Age and gender differences in conviction and crash occurrence subsequent to being directed to Iowa's driver improvement program

Introduction

This paper investigates potential gender and age differences in conviction and crash occurrence subsequent to being directed to attend Iowa's Driver Improvement Program (DIP).

Methods

Binary logit models were developed to investigate the factors that influence conviction occurrence after DIP by gender and age. Because of the low crash occurrence subsequent to DIP, association rules were applied to investigate the factors that influence crash occurrence subsequent to DIP, in lieu of econometric models.

Results

There were statistical significant differences by driver gender, age, and conviction history in the likelihood of subsequent convictions. However, this paper found no association between DIP outcome, crash history, and crash occurrence.

Impact on industry

Evaluating the differences in conviction and crash occurrence subsequent to DIP between female and male drivers, and among different age groups can lead to improvements of the effectiveness of DIPs and help to identify low-cost intervention measures, customized based on drivers’ gender and age, for improving driving behaviors.     

Enhancing older driver safety: A driving survey and evaluation of the CarFit program

Objective

To evaluate CarFit, an educational program designed to promote optimal alignment of driver with vehicle.

Methods

A driving activity survey was sent to 727 randomly selected participants living in retirement communities. Drivers (n = 195) were assigned randomly to CarFit intervention (n = 83, M age = 78.1) or Comparison (n = 112, M age = 79.6) groups. After 6 months, participants completed a post-test of driving activity and CarFit recommendations.

Results

Nonconsenting drivers were older and participated in fewer driving activities. CarFit participation was moderate (71%) with 86% of the participants receiving recommendations. 60% followed the recommendations at the 6-month re-evaluation). The CarFit (67.6%) and Comparison (59.3%) groups reported at least one type of self-regulation of driving activity at baseline. There was no significant change in the driving behaviors at the six-month follow-up.

Conclusion

CarFit was able to detect addressable opportunities that may contribute to the safety of older drivers.

Impact on industry

CarFit recommendations may need stronger reinforcement in order to be enacted by a participant.     

The use of navigation systems in naturalistic driving

Objective: In this study, we assessed the use of portable navigation systems in everyday driving by applying in-vehicle naturalistic driving.

Method: Experienced users of navigation systems, 7 females and 14 males, were provided with a specially equipped vehicle for approximately 1 month. Their trips were recorded using 4 cameras, Global Positioning System (GPS) data, and other sensor data. The drivers’ navigation system use data were coded from the video recordings, which showed how often and for how long the system was activated and how often and for how long a driver operated the system.

Results: The system was activated for 23% of trips, predominantly on longer and unique trips. Analyses of the percentage of time for which the speed limit was exceeded showed no evidence of differences between trips for which the navigation system was used or not used. On trips for which the navigation system was activated, participants spent about 5% of trip time interacting with the device. About 40% of interacting behavior took place in the first 10% of the trip time, and about 35% took place while the car was standing still or moving at a very low speed; that is, 0–10 km/h.

Conclusion: These results shed light on how and when drivers use navigation systems. They suggest that although drivers regulate their use of such systems to some extent, they often perform risky tasks while driving.     

Covariability in three dimensions of teenage driving risk behavior: impaired driving,risky and unsafe driving behavior,and secondary task engagement

Objective: This research examined the extent to which teenagers who engaged in one form of risky driving also engaged in other forms and whether risky driving measures were reciprocally associated over time.

Methods: The data were from waves 1, 2, and 3 (W1, W2, and W3) of the NEXT Generation study, with longitudinal assessment of a nationally representative sample starting with 10th graders starting in 2009–2010. Three measures of risky driving were assessed in autoregressive and cross-lagged analyses: driving while alcohol/drug impaired (DWI), Checkpoints Risky Driving Scale (risky and unsafe driving), and secondary task engagement while driving.

Results: In adjusted autoregression models, the risk variables demonstrated high levels of stability, with significant associations observed across the 3 waves. However, associations between variables were inconsistent. DWI at W2 was associated with risky and unsafe driving at W3 (β = 0.21, P < .01); risky and unsafe driving at W1 was associated with DWI at W2 (β = 0.20, P < .01); and risky and unsafe driving at W2 is associated with secondary task engagement at W3 (β = 0.19, P < .01). Over time, associations between DWI and secondary task engagement were not significant.

Conclusions: Our findings provide modest evidence for the covariability of risky driving, with prospective associations between the Risky Driving Scale and the other measures and reciprocal associations between all 3 variables at some time points. Secondary task engagement, however, appears largely to be an independent measure of risky driving. The findings suggest the importance of implementing interventions that addresses each of these driving risks.     

The role of self-regulation in the context of driver distraction: A simulator study

Objective: There is considerable evidence for the negative effects of driver distraction on road safety. In many experimental studies, drivers have been primarily viewed as passive receivers of distraction. Thus, there is a lack of research on the mediating role of their self-regulatory behavior. The aim of the current study was to compare drivers' performance when engaged in a system-paced secondary task with a self-paced version of this task and how both differed from baseline driving performance without distraction.

Methods: Thirty-nine participants drove in a simulator while performing a secondary visual–manual task. One group of drivers had to work on this task in predefined situations under time pressure, whereas the other group was free to decide when to work on the secondary task (self-regulation group). Drivers' performance (e.g., lateral and longitudinal control, brake reaction times) was also compared with a baseline condition without any secondary task.

Results: For the system-paced secondary task, distraction was associated with high decrements in driving performance (especially in keeping the lateral position). No effects were found for the number of collisions, probably because of the lower driving speeds while distracted (compensatory behavior). For the self-regulation group, only small impairments in driving performance were found. Drivers engaged less in the secondary task during foreseeable demanding or critical driving situations.

Conclusions: Overall, drivers in the self-regulation group were able to anticipate the demands of different traffic situations and to adapt their engagement in the secondary task, so that only small impairments in driving performance occurred. Because in real traffic drivers are mostly free to decide when to engage in secondary tasks, it can be concluded that self-regulation should be considered in driver distraction research to ensure ecological validity.     

Relationship of traffic fatality rates to maximum state speed limits

Objectives: The objective of this study was to examine the safety effects of increases in U.S. state maximum speed limits during the period 1993–2013.

Methods: Poisson regression was used to model state-by-state annual traffic fatality rates per mile of travel as a function of time, the unemployment rate, the percentage of the driving age population that was younger than 25, per capita alcohol consumption, and the maximum posted speed limit on any road in the state. Separate analyses were conducted for all roads, interstates and freeways, and all other roads.

Results: A 5 mph increase in the maximum state speed limit was associated with an 8% increase in fatality rates on interstates and freeways and a 4% increase on other roads. In total, there were an estimated 33,000 more traffic fatalities during the years 1995–2013 than would have been expected if maximum speed limits had not increased. In 2013 alone, there were approximately 1,900 additional deaths—500 on interstates/freeways and 1,400 on other roads.

Conclusions: There is a definite trend of increased fatality risk when speed limits are raised. As roadway sections with higher speed limits have become more ubiquitous, the increase in fatality risk has extended beyond these roadways. The increase in risk has been so great that it has now largely offset the beneficial effects of some other traffic safety strategies. State policy makers should keep this trade-off in mind when considering proposals to raise speed limits.     

Virtual street-crossing performance in persons with multiple sclerosis: Feasibility and task performance characteristics

Objectives: Multiple sclerosis (MS) is a neurological disease that commonly results in physical and cognitive dysfunction. Accordingly, MS might impact the ability to safely cross the street. The purpose of this study was to examine the feasibility of a simulated street-crossing task in persons with MS and to determine differences in street-crossing performance between persons with MS and non-MS controls.

Methods: 26 participants with MS (median Expanded Disability Status Scale [EDSS] score = 3.5) and 19 controls completed 40 trials of a virtual street-crossing task. There were 2 crossing conditions (i.e., no distraction and phone conversation), and participants performed 20 trials per condition. Participants were instructed that the goal of the task was to cross the street successfully (i.e., without being hit be a vehicle). The primary outcome was task feasibility, assessed as completion and adverse events. Secondary outcomes were measures of street-crossing performance.

Results: Overall, the simulated street-crossing task was feasible (i.e., 90% completion, no adverse events) in participants with MS. Participants with MS waited longer and were less attentive to traffic before entering the street compared with controls (all P < .05). Participants with MS also took longer to cross the street and were closer to oncoming vehicles when exiting the street compared to controls (all P < .05). When distracted, all participants took longer to initiate crossing, took longer to cross the street, and made more head turns while crossing (all P < .05). There were no significant group by condition interaction effects (all P > .05).

Conclusions: A virtual street-crossing task is feasible for studying street-crossing behavior in persons with mild MS and most individuals with moderate MS. Virtual street-crossing performance is impaired in persons with MS compared to controls; however, persons with MS do not appear to be more vulnerable to a distracting condition. The virtual reality environment presents a safe and useful setting for understanding pedestrian behavior in persons with MS.     

Nighttime effectiveness of the pedestrian hybrid beacon,rectangular rapid flashing beacon,and LED-embedded crossing sign

Introduction: A large majority of pedestrian fatal crashes occurred during the nighttime. The focus of this research was to identify if the following pedestrian crossing treatments were more or less effective at night: pedestrian hybrid beacon (PHB), rectangular rapid flashing beacon (RRFB), or LED-embedded crossing warning sign (LED-Em). Method: For each treatment, two statistical evaluations were used on the staged pedestrian data: ANCOVA models that considered per site mean yield rates and logistic regression that considered the individual driver response to the crossing pedestrian. Results: For the PHB, essentially no difference was found between the very high daytime and nighttime driver yielding values. The research found RRFBs to be more effective at night, and the LED-Em to be more effective during the day. Using the results from the logistic regression evaluation, higher driver yielding was observed at LED-Em sites in the lower speed limit group (30 or 35 mph (48.3 or 56.3 kph), with 2 lanes (rather than 4 lanes), with narrow lanes of 10.5 or 11 ft (3.2 or 3.4 m) widths (rather than 11.5 or 12 ft (3.5 or 3.7 m) widths), and lower hourly volumes. The results from the ANCOVA model for LED-Ems also showed a statistically significant difference for yield lines (higher yielding when present). Conclusions: This analysis represents the only known study to date on the effectiveness of pedestrian crossing treatments at night. Practical Applications: This study provides additional support for the PHB as a treatment because the PHB was found to be highly effective during the nighttime as well as the daytime. The value of using advance yield lines was also demonstrated. The findings offer a caution regarding the use of the LED-Em treatment on higher speed, higher volume, or wider roads.     

Examining the relationship between driver distraction and driving errors: A discussion of theory, studies and methods

Over the past two decades the concept of driver distraction has been the focus of intense research attention. One aspect of distraction for which there has been limited systematic research, however, is its role in driver error causation. This article presents a review of the distraction literature with a view to elucidating what is currently known about the types of driving errors that distraction contributes to and the mechanisms by which distraction induces these errors. The review revealed a number of fundamental gaps in our knowledge, including the number and nature of errors made by drivers when distracted; the mechanisms by which distraction causes errors; whether and how distraction disrupts drivers’ ability to recover from errors; and how system-wide factors moderate the relationship between distraction and error. In closing, we attempt to identify the most appropriate theoretical and methodological approach to drive the integrated study of distraction and error forward. We conclude that it is only through the adoption of a systems approach that integrated countermeasures can be proposed and implemented to mitigate driver errors caused by distraction.     

Effect prediction of time-gaps for adaptive cruise control (ACC) and in-vehicle tasks on bus driver performance

Researchers have devoted a great deal of attention to the effects of driver assist systems on driver performance. This article describes a modeling approach to simulate the effects of time-gaps for adaptive cruise control (ACC) and manual in-vehicle tasks on bus-driver performance. A concept model was built with the knowledge of modularization, parameterization, and parallel processing. By running the model, the predictions for the effects of five levels of time-gaps and two types of in-vehicle tasks were collected in three measures: (1) mean gap, (2) minimum gap, and (3) collision rate. The model performed well in prediction, especially when driving with in-vehicle tasks. Predictions from the model were validated by the experiment with a verified fixed-base bus-driving simulator, used in the authors’ previous studies. Throughout the modeling approach, this research provides a theoretical and accurate way to assess effects of time-gaps and vehicle-equipped interfaces. In follow-up research, the authors will apply this approach to evaluate other driving assist systems (e.g. collision warning systems and navigation systems) to create a customized software kit.