The Deployment of Indoor Point Clouds for Firefighting Strategy project was realised as a Synthesis Project of the Geomatics Master Programme of the Built Environment Faculty at the Technical University of Delft. This project was executed by a team of five Master students in collaboration with the Dutch response team collective Veiligheidsregio Rotterdam-Rijnmond. The objective of this project is to develop an information system that makes use of indoor data to support tactical decision-making during fire emergency responses. The main challenge that response teams are facing when they develop deployment plans is the lack of appropriate information about indoor spaces. As a result, response teams may end up relying on inaccurate assumptions which can lead to dangerous situations. New technologies such as SLAM devices and augmented reality displays, combined with processing techniques, can be used to supply them with the information needed to make the right choices. The result of this project is a prototypical information system containing an interactive, 3D environment that can receive updates, merge data from different data sources, and accommodate mixed reality information sharing in real-time.

In recent decades, it is well known that transportation systems have a crucial role in the economic development and social prosperity of modern societies. While road width can be considered as one of the most important factors of the road environments, there is no clear definition of it. To better understand this, we need to reconsider the width of a road not as a single numerical value but as a complex concept that can be interpreted in different ways. Different road users may refer to different width values for the same road. Thus, while estimating road width seems to come with great benefits for different real-world cases, a fundamental rethinking of the purpose of this entire process is necessary. Road safety management is an application whose overall process is strongly affected by the width of the road. While there are conflicting theories about the effect that road width can have on road safety, we may need to reconsider a few things before exploring their relation. In this thesis, we introduce a novel approach for estimating road width and linking it with roads in such a way that the overall process of road safety management application could benefit. Moreover, even road width estimation is not a new topic most of the studies so far use LiDAR point cloud or satellite images as input. In our approach, vector data coming from open-sources are used. Different inputs come with different limitations. The advantages, as well as the drawbacks of the different inputs, will be discussed. Finally, one of the main objectives of this project is to develop a methodology that will be generally applicable. Vector data that can be found in different datasets would be used. Some additional deliverables will result from our efforts to overcome some of the challenges that have arisen in achieving this goal. A methodology that standardizes road vector data and a methodology that identifies the location and the type of the different intersections will be developed