A Random,Roadside Breathalyzer Survey of Alcohol Impaired Driving in Ghana

To ascertain the prevalence and pattern of alcohol impaired driving in an African nation, we conducted a random, roadside, breathalyzer survey of drivers in Ghana. A total of 149 (21%) of 722 drivers tested had a detectable blood alcohol concentration (BAC). In addition, 7.3% of drivers had a BAC ≥ 80 mg/dl. The prevalence of impaired driving (BAC ≥ 80) was higher among private drivers (9.8%) than commercial drivers (6.4%). However, due to a higher volume, the majority (64%) of impaired drivers were commercial drivers. Alcohol use was higher among uneducated (11%) compared to educated drivers (5.4%) and was higher among middle aged drivers (30 - 49 years, 9.1% impaired) compared with younger (< 30 years; 5.0%) or older drivers (≥ 50 years; 0%). Alcohol impaired driving is a significant problem in this African nation. Anti-drunk driving measures should be an important component of road safety efforts. Such measures may need to be different than industrialized nations and will need to target less educated drivers, middle aged drivers, and commercial drivers.     

Identifying risky drivers with simulated driving

Objective: The present study aimed to examine whether high-risk drivers differ from low-risk drivers in driving behavior in a simulated environment.

Method: The 2 risk groups including 36 drivers (18 males and 18 females) performed driving tasks in a simulated environment. The simulated driving behaviors are compared between the 2 risk groups.

Results: The high-risk drivers drove much faster and exhibited larger offsets of the steering wheel than did the low-risk drivers in events without incidents. Additionally, the high-risk drivers used turn signals and horns less frequently than the low-risk drivers.

Conclusions: The present study revealed that the high-risk group differed from the low-risk group in driving behavior in a simulated environment. These results also suggest that simulated driving tasks might be useful tools for the evaluation of drivers’ potential risks.     

The on-road experiences and awareness of sleepiness in a sample of Australian highway drivers: A roadside driver sleepiness study

Objective: Driver sleepiness contributes substantially to road crash incidents. Simulator and on-road studies clearly reveal an impairing effect from sleepiness on driving ability. However, the degree to which drivers appreciate the dangerousness of driving while sleepy is somewhat unclear. This study sought to determine drivers' on-road experiences of sleepiness, their prior sleep habits, and personal awareness of the signs of sleepiness.

Methods: Participants were a random selection of 92 drivers traveling on a major highway in the state of Queensland, Australia, who were stopped by police as part of routine drink driving operations. Participants completed a brief questionnaire that included demographic information, sleepy driving experiences (signs of sleepiness and on-road experiences of sleepiness), and prior sleep habits. A modified version of the Karolinska Sleepiness Scale (KSS) was used to assess subjective sleepiness in the 15 min prior to being stopped by police.

Results: Participants' ratings of subjective sleepiness were quite low, with 90% reporting being alert to extremely alert on the KSS. Participants were reasonably aware of the signs of sleepiness, with many signs of sleepiness associated with on-road experiences of sleepiness. Additionally, the number of hours spent driving was positively correlated with the drivers' level of sleep debt.

Conclusions: The results suggest that participants had moderate experiences of driving while sleepy and many were aware of the signs of sleepiness. The relationship between driving long distances and increased sleep debt is a concern for road safety. Increased education regarding the dangers of sleepy driving seems warranted.     

Delays in DUI blood testing: Impact on cannabis DUI assessments

Objective: This study examined the time from law enforcement dispatch to the first blood draw in cases of driving under the influence (DUI) vehicular homicide and a subset of DUI vehicular assault cases in Colorado in 2012. Laboratory toxicology results were also examined to understand the implications of delays in blood draws in cases of driving while under the influence of marijuana's delta-9-tetrahydrocannabinol (THC).

Methods: Colorado court records were reviewed and information regarding charges, presence of alcohol and/or drugs, time of law enforcement contact and blood draw, crash location, and other contextual factors were identified. The distributions of first blood draw times were studied by charge and by responding law enforcement agency. Toxicology data from a different cohort of DUI traffic arrests in Colorado and Washington were examined to determine the proportion of blood tests for THC that were above specified legal limits in those states.

Results: The average time from law enforcement dispatch to blood draw in cases of vehicular homicide and vehicular assault was 2.32 h (SD ± 1.31 h), with a range of 0.83 to 8.0 h and a median of 2.0 h. Data from DUI traffic arrests found that between 42 and 70% of all cannabinoid-positive traffic arrests tested below 5 ng/ml THC in blood, which is the legal limit in Colorado and Washington.

Conclusion: Given the current delays to blood testing in cases of arrests for vehicular homicide and vehicular assault in Colorado, many blood tests are unlikely to confirm that drivers who are impaired from smoking marijuana have THC levels above established legal limits.     

State all-driver distracted driving laws and high school students' texting while driving behavior

Objective: Texting while driving is highly prevalent among adolescents and young adults in the United States. Texting while driving can significantly increase the risk of road crashes and is associated with other risky driving behaviors. Most states have enacted distracted driving laws to prohibit texting while driving. This study examines effects of different all-driver distracted driving laws on texting while driving among high school students.

Methods: High school student data were extracted from the 2013 National Youth Risk Behavior Survey. Distracted driving law information was collected from the National Conference of State Legislatures. The final sample included 6,168 high school students above the restricted driving age in their states and with access to a vehicle. Logistic regression was applied to estimate odds ratios of laws on texting while driving.

Results: All-driver text messaging bans with primary enforcement were associated with a significant reduction in odds of texting while driving among high school students (odds ratio = 0.703; 95% confidence interval, 0.513–0.964), whereas all-driver phone use bans with primary enforcement did not have a significant association with texting while driving (odds ratio = 0.846; 95% confidence interval, 0.501–1.429).

Conclusions: The findings indicate that all-driver distracted driving laws that specifically target texting while driving as opposed to all types of phone use are effective in reducing the behavior among high school students.     

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.     

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.     

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.     

中国城市轻型车的排放特性

采用机动车实际上路排放测试系统对北京、重庆和成都3城市27辆轻型车进行了测试和分析;采用发动机比功率VSP、发动机负荷ES和排放单元BIN分析了轻型车瞬态排故的特征及影响排放的主要因素.结果表明.发动机技术和累计行驶里程对排放的影响很大,而VSP等概念还反映了道路坡度对排放因子的影响;由于城市道路坡度的差异,导致同一测试车辆在重庆和成都2个城市的排放水平相差10%～100%.     

基于隐性危险驾驶人感知特性及判别模型研究*

为研究驾驶人在隐性危险场景中危险感知行为,基于Bayes判别法,将驾驶行为指标作为输入变量,建立驾驶人危险感知能力预测模型。结果表明:驾驶员在显性危险场景的纵向加速度显著低于隐性危险场景;驾驶人在隐性危险场景中TTC值小于显性危险场景;在被试车辆与轿车、行人、非机动车冲突3种交通冲突场景中,驾驶人对行人危险感知能力最弱。研究结果对提高道路交通安全水平以及驾驶人应急避险能力具有一定实际指导意义。