In this paper a novelty method to combine knowledge of traffic safety experts, in order to detect driving risk situations, is presented. A set of driving sessions were executed in a very realistic truck simulator where several magnitudes and visual information from the vehicle, driver and road were collected. Two kind of experiments were designed: controlled driving sessions (where several risky situations were induced), and natural driving sessions (where a natural driving behavior was expected). A group of traffic safety experts were consulted to evaluate the driving risk in each session. The information acquired from the traffic safety experts was used to develop a methodology to combine the information and to define a set of driving risk models. The developed system detected most of the induced risk situations besides of several non-induced risk situations. The methodology presented in this paper can be used to obtain a driving risk ground truth in order to compare and evaluate risk detection algorithms and to analyze the influence of vehicle, driver and road variables on the driving risk.
Combining traffic safety knowledge for driving risk detection
01.10.2011
1607325 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
Subjective Traffic Safety Experts' Knowledge for Driving-Risk Definition
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