The impact of changes to the NSW graduated driver licensing system on subsequent crash and offense experience

Introduction: In mid-2007 the State of New South Wales (NSW) in Australia introduced modifications to the existing graduated driver licensing system, lengthening the mandatory number of supervised hours for learner drivers aged under 25 years from 50 to 120 and extending the minimum learner period from 6 to 12 months. Additional driving restrictions were also introduced for young drivers in the two provisional licensed periods, P1, P2. This paper aims to evaluate this change by comparing the crash and offense experiences of young learner drivers before and after it occurred. Method: From driver licensing files supplied by the NSW transport authority two cohorts of persons obtaining their initial learner's permits in the year prior to the changes and in the subsequent year were constructed with demographic data, dates of transition to the driving phases, dates of crashes, and dates and types of traffic offenses. Both cohorts comprised around 100,000 individuals. Crash rates per 100 years of person-time under observation post P1 with their standard errors were calculated. Using a survival-analytic approach the proportion of crashes of all types were graphed in three month periods post P1. Sexes were treated separately as were initial learner ages of 16, 17, 18–21, and 22–24 years. The distribution of traffic offense types during P1 and P2 phases were also compared. With such large numbers formal statistical testing was avoided. Results: No meaningful differences in the crash or offense experiences of the two cohorts in either sex or at any age were observed. Delaying progress to unsupervised driving has road safety benefits. Conclusions: At least in conditions similar to those in NSW, requiring more than 50 h of supervised driving seems to have few road safety benefits. Practical applications: Licensing authorities should be cautious in extending the mandated number of supervised driving hours beyond 50.     

Factors associated with driving under the influence of alcohol

Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.

Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).

Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.

Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy.     

Low-manpower checkpoints: can they provide effective DUI enforcement in small communities?

OBJECTIVE: Sobriety checkpoints can be effective in reducing alcohol-impaired driving. Checkpoints are underutilized, however, partially because police believe a large number of officers are required. This study evaluated the feasibility and impact of conducting small-scale checkpoints in rural communities. METHODS: Law enforcement agencies in two counties agreed to conduct weekly checkpoints for one year. Two nonadjacent counties did not undertake additional checkpoints. Evaluation included public-awareness surveys and roadside surveys (including blood alcohol concentration [BAC] measurements) of weekend nighttime drivers. RESULTS: Relative to drivers in the comparison counties, the proportion of drivers in the experimental counties with BACs >0.05% was 70% lower. Drivers surveyed at driver's license offices in the experimental counties after program implementation were more likely to report seeing or passing through a checkpoint and were more aware of publicity on driving under the influence (DUI) enforcement. CONCLUSIONS: Small rural communities can safely and effectively conduct low-staff sobriety checkpoints on a weekly basis. Such programs can be expected to result in large reductions in drivers operating at higher BACs.     

Fatal hit-and-run crashes: Factors associated with leaving the scene

Introduction: Hit-and-run crashes are a criminal offense that leave the victim without prompt medical care or the ability to receive financial compensation. Method: The purpose of the current study was to quantify the factors associated with the probability that a driver leaves the scene of a fatal crash, using multiple imputation to incorporate information from drivers who were never apprehended and thus whose characteristics were unknown. Results: The results of this study show that in addition to driver, vehicle, and environmental factors having significant impacts on the likelihood of a driver fleeing the scene, economic and demographic factors are important as well. Practical Applications: This analysis allows for a more holistic understanding of hit-and-run crashes and informs potential countermeasures and future research.     

Modelling the relationship of driver license and offense history with fatal and serious injury (FSI) crash involvement

Introduction: Previous research has indicated that increases in traffic offenses are linked to increased crash involvement rates, making reductions in offending an appropriate measure for evaluating road safety interventions in the short-term. However, the extent to which traffic offending predicts fatal and serious injury (FSI) crash involvement risk is not well established, prompting this new Victorian (Australia) study. Method: A preliminary cluster analysis was performed to describe the offense data and assess FSI crash involvement risk for each cluster. While controlling demographic and licensing variables, the key traffic offenses that predict future FSI crash involvement were then identified. The large sample size allowed the use of machine learning methods such as random forests, gradient boosting, and Least Absolute Shrinkage and Selection Operator (LASSO) regression. This was done for the ‘all driver’ sample and five sometimes overlapping groups of drivers; the young, the elderly, and those with a motorcycle license, a heavy vehicle license endorsement and/or a history of license bans. Results: With the exception of the group of drivers who had a history of bans, offense history significantly improved the accuracy of models predicting future FSI crash involvement using demographic and licensing data, suggesting that traffic offenses may be an important factor to consider when analyzing FSI crash involvement risk and the effects of road safety countermeasures. Conclusions: The results are helpful for identifying driver groups to target with further road safety countermeasures, and for showing that machine learning methods have an important role to play in research of this nature. Practical Application: This research indicates with whom road safety interventions should particularly be applied. Changes to driver demerit policies to better target offenses related to FSI crash involvement and repeat traffic offenders, who are at greater risk of FSI crash involvement, are recommended.     

Does longevity impact the severity of traffic crashes? A comparative study of young-older and old-older drivers

Introduction: This article analyzes the effect of driver’s age in crash severity with a particular focus on those over the age of 65. The greater frequency and longevity of older drivers around the world suggests the need to introduce a possible segmentation within this group at risk, thus eliminating the generic interval of 65 and over as applied today in road safety data and in the automobile insurance sector. Method: We investigate differences in the severity of traffic crashes among two subgroups of older drivers –young-older (65–75) and old-older (75+), and findings are compared with the age interval of drivers under 65. Here, we draw on data for 2016 provided by Spanish Traffic Authority. Parametric and semi-parametric regression models are applied. Results: We identified the factors related to the crash, vehicle, and driver that have a significant impact on the probability of the crash being slight, serious, or fatal for the different age groups. Conclusions: We found that crash severity and the expected costs of crashes significantly increase when the driver is over the age of 75. Practical Applications: Our results have obvious implications for regulators responsible for road safety policies – most specifically as they consider there should be specific driver licensing requirements and driving training for elderly – and for the automobile insurance industry, which to date has not examined the impact that the longevity of drivers is likely to have on their balance sheets.     

Alcohol-impaired motorcyclists versus car drivers: A comparison of crash involvement and legal consequence from adjudication data

Introduction: Driving under the influence (DUI) increases the probability of motor-vehicle collisions, especially for motorcycles with less protections. This study aimed to identify commonalities and differences between criminally DUI offenses (i.e., with a blood alcohol concentration (BAC) of 80 mg/dL or higher) committed by motorcyclists and car drivers. Methods: A total of 10,457 motorcycle DUIs and 8,402 car DUIs were compared using a series of logistic regression models, using data extracted from the documents of adjudication decisions by the courts of Jiangsu, China. Results: The results revealed that offenders from the high-BAC group (i.e., 200 mg/dL or higher) accounted for more than 20% of the total DUI offenses, and were more likely to be involved in a crash and punished with a longer detention. Motorcyclists had a higher likelihood of crash involvement, and were also more likely to be responsible for single-vehicle crashes associated with higher odds of injury sustained, compared to alcohol-impaired car drivers. In the verdict, motorcycle offenders were more likely to receive a less severe penalty. Conclusions: Interventions are clearly required to focus on reducing in the high-BAC group of offenders. For alcohol-impaired motorcyclists, their risks of crash and injury against BAC climb more steeply than the risks for car drivers. The factors including frequent occurrences, uncertainty of detection, and short-term sentences may weaken the deterrence effect of the criminalization of motorcycle DUI. Practical Applications: The traffic-related adjudication data support traffic safety analysis. Strategies such as combating motorcycle violations (e.g., unlicensed operators or driving unsafe vehicles), undertaking education and awareness campaigns, are expected for DUI prevention.     

Drinking and driving and perceptions of arrest risk among California drivers: Relationships with DUI arrests in their city of residence

Objective: Addressing drinking and driving remains a challenge in the United States. The present study aims to provide feedback on driving under the influence (DUI) in California by assessing whether drinking and driving behavior is associated with the DUI arrest rates in the city in which the driver lives; whether this is due to perceptions that one can get arrested for this behavior; and whether this differed by those drivers who would be most affected by deterrence efforts (those most likely to drink outside the home).

Methods: This study consisted of a 2012 roadside survey of 1,147 weekend nighttime drivers in California. City DUI arrest rates for 2009–2011 were used as an indicator of local enforcement efforts. Population average logistic modeling was conducted modeling the odds of perceived high arrest likelihood for DUI and drinking and driving behavior within the past year.

Results: As the DUI arrest rates for the city in which the driver lives increased, perceived high risk of DUI arrest increased. There was no significant relationship between either city DUI arrest rates or perceived high risk of DUI arrest with self-reported drinking and driving behavior in the full sample. Among a much smaller sample of those most likely to drink outside the home, self-reported drinking and driving behavior was negatively associated with DUI arrests rates in their city of residence but this was not mediated by perceptions.

Conclusion: The results of the present study suggest that perceptions are correlated with one aspect of DUI efforts in one's community. Those who were more likely to drink outside the home could be behaviorally influenced by these efforts.     

The effect of extending graduated driver licensing to older novice drivers in Indiana

Introduction: Graduated driver licensing (GDL) systems have been shown to reduce rates of crashes, injuries, and deaths of young novice drivers. However, approximately one in three new drivers in the United States obtain their first driver’s license at age 18 or older, and thus are exempt from most or all provisions of GDL in most states. Method: In July 2015, the state of Indiana updated its GDL program, extending its restrictions on driving at night and on carrying passengers during the first 6 months of independent driving, previously only applicable to new drivers younger than 18, to all newly-licensed drivers younger than 21 years of age. The current study examined monthly rates of crashes per licensed driver under the affected conditions (driving at night and driving with passengers) among Indiana drivers first licensed at ages 18, 19, and 20 under the updated GDL system compared with drivers licensed at the same ages under the previous GDL system. We used Poisson regression to estimate the association between the GDL system and crash rates, while attempting to control for other factors that might have also influenced crash rates. We used linear regression to estimate the association between the GDL system and the proportion of all crashes that occurred under conditions restricted by the GDL program. Results: Results showed, contrary to expectations, that rates of crashes during restricted nighttime hours and with passengers were higher among drivers licensed under the updated GDL system. This mirrored a statewide increase in crash rates among drivers of all ages over the study period and likely reflected increased overall driving exposure. The proportions of all crashes that were at night or with passengers did not change. Practical Applications: More research is needed to understand how older novice drivers respond when GDL systems originally designed for younger novice drivers are applied to them.     

Driving under the influence of alcohol and the effects of alcohol prohibition—Case study in Serbia

Objective: The purpose of this study is to provide an overview of the prevalence of driving under the influence of alcohol (DUI) according to day of the week, specific roads (urban/rural), daytime or nighttime, and vehicle category. In addition, this study examines how the prohibition of selling alcoholic drinks in shops and supermarkets (not in restaurants) after 10 p.m. has affected the prevalence of DUI.

Method: Breath alcohol concentration (BrAC) was collected from all drivers through police checkpoints at 54 locations in Serbia. In this study, 17,945 drivers were tested in urban areas and 19,507 in rural areas. The relationship between DUI during the prohibition on alcohol sales in Belgrade and other large cities in Serbia was determined using logistic regression.

Results: On average, every 100th driver in traffic in Serbia was DUI (0.99%). This study shows that the 0 blood alcohol concentration (BAC) limit for motorcyclists does not have an influence on DUI. Moreover, motorcyclists represent the category with the highest share of DUI, with a statistically significantly larger difference compared to drivers of other vehicle categories. These results may be a consequence of the fact that a large number of drivers drive both motorcycles and other vehicle categories (cars or mopeds), so the different BAC limits for nonprofessional drivers may create confusion about the legal BAC limit.

Conclusions: This study suggests that the required legal BAC limit for nonprofessional drivers should be the same. The prohibition of selling alcoholic drinks in Belgrade after 10 p.m. does not decrease the prevalence of DUI.     

Socio-demographic and experience factors affecting drivers’ runoff risk along horizontal curves of two-lane rural highway

Introduction: An improper driving strategy is one of the causative factors for a high probability of runoff and overturning crashes along the horizontal curves of two-lane highways. The socio-demographic and driving experience factors of a driver do influence driving strategy. Hence, this paper explored the effect of these factors on the driver’s runoff risk along the horizontal curves. Method: The driving performance data of 48 drivers along 52 horizontal curves was recorded in a fixed-base driving simulator. The driving performance index was estimated from the weighted lateral acceleration profile of each driver along a horizontal curve. It was clustered and compared with the actual runoff events observed during the experiment. It yielded high, moderate, and low-risk clusters. Using cross-tabulation, each risk cluster was compared with the socio-demographic and experience factors. Further, generalized mixed logistic regression models were developed to predict the high-risk and high to moderate risk events. Results: The age and experience of drivers are the influencing factors for runoff crash. The high-risk event percentage for mid-age drivers decreases with an increase in driving experience. For younger drivers, it increases initially but decreases afterwards. The generalized mixed logistic regression models identified young drivers with mid and high experience and mid-age drivers with low-experience as the high-risk groups. Conclusions: The proposed index parameter is effective in identifying the risk associated with horizontal curves. Driver training program focusing on the horizontal curve negotiation skills and graduated driver licensing could help the high-risk groups. Practical applications: The proposed index parameter can evaluate driving behavior at the horizontal curves. Driving behavior of high-risk groups could be considered in highway geometric design. Motor-vehicle agencies, advanced driver assistance systems manufacturers, and insurance agencies can use proposed index parameter to identify the high-risk drivers for their perusal.     

Ability to monitor driving under the influence of marijuana among non-fatal motor-vehicle crashes: An evaluation of the Colorado electronic accident reporting system

Introduction: As more states legalize medical/recreational marijuana use, it is important to determine if state motor-vehicle surveillance systems can effectively monitor and track driving under the influence (DUI) of marijuana. This study assessed Colorado's Department of Revenue motor-vehicle crash data system, Electronic Accident Reporting System (EARS), to monitor non-fatal crashes involving driving under the influence (DUI) of marijuana. Methods: Centers for Disease Control and Prevention guidelines on surveillance system evaluation were used to assess EARS' usefulness, flexibility, timeliness, simplicity, acceptability, and data quality. We assessed system components, interviewed key stakeholders, and analyzed completeness of Colorado statewide 2014 motor-vehicle crash records. Results: EARS contains timely and complete data, but does not effectively monitor non-fatal motor-vehicle crashes related to DUI of marijuana. Information on biological sample type collected from drivers and toxicology results were not recorded into EARS; however, EARS is a flexible system that can incorporate new data without increasing surveillance system burden. Conclusions: States, including Colorado, could consider standardization of drug testing and mandatory reporting policies for drivers involved in motor-vehicle crashes and proactively address the narrow window of time for sample collection to improve DUI of marijuana surveillance. Practical applications: The evaluation of state motor-vehicle crash systems' ability to capture crashes involving drug impaired driving (DUID) is a critical first step for identifying frequency and risk factors for crashes related to DUID.     

Near crash characteristics among risky drivers using the SHRP2 naturalistic driving study

Problem: Previous research have focused extensively on crashes, however near crashes provide additional data on driver errors leading to critical events as well as evasive maneuvers employed to avoid crashes. The Strategic Highway Research Program 2 (SHRP2) Naturalistic Driving Study contains extensive data on real world driving and offers a reliable methodology to study near crashes. The current study utilized the SHRP2 database to compare the rate and characteristics associated with near crashes among risky drivers. Methods: A subset from the SHRP2 database consisting of 4,818 near crashes for teen (16–19 yrs), young adult (20–24 yrs), adult (35–54 yrs), and older (70+ yrs) drivers was used. Near crashes were classified into seven incident types: rear-end, road departure, intersection, head-on, side-swipe, pedestrian/cyclist, and animal. Near crash rates, incident type, secondary tasks, and evasive maneuvers were compared across age groups. For rear-end near crashes, near crash severity, max deceleration, and time-to-collision at braking were compared across age. Results: Near crash rates significantly decreased with increasing age (p < 0.05). Young drivers exhibited greater rear-end (p < 0.05) and road departure (p < 0.05) near crashes compared to adult and older drivers. Intersection near crashes were the most common incident type among older drivers. Evasive maneuver type did not significantly vary across age groups. Near crashes exhibited a longer time-to-collision at braking (p < 0.01) compared to crashes. Summary: These data demonstrate increased total near crash rates among young drivers relative to adult and older drivers. Prevalence of specific near crash types also differed across age groups. Timely execution of evasive maneuvers was a distinguishing factor between crashes or near crashes. Practical Applications: These data can be used to develop more targeted driver training programs and help OEMs optimize ADAS to address the most common errors exhibited by risky drivers.     

Implementation of Washington State's zero tolerance law: patterns of arrests, dispositions, and recidivism

OBJECTIVES: Zero tolerance (ZT) laws have been effective in reducing alcohol-related crashes among underage drivers. However, enforcement in some states has not been rigorous, and ZT offenses may not be viewed as serious offenses. On July 1, 1994, the state of Washington implemented a ZT law that allowed police to request a test for alcohol on suspicion of either a ZT or driving-under-the-influence (DUI) offense. The present study examined effects of the ZT law on arrests and case dispositions among underage offenders as a function of blood alcohol concentration (BAC) and post-law patterns of recidivism. METHODS: Times-series analyses examined the effects of the ZT law on trends in arrests of underage drivers between 1991 and 1999. Based on arrest records matched with driver's license records, the effects of the law on dispositions of alcohol-related offenses among underage drivers were examined, and rates of recidivism among underage offenders were examined for the period following the ZT law. RESULTS: There was a substantial increase in arrests of underage drivers beginning immediately after implementation of the ZT law, especially among drivers with low BACs. The types of court or administrative dispositions received by underage offenders changed markedly after the ZT law was implemented. Underage offenders with lower BACs became far more likely to receive alcohol-related convictions and/or license suspensions. However, the percentage of underage offenders with higher BACs receiving DUI convictions declined as some of these offenders received the lesser ZT disposition. After the ZT law, underage offenders with BACs of 0.10 g/dL or higher were more likely to recidivate than those with lower BACs, but appreciable proportions of drivers were re-arrested for another alcohol offense, whatever the BAC and however they were penalized. CONCLUSIONS: Implementation of Washington's law indicates that a ZT law can increase the likelihood that an underage person will be sanctioned for drinking and driving. However, recidivism remains an issue as more than one in four underage drivers arrested with low BACs subsequently were re-arrested.     

Association between driver and child passenger restraint: Analysis of community-based observational survey data from 2005 to 2019

Introduction: Crash data suggest an association between driver seatbelt use and child passenger restraint. However, community-based restraint use is largely unknown. We examined the association between driver seatbelt use and child restraint using data from a state-wide observational study. Methods: Data from Iowa Child Passenger Restraint Survey, a representative state-wide survey of adult seat belt use and child passenger safety, were analyzed. A total of 44,996 child passengers age 0–17 years were observed from 2005 to 2019. Information about driver seatbelt use and child restraint was directly observed by surveyors and driver age was reported. Logistic regression was used to examine the association between driver seatbelt use and child restraint adjusting for vehicle type, community size, child seating position, child passenger age, and year. Results: Over the 15-year study period, 4,114 (9.1%) drivers were unbelted, 3,692 (8.2%) children were completely unrestrained, and another 1,601 (3.6%) children were improperly restrained (analyzed as unrestrained). About half of unbelted drivers had their child passengers unrestrained (51.8%), while nearly all belted drivers had their child passengers properly restrained (92.3%). Compared with belted drivers, unbelted drivers had an 11-fold increased odds of driving an unrestrained child passenger (OR = 11.19, 95%CI = 10.36, 12.09). The association between driver seatbelt use and child restraint was much stronger among teenage drivers. Unbelted teenage drivers were 33-fold more likely (OR = 33.34, 95%CI = 21.11, 52.64) to have an unrestrained child passenger. Conclusion: These data suggest that efforts to increase driver seatbelt use may also have the added benefit of increasing child restraint use. Practical applications: Enforcement of child passenger laws and existing education programs for new drivers could be leveraged to increase awareness of the benefits of seatbelt use for both drivers themselves and their occupants. Interventions aimed at rural parents could emphasize the importance of child safety restraints.     

Age-related differences in effects of non-driving related tasks on takeover performance in automated driving

Introduction: During SAE level 3 automated driving, the driver’s role changes from active driver to fallback-ready driver. Drowsiness is one of the factors that may degrade driver’s takeover performance. This study aimed to investigate effects of non-driving related tasks (NDRTs) to counter driver’s drowsiness with a Level 3 system activated and to improve successive takeover performance in a critical situation. A special focus was placed on age-related differences in the effects. Method: Participants of three age groups (younger, middle-aged, older) drove the Level 3 system implemented in a high-fidelity motion-based driving simulator for about 30 min under three experiment conditions: without NDRT, while watching a video clip, and while switching between watching a video clip and playing a game. The Karolinska Sleepiness Scale and eyeblink duration measured driver drowsiness. At the end of the drive, the drivers had to take over control of the vehicle and manually change the lane to avoid a collision. Reaction time and steering angle variability were measured to evaluate the two aspects of driving performance. Results: For younger drivers, both single and multiple NDRT engagements countered the development of driver drowsiness during automated driving, and their takeover performance was equivalent to or better than their performance without NDRT engagement. For older drivers, NDRT engagement did not affect the development of drowsiness but degraded takeover performance especially under the multiple NDRT engagement condition. The results for middle-aged drivers fell at an intermediate level between those for younger and older drivers. Practical Applications: The present findings do not support general recommendations of NDRT engagement to counter drowsiness during automated driving. This study is especially relevant to the automotive industry’s search for options that will ensure the safest interfaces between human drivers and automation systems.     

Introducing a multi-variate classification method: Risky driving acceptance among different heterogeneous driver sub-cultures

Introduction: Heterogeneous driving populations with many different origins are likely to have various sub-cultures that comprise of drivers with shared driver characteristics, most likely with dissimilar traffic safety cultures. An innovative methodology in traffic safety research is introduced which is beneficial for large datasets with multiple variables, making it useful for the multi-variate classification of drivers, driving attitudes and/or (risky) driving behaviours. Method: With the application of multidimensional scaling analysis (MDS), this study explores traffic safety culture in the State of Qatar using a questionnaire and investigates the similarity patterns between the questionnaire items, aiming to classify attitudes towards risky driving behaviours into themes. MDS is subsequently applied to classify drivers within a heterogeneous driving sample into sub-cultures with shared driver characteristics and different risky driving attitudes. Results: Results show that acceptance of speeding is highest among the young Arabic students and acceptance of distraction and drivers’ negligence such as phone use and not wearing a seatbelt is highest among male Arab drivers. Acceptance of extreme risk-taking like intoxicated driving and red-light running is highest among South-Asian business drivers. Conclusion: It is important and practical to understand risky behavioural habits among sub-cultures and thereby focussing on groups of drivers instead of individuals, because groups are easier to approach and drivers within sub-cultures are found to influence each other. By indicating which groups of drivers are most likely to perform specific risky driving themes, it is possible to target these groups and effectively emphasise certain subsets of risky driving behaviours during training or traffic safety education. Practical Applications: This study provides guidance for the improvement of driver education and targeted traffic safety awareness campaigns, intending to make changes to attitudes and habits within specific driver sub-cultures with the aim to improve traffic safety on the longer term.     

Safer than the average human driver (who is less safe than me)? Examining a popular safety benchmark for self-driving cars

Although the level of safety required before drivers will accept self-driving cars is not clear, the criterion of being safer than a human driver has become pervasive in the discourse on vehicle automation. This criterion actually means “safer than the average human driver,” because it is necessarily defined with respect to population-level data. At the level of individual risk assessment, a body of research has shown that most drivers perceive themselves to be safer than the average driver (the better-than-average effect). Method: Using an online sample, this study examined U.S. drivers’ ratings of their own ability to drive safely and their desired level of safety for self-driving vehicles. Results: This study replicated the better-than average effect and showed that most drivers stated a desire for self-driving cars that are safer than their own perceived ability to drive safely before they would: (1) feel reasonably safe riding in a self-driving vehicle; (2) buy a self-driving vehicle, all other things (cost, etc.) being equal; and (3) allow self-driving vehicles on public roads. Conclusions: Since most drivers believe they are better than average drivers, the benchmark of achieving automation that is safer than a human driver (on average) may not represent acceptably safe performance of self-driving cars for most drivers. Practical applications: If perceived level of safety is an important contributor to acceptance of self-driving vehicles, the popular “safer than a human driver” benchmark may not be adequate for widespread acceptance.     

Validation of not-at-fault driver representativeness assumption for quasi-induced exposure using U.S. national traffic databases

Introduction:The quasi-induced exposure (QIE) method has been widely implemented into traffic safety research. One of the key assumptions of QIE method is that not-at-fault drivers represent the driving population at the time of a crash. Recent studies have validated the QIE representative assumption using not-at-fault drivers from three-or-more vehicle crashes (excluding the first not-at-fault drivers; D3_other) as the reference group in single state crash databases. However, it is unclear if the QIE representativeness assumption is valid on a national scale and is a representative sample of driving population in the United States. The aims of this study were to assess the QIE representativeness assumption on a national scale and to evaluate if D3_other could serve as a representative sample of the U.S. driving population. Method: Using the Fatality Analysis Reporting System (FARS) and the National Occupant Protection Use Survey (NOPUS), distributions of driver gender, age, vehicle type, time, and roadway type among the not-at-fault drivers in clean two-vehicle crashes, the first not-at-fault drivers in three-or-more-vehicle crashes, and the remaining not-at-fault drivers in three-or-more vehicle crashes were compared to the driver population observed in NOPUS. Results: The results showed that with respect to driver gender, vehicle type, time, and roadway type, drivers among D3_other did not show statistical significant difference from NOPUS observations. The age distribution of D3_other driver was not practically different to NOPUS observations. Conclusions: Overall, we conclude that D3_other drivers in FARS represents the driving population at the time of the crash. Practical applications: Our study provides a solid foundation for future studies to utilize D3_other as the reference group to validate the QIE representativeness assumption and has potential to increase the generalizability of future FARS studies.