Mobilapp för mätning av cykelvägars ojämnheter: en studie av möjligheterna

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In this study the researchers have investigated the possibilities of measuring irregularities on a cycle path with the aid of the accelerometers in smartphones. Smoothness is an important parameter for describing the functional state of the cycle infrastructure. Measurements and methods of measurement objectively describing functional status are needed so that interaction effects can be identified and functional requirements which take the needs and circumstances of cyclists into account can be defined. Objective measurements of functional status can also be fed into maintenance planning, choice of action and monitoring of action outcomes. Using mainly field studies, we have evaluated a mobile app developed at VTI for measuring surface smoothness. Cyclists have collected quantitative data with the VTI app, using a phone fitted to the handlebars and were also asked to rate their subjective perception of comfort when riding over different surfaces. The results show that the acceleration values recorded with the VTI app vary from one measurement to another but that it is possible, on the basis of these values, to distinguish between surfaces of differing quality. However, the observed acceleration values hinge on the mobile phone used, the cyclist’s lateral positioning and speed etc. The results of measurements with the VTI app tally quite well with the cyclists’ subjective ratings of the ride quality of different surfaces. This project presents results from the project CyCity Theme C - Dp10 and a project from the Swedish Road Administration, Evaluation of ways to monitor cycle path condition with a smartphone. CyCity Theme C - Dp10 is part of the Vinnova-funded research programme CyCity. One conclusion is that there are good prospects of supplementing the BikeRoute cycle planning tool, devised within CyCity, by gathering data with the VTI app describing the smoothness of cycle paths using the VTI app. The VTI app is not yet applicable for crowdsoursing, but valuable when gathering data under controlled settings and is worth developing further for measuring the status of cycle path surfacing.

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