Driving exposure by driver age in Michigan

Background

This study compared driving exposure between two high-crash-risk groups (16–17 and 18-24-year-olds), with a low-crash-risk group (35-64-year-olds). In addition, patterns of association between driving exposure measures and demographic and driving behavior variables were examined.

Methods

Respondent's total miles, minutes, and trips driven were calculated within a 48-hour period, using state-wide survey data collected in 2004 and 2005.

Results

The youngest drivers drove fewer miles and minutes, but a comparable number of trips as the two older groups. Employment and high vehicle access were associated with greater driving exposure for 16-17-year-olds and 18-24-year-olds. Employment, high household income, large household size, and low vehicle access were associated with greater driving exposure for 35-64-year-olds. More driving was done alone than with passengers present and during the day than at night across all ages. There was a positive association between two driving exposure measures (miles and minutes driven) and demographic and driving behavior variables, which did not extend to trips driven.

Discussion

Driving exposure is directly related to stage of life. The entire sample of 16-17-year-old respondents were in high school, which directly influenced their driving times, destinations, and purpose. Those aged 18–24 years displayed driving behavior patterns that were closer to the older drivers, while retaining some differences. The oldest drivers were likely to be shouldering the greatest household responsibilities, and their greater driving exposure may reflect this reality.

Impact on industry

These findings provide new information about driving exposure for two high-risk and one low-risk group of drivers. They also raise concern over potential workplace safety issues related to teens’ higher driving exposure, and concomitant crash risk, related to being employed. Future research should examine this issue more carefully so that evidence based recommendations can be made to enhance the safety of teens who are employed, especially those who are employed as drivers.     

Quantifying driver cell phone use at signalized intersections using software-defined radio

Objective: This article outlines a data collection process that quantifies driver cell phone use using a software-defined radio (SDR) at a signalized intersection. Cell phone use while driving has been shown to be factor that increases the risk of a crash incident. Both operational and enforcement strategies can be applied at locations where high driver cell phone use is identified.

Methods: A baseline driver cell phone use observation was made at the intersection, where 9,699 vehicles were observed at the intersection of Carlton Road and State Route 31 (Pennington Road) in Ewing, New Jersey. An SDR cell phone detection device created as part of this study was then deployed at the same intersection to determine whether the SDR device could detect an active cell phone signal. The identification of vehicle cell phone activity using the SDR was conducted a sample of 4,000 vehicles. A visual observation, along with a motion detection camera, was made alongside the SDR to visually confirm cell phones use.

Results: Of the 4,000 vehicles sampled using the SDR cell phone detection device, 6.1% of the a.m. peak travel time and 7.6% of the p.m. peak travel time had an active cellular device. A concurrent visual field verification of driver cell phone use showed that approximately 57% (a.m. peak) and 67% (p.m. peak) of the SDR-detected cell phones were visually confirmed to be associated with distracted cell phone use.

Conclusions: Once characterized, the frequency of driver cell phone use can be used to justify changes to signal timing protocols. These adjustments could include extending the signal’s “all-red time” or holding “yellow time” longer in order to properly clear the intersection. These data can also be used to identify locations that may require more enforcement measures to dissuade driver cell phone use. Furthermore, the impact of anti–cell phone campaigns or new laws can be quantified by measuring before and after cell phone use in the near term rather than waiting for crash studies at intersections to be completed and analyzed.     

通用桥式起重机驾驶员操作可靠度研究

为有效改善桥式起重机驾驶员的操作水平,通过分析和确定这种起重机的工作流程,建立驾驶员基本动作序列。采用第二代人因可靠性分析(HRA)模型,按正常工作状态与紧急工作状态2种情况,对驾驶员操作可靠度进行全面、定量的分析与研究。结果表明,驾驶员操作可靠度定量研究中,重要的是要考虑起重机机型和基本操作动作序列、工作状态、动作时间、人机工效、作业环境等复杂因素。建立驾驶室人机工效定量分析与评价机制,加强驾驶员专业教育培训及考核制度、改善工作环境等技术措施,从根本上提高驾驶员操作可靠度等级,才能符合起重机械安全的发展趋势。     

中国老年人驾车安全问题及其对策

随着中国进入老龄化社会,老年驾驶员数量将持续增加,这给交通安全带来了新的问题。为保障老年驾驶员的交通安全,在分析老年人生理和心理特征以及老年驾驶员交通事故特点的基础上,提出了适合中国国情的老年驾驶员驾车安全对策。     

Michigan's graduated driver licensing program: evaluation of the first four years

INTRODUCTION: To evaluate the four-year outcome of Michigan's graduated driver licensing (GDL) program, motor-vehicle crash data for 16-year-old drivers in 1996 (pre-GDL), and 1998-2001 (post-GDL) were analyzed. METHOD: Relative risks and 95% confidence intervals for several crash types were computed, and pre-post-GDL population-based crash rates were compared. Reductions in crash risks among 16-year-olds previously found in 1998 and 1999 were generally maintained in 2000 and 2001. RESULTS: Reductions in crash risk among 16-year-olds from 1996 to 2001 were 29% for all, 44% for fatal, 38% each for nonfatal-injury and fatal-plus-nonfatal-injury, 32% for day, 31% for evening, 59% for night, 32% for single-vehicle, and 28% for multi-vehicle crashes. Even after adjusting for more general population-wide changes among drivers 25 years and older that might have contributed to changes in 16-year-old crash risk, reductions remained impressive (19% for all crashes in 2001). IMPACT ON INDUSTRY: As one approach to reducing teenage motor-vehicle morbidity and mortality, GDL remains promising.     

On-road driving evaluations: a potential tool for helping older adults drive safely longer

PROBLEM: This paper explores the potential use of on-road driving evaluations as a tool for helping older adults extend their safe driving years. METHOD: Three separate research activities were carried out. The first was a national telephone survey of current and former older drivers. The results of this survey provide information relevant to the potential market for on-road driving evaluations. The second was a series of focus groups with potential stakeholders in the process: driver educators, occupational therapists, and physicians. These groups explored the feasibility and requirements of offering on-road driving evaluations to the wider public. Supplemental data were also collected from a mail survey of driving schools nationwide. RESULTS: Based on the results of these efforts, a number of recommendations are presented for expanding the availability of on-road driving evaluations, specifically to help older adults make more responsible decisions about continuing or stopping driving, and more generally to help them drive safely longer.     

机车双司机驾驶行为可靠性研究

在人机系统可靠性理论与机车驾驶行为链的基础上,结合双司机作业特点,构建了基于感知、判断、操作元件及模块组的单司机及双司机驾驶行为模型。基于该模型,在确定单项器官元件可靠度测试与计算方法后,运用可靠性理论给出了功能模块可靠度、单司机驾驶行为可靠度、双司机驾驶行为可靠度模型,并对信息感知差系数、正副司机主次差系数等参数进行了分析和讨论,从而构建了一套较为完善的驾驶行为可靠性测试分析方法。最后对4组16名机车司机按事故与非事故组进行分时段连续测试与可靠度计算,其结果表明,双司机驾驶行为可靠性不仅决定于单司机驾驶行为可靠性,并且正副司机间的协调性密切相关,同时与作业时间呈凹函数分布。     

Effects of passengers on bus driver celeration behavior and incident prediction

PROBLEM: Driver celeration (speed change) behavior of bus drivers has previously been found to predict their traffic incident involvement, but it has also been ascertained that the level of celeration is influenced by the number of passengers carried as well as other traffic density variables. This means that the individual level of celeration is not as well estimated as could be the case. Another hypothesized influence of the number of passengers is that of differential quality of measurements, where high passenger density circumstances are supposed to yield better estimates of the individual driver component of celeration behavior. METHOD: Comparisons were made between different variants of the celeration as predictor of traffic incidents of bus drivers. The number of bus passengers was held constant, and cases identified by their number of passengers per kilometer during measurement were excluded (in 12 samples of repeated measurements). RESULTS: After holding passengers constant, the correlations between celeration behavior and incident record increased very slightly. Also, the selective prediction of incident record of those drivers who had had many passengers when measured increased the correlations even more. CONCLUSIONS: The influence of traffic density variables like the number of passengers have little direct influence on the predictive power of celeration behavior, despite the impact upon absolute celeration level. Selective prediction on the other hand increased correlations substantially. This unusual effect was probably due to how the individual propensity for high or low celeration driving was affected by the number of stops made and general traffic density; differences between drivers in this respect were probably enhanced by the denser traffic, thus creating a better estimate of the theoretical celeration behavior parameter C. The new concept of selective prediction was discussed in terms of making estimates of the systematic differences in quality of the individual driver data.     

Combining Coordination of Motion Actuators with Driver Steering Interaction

Objective: A new method is suggested for coordination of vehicle motion actuators; where driver feedback and capabilities become natural elements in the prioritization.

Methods: The method is using a weighted least squares control allocation formulation, where driver characteristics can be added as virtual force constraints. The approach is in particular suitable for heavy commercial vehicles that in general are over actuated. The method is applied, in a specific use case, by running a simulation of a truck applying automatic braking on a split friction surface. Here the required driver steering angle, to maintain the intended direction, is limited by a constant threshold. This constant is automatically accounted for when balancing actuator usage in the method.

Results: Simulation results show that the actual required driver steering angle can be expected to match the set constant well. Furthermore, the stopping distance is very much affected by this set capability of the driver to handle the lateral disturbance, as expected.

Conclusion: In general the capability of the driver to handle disturbances should be estimated in real-time, considering driver mental state. By using the method it will then be possible to estimate e.g. stopping distance implied from this. The setup has the potential of even shortening the stopping distance, when the driver is estimated as active, this compared to currently available systems. The approach is feasible for real-time applications and requires only measurable vehicle quantities for parameterization. Examples of other suitable applications in scope of the method would be electronic stability control, lateral stability control at launch and optimal cornering arbitration.     

Required hours of practice for learner drivers: A comparison between two Australian jurisdictions

Problem

This study considers whether requiring learner drivers to complete a set number of hours while on a learner license affects the amount of hours of supervised practice that they undertake. It compares the amount of practice that learners in Queensland and New South Wales report undertaking. At the time the study was conducted, learner drivers in New South Wales were required to complete 50 hours of supervised practice while those from Queensland were not.

Method

Participants were approached outside driver licensing centers after they had just completed their practical driving test to obtain their provisional (intermediate) license. Those agreeing to participate were interviewed over the phone later and asked a range of questions to obtain information including socio-demographic details and amount of supervised practice completed.

Results

There was a significant difference in the amount of practice that learners reported undertaking. Participants from New South Wales reported completing a significantly greater amount of practice (M = 73.3 hours, sd = 29.12 hours) on their learner license than those from Queensland (M = 64.1 hours, sd = 51.05 hours). However, the distribution of hours of practice among the Queensland participants was bimodal in nature. Participants from Queensland reported either completing much less or much more practice than the New South Wales average.

Summary

While it appears that the requirement that learner drivers complete a set number of hours may increase the average amount of hours of practice obtained, it may also serve to discourage drivers from obtaining additional practice, over and above the required hours.

Impact on Industry

The results of this study suggest that the implications of requiring learner drivers to complete a set number of hours of supervised practice are complex. In some cases, policy makers may inadvertently limit the amount of hours learners obtain to the mandated amount rather than encouraging them to obtain as much practice as possible.