Survival risk factors for fatal injured car and motorcycle drivers in single alcohol-related and alcohol-unrelated vehicle crashes

Introduction

A high percentage of drivers who die as a result of a single vehicle crash are under the influence of alcohol. We aimed to better understand the prevalence of these fatalities and the ratio of death to injuries based on various risk factors. We focused on alcohol-related and -unrelated single-vehicle crashes to investigate the influence of such risk factors on the time until death for car and motorcycle drivers.

Methods

We combined data from national police reports and a vital registration database in Taiwan. Survival analysis using Cox regression models was used to identify the risk factors of time until death.

Results

Overall, nearly 60% of car driver fatalities and 40% of motorcycle driver fatalities involved the consumption of alcohol. Survival analysis of single-vehicle crashes suggested that the traffic island separation between a car moving at a higher speed and motorcycle traffic resulted in a higher risk of death over time for motorcycle drivers who consumed alcohol. The factors attributed to a higher risk of death over time for motorcycle drivers were older age, crashing into trees, night-time driving, driving on curved roads, and driving on local roads. Driving without restraints and driving on roads with higher speed limits attributed to a higher risk of death over time for car drivers.

Conclusions

The factors that influence the risk of death over time in a motor-vehicle accident involving alcohol depended on different elements, which should each be considered when attempting to reduce this risk.

Impact on Industry

More efforts should be made to investigate the various risk factors in areas with large motorcycle populations.     

Characteristics of speeders

OBJECTIVE: To determine the characteristics of speeders, defined as drivers of vehicles traveling at least 15 mph above the posted speed limit and relatively faster than surrounding vehicles. METHODS: Vehicle speeds were recorded on 13 roads in Virginia with speed limits ranging from 40 to 55 mph. Speeders were compared with slower drivers, defined as drivers of adjacent vehicles traveling no more than 5 mph above the speed limit. License plates were used to identify vehicle owners; owners were inferred to have been driving if observed gender and estimated age matched those of the registered owner. For these drivers, information on exact driver age and gender, vehicle make and model, and driving record was obtained from the Virginia Department of Motor Vehicles. RESULTS: Five percent of the vehicles observed were traveling at least 15 mph above the limit, and 3% qualified as speeders, as defined in this study. Speeders were younger than drivers in the comparison group, drove newer vehicles, and had more speeding violations and other moving violations on their records. They also had 60% more crashes. DISCUSSION: Speeders are a high-risk group. Their speeding behavior is not likely to be controlled without vigorous, consistent enforcement, including the use of automated technology.     

Measures of speeding from a GPS-based travel behavior survey

Objective: Lacking information about actual driving speed on most roads in the Minneapolis–St. Paul region, we determine car speeds using observations from a Global Positioning System (GPS)-based travel survey. Speed of travel determines the likelihood and consequences of collisions. We identify the road segments where speeding occurs. This article then analyzes the relationship between link length, traveler characteristics, and speeding using GPS data collected from 152 individuals over a 7-day period as part of the Minneapolis–St. Paul Travel Behavior Inventory.

Methods: To investigate the relationship, we employed an algorithm and process to accurately match the GPS data with geographic information system (GIS) databases. Comparing actual travel speed from GPS data with posted speed limits, we measure where and when speeding occurs and by whom. We posit that link length and demographics shape the decision to speed.

Results: Speeding is widespread under both high speed limits (e.g., 60?mph [97?km/h]) and low speed limits (less than 25?mph [40?km/h]); in contrast, speeding is less common at 30–35?mph (48–56?km/h). The results suggest that driving patterns depend on the road type. We also find that when there are many intersections, the average link speed (and speeding) drops. Long links are conducive to speeding. Younger drivers and more educated drivers also speed more, and speeding occurs more often in the evening.

Conclusions: Road design and link length (or its converse, frequency of intersections) affect the likelihood of speeding. Use of increasingly available GPS data allows more systematic empirical analysis of designs and topologies that are conducive to road safety.     

Fatal crash trends for Australian young drivers 1997-2007: Geographic and socioeconomic differentials

Background

Little has been published on changes in young driver fatality rates over time. This paper examines differences in Australian young driver fatality rates over the last decade, examining important risk factors including place of residence and socioeconomic status (SES).

Methods

Young driver (17-25 years) police-recorded passenger vehicle crashes were extracted from New South Wales State records from 1997-2007. Rurality of residence and SES were classified into three levels based on drivers’ residential postcode: urban, regional, or rural; and high, moderate, or low SES areas. Geographic and SES disparities in trends of fatality rates were examined by the generalized linear model. Chi-square trend test was used to examine the distributions of posted speed limits, drinking driving, fatigue, seatbelt use, vehicle age, night-time driving, and the time from crash to death across rurality and socioeconomic status.

Results

Young driver fatality rate significantly decreased 5% per year (p < 0.05); however, stratified analyses (by rurality and by SES) showed that only the reduction among urban drivers was significant (average 5% decrease per year, p < 0.01). The higher relative risk of fatality for rural versus urban drivers, and for drivers of low versus high SES remained unchanged over the last decade. High posted speed limits, fatigue, drink driving and seatbelt non-use were significantly associated with rural fatalities, whereas high posted speed limit, fatigue, and driving an older vehicle were significantly related to low SES fatality.

Conclusion

The constant geographic and SES disparities in young driver fatality rates highlight safety inequities for those living in rural areas and those of low SES. Better targeted interventions are needed, including attention to behavioral risk factors and vehicle age.     

Analyses of rear-end crashes based on classification tree models

OBJECTIVE: Signalized intersections are accident-prone areas especially for rear-end crashes due to the fact that the diversity of the braking behaviors of drivers increases during the signal change. The objective of this article is to improve knowledge of the relationship between rear-end crashes occurring at signalized intersections and a series of potential traffic risk factors classified by driver characteristics, environments, and vehicle types. METHODS: Based on the 2001 Florida crash database, the classification tree method and Quasi-induced exposure concept were used to perform the statistical analysis. Two binary classification tree models were developed in this study. One was used for the crash comparison between rear-end and non-rear-end to identify those specific trends of the rear-end crashes. The other was constructed for the comparison between striking vehicles/drivers (at-fault) and struck vehicles/drivers (not-at-fault) to find more complex crash pattern associated with the traffic attributes of driver, vehicle, and environment. RESULTS: The modeling results showed that the rear-end crashes are over-presented in the higher speed limits (45-55 mph); the rear-end crash propensity for daytime is apparently larger than nighttime; and the reduction of braking capacity due to wet and slippery road surface conditions would definitely contribute to rear-end crashes, especially at intersections with higher speed limits. The tree model segmented drivers into four homogeneous age groups: < 21 years, 21-31 years, 32-75 years, and > 75 years. The youngest driver group shows the largest crash propensity; in the 21-31 age group, the male drivers are over-involved in rear-end crashes under adverse weather conditions and the 32-75 years drivers driving large size vehicles have a larger crash propensity compared to those driving passenger vehicles. CONCLUSIONS: Combined with the quasi-induced exposure concept, the classification tree method is a proper statistical tool for traffic-safety analysis to investigate crash propensity. Compared to the logistic regression models, tree models have advantages for handling continuous independent variables and easily explaining the complex interaction effect with more than two independent variables. This research recommended that at signalized intersections with higher speed limits, reducing the speed limit to 40 mph efficiently contribute to a lower accident rate. Drivers involved in alcohol use may increase not only rear-end crash risk but also the driver injury severity. Education and enforcement countermeasures should focus on the driver group younger than 21 years. Further studies are suggested to compare crash risk distributions of the driver age for other main crash types to seek corresponding traffic countermeasures.     

Use of manual speed alerting and cruise control devices by car drivers

A number of in-vehicle technologies have been developed that have significant potential to reduce the incidence and severity of speed-related crashes. Two of the most widely implemented of these are conventional cruise control and manual speed alerting devices. However, almost nothing is known about the extent to which drivers use these devices and whether they are effective in helping drivers reduce speeding. This study assessed the use, acceptability and effectiveness in reducing speeding of manual speed alerting and cruise control devices to a sample of drivers from the Australian state of New South Wales. Four focus groups were conducted; two in Sydney (metropolitan) and two in Wagga Wagga (rural), involving 31 drivers aged 25–49 years, who were either users or non-users of the devices. The participants held positive attitudes towards manual speed alerting and cruise control systems and felt that these devices are generally effective in helping them to control and maintain their speed. However, the rural participants use cruise control more regularly than metropolitan participants, while the metropolitan participants reported that they use their speed alerting system more than rural participants. Preliminary recommendations deriving from the research are made.     

Aggressive driving behaviour in young drivers (aged 16 through 25) involved in fatal crashes

IntroductionWe wished to determine the extent to which number of passengers, driver age, and sex were associated with aggressive driving actions (ADAs) in young drivers involved in a fatal crash.MethodsWe used U.S. fatal-crash data from Fatality Analysis Reporting System (FARS), 1991 –2008. Proxy measures of aggressive driving included ADA presence and speed differential (posted speed limit minus estimated travel speed). We examined the odds of an ADA and speed differential in young drivers (aged 16 to 25) by passenger status.ResultsCompared to driving alone young drivers (aged 16) had increased odds of an ADA between 14% (OR: 1.14; 95% CI: 1.07; 1.22) and 95% (OR: 1.95; 95% CI: 1.40; 2.74) when accompanied by one and five passengers, respectively. Further, carrying a higher number of passengers was a stronger predictor of speeding in younger drivers.ConclusionsThis study supports the use of graduated licensing approaches. Specifically, developing interventions to reduce aggressive driving appear imperative.Impact on IndustryWhile the results of our study support the use of graduated licensing approaches there is room for improvement. Our study indicates that tackling impaired driving is not sufficient to drastically reduce aggressive driving among the youngest drivers. Further research on young drivers is required to understand the influence of peers and the role of gender on driving behavior. Strategies to reduce aggressive driving behaviors among the youngest drivers may not only prevent crashes during their early driving careers but may also translate into a reduced crash risk over their lifetime.     

Crash rates over time among younger and older drivers in the SHRP 2 naturalistic driving study

Objective: To examine crash rates over time among 16–17-year-old drivers compared to older drivers. Methods: Data were from a random sample of 854 of the 3,500 study participants in SHRP 2, a U.S. national, naturalistic driving (instrumented vehicle) study. Crashes/10,000 miles by driver age group, 3-month period, and sex were examined within generalized linear mixed models. Results: Analyses of individual differences between age cohorts indicated higher incidence rates in the 16–17-year old cohort relative to older age groups each of the first four quarters (except the first quarter compared to 18–20 year old drivers) with incident rate ratios (IRR) ranging from 1.98 to 18.90, and for the full study period compared with drivers 18–20 (IRR = 1.69, CI = 1.00, 2.86), 21 to 25 (IRR = 2.27, CI = 1.31, 3.91), and 35 to 55 (IRR = 4.00, CI = 2.28, 7.03). Within the 16–17-year old cohort no differences were found in rates among males and females and the decline in rates over the 24-month study period was not significant. Conclusions: The prolonged period of elevated crash rates suggests the need to enhance novice young driver prevention approaches such as Graduated Driver’s Licensing limits, parent restrictions, and post-licensure supervision and monitoring. Practical Applications: Increases are needed in Graduated Driver’s Licensing limits, parent restrictions, and postlicensure supervision and monitoring.     

Risk factors associated with bus accident severity in the United States: A generalized ordered logit model

IntroductionRecent years have witnessed a growing interest in improving bus safety operations worldwide. While in the United States buses are considered relatively safe, the number of bus accidents is far from being negligible, triggering the introduction of the Motor-coach Enhanced Safety Act of 2011.MethodThe current study investigates the underlying risk factors of bus accident severity in the United States by estimating a generalized ordered logit model. Data for the analysis are retrieved from the General Estimates System (GES) database for the years 2005–2009.ResultsResults show that accident severity increases: (i) for young bus drivers under the age of 25; (ii) for drivers beyond the age of 55, and most prominently for drivers over 65 years old; (iii) for female drivers; (iv) for very high (over 65 mph) and very low (under 20 mph) speed limits; (v) at intersections; (vi) because of inattentive and risky driving.     

To speed or not to speed: Thematic analysis of American driving narratives

IntroductionSpeeding is a major cause of unintentional roadway death in the United States. Existing data show that U.S. drivers tend to speed less as they age, but reasons for this change remain largely unknown. Limited research has examined why U.S. drivers decide to speed or why U.S. drivers decide not to speed, and none to date has determined why speeding behaviors change over the life course. Research into these issues can provide insight that may be harnessed for more effective anti-speeding interventions that catalyze decisions not to speed. Methods: The current study asked a national sample of U.S. drivers (N = 309) about their driving behaviors and how they have changed over time using an open-ended prompt in an online survey. The authors qualitatively coded responses using a narrative analysis lens to identify common themes. Results: Results show U.S. drivers often make deliberate choices to speed and some do not consider speeding to be dangerous after achieving perceived mastery of driving skills. Participants tended to report speeding less over time, citing increased concern for family and other roadway users, which may help explain national speeding data trends. Several other themes emerged identifying individual cognitive factors, environmental contexts, and key persons impacting speeding decisions. Practical Applications: Findings show that the most effective means of encouraging U.S. drivers to decide not to speed may be multi-pronged intervention approaches highlighting how speeding reduces roadway driver control, connecting speeding with safety, and encompassing road design and law enforcement strategies.     

Peer influence predicts speeding prevalence among teenage drivers

Impact on IndustryPreventing speed-related crashes could reduce costs and improve efficiency in the transportation industry.ObjectiveThis research examined the psychosocial and personality predictors of observed speeding among young drivers.MethodSurvey and driving data were collected from 42 newly-licensed teenage drivers during the first 18 months of licensure. Speeding (i.e., driving 10 mph over the speed limit; about 16 km/h) was assessed by comparing speed data collected with recording systems installed in participants' vehicles with posted speed limits.ResultsSpeeding was correlated with elevated g-force event rates (r = 0.335, pb0.05), increased over time, and predicted by day vs. night trips, higher sensation seeking, substance use, tolerance of deviance, susceptibility to peer pressure, and number of risky friends. Perceived risk was a significant mediator of the association between speeding and risky friends.ConclusionThe findings support the contention that social norms may influence teenage speeding behavior and this relationship may operate through perceived risk.     

Older women drivers: fatal crashes in good conditions

PROBLEM: By 2030, there will be approximately 70 million older people (65+) in the United States, more than twice their number in 2000. This increase also represents an increased percentage of older licensed drivers. Thus, it is important to understand the special circumstances of how they may be involved in traffic crashes. METHOD: This study used the Fatality Analysis Reporting System (FARS), which is a census of all fatal crashes occurring in the United States over the last two decades maintained by the National Highway Traffic Safety Administration (NHTSA), to study the special characteristics of fatal crashes involving females older than 70 years. RESULTS: The results indicate that senior women are overrepresented in crashes that occur under the "safest" conditions, on roads with low speed limits, in daylight, when traffic is low (not at rush hour), when the weather is good, and when the roads are dry.     

Using SHRP2 naturalistic driving data to examine driver speeding behavior

Problem: Speeding-related crashes continue to be a serious problem in the United States. According to the National Highway Traffic Safety Administration, 26% of all fatal crashes in 2017 had speeding as a contributing factor. Method: Vehicle speed data recorded during the Strategic Highway Research Program 2 (SHRP 2) Naturalistic Driving Study were analyzed to identify the frequency of speeding episodes. Up to 100 trips were sampled from 2,910 individual drivers aged 16–64. Vehicle speed data from individual trips were parsed into continuous speeding episodes (SEs) and Free-Flow Episodes (FFEs), which approximated opportunities to speed. Results & Discussion: Driving 10 mph above the posted speed limit (PSL) was common, and 99.8% of drivers had at least one occurrence SE within their trip sample, yielding an average of 2.75 SEs per trip (623,202 SEs in total). The analysis focused on a subset of higher-speed SEs in which the vehicle reached speeds of at least 15 mph above the PSL during the SE (71,113 SEs in total). Average maximum speeds for most higher-speed SEs ranged between 12 mph to 15 mph above the PSL, and most also lasted less than 2 min. Most drivers spent less than 5% of the FFE time speeding, and only a small number of drivers spent more than 10% of the time speeding. There was also a clear trend towards the younger group having higher overall percentages of SE time relative to FFE time. Practical Applications: The methods and measures developed in this study provide the foundation for future analyses to determine if there are different types of speeding that vary in terms of risky characteristics, and further, if certain drivers are more likely to engage in riskier speeding behavior. Identifying higher-risk speeders is an important step for developing countermeasures and strategies targeting drivers that are at greatest risk of speed-related crashes.     

Road characteristics and driver fatigue: a simulator study

Two experiments examined the influence of road characteristics on driver fatigue in a prolonged simulator drive. In experiment one, ten military truck drivers drove a mixed route, with straight, winding, and straight highway segments. In experiment two, 16 additional drivers drove either a straight, a winding, or a mixed route. Fatigue symptoms were assessed using performance, subjective, and psychophysiological measures (HRV). We hypothesized that drivers adopt different fatigue-coping strategies relative to the demands of the drive. Thus, on straight roads drivers are more likely to loosen their driving demands by either increasing their driving speed and/or not maintaining the lane position, as the road is tolerant to both strategies, whereas on winding roads, drivers are more likely to increase their speed but not their lane positioning. Our results confirm that decremental changes in driving performance varied among road types. In the straight road components, we found decrements in the quality of lane maintaining (experiment one) and steering quality (experiments one and two) and longitudinal speed (experiment two). In the winding road, we found that drivers increased their driving speed over time (experiments one and two).     

驾驶行为特性与人格特征关系研究

为了开展驾驶行为特性与人格特征关系的研究,选用26名被试人员,运用自主研 发的驾驶员综合能力测试系统,利用数理统计规律,研究被试者复杂反应、速度估计与 人格特征之间的关系。结果表明:在相同的试验环境下,所有被试者在伴有蜂鸣声时复 杂反应错误次数明显多于无蜂鸣声时;男女驾驶员在复杂反应时间方面表现出显著性差 异, 而在复杂反应错误次数方面未表现出明显差异;男女驾驶员在速度估计方面未表现 出显著性差异,但部分驾驶员表现出过高或过低估计速度的倾向;复杂反应指数和速度 估计指数与驾驶员的攻击性、独立性和敢为性之间存在着较强的正相关性,与社会向性 、稳定性之间存在着较强的负相关性;男性驾驶员表现出较强的攻击性、敢为性和独立 性,而女性驾驶员表现出较强的稳定性和社会向性。自主研发的系统能有效地分析了驾 驶行为特性与人格特征之间的内在关系,可以检测出潜在的事故倾向性大的驾驶员,有 利于减少交通事故的发生。     

Assessment of temporal stability in risk factors of crashes at horizontal curves on rural two-lane undivided highways

Introduction: Safety of horizontal curves on rural two-lane, two-way undivided roadways is not fully explored. This study investigates factors that impact injury severity of such crashes. Method: To achieve the aim of this paper, issues associated with police-reported crash data such as unobserved heterogeneity and temporal stability need to be accounted for. Hence, a mixed logit model was estimated, while heterogeneity in means and variances is investigated by considering four injury severity outcomes for drivers: severe injury, moderate injury, possible injury, and no injury. Crash data for the period between 2011 and 2016 for crashes that occurred in the state of Oregon was analyzed. Temporal stability in factors determining the injury severity was investigated by identifying three time periods through splitting crash data into 2011–2012, 2013–2014, and 2015–2016. Results: Despite some factors affecting injuries in all specified time periods, the values of the marginal effects showed relative differences. The estimation results revealed that some factors increased the risk of being involved in severe injury crashes, including head-on collisions, drunk drivers, failure to negotiate curves, older drivers, and exceeding the speed limits. Conclusions: The hypothesis that attributes of injury severity are temporally stable is rejected. For example, young drivers (30 years old and younger) and middle-aged drivers were found to be temporally instable over time. Practical applications: The findings could help transportation authorities and safety professionals to enhance the safety of horizontal curves through appropriate and effective countermeasures.     

Driver speed selection and crash risk: Insights from the naturalistic driving study

IntroductionThis study investigates how speed limits affect driver speed selection, as well as the related crash risk, while controlling for various confounding factors such as traffic volumes and roadway geometry. Data from a naturalistic driving study are used to examine how driver speed selection varies among freeways with different posted speed limits, as well as how the likelihood of crash/near-crash events change with respect to mean speed and standard deviation.MethodRegression models are estimated to assess three measures of interest: the average speed of vehicles during the time preceding crash/near-crash and baseline (i.e., normal) driving events; the variation in travel speeds leading up to each event as quantified by the standard deviation in speeds over this period; and the probability of a specific event resulting in a crash/near-crash based on speed selection and other factors.ResultsSpeeds were relatively stable across levels-of-service A and B, within a range of 1.5 mph on average. Speeds were marginally lower (3.3 mph) on freeways posted at 65 mph versus 70 mph. In comparison, speeds were approximately 10.2 to 13.4 mph lower on facilities posted at 55 mph or 60 mph. Speeds were shown to be 2.5 mph lower in rainy weather and 11 mph lower under snow or sleet.ConclusionsSignificant correlation was observed with respect to speed selection behavior among the same individuals. Mean speeds are shown to increase with speed limits. However, these increases are less pronounced at higher speed limits. Drivers tend to reduce their travel speeds in presence of junctions and work zones, under adverse weather conditions, and particularly under heavy congestion. Crash risk increased with the standard deviation in speed, as well as on vertical curves and ramp junctions, and among the youngest and oldest age groups of drivers.     

The effect of driver eye height on speed choice, lane-keeping, and car-following behavior: results of two driving simulator studies

OBJECTIVE: Two simulator studies were conducted that assessed the effect of driver eye height on speed choice, lane-keeping, and car-following behavior. The effect of eye height on the subjective variables of mental workload, frustration, and confidence was also investigated, as was the contribution of drivers' aggression. METHODS: A total of 43 participants drove a simulated route while seated at two different eye heights: one that represented the view of the road from a large SUV and one that represented the view of the road from a small sports car. Driving scenarios were comprised of both open road and car-following segments. Dependent variables included driver-selected speed, speed variability, lane position, following distance to a slower-moving lead vehicle, and the subjective variables of frustration, confidence, and mental workload. RESULTS: When viewing the road from a high eye height, drivers drove faster, with more variability, and were less able to maintain a consistent position within the lane than when viewing the road from a low eye height. Driver eye height did not influence following distance to a slower-moving lead vehicle. Driver aggression had no effect on any of the dependent variables except level of frustration. CONCLUSIONS: The two studies demonstrate that, when they are not able to reference a speedometer, drivers choose to drive faster when they view the road from an eye height that is representative of a large SUV compared to that of a small sports car. There is a need to educate drivers of SUVs and other tall vehicles of this perceptual phenomenon in order to prevent collisions that may occur in conditions where it is impossible for drivers to base their speed selection solely on posted speed limits, such as in inclement weather.     

Do recommended driving limits affect teen-reported traffic violations and crashes during the first 12 months of independent driving?

OBJECTIVES: Motor vehicle crashes are highly elevated among newly licensed teenage drivers. Limits on high-risk driving conditions by driver licensing policies and parents can protect novice teens from negative driving outcomes, while they experience and driving proficiency. The purpose of this research was to evaluate the effects of strict parent-imposed driving limits on driving outcomes during the first year of licensure. METHODS: A sample of 3,743 Connecticut teens was recruited and randomized to the Checkpoints Program or comparison condition. Assessments conducted at baseline, licensure, 3-, 6-, and 12-months postlicensure included parent-imposed driving limits, traffic violations, and crashes. Bivariate and multivariate analyses were conducted to assess the effects of strict parent limits on traffic violations and crashes during the first year of licensure. RESULTS: Thirty percent of teens reported at least one traffic violation and 40% reported at least one crash. More strict parent-imposed limits at licensure, 3-, 6-, and 12-months postlicensure, were associated with fewer violations and crashes in multivariate analyses. Notably, adherence to recommended night curfew was consistently associated with fewer violations and crashes. CONCLUSIONS: The findings indicate that strict parent-imposed limits may protect novice teen drivers from negative driving outcomes.     

Driving performance while using cell phones: an observational study

INTRODUCTION: Through spontaneous driving observations, this study sought to examine the impact of using a hands-free cell phone while driving on speed and safe gap keeping behaviors. The study also examined the association between the measure of disturbance created by using a cell phone and the driver's awareness of the disturbance. METHOD: Twenty-three male adults were observed while driving for an hour and a half each; drivers were unaware of being observed. During the session, each of the participants received a phone call, initiated by an associate of the observer. The experiment was divided into two periods during which the experimental parameters were monitored: 10 minutes during conversation on a cell phone and 10 minutes of non-conversation on a hands-free cell phone. After the experiment, the driver was questioned concerning the extent to which his/her driving was disturbed by the cell phone conversation. RESULTS: T-test for matched samples revealed that the gaps between the drivers' cars and those in front of them diminished when drivers were engaged in the cell phone conversations. Repeated measures ANOVA revealed that drivers that had short conversations did not change their speed, while drivers who were engaged in long (over 16 minutes) conversations drove faster. No effect of drivers' awareness toward cell phone-related disturbance on actual driving behavior monitored in the present study was found.