes parameters such as background information, the participation process, planning documents, and responses and their respective impacts. This matrix will be applied in the BIM4People research project, funded by the Ministry of Digital and Transport (BMDV), to identify improvements in current participation processes and explore how BIM models can optimize them.

Public participation is a central component of democratic decision-making processes, particularly in planning and approval procedures. However, increasing data complexity and the growing number of submitted objections significantly raise the effort required for their review and processing. Against this background, this study developed an AI-supported objection management system that uses a large language model (LLM) to automatically pre-sort objections by topic and generate response suggestions based on historical objection texts from previous infrastructure projects. The aim is to increase efficiency in the processing workflow while maintaining consistent response quality without replacing human decision-making. The prototype development is preceded by a literature review to identify key user requirements and derive relevant use cases. Subsequently, four expert workshops with representatives from German road and rail infrastructure administrations at the state and federal level were conducted to evaluate the prototype. The results indicate significant efficiency potential, particularly through automated thematic pre-sorting of objections. However, topic structures must be adapted to the specific procedure. AI currently mainly serves as supportive pre-processing and requires human review (“human-in-the-loop”). Transparent labeling of AI use is also necessary to ensure traceability and acceptance. The findings will be incorporated into the ongoing development of the prototype within the BIM4People research project funded by the German Federal Ministry of Transport (BMV), with the aim of further improving the system’s functionality and exploring additional applications.

Public participation is critical to the success of construction projects as it enables citizens to influence and engage in planning processes. Traditional participation methods often rely on two-dimensional technical plans, which are frequently perceived as difficult to understand, particularly by non-experts. In recent years, digital visualization techniques, especially 3D models, have emerged as promising alternatives. These approaches promise to enhance communication among stakeholders and deepen engagement by offering clearer and more comprehensible representations of construction projects. This paper explores how public participation based on 3D BIM model data can be implemented and examines the user experiences associated with such an approach. The concept is built on a 3D BIM modelbased participation platform integrated with a Common Data Environment (CDE), which serves as the source for three different model variants. A prototype of the participation platform was tested in the context of public involvement for the redesign of a mobility space in a German city. Citizens were therefore invited to interact with the various model variants and actively participate in the process. Findings from this initiative demonstrate that guided textual information with 3D visuals enhances citizens' comprehension of the project. Users particularly valued the 3D models for enhancing their understanding, while expressing a preference for rather realistic models, even if they are more complex. In summary, the results suggest that BIM models can significantly enhance public participation by improving comprehension and engagement, ultimately contributing to social sustainability.

In the context of infrastructure planning, citizen objections play a central role in the participation process and in political decision-making. As these objections are often unstructured and not machine-readable, processing them is time-consuming and causes delays and inefficiencies in the management of public concerns.

Public participation is a central element of democratic decision-making processes, but it often faces challenges within planning approval procedures due to problems of understanding and accessibility. This paper aims to counteract these challenges through the conceptual development, prototypical implementation and validation of a chatbot. The chatbot is designed to facilitate access to planning documents and improve the participation process as a whole. After presenting the theoretical foundations of chatbots and large language models (LLMs), three central use cases are described. The main tasks of the chatbot are to simplify the language of complex planning documents, find documents and information, and answer frequently asked questions. The underlying architecture of the prototype is based on the concept of retrieval augmented generation (RAG) and uses a vector database in which the information is embedded and stored as vectors. To evaluate the developed prototype, four focus workshops were conducted with professionals affiliated with road and rail infrastructure administrations at both state and federal levels in Germany. During these workshops, participants tested the core functionalities and assessed the system using both quantitative and qualitative criteria. The results indicate a strong potential for improving the handling of standard inquiries. By improving access to complex planning documents, the system may also contribute to a reduction in objections. At the same time, the evaluation emphasizes the importance of limiting hallucinations through appropriate technical safeguards and clearly indicating the use of AI to users. The insights gained from this study will be incorporated into the prototype developed within the BIM4People research project, funded by the German Federal Ministry of Transport. The aim therefore is to implement additional use cases and continuously optimize the functionality of the system through an iterative development process.