During overtaking maneuvers on two-way highways drivers must temporarily cross into the opposite lane of traffic, and may face oncoming vehicles. To judge when it is safe to overtake, drivers must estimate the time-to-contact (TTC) of the oncoming vehicle. Information about an oncoming vehicle's TTC is available in the optical expansion pattern, but it is below threshold during high-speed overtaking maneuvers, which require a large passing distance. Consequently, we hypothesized that drivers would rely on perceived distance and velocity, and that their overtaking judgments would be influenced by oncoming vehicle size. A driving simulator was used to examine whether overtaking judgments are influenced by the size of an oncoming vehicle, and by whether a driver actively conducts the overtaking maneuver or passively judges whether it is safe to overtake. Oncoming motorcycles resulted in more accepted gaps and false alarms than larger cars or trucks. Results were due to vehicle size independently of vehicle type, and reflected shifts in response bias rather than sensitivity. Drivers may misjudge the distances of motorcycles due to their relatively small sizes, contributing to accidents due to right-of-way violations. Results have implications for traffic safety and the potential role of driver-assistance technologies.

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In 2011, 89,000 accidents in the United States involved a vehicle passing another vehicle, which resulted in 740 deaths and 19,000 injuries (NHTSA, 2011). When passing a vehicle on a two-way highway (overtaking), a driver often must temporarily cross into the opposite lane of traffic, and may face oncoming vehicles. To avoid a collision with an oncoming vehicle, the overtaking driver must estimate the time remaining until a collision would occur with the vehicle. Although information about an oncoming vehicle's time-to-collision is theoretically available in the optical invariant tau (Lee, 1976), it is below threshold during high-speed overtaking maneuvers, which require a large passing distance. Under such conditions, we expect drivers to rely on the oncoming vehicle's apparent distance and velocity, and thus depth cues such as relative size. We used a driving simulator to determine whether overtaking judgments are influenced by an oncoming vehicle's size, and on whether such judgments differ between active driving and passive viewing. Twenty-four participants viewed computer-generated scenes in which they were following a lead vehicle on a straight, two-lane, two-way highway. At the start of each scene an oncoming vehicle (motorcycle, car, delivery truck) was visible in the opposite lane. Seven seconds after the scene an auditory tone signaled participants to make an overtaking decision. Participants in the active condition passed the lead vehicle if they thought it was safe to do so. Participants in the passive condition indicated whether it was safe to pass by pressing buttons on the steering wheel. We manipulated the participant's (and lead vehicle's) speed (48.28 km/h, 64.37 km/h, 80.47 km/h) and the oncoming vehicle's speed (72.42 km/h, 88.51 km/h, 104.61 km/h) and distance when the tone occurred (457.20 m, 609.60 m). This resulted in 9 safe and 9 unsafe temporal gaps based on an equation generated from analyses of actual overtaking performance (Gordon & Mast, 1970). Results indicated more accepted gaps and more false alarms (accepted gap when unsafe) in front of motorcycles than larger cars or trucks. The judgments made by participants in the active and passive conditions did not differ. Analyses of signal detection theory measures of sensitivity (d-prime) and response bias (beta) suggested that the effect of vehicle size was due to shifts in response bias rather than sensitivity. Results have implications for traffic safety and for the potential role of driver-assistance technologies.

Despite ample research on the effects of cell phone conversations on driving, the effects of such conversations on the looming threshold for an immediate hazard are not known. Prior research on the looming threshold for an immediate hazard in the absence of cell phone conversation indicated that the rate of optical expansion at threshold was .006 radians per second. We measured the rate of optical expansion and headway distance at first driving input when participants encountered a stopped lead vehicle while completing a car-following task. Half of them concurrently completed the Last Letter Task, a cognitive task that emulates a cell phone conversation. When compared to the second, third, and fourth scenario exposures to the stopped lead vehicle, the participant’s response on the first scenario exposure occurred when the lead vehicle’s optical expansion rate was relatively smaller and headway distance was larger. However, this effect of scenario exposure occurred only when drivers were engaged in a cell phone conversation. Additionally, participants started to initiate a response when the rate of optical expansion was much lower than the looming threshold reported in previous research. Our results indicate that the first driver input, as operationalized in the current study, does not indicate when drivers first perceive an immediate hazard.

An errorable car-following model is presented in this paper. The model was developed to predict the situational risk associated with distracted driving. To obtain longitudinal driving patterns, this paper analyzed and synthesized the NGSIM naturalistic driver and traffic database to identify essential driver behavior and characteristics. NGSIM data was modified according to data from cognitive psychology concepts to examine the probabilistic nature of distracted driving due to internal vehicle distractions. The errorable microscopic carfollowing model was developed and validated, which can be fully integrated with the naturalistic data and incorporate the probabilities of driver distraction. The proposed model predicts that distracted driving in congested conditions can result in crash rates 3.25 times that of normal driving conditions.