Browsing by Author "Raninen, Mikko"

Due to increasing population in cities transportation is facing a major challenge. Passenger car traffic cannot increase at the same rate as urban population increases. Negative externalities like carbon dioxide emissions and congestion are becoming more and more significant issues in urban areas. Only possible way to reduce these negative issues are offering sustainable transportation modes and making them as attractive as possible. Especially leisure trips have increased in past years which means that cities have become more mobile. Active and sustainable mobility like walking and cycling play key roles in transportations strategies. City of Helsinki has started to support cycling over the last few years by investing cycling infrastructure for example. In the context in which cycling has become important in urban areas several cities have opened bike sharing systems. In addition to upswing of cycling, technological development of bike sharing systems have made it possible for them to succeed. In Helsinki, the bike sharing system was launched in 2016 and in 2017 it was expanded threefold compared to the first year of operation. Understanding how recently opened system works requires a proper analysis which is made possible by the travel data produced by the system. Study design consists of revealing spatiotemporal patterns of bike share usages in Helsinki. The aim of the study is to produce important information to support operational planning of the system. On the other hand, the aim is to express the mobility and the rhythm of Helsinki by a novel data source. According to previous international studies, data mining of travel data produced by bike sharing systems has revealed clear activity patterns of bike share usage. The results show that the use of bike sharing system in Helsinki has been a success compared to other European cities for example. According to the results, bike share trips have been short which is typical to bike sharing systems. Temporally, the usage was most active during summer and spatially in the city center as well as near subway stations. The usage was found to vary considerably between weekdays and weekends. On weekdays, the usage peaked at morning rush hour and again at afternoon rush hour. At weekday morning, the rhythm of the city seems to be routine, whereas at weekday afternoon and evening mobility patterns are more complex. Spatiotemporal activity patterns revealed imbalances between departures and arrivals in few bike sharing stations. Cluster analysis revealed eight different activity patterns among bike sharing station usage. The bike sharing system has been a great success in Helsinki. City bikes are used as a part of multimodal travel chain, moving from one place to another and for leisure trips. Understanding the spatiotemporal patterns of bike share usage supports planning of bike share station network. It also tells a story of the mobility and rhythm of Helsinki by a novel data source.