In Mexico, car accidents are the leading cause of death among young people. Thus, the identification of drivers that can be potentially involved in car accidents is of particular interest. There are certain risky driving behaviors that are highly correlated to car accidents, including speeding, overtaking, and tailgating. In this work, we present a preliminary approach for automated detection of risky driving in urban environments. The system, Tracko, makes use of GPS data to compute mobility traces, which are used to preliminarily characterize driving behaviors. This work presents the design of the system as well as preliminary data to be used for automated identification of risky driving behaviors. © Springer International Publishing 2013.
CITATION STYLE
Cruz, L. C., Macías, A., Domitsu, M., Castro, L. A., & Rodríguez, L. F. (2013). Risky driving detection through urban mobility traces: A preliminary approach. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8276 LNCS, pp. 382–385). https://doi.org/10.1007/978-3-319-03176-7_51
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