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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorVoinov, A.A.
dc.contributor.authorSteenbergen, T.
dc.date.accessioned2015-07-27T17:01:17Z
dc.date.available2015-07-27T17:01:17Z
dc.date.issued2015
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/20572
dc.description.abstractScooters in the Netherlands are becoming more popular, especially the light-mopeds in urbanized areas. They are more affordable and mobile than cars, especially light-mopeds which may use bicycle lanes. Due to the increase in scooters, a growing number of people is annoyed by the noise scooters bring with them. Noise annoyance is related to health problems like tinnitus and stress. An Agent Based Model was constructed to identify which areas in the city have the most scooters driving by and in what way is this connected to noise annoyance. The Agent Based Model was constructed by using an activity based model. Each individual has a set of activities scheduled and uses the scooter to move from one destiny to the other. Most common activities are work/school/shop/sport. Noise annoyance data is based on a questionnaire and is, together with model output data, analyzed with a logistic regression method. It is found that an increase in regular-mopeds is positively associated with serious noise annoyance. An increase of 100 regular- mopeds per road has a 6% to 17% higher chance of people experiencing serious noise annoyance. Light-mopeds have no association with noise annoyance. Due to a continuing increase in scooters over the next years, it is to be assumed that serious noise annoyance will grow in urban areas, although the most impact will be on people living next to highly dense traffic roads.
dc.description.sponsorshipUtrecht University
dc.format.extent3355653
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleScooters, and their impact on noise annoyance: A case study in Amsterdam
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsAgent Based Model; Scooters; Case Study; Noise Annoyance; GAMA; Amsterdam; Logistic regression
dc.subject.courseuuGeographical Information Management and Applications (GIMA)


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