Bayesian modeling of the microscopic traffic characteristics of overtaking in two-lane highways

Bayesian networks are employed to model the uncertainty hindering in the overtaking behavior of young drivers in two-lane highways and reveal the traffic related microscopic characteristics that may influence the decision to overtake. Results using data from an experiment conducted on driving simulator show that male drivers, on average, accept smaller gaps for overtaking than female drivers. For both male and female drivers, the spacing with the lead and the opposing vehicle is more influential to the probability to overtake compared to vehicle speed. Moreover, a thorough look at the relationships between the microscopic traffic characteristics and the probability to overtake reveals differences between male and female drivers regarding the road traffic scene appraisal mechanism on the emergence of an opportunity to overtake.

► We model the overtaking of young drivers in two-lane highways via Bayesian Networks.
► Relevant data are derived from a driving simulator experiment.
► Male drivers, on average, accept smaller gaps for overtaking than female drivers.
► Microscopic traffic characteristics are found to influence the decision to overtake.
► The spacing is more influential than vehicle’s speed to the probability to overtake.