A Review of Hazard Anticipation Training Programs for Young Drivers.

PURPOSE: Poor hazard anticipation skills are a risk factor associated with high motor vehicle crash rates of young drivers. A number of programs have been developed to improve these skills. The purpose of this review was to assess the empirical literature on hazard anticipation training for young drivers. METHODS: Studies were included if they (1) included an assessment of hazard anticipation training outcomes; (2) were published between January 1, 1980 and December 31, 2013 in an English language peer-reviewed journal or conference proceeding; and (3) included at least one group that uniquely comprised a cohort of participants aged <21 years. Nineteen studies met inclusion criteria. RESULTS: Studies used a variety of training methods including interactive computer programs, videos, simulation, commentary driving, or a combination of approaches. Training effects were predominantly measured through computer-based testing and driving simulation with eye tracking. Four studies included an on-road evaluation. Most studies evaluated short-term outcomes (immediate or few days). In all studies, young drivers showed improvement in selected hazard anticipation outcomes but none investigated crash effects. CONCLUSIONS: Although there is promise in existing programs, future research should include long-term follow-up, evaluate crash outcomes, and assess the optimal timing of hazard anticipation training taking into account the age and experience level of young drivers.

The influence of clear zone size and roadside vegetation on driver behavior.

INTRODUCTION: Roadside vegetation provides numerous environmental and psychological benefits to drivers. Previous studies have shown that natural landscapes can effectively lower crash rates and cause less frustration and stress to the driver. However, run-off-the-road crashes resulting in a collision with a tree are twice as likely to result in a fatality, reinforcing the need to examine the placement of vegetation within the clear zone. METHOD: This study explores the relationship between the size of the clear zone and the presence of roadside vegetation on vehicle speed and lateral position. A static evaluation, distributed electronically to 100 licensed drivers, was utilized to gather speed selections for both real and virtual roads containing four combinations of clear zone sizes and roadside vegetation densities. A case study was included in the static evaluation to investigate the presence of utility poles near the edge of the road on speed selection. Validation of the static evaluation was performed by a field data collection on the same roadways shown to participants in the evaluation. RESULTS: The speeds observed in the field for roadways with medium clear zone/dense vegetation or large clear zone/spare vegetation correlated with the speeds chosen by static evaluation participants. Further field data were obtained on vehicle speeds and lateral positions for additional roads demonstrating the same clear zone size/vegetation density combinations. PRACTICAL APPLICATION: This study successfully demonstrates the relationship between clear zone design and driver behavior, which could improve clear zone design practices and thus roadway safety.

The long-term effects of active training strategies on improving older drivers' scanning in intersections: a two-year follow-up to Romoser and Fisher (2009).

OBJECTIVE: To determine the long-term effects of active training on older drivers' scanning in intersections, the present article reports the results of a 2-year followup with drivers who had previously participated the older driver training study reported in Romoser and Fisher. BACKGROUND: Customized feedback coupled with active learning in a simulator has been shown to be an effective means of significantly improving the intersection scanning behavior of older drivers. However, the long-term effect of such training has not been established. METHOD: Older drivers from the active learning and control groups from Romoser and Fisher were invited to participate in a 2-year follow-up field drive in their own vehicle starting at their home. Secondary looks, defined as looking away from the path of the vehicle while entering the intersections toward regions to the side from which other vehicles could appear, were recorded. RESULTS: Two years after their training, older drivers in the active learning group still took secondary looks more than one and a half times as often as 2009 pretraining levels. Control group drivers saw no significant change in performance over the 2-year period. CONCLUSION: Customized feedback and active learning in a simulator is an effective strategy for improving the safe driving habits of older drivers over the long term. It provides drivers a means by which to reincorporate previously extinguished behaviors into their driving habits. APPLICATION: These results can guide the development of older driver retraining programs that could have the potential to reduce intersection crashes.

Comparing the Glance Patterns of Older versus Younger Experienced Drivers: Scanning for Hazards while Approaching and Entering the Intersection.

Older drivers are known to look less often for hazards when turning at T-intersections or at four way intersections. The present study is an extension of Romoser & Fisher (2009) and attempts to further analyze the differences in scanning behavior between older and experienced younger drivers in intersections. We evaluated four hypotheses that attempt to explain the older drivers' failure to properly scan in intersections: difficulty with head movements, decreases in working memory capacity, increased distractibility, and failure to recall specific scanning patterns. To test these hypotheses, older and younger experienced drivers' point-of-gaze was monitored while they drove a series of simulated intersections with hidden hazards outside of the turning path. Our results suggest that none of these hypotheses can fully explain our finding that older adults are more likely to remain fixated on their intended path of travel and look less than younger drivers towards other areas where likely hazards might materialize. Instead, the results support a complementary hypothesis that at least some of the difficulties older adults have scanning intersections are due to a specific attentional deficit in the older drivers' ability to inhibit what has become their prepotent goal of monitoring the vehicle's intended path of travel, thereby causing older drivers to fail to scan hazardous areas outside this intended path of travel.

Identifying and Remediating Failures of Selective Attention in Older Drivers.

Older drivers are primarily overinvolved in crashes at intersections, and failure to attend to regions that contain relevant information about potential hazards is a major contributor to this problem. Corroborating this, we have found that older drivers in both controlled scenarios on a driving simulator and somewhat less controlled situations on the road attend to (i.e., fixate) target regions in intersections significantly less frequently than do younger experienced drivers. Moreover, we have developed a training program that substantially improves older drivers' attention to these regions. Together, these findings indicate that older drivers' less frequent scanning of regions at intersections from which hazards may emerge may be due to their developing something like an unsafe habit rather than to deteriorating physical or mental capabilities and thus that training may be effective in reducing crashes.

Do Advance Yield Markings Increase Safe Driver Behaviors at Unsignalized, Marked Midblock Crosswalks? Driving Simulator Study.

In the United States, 78% of pedestrian crashes occur at noninter-section crossings. As a result, unsignalized, marked midblock crosswalks are prime targets for remediation. Many of these crashes occur under sight-limited conditions in which the view of critical information by the driver or pedestrian is obstructed by a vehicle stopped in an adjacent travel or parking lane on the near side of the crosswalk. Study of such a situation on the open road is much too risky, but study of the situation in a driving simulator is not. This paper describes the development of scenarios with sight limitations to compare potential vehicle-pedestrian conflicts on a driving simulator under conditions with two different types of pavement markings. Under the first condition, advance yield markings and symbol signs (prompts) that indicated "yield here to pedestrians" were used to warn drivers of pedestrians at marked, midblock crosswalks. Under the second condition, standard crosswalk treatments and prompts were used to warn drivers of these hazards. Actual crashes as well as the drivers' point of gaze were measured to determine if the drivers approaching a marked midblock crosswalk looked for pedestrians in the crosswalk more frequently and sooner in high-risk scenarios when advance yield markings and prompts were present than when standard markings and prompts were used. Fewer crashes were found to occur with advance yield markings. Drivers were also found to look for pedestrians much more frequently and much sooner with advance yield markings. The advantages and limitations of the use of driving simulation to study problems such as these are discussed.

Do Crashes and Near Crashes in Simulator-Based Training Enhance Novice Drivers' Visual Search for Latent Hazards?

Young drivers (younger than 25 years of age) are overrepresented in crashes. Research suggests that a relevant cause is inadequate visual search for possible hazards that are hidden from view. The objective of this study was to develop and evaluate a low-cost, fixed-base simulator training program that would address this failure. It was hypothesized that elicited crashes in the simulator training would result in better scanning for latent hazards in scenarios that were similar to the training scenarios but situated in a different environment (near transfer), and, to a lesser degree, would result in better scanning in scenarios that had altogether different latent hazards than those contained in the training scenarios (far transfer). To test the hypotheses, 18 trained and 18 untrained young novice drivers were evaluated on an advanced driving simulator (different from the training simulator). The eye movements of both groups were measured. In near transfer scenarios, trained drivers fixated the hazardous region 84% of the time, compared with only 57% of untrained drivers. In far transfer scenarios, trained drivers fixated the hazardous region 71 % of the time, compared with only 53% of untrained drivers. The differences between trained and untrained drivers in both the near transfer scenarios and the far transfer scenarios were significant, with a large effect size in the near transfer scenarios and a medium effect size in the far transfer scenarios [respectively: U = 63.00, p(2-tailed) < .01, r = -.53, and U = 88.00, p(2-tailed)<.05,r = -.39].

Predicting Route Choices of Drivers Given Categorical and Numerical Information on Delays Ahead: Effects of Age, Experience, and Prior Knowledge.

In recent years there has been a considerable increase in the systems used to provide real-time traffic information to motorists. Examples of such systems include dynamic message signs and 511 travel information systems. However, such systems can be used to reduce congestion-one of their primary purposes-only if one can predict the route choices of drivers as a function of the information displayed. This simulator study looks at the diversion pattern that occurs when delays are reported ahead on the main route and how these diversion patterns vary as a function of delay times (for numerical delay signs), message content (for categorical delay signs), use of 511, and drivers' familiarity with the alternative route travel times across two different age groups. For numerical delay signs, the study shows that one can reliably predict the diversion frequencies at the different delays and across the different ages; then it is possible for traffic engineers to know ahead of time how likely it is for drivers to take an alternative route. For categorical delay signs, the findings indicate that drivers' knowledge of the alternative route travel time affects the choices of older versus younger or middle-aged adults differently. When the times are not known, the two groups behave differently; when the times are known, the groups behave similarly. This finding suggests that traffic engineers should try where possible to present the alternative route travel times as well as the delays on the main route.

The effect of active versus passive training strategies on improving older drivers' scanning in intersections.

OBJECTIVE: This study aimed (a) to determine whether older drivers looked less often for potential threats while turning than younger drivers and (b) to compare the effectiveness of active and passive training on older drivers' performance and evaluation of their driving skills in intersections. BACKGROUND: Age-related declines in vision, physical abilities, psychomotor coordination, and cognition combine to make it less likely that older drivers will look for potential threats during a turn. Research suggests that active training should be an effective means of improving older drivers' performance and self-awareness. METHOD: In Experiment 1, younger and older participants drove a series of virtual intersection scenarios, were shown video replays, and were provided feedback. In Experiment 2, older drivers were assigned to one of three cohorts: active simulator training, passive classroom training, or no training. Pre- and posttraining simulator and field drives assessed training effectiveness. RESULTS: In Experiment 1, older drivers looked less often during turns than younger drivers. Customized feedback was successful in altering drivers' perception of their abilities. In Experiment 2, active training increased a driver's probability of looking for a threat during a turn by nearly 100% in both posttraining simulator and field drives. Those receiving passive training or no training showed no improvement. CONCLUSION: Compared with passive training, active training is a more effective strategy for increasing older drivers' likelihood of looking for threats during a turn. APPLICATION: The results of this research can guide the development of programs that could reduce intersection crashes among older drivers.