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• Young drivers' overtaking decisions on two-lane highways depend on levels of anxiety and depression. • Driving simulation and surveys capture the interplay of traffic and psychology in young driver overtaking behavior. • In moderately risky traffic scenarios, impulsiveness and mindfulness impact overtaking decisions. • In minimally risky traffic scenarios, attitude towards rule violation and speeding impacts overtaking behavior. • In all cases, male drivers are more likely to overtake than females. • In risky traffic scenarios, young drivers are more likely to overtake than older drivers. Overtaking maneuvers – the passing of a vehicle traveling in the same direction through use of an opposing lane – on two-lane, two-way highways have significant implications on safety and highway performance. This research examines the interplay between young drivers' psychological traits and traffic variables to better understand overtaking behavior. A total of 111 licensed drivers between the ages of 18 and 28 (inclusive) successfully completed four unique traffic scenarios presented in random order. In all four scenarios, the lead vehicle was a truck for which the speed and passing gap size varied. A standardized self-report questionnaire captured demographic and psychological factors including impulsiveness, mindfulness, attitude towards driving and depression. Results revealed that, irrespective of the traffic scenario, the propensity to overtake a lead vehicle is associated with lower attitudes towards rule violations and speeding. In more difficult traffic scenarios, the effects of impulsiveness and mindfulness are more pronounced. Concerning moods, young drivers with higher depressive symptoms are more likely to overtake in the most dangerous scenarios. These findings can enhance driver education campaigns and targeted curricula for young drivers promoting safe driving to lessen the social and economic burdens of high-impact crashes. [ABSTRACT FROM AUTHOR]

Intersections are critical points within the highway system at which the risk of crashes increases. This study seeks to better understand drivers' behavior at an intersection by examining the relationship between their observed driving behavior, psychological attributes and decision to proceed through an intersection. A driving simulator and self-report questionnaire were used to understand driver decision-making at the onset of the yellow phase across several signalized intersections. The simulator measured driving outcomes such as speed, braking, and throttle as drivers cross through four increasingly difficult intersections. The questionnaires measured demographics, psychological traits including mindfulness and impulsiveness along with self-reported driving behaviors. A total of 102 participants completed the questionnaire as well as the driving simulator experiment. Hierarchical clustering served to classify drivers into four groups on the basis of their observed driving in the simulator: the safest drivers, safe drivers, speed demons, and aggressive drivers. These driving styles moderated the relationship between the drivers' psychological traits and their decision to stop or proceed at each intersection. Results showed that mindfulness was highly related to the safest drivers' decision to stop at the first intersection, while impulsiveness and anxiety were related to the speed demons' decision to stop at the third intersection. These findings lay a strong foundation for developing progressive educational campaigns incorporating driver psychology in their methodology. Findings also provide support for research linking driving performance and psychological traits with implications for intersection design. [ABSTRACT FROM AUTHOR]

This paper examines the value of utilizing dynamic, revenue-maximizing, congestion pricing on a privately operated tolled route, when the only alternative is a highly congested, public, free-access route. Three methods are specified by which revenue can be maximized-through the selection of a fixed percent of users to set the toll price for, through the selection of a fixed level of service on the toll road, and through the use of a nonlinear optimization model. These methods are tested on a case study involving a highly congested corridor. In simulation, the corridor’s flow rates are observed following the posting of a toll, the toll is updated, and the new flow observed until a subsequent round of revenue maximizing is applied to the new conditions. It was concluded that in a highly congested corridor a dynamic, revenue-maximizing toll can finance the construction of new capacity without degrading social welfare. [ABSTRACT FROM AUTHOR]