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However, the expansion and increased use of bike infrastructure has been accompanied by a glut of bike accidents, a trend jeopardizing the urban bike movement. This paper leverages data from a diverse spectrum of sources to characterise geolocated bike accident severity and, ultimately, study cycling risk and discomfort. Kernel density estimation generates a continuous, empirical, spatial risk estimate which is mapped in a case study of Z\u00fcrich city. The roles of weather, time, accident type, and severity are illustrated. A predominance of self-caused accidents motivates an open-source software artifact for personalized route recommendations. This software is used to collect open baseline route data that are compared with alternative routes minimizing risk and discomfort. These contributions have the potential to provide invaluable infrastructure improvement insights to urban planners, and may also improve the awareness of risk in the urban environment among experienced and novice cyclists alike.<\/jats:p>","DOI":"10.1007\/s00607-019-00771-y","type":"journal-article","created":{"date-parts":[[2019,12,9]],"date-time":"2019-12-09T14:02:51Z","timestamp":1575900171000},"page":"1259-1274","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":20,"title":["On cycling risk and discomfort: urban safety mapping and bike route recommendations"],"prefix":"10.1007","volume":"102","author":[{"given":"David","family":"Castells-Graells","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Christopher","family":"Salahub","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3900-2057","authenticated-orcid":false,"given":"Evangelos","family":"Pournaras","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,12,9]]},"reference":[{"key":"771_CR1","doi-asserted-by":"crossref","unstructured":"Amini S, Gerostathopoulos I, Prehofer C (2017) Big data analytics architecture for real-time traffic control. 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