2026-05-31T01:38:25Zhttps://riubu.ubu.es/oai/request

oai:riubu.ubu.es:10259/52452024-05-20T09:54:47Zcom_10259_5501com_10259_5086com_10259_2604col_10259_5504

00925njm 22002777a 4500 dc García Herrero, Susana author Aldred, Rachel author Anaya Boig, Esther author Mariscal Saldaña, Miguel Ángel author 2019 The goal of this research is to explore the role of the collision partner – vehicle type and driver culpability – in incidents involving injuries to people cycling. Previous research has explored a range of factors affecting cyclist injury severity, but were more frequently focused on cyclist behaviour and/or road conditions. The database for our study includes a total of 12,318 drivers or riders of any vehicles involved in traffic injuries with victims in Spain in 2016, of which 7,488 are injured bicycle riders. The database used in our research was provided by Spain's National Traffic Department (Dirección General de Tráfico - DGT). This research uses Bayesian machine learning techniques. These have been recently used to study the severity of traffic injuries, since they provide a sound methodology for analyzing their causes and risks and predicting the probability of traffic injuries with serious injuries or fatalities. We have found proof that involvement of heavy vehicles substantially increases the likelihood of cyclists being killed or seriously injured, and that drivers are more likely than cyclists to be held responsible for the injury. http://hdl.handle.net/10259/5245 10.3850/978-981-11-2724-3_0125-cd Road injuries Driver behaviour Bayesian network Cyclists Vehicle type Culpability Vulnerability of cyclists on the road. A probabilistic analysis of the database of traffic injuries in Spain focusing on type of involved vehicle and driver culpability