Cyclists' perceived safety on intersections and roundabouts - A qualitative bicycle simulator study.

INTRODUCTION: Although cycling provides both individual and societal benefits, the mode share in Germany remains at a relatively low level. One reason described in literature is the lack of perceived safety due to the cycling infrastructure, especially at junctions. The study addresses the influence of junction design on cyclists' perceived safety. METHOD: Three intersections (BS: Berlin Standard, PI: protected intersection, CbC: cycle lanes between car lanes) and one roundabout were modeled in a virtual environment. Using a bicycle simulator, n = 46 participants cycled through each junction design, followed by a qualitative interview. We conducted a structured content analysis on the interview transcripts. RESULTS: Regarding the quality of statements, PI provides the highest level of perceived safety whereas CbC provides the lowest level. Both roundabout and BS provide medium to low perceived safety. Specific design features, such as continuous cycling infrastructure, physical separation and elements enhancing cyclists' visibility improve participants' perceived safety. On the other hand, curbs, bends, and elements obstructing visibility decrease perceived safety. Our findings also point towards a difference between overextending and manageable interactions between cars and cyclists. While manageable interactions raise attention to an appropriate extent, overextending interactions diminish the quality of the cycling experience so that some cyclists rather violate rules instead of using the designated cycling infrastructure. Furthermore, three factors influence participants' perception of infrastructure design: comprehensibility, comfort, and perceived safety. CONCLUSIONS: To provide a cycling friendly infrastructure, planners should consider cyclists' perceived safety as well as comfort and comprehensibility. Furthermore, in contrast to isolated segments, a continuous high-quality cycling infrastructure network should be implemented. Lastly, infrastructure might focus on manageable interactions rather than cause overextending interactions. PRACTICAL APPLICATION: The findings should be considered in future cycling infrastructure planning. Planners may test and modify temporary solutions to find appropriate designs for each junction.

Methodology for a reverse engineering process chain with focus on customized segmentation and iterative closest point algorithms.

One-off construction is characterized by a multiplicity of manual manufacturing processes whereby it is based on consistent use of digital models. Since the actual state of construction does not match the digital models without manually updating them, the authors propose a method to automatically detect deviations and reposition the model data according to reality. The first essential method is based on the "Segmentation of Unorganized Points and Recognition of Simple Algebraic Surfaces" presented by Marek Vanco (2003). The second method is the customization of the iterative closest point (ICP) algorithm. The authors present the overall structure of the implemented software, based on open source and relate it to the general reverse engineering (RE) framework by Buonamici et al. (2017). A highlight will be given on.•The general architecture of the software prototype.•A customized segmentation and clustering of unorganized points and recognition of simple algebraic surfaces.•The deviation analysis with a customized iterative closest point (CICP) algorithm.Especially in the field of one-off construction, characterized by small and medium companies, automated assessment of 3D scan data during the design process is still in its infancy. By using an open source environment progress for consistent use of digital models could be accelerated.

Configurable Sensor Model Architecture for the Development of Automated Driving Systems.

Sensor models provide the required environmental perception information for the development and testing of automated driving systems in virtual vehicle environments. In this article, a configurable sensor model architecture is introduced. Based on methods of model-based systems engineering (MBSE) and functional decomposition, this approach supports a flexible and continuous way to use sensor models in automotive development. Modeled sensor effects, representing single-sensor properties, are combined to an overall sensor behavior. This improves reusability and enables adaptation to specific requirements of the development. Finally, a first practical application of the configurable sensor model architecture is demonstrated, using two exemplary sensor effects: the geometric field of view (FoV) and the object-dependent FoV.