Mobile Pedestrian Navigation Framework for Multi-factors Resources Allocation (original) (raw)
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Zusammenfassung ...............................................................................................237 Summary .............................................................................................................238
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Smart and sustainable mobility have recently emerged as a solution to the problems incurred by the intensive use of motorised transport modes. For many decades, cities have been planned based on the needs of vehicle traffic, neglecting basic human needs for active mobility and the adverse effects of motorised traffic on the natural environment. However, walking is an environmentally friendly transport mode and a healthy form of making physical activity. Thus, walking becomes an essential component of the transport and urban policies for achieving a more sustainable development process. This paper presents the research project Smart Pedestrian Network (SPN) that aims at promoting walkability as one of the critical dimensions of smart and sustainable mobility in cities. The paper analyses the various components linked to SPN that can make a pedestrian network "smart" and, therefore, a feasible alternative to motorised transport modes. Three integrated components are analysed: i) an urban planning component supported in a GIS-based multi-criteria model to assess the conditions provided to pedestrians and to support the adoption of planning policies; ii) a smartphone app for pedestrian navigation, displaying optional routes according to the pedestrian preferences and needs; and iii) a business component to estimate and disseminate the multiple benefits of walking as well as the market potential of SPN. By promoting an innovative linkage of these three components, SPN has a great potential for improving walkability and, therefore, for creating more sustainable and liveable urban spaces.
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Navigation in urban public spaces has proved to be very important factor in creating public life in public spaces. Tracking people movement in most of the studies was done in situ, limited by a small sample of respondents, and the processing of this data was exhausting and long-lasting because it comes down to manual work. On the other hand, virtual environments represent an ideal test site, as the researcher has complete control over the environment. This paper will deal with the method of collecting and processing data about the pedestrian movement through virtual urban space and visualization of these data in parametric software in order to get relevant quantitative sample.