DAIMOND
Full title: Data and AI for decision making support in traffic infrastructure development
DAIMOND is a continuation of SAFER-associated pre-study SINTIA.
This project is starting the AI journey at the Urban Development and Traffic Department in the Jönköping municipality. To achieve positive and cost-efficient outcomes in road infrastructure planning and development, particularly focusing on the safety and comfort of sustainable, active and inclusive modes of mobility, the department needs to shift away from decision-making based on assumptions and individual opinions. Instead, we aim to embrace the use of data driven and AI methods to gain insights and indicators, providing a solid foundation for making informed decisions.
For this initiative, we are introducing AI methods through a case study that focuses on choosing the street crossing types in school areas within Jönköping. Today, advances in machine learning techniques enable the analysis of the data collected from infrastructure sensors and available in municipality's databases, which helps us to understand the behaviors of vulnerable road users like children. Despite the potential offered by these technologies, the effective use of AI for pedestrian safety analysis requires expertise and experience that is currently lacking.
Therefore, this project aims to address this gap by initiating our AI journey within the department. Furthermore, the project aims to develop a prototype for providing decision support in street design, which will be based on the understanding of the road user behaviors. The prototype will serve the purpose of both testing and demonstrating the capabilities of AI technologies.
