Evaluating the crash risk of powered two-wheelers in urban mixed traffic environments: a conflict threshold perspective

The study investigates the crash risk of powered two-wheelers (PTWs) involved in multiple conflict types, with different vehicle classes constituting a mixed traffic stream. This study uses the extreme value theory to estimate the crash risk after establishing the conflict thresholds for potential rear-end and side-swipe conflicts by accounting for interacting vehicle types. The study considers four vehicle pairs involving PTWs: PTW-PTW, PTW-MThW (motorized three-wheeler), PTW-Car, and PTW-Bus. The study found that the conflict thresholds corresponding to rear-end and side-swipe types increase with the interacting vehicle size. The crash risk is lowest for the PTW-PTW pair (0.315%) in rear-end conflicts, whereas the risk is the highest for the PTW-MThW pair (3.7%) in side-swipe conflicts. The crash risk corresponding to the PTW interacting with other vehicle types is higher than that of the PTW-PTW pair. Hence, the implementation of exclusive PTW lanes could be an effective risk mitigation strategy for PTW-dominant mixed traffic environments.

Classifying safe following distance for motorcycles to prevent rear-end collisions

This study aims to classify motorcycle (MC) following distance based on trajectory traffic data and identify the risks associated with MC following distances to prevent rear-end collisions. A total of 8,223 events of a MC following a vehicle were investigated in Pathum Thani, Thailand, and 41 cases of MC rear-end crashes were analyzed between 2017 and 2021. Time headway (TH), safe stopping distance (SSD) and time to collision (TTC) were applied to the proposed concept to determine safe following distance (SFD). Speed and following distance for actual rear-end crashes were applied to validate SFD. Results showed that the proposed SFD model identified the causes of MC rear-end collision events as mostly due to longitudinal critical area (38 cases, 92.68%), implying insufficient MC rider reaction and decision time for evasive action. The longitudinal warning area had relatively few chances for rear-end collisions to occur, with only 3 cases recorded. VDO clip extracts from MC rear-end crashes illustrated 11 cases (26.83%) of rider fatality. The study findings revealed that the SFD concept can help to prevent MC rear-end collision events by developing reminder systems when the rider reached the following distances of both warning and critical areas.

Examination of the Effect of Task Complexity and Coping Capacity on Driving Risk: A Cross-Country and Transportation Mode Comparative Study

The i-DREAMS project established a 'Safety Tolerance Zone (STZ)' to maintain operators within safe boundaries through real-time and post-trip interventions, based on the crucial role of the human element in driving behavior. This paper aims to model the inter-relationship among driving task complexity, operator and vehicle coping capacity, and crash risk. Towards that aim, data from 80 drivers, who participated in a naturalistic driving experiment carried out in three countries (i.e., Belgium, Germany, and Portugal), resulting in a dataset of approximately 19,000 trips were collected and analyzed. The exploratory analysis included the development of Generalized Linear Models (GLMs) and the choice of the most appropriate variables associated with the latent variables "task complexity" and "coping capacity" that are to be estimated from the various indicators. In addition, Structural Equation Models (SEMs) were used to explore how the model variables were interrelated, allowing for both direct and indirect relationships to be modeled. Comparisons on the performance of such models, as well as a discussion on behaviors and driving patterns across different countries and transport modes, were also provided. The findings revealed a positive relationship between task complexity and coping capacity, indicating that as the difficulty of the driving task increased, the driver's coping capacity increased accordingly, (i.e., higher ability to manage and adapt to the challenges posed by more complex tasks). The integrated treatment of task complexity, coping capacity, and risk can improve the behavior and safety of all travelers, through the unobtrusive and seamless monitoring of behavior. Thus, authorities should utilize a data system oriented towards collecting key driving insights on population level to plan mobility and safety interventions, develop incentives for road users, optimize enforcement, and enhance community building for safe traveling.

Indicators of Crash Risk in Older Adults: A Longitudinal Analysis From the ACTIVE Study

Objective: This study aims to examine indicators of crash risk longitudinally in older adults (n = 486). Method: This study applied secondary data analyses of the 10 years of follow-up for the ACTIVE study combined with state-recorded crash records from five of the six participating sites. Cox proportional hazards models were first used to examine the effect of each variable of interest at baseline after controlling for miles driven and then to assess the three cognitive composites as predictors of time to at-fault crash in covariate-adjusted models. Results: Older age, male sex, and site location were each predictive of higher crash risk. Additionally, worse scores on the speed of processing cognitive composite were associated with higher crash risk. Discussion: Results support previous findings that both age and male sex are associated with higher crash risk. Our significant finding of site location could be attributed to the population density of our testing sites and transportation availability.

Crash Risk Predictors in Older Drivers: A Cross-Sectional Study Based on a Driving Simulator and Machine Learning Algorithms

The ability to drive depends on the motor, visual, and cognitive functions, which are necessary to integrate information and respond appropriately to different situations that occur in traffic. The study aimed to evaluate older drivers in a driving simulator and identify motor, cognitive and visual variables that interfere with safe driving through a cluster analysis, and identify the main predictors of traffic crashes. We analyzed the data of older drivers (n = 100, mean age of 72.5 ± 5.7 years) recruited in a hospital in São Paulo, Brazil. The assessments were divided into three domains: motor, visual, and cognitive. The K-Means algorithm was used to identify clusters of individuals with similar characteristics that may be associated with the risk of a traffic crash. The Random Forest algorithm was used to predict road crash in older drivers and identify the predictors (main risk factors) related to the outcome (number of crashes). The analysis identified two clusters, one with 59 participants and another with 41 drivers. There were no differences in the mean of crashes (1.7 vs. 1.8) and infractions (2.6 vs. 2.0) by cluster. However, the drivers allocated in Cluster 1, when compared to Cluster 2, had higher age, driving time, and braking time (p < 0.05). The random forest performed well (r = 0.98, R² = 0.81) in predicting road crash. Advanced age and the functional reach test were the factors representing the highest risk of road crash. There were no differences in the number of crashes and infractions per cluster. However, the Random Forest model performed well in predicting the number of crashes.

Analysis of factors influencing aggressive driver behavior and crash involvement

OBJECTIVE

Aggressive driver behavior is one of the major contributing factors to road crashes. However, the relationship between aggressive driver behavior and crash risk is scarcely explored. The present study focused on quantifying the effect of aggressive driver behavior on crash probability.

METHOD AND DATA SOURCES

A sample of 405 Indian drivers were analyzed to model the aggressive driver behavior using self-reported measures. Generalized linear models were developed to quantify the effects of independent variables such as age, gender, personality traits (e.g., driving anger, physical aggression, hostility), and individual predilections to commit violations (e.g., excessive speeding and frequent risky overtaking) on aggressive driver behavior and crash probabilities.

RESULTS

K-means clustering technique was applied to the Aggressive Driving Scale (ADS) scores to cluster the drivers into three groups (aggressive, normal, and cautious). Gender was significantly correlated with aggressive driver behavior. Compared to female drivers, male drivers were 2.57 times more likely to engage in aggressive driving. Driver's age was negatively correlated with aggressive driving. With one-year increment in driver's age, the tendency of a driver to engage in aggressive driving was reduced by 26%. In addition, the likelihood of being engaged in aggressive driving was increased by 2.98 times and 2.15 times for the drivers who engage in excessive speeding and frequent risky overtaking, respectively. Driver's personality traits were significantly correlated with aggressive drivers. The crash involvement model showed that aggressive drivers were 2.79 times more likely to be involved in road crashes than cautious drivers. Further, married drivers were 2.17 times less likely to be involved in crashes, whereas for professional drivers the crash involvement probability was increased by 75%.

CONCLUSIONS

The results revealed that in addition to age and gender personality traits were significant predictors of driving aggression. Further, the driver's marital status was negatively correlated with the crash involvement and professional drivers were more likely to be involved in crashes than nonprofessional drivers. The study findings can be used in identifying specific risk-prone drivers to provide safety measures via in-vehicle Advanced Driver Assistance Systems (ADAS).

Identifying Interactive Factors That May Increase Crash Risk between Young Drivers and Trucks: A Narrative Review

Sharing the road with trucks is associated with increased risk of serious injury and death for passenger vehicle drivers. However, the onus for minimising risk lies not just with truck drivers; other drivers must understand the unique performance limitations of trucks associated with stopping distances, blind spots, and turning manoeuverability, so they can suitably act and react around trucks. Given the paucity of research aimed at understanding the specific crash risk vulnerability of young drivers around trucks, the authors employ a narrative review methodology that brings together evidence from both truck and young driver road safety research domains, as well as data regarding known crash risks for each driving cohort, to gain a comprehensive understanding of what young drivers are likely to know about heavy vehicle performance limitations, where there may be gaps in their understanding, and how this could potentially increase crash risk. We then review literature regarding the human factors affecting young drivers to understand how perceptual immaturity and engagement in risky driving behaviours are likely to compound risk regarding both the frequency and severity of collision between trucks and young drivers. Finally, we review current targeted educational initiatives and suggest that simply raising awareness of truck limitations is insufficient. We propose that further research is needed to ensure initiatives aimed at increasing young driver awareness of trucks and truck safety are evidence-based, undergo rigorous evaluation, and are delivered in a way that aims to (i) increase young driver risk perception skills, and (ii) reduce risky driving behaviour around trucks.

Validating the representativeness assumption of the quasi-induced exposure method using a national representative field observation survey

OBJECTIVE

The quasi-induced exposure (QIE) method was developed to estimate relative crash risk exposure. A fundamental assumption often made in applying the QIE method is that not-at-fault drivers in clean two-vehicle crashes (i.e., one and only one driver is at-fault) represent the general exposure of the driving population to crash risk in the absence of the intervention being studied. Our study used direct field observation data to test the representativeness of the assumption for not-at-fault drivers obtained from the General Estimating System (GES) crash data, a national crash database in the United States.

METHODS

Distributions of driver gender, age group, vehicle type, and time-of-crash among the not-at-fault drivers in clean two-vehicle crashes (D2) and the ones in two-or-more-vehicle crashes (i.e., all not-at-fault drivers) from the GES data were compared to the driving population estimated from the National Occupant Protection Use Survey (NOPUS), a national representative field observation survey.

RESULTS

The gender and vehicle-type distributions of D2 and all not-at-fault drivers were not statistically significantly different from the ones in the NOPUS data. Age-group distributions for both not-at-fault driving populations were marginally similar to the ones estimated from NOPUS.

CONCLUSION

By system-wide comparisons on gender, age group, vehicle type, and period, our study suggests that the not-at-fault drivers in crash databases with crashes ranging from no injury to fatal injury reflect the general driving population when the collision occurred. Future study should evaluate the representativeness assumption among other important factors, including roadway type, road geometry, and level of urbanization. Our study supports the credibility of applying the QIE method in traffic safety research using crash databases of all crashes with all severities.

A spatial econometrics perspective on the characteristics of urban traffic accidents: focusing on elderly drivers' accidents in Seoul, South Korea

Due to the rapid ageing of the population, the number of traffic accidents involving elderly drivers has dramatically increased in Northeast Asia countries including South Korea. In order to ensure the mobility of elderly drivers and prevent the risk of accidents, it is necessary to consider various factors, which may affect elderly drivers while driving in urban areas. The primary goal of this study is to examine the characteristics of elderly drivers' traffic accidents in urban areas using spatial econometrics models. The study reveals that the highly populated areas (e.g. commercial areas, employment centres, and subway station catchment areas) have a higher risk of accidents involving elderly drivers. Also, due to an increase in cognitive response time and physical ageing of the elderly, the factors which represent complex driving condition for elderly drivers (e.g. traffic islands, intersections, and school zones) are found to be positively associated with the risk of accidents.

Perceptions and attitudes toward risk and personal responsibility in the context of medical fitness to drive

Objective: Although there is a considerable body of literature probing the knowledge and awareness of doctors of guidelines on medical fitness to drive, little is known of knowledge and awareness of such guidelines among the general public. We investigated awareness, perceptions and attitudes among a range of adults toward risk and personal responsibility in the context of medical fitness to drive.Methods: This quasi-experimental between groups study assessed response differences between healthcare (33%) and non-healthcare professionals. Five hundred and fourteen adults (f = 342) completed a 15-item online survey, which assessed their license status, direct and secondhand experience with key medical conditions, perceptions of risk, driving intentions if advised to stop driving by a doctor and beliefs about responsibility for ensuring driver fitness.Results: Most of the participants had a driver license. Although the majority (87%) had no first-hand experience with key medical conditions contained in the Irish medical fitness to drive guidelines, two-thirds knew someone with at least one of these conditions. No participant admitted to an alcohol or drug misuse/dependence problem. Alcohol misuse/dependence and fatigue/chronic sleep loss were perceived as the greatest crash risk for drivers and for vulnerable road users. Risk perceptions in general public and the medical professionals were similar for most conditions but where they differed, the medical professionals perceived lower risk. Most respondents indicated that they would cease driving immediately if advised by their doctor for temporary and long-term conditions. No effects of age, gender, experience with medical conditions or professional status were noted on perceived intentions to cease driving. Perceptions about who is responsible for ensuring people are fit to drive fell into two categories. Drivers were perceived as chiefly responsible where alcohol, non-prescription drugs, fatigue and age were factors and doctors were identified as responsible in cases of diabetes, epilepsy, stroke, heart conditions and physical disabilities.Conclusions: These results suggest that more needs to be done to raise awareness of the risks posed by medical and other factors that reduce driver capability and also about drivers' responsibility to ensure that they are fit to drive and thus improve road safety.

Personality and Behavioral Predictors of Cyclist Involvement in Crash-Related Conditions

In recent years, the increasing rate of road crashes involving cyclists with a disproportionate overrepresentation in injury statistics has become a major concern in road safety and public health. However, much remains unknown about factors contributing to cyclists’ high crash rates, especially those related to personal characteristics. This study aims to explore the influence of cyclist personality traits and cycling behaviors on their road safety outcomes using a mediated model combining these constructs. A total of 628 cyclists completed an online questionnaire consisting of questions related to cycling anger, impulsiveness, normlessness, sensation seeking, risky cycling behaviors, and involvement in crash-related conditions in the past year. After the psychometric properties of the employed scales were examined, the relationships among the tested constructs were investigated using structural equation modeling. The results showed that cyclists’ crash risks were directly predicted by risky cycling behaviors and cycling anger, and the effects of cycling anger, impulsiveness, as well as normlessness on crash risks, were mediated by cycling behaviors. The current findings provide insight into the importance of personality traits in impacting cycling safety and could facilitate the development of evidence-based prevention and promotion strategies targeting cyclists in China.

Risk-Exposure Density and Mileage Bias in Crash Risk for Older Drivers

Crash rates per mile indicate a high risk of vehicle crash in older drivers. A reliance on mileage alone may underestimate the risk exposure of older drivers because they tend to avoid highways and travel more on nonfreeways (e.g., urban roads), which present greater hazards. We introduce risk-exposure density as an index of exposure that incorporates mileage, frequency of travel, and travel duration. Population-wide driver fatalities in the United States during 2002-2012 were assessed according to driver age range (in years: 16-20, 21-29, 30-39, 40-49, 50-59, 60-69, ≥70) and sex. Mileage, frequency, and duration of travel per person were used to assess risk exposure. Mileage-based fatal crash risk increased greatly among male (relative risk (RR) = 1.73; 95% CI: 1.62, 1.83) and female (RR = 2.08; 95% CI: 1.97, 2.19) drivers from ages 60-69 years to ages ≥70 years. Adjusting for their density of risk exposure, fatal crash risk increased only slightly from ages 60-69 years to ages ≥70 years among male (RR = 1.09; 95% CI: 1.03, 1.15) and female (RR = 1.22; 95% CI: 1.16, 1.29) drivers. While ubiquitous in epidemiologic research, mileage-based assessments can produce misleading accounts of driver risk. Risk-exposure density incorporates multiple components of travel and reduces bias caused by any single indicator of risk exposure.

Driving in search of analyses

Although transportation safety has greatly improved over the past 2 decades, motor vehicle crash injuries remain a leading cause of morbidity and mortality, particularly among young drivers. Driver errors and behaviors such as speeding and distraction contribute disproportionately to crashes among inexperienced novices, who develop safe driving judgment only with substantial driving experience, commonly described as the "young driver problem." Research on young drivers has applied a range of research methods, including analyses of national archival data (mainly from police reports), crash analyses, observation of driver behavior, surveys of driver behavior and dispositions, and experimental research on driver behavior and vehicle crash worthiness. Prominent research questions regarding young driver safety include what and how do novices learn to drive safely, what are the predictors of young driver crashes, what is the variability and overtime trajectories of young driver performance and outcomes, and to what extent is the young driver problem due mainly to average population risk or high-risk groups? Current research on young drivers is complicated by small sample sizes, relatively rare events, high within and between group variability, missing data, the need to estimate exposure, and the lack of longitudinal and experimental designs, problems that require complex analytic methods. In this paper, we provide an overview of driving research methods, examples of research addressing the young driver problem, and examples of statistical collaboration on young driver research, focusing particularly on estimating prediction of crash risk and estimating variability in young driver performance and outcomes.

Powered two-wheeler riders' risk of crashes associated with filtering on urban roads

OBJECTIVE

The objective of this study is to estimate the crash risk per kilometer traveled by powered two-wheeler (PTW) riders filtering through traffic on urban roads.

METHODS

Using the traffic injury crashes recorded by the police over a period of 3 years on 14 sections of urban roads in the city of Marseille, France, and a campaign of observations of PTWs, the crash risk per kilometer traveled by PTWs filtering was estimated and compared to the risk of PTWs that did not filter.

RESULTS

The results show that the risk of PTW riders being involved in injury crashes while filtering is significantly higher than the risk for riders who do not filter. For the 14 sections studied, it is 3.94 times greater (95% confidence interval [CI], 2.63, 5.89). This excess risk occurred for all PTW categories. Furthermore, no space appears to be safer than the others for filtering. Riders filtering forward along the axis of the carriageway, along bus lanes, or between traffic lanes (lane-splitting) all have a crash risk greater than the risk of those who do not filter.

CONCLUSIONS

All measures limiting the practice of filtering by PTWs on urban roads would probably contribute to improving the safety of their users.

The useful field of view assessment predicts simulated commercial motor vehicle driving safety

OBJECTIVE

The Useful Field of View (UFOV) assessment, a measure of visual speed of processing, has been shown to be a predictive measure of motor vehicle collision (MVC) involvement in an older adult population, but it remains unknown whether UFOV predicts commercial motor vehicle (CMV) driving safety during secondary task engagement. The purpose of this study is to determine whether the UFOV assessment predicts simulated MVCs in long-haul CMV drivers.

METHOD

Fifty licensed CMV drivers (Mage = 39.80, SD = 8.38, 98% male, 56% Caucasian) were administered the 3-subtest version of the UFOV assessment, where lower scores measured in milliseconds indicated better performance. CMV drivers completed 4 simulated drives, each spanning approximately a 22.50-mile distance. Four secondary tasks were presented to participants in a counterbalanced order during the drives: (a) no secondary task, (b) cell phone conversation, (c) text messaging interaction, and (d) e-mailing interaction with an on-board dispatch device.

RESULTS

The selective attention subtest significantly predicted simulated MVCs regardless of secondary task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC in the simulated drive. The e-mail interaction secondary task significantly predicted simulated MVCs with a 4.14 times greater risk of an MVC compared to the no secondary task condition. Subtest 3, a measure of visual speed of processing, significantly predicted MVCs in the email interaction task. Each 20 ms slower on subtest 3 was associated with a 25% increase in the risk of an MVC during the email interaction task.

CONCLUSIONS

The UFOV subtest 3 may be a promising measure to identify CMV drivers who may be at risk for MVCs or in need of cognitive training aimed at improving speed of processing. Subtest 3 may also identify CMV drivers who are particularly at risk when engaged in secondary tasks while driving.

Circadian Sleep Propensity and Alcohol Interaction at the Wheel

STUDY OBJECTIVES

The study was aimed at estimating the effect of alcohol consumption, time of day, and their interaction on traffic crashes in a real regional context.

METHODS

Blood alcohol concentration (BAC) data were collected from drivers involved in traffic accidents during one year in an Italian region and in a control group of drivers over the same road network. Mean circadian sleep propensity was estimated from a previous study as function of time of day. Accident risk was analyzed by logistic regression as function of BAC and circadian sleep propensity.

RESULTS

BAC values greater than zero were found in 72.0% of the drivers involved in crashes and in 40.4% of the controls. Among the former 23.6% of the drivers exceeded the BAC legal threshold of 0.05 g/dL, while illegal values were found in 10.4% of the controls. The relative risk showed a significant increase with both BAC and circadian sleep propensity (as estimated from time of day) and their interaction was significant.

CONCLUSIONS

Due to the significant interaction, even low BAC levels strongly increased accident risk when associated with high sleep propensity.

Driver crash risk factors and prevalence evaluation using naturalistic driving data

The accurate evaluation of crash causal factors can provide fundamental information for effective transportation policy, vehicle design, and driver education. Naturalistic driving (ND) data collected with multiple onboard video cameras and sensors provide a unique opportunity to evaluate risk factors during the seconds leading up to a crash. This paper uses a National Academy of Sciences-sponsored ND dataset comprising 905 injurious and property damage crash events, the magnitude of which allows the first direct analysis (to our knowledge) of causal factors using crashes only. The results show that crash causation has shifted dramatically in recent years, with driver-related factors (i.e., error, impairment, fatigue, and distraction) present in almost 90% of crashes. The results also definitively show that distraction is detrimental to driver safety, with handheld electronic devices having high use rates and risk.

Obstructive sleep apnea, health-related factors, and long distance heavy vehicle crashes in Western Australia: a case control study

STUDY OBJECTIVES

To determine the association between obstructive sleep apnea (OSA), health-related factors and the likelihood of heavy vehicle crashes in Western Australia (WA).

METHODS

This case-control study included 100 long-haul heavy vehicle drivers who were involved in a police-reported crash in WA during the study period (cases) and 100 long-haul heavy vehicle drivers recruited from WA truck stops, who were not involved in a crash during the past year (controls). Driver demographics, health, and fatigue-related characteristics were obtained using an interviewer administered questionnaire. Drivers were tested for OSA using a diagnostic Flow Wizard. Logistic regression was used to determine health-related factors associated with crash involvement among long distance heavy vehicle drivers.

RESULTS

Heavy vehicle drivers diagnosed with OSA through the use of the FlowWizard were over three times more likely to be involved in a crash than drivers without OSA (adjusted OR: 3.42, 95% CI: 1.34-8.72). The risk of crash was significantly increased if heavy vehicle drivers reported a diagnosis of depression (adjusted OR: 6.59, 95% CI: 1.30-33.24) or had not completed fatigue management training (adjusted OR: 6.05, 95% CI: 1.80-20.24). Crash risk was 74% lower among older drivers (> 35 years) than younger drivers (adjusted OR: 0.25, 95% CI: 0.08-0.82).

CONCLUSION

The results suggest that more rigorous screening and subsequent treatment of OSA and depression by clinicians as well as compulsory fatigue management training may reduce crashes among heavy vehicle drivers.

COMMENTARY

A commentary on this article appears in this issue on page 409.

The risk of a safety-critical event associated with mobile device use in specific driving contexts

OBJECTIVE

We explored drivers' mobile device use and its associated risk of a safety-critical event (SCE) in specific driving contexts. Our premise was that the SCE risk associated with mobile device use increases when the driving task becomes demanding.

METHODS

Data from naturalistic driving studies involving commercial motor vehicle drivers and light vehicle drivers were partitioned into subsets representative of specific driving contexts. The subsets were generated using data set attributes that included level of service and relation to junction. These attributes were selected based on exogenous factors known to alter driving task demands. The subsets were analyzed using a case-cohort approach, which was selected to complement previous investigations of mobile device SCE risk using naturalistic driving data.

RESULTS

Both commercial motor vehicle and light vehicle drivers varied as to how much they conversed on a mobile device but did not vary their engagement in visual-manual subtasks. Furthermore, commercial motor vehicle drivers conversed less frequently as the driving task demands increased, whereas light vehicle drivers did not. The risk of an SCE associated with mobile device use was dependent on the subtask performed and the driving context. Only visual-manual subtasks were associated with an increased SCE risk, whereas conversing was associated with a decreased risk in some driving contexts.

CONCLUSION

Drivers' engagement in mobile device subtasks varies by driving context. The SCE risk associated with mobile device use is dependent on the types of subtasks performed and the driving context. The findings of this exploratory study can be applied to the design of driver-vehicle interfaces that mitigate distraction by preventing visual-manual subtasks while driving.

The effectiveness of a 0.05 blood alcohol concentration (BAC) limit for driving in the United States

The National Transportation Safety Board recently recommended that states establish a per se blood alcohol concentration (BAC) limit of 0.05 or lower for all drivers who are not already required to adhere to lower BAC limits in a national effort to reduce alcohol-impaired driving. There is strong evidence for adopting this recommendation. A comprehensive review of the literature on BAC limits was conducted. The research indicates that virtually all drivers are impaired regarding at least some driving performance measures at a 0.05 BAC. The risk of being involved in a crash increases significantly at 0.05 BAC and above. The relative risk of being killed in a single-vehicle crash with BACs of 0.05-0.079 is 7-21 times higher than for drivers at 0.00 BAC. Lowering the BAC limit from 0.08 to 0.05 has been a proven effective countermeasure in numerous countries around the world. Most Americans do not believe a person should drive after having two or three drinks in 2 hours. It takes at least four drinks for the average 170-pound male to exceed 0.05 BAC in 2 hours (three drinks for the 137-pound female). Most industrialized nations have established a 0.05 BAC limit or lower for driving. Progress in reducing the proportion of drivers in fatal crashes with illegal BACs has stalled over the past 15 years. Lowering the BAC limit for driving from the current 0.08 to 0.05 has substantial potential to reduce the number of people who drink and drive in the United States and get involved in fatal crashes.

Limits of spatial attention in three-dimensional space and dual-task driving performance

The present study examined the limits of spatial attention while performing two driving relevant tasks that varied in depth. The first task was to maintain a fixed headway distance behind a lead vehicle that varied speed. The second task was to detect a light-change target in an array of lights located above the roadway. In Experiment 1 the light detection task required drivers to encode color and location. The results indicated that reaction time to detect a light-change target increased and accuracy decreased as a function of the horizontal location of the light-change target and as a function of the distance from the driver. In a second experiment the light change task was changed to a singleton search (detect the onset of a yellow light) and the workload of the car following task was systematically varied. The results of Experiment 2 indicated that RT increased as a function of task workload, the 2D position of the light-change target and the distance of the light-change target. A multiple regression analysis indicated that the effect of distance on light detection performance was not due to changes in the projected size of the light target. In Experiment 3 we found that the distance effect in detecting a light change could not be explained by the location of eye fixations. The results demonstrate that when drivers attend to a roadway scene attention is limited in three-dimensional space. These results have important implications for developing tests for assessing crash risk among drivers as well as the design of in vehicle technologies such as head-up displays.

Do older drivers at-risk for crashes modify their driving over time?

Five-year driving habit trajectories among older adults (n = 645) at-risk for crashes were examined. Performance measures included Useful Field of View (UFOV). Motor-Free Visual Perception Test, Rapid Walk, and Foot Tap. Self-report measures included demographics and the Driving Habits Questionnaire. Longitudinal random-effects models revealed that drivers at-risk for subsequent crashes, based upon UFOV, regulated their driving more than the lower-risk participants. Restricted driving was present at baseline for the at-risk group and was observed in longitudinal trajectories that controlled for baseline differences. Results indicate that persons at-risk for subsequent crashes increasingly limit their driving over time. Despite this self-regulation, a larger sample of such older drivers was twice as likely to incur subsequent at-fault crashes. Results suggest that self-regulation among older drivers at-risk for crashes is an insufficient compensatory approach to eliminating increased crash risk. UFOV is a registered trademark of Visual Awareness, Inc.