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Reggiani, G. (author)Although many agree that the use of bicycles improves mobility and quality of life in a city, much less clear is how to assess the progress being made in this direction and how to plan bikeable cities. The bikeability of a city depends on many diverse and interrelated factors such as the land use and transport system, culture and social norms,...doctoral thesis 2022
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Reggiani, G. (author), Salomons, A.M. (author), Sterk, M.A.H. (author), O'Hern, Steve (author), Daamen, W. (author), Yuan, Y. (author), Hoogendoorn, S.P. (author)Similarly to Maslow’s pyramid of human needs, we theorize that cities have a pyramid of bicycle network needs that depends on their level of bicycle culture. As an increasing number of data sources emerge for bicycle data collection, transport authorities face the challenge of understanding how to use the data and which data sources are fit for...journal article 2022
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Reggiani, G. (author), van Oijen, T.P. (author), Hamedmoghadam, Homayoun (author), Daamen, W. (author), Vu, Hai L. (author), Hoogendoorn, S.P. (author)A fully separated bicycle network from vehicular traffic is not realistic even for the most bicycle-friendly cities. Thus, all around the world urban cycling entails switching between streets of different safety, convenience, and comfort levels. As a consequence, the quality of bicycle networks should be evaluated not based on one but multiple...journal article 2021
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Reggiani, G. (author), Dabiri, A. (author), Daamen, W. (author), Hoogendoorn, S.P. (author)A tool for travel time estimation of cyclists approaching a traffic light can monitor level of service of intersections in bike crowded cities. This work represents a first step in developing such a tool. Neural Network models are evaluated on how they perform in estimating individual travel time of cyclists approaching a signalized...conference paper 2020
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Reggiani, G. (author), Dabiri, A. (author), Daamen, W. (author), Hoogendoorn, S.P. (author)The number of queued bicycles on a signalised link is crucial information for the adoption of intelligent transport systems, aiming at a better management of cyclists in cities. An unsupervised machine learning methodology is deployed to produce estimations of accumulation levels based on data retrieved from a bicycle street of the Netherlands....conference paper 2019