Analysis of effects of driver’s evasive action time on rear-end collision risk using a driving simulator

Introduction: Driver’s evasive action is closely associated with collision risk in a critical traffic event. To quantify collision risk, surrogate safety measures (SSMs) have been estimated using vehicle trajectories. However, vehicle trajectories cannot clearly capture presence and time of driver’s evasive action. Thus, this study determines the driver’s evasive action based on his/her use of accelerator and brake pedals, and analyzes the effects of the driver’s evasive action time (i.e., duration of evasive action) on rear-end collision risk. Method: Fifty drivers’ car-following behavior on a freeway was observed using a driving simulator. An SSM called “Deceleration Rate to Avoid Crash (DRAC)” and the evasive action time were determined for each driver using the data from the driving simulator. Each driver tested two traffic scenarios – Cars and Trucks scenarios where conflicting vehicles were cars and trucks, respectively. The factors related to DRAC were identified and their effects on DRAC were analyzed using the Generalized Linear Models and random effects models. Results: DRAC decreased with the evasive action time and DRAC was closely related to drivers’ gender and driving experience at the road sections where evasive action to avoid collision was required. DRAC was also significantly different between Cars and Trucks scenarios. The effect of the evasive action time on DRAC varied among different drivers, particularly in the Trucks scenario. Conclusions: Longer evasive action time can significantly reduce crash risk. Driver characteristics are more closely related to effective evasive action in complex driving conditions. Practical Applications: Based on the findings of this study, driver warning information can be developed to alert drivers to take specific evasive action that reduces collision risk in a critical traffic event. The information is likely to reduce the variability of the driver’s evasive action and the speed variations among different drivers.     

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.     

Assessing driver behavior using shrp2 adverse weather data

IntroductionThis study explored how drivers adapt to inclement weather in terms of driving speed, situational awareness, and visibility as road surface conditions change from dry to slippery and visibility decreases. The proposed work mined existing data from the SHRP 2 NDS for drivers who were involved in weather-related crash and near-crash events. Baseline events were also mined to create related metadata necessary for behavioral comparisons. Methods: Researchers attempted, to the greatest extent possible, to match non-adverse-weather driving scenarios that are similar to the crash and near-crash event for each driver. The ideal match scenario would be at a day prior to the crash during non-adverse weather conditions having the same driver, at the same time of day, with the same traffic level on the same road on which the crash or near-crash occurred. Once the matched scenarios have been identified, a detailed analysis will be performed to determine how a driver’s behavior changed from normal driving to inclement-weather driving. Results: Data collected indicated that, irrespective of site location (i.e., state), most crashes and near-crashes occurred in rain, with only about 12% occurring in snowy conditions. Also, the number of near-crashes was almost double the number of crashes showing that many drivers were able to avoid a crash by executing an evasive maneuver such as braking or steering. Conclusions: Most types of near crashes were rear-end and sideswipe avoidance epochs, as the drivers may have had a difficult time merging or trying to change lanes due to low visibility or traffic. Hard braking combined with swerving were the most commonly used evasive maneuvers, occurring when drivers did not adjust their speeds accordingly for specific situations. Practical applications: Results from this study are expected to be utilized to educate and guide drivers toward more confident and strategic driving behavior in adverse weather.     

Traffic climate and driver behaviors: The moderating role of driving skills in Turkey and China

Introduction: While road traffic accidents and fatalities are a worldwide problem, the rates of road traffic accidents and fatalities show differences among countries. Similarly, driver behaviors, traffic climate, and their relationships also show differences among countries. The aim of the current study is to investigate the moderating effect of driving skills on the relationship between traffic climate and driver behaviors by country. (Turkey and China). Method: There were 294 Turkish drivers and 292 Chinese drivers, and they completed the Traffic Climate Scale, the Driving Skills Inventory, and the Driver Behavior Questionnaire. The moderated moderation analyses were conducted with Hayes PROCESS tool on SPSS. Results: The results showed that safety skills moderated the relationship between internal requirements and violations both in Turkey and China. Safety skills also moderated the relationship between internal requirements and errors only in China and the relationship between functionality and violations in Turkey. Perceptual-motor skills moderated the relationships between external affective demands and errors, and also the relationship between internal requirements and positive driver behaviors in Turkey. It can be inferred that driving skills has different influences on traffic climate-driver behaviors relationship in different cultures and there might be cultural differences in the evaluation of drivers’ own driving skills. Practical Applications: Among driving skills, safety skills have a more critical role to increase road safety by decreasing number of violations. Interventions to increase safety skills of drivers might be promising for road safety.     

Using naturalistic driving study data to investigate the impact of driver distraction on driver's brake reaction time in freeway rear-end events in car-following situation

IntroductionThe rear-end crash is one of the most common freeway crash types, and driver distraction is often cited as a leading cause of rear-end crashes. Previous research indicates that driver distraction could have negative effects on driving performance, but the specific association between driver distraction and crash risk is still not fully revealed. This study sought to understand the mechanism by which driver distraction, defined as secondary task distraction, could influence crash risk, as indicated by a driver's reaction time, in freeway car-following situations.MethodA statistical analysis, exploring the causal model structure regarding drivers’ distraction impacts on reaction times, was conducted. Distraction duration, distraction scenario, and secondary task type were chosen as distraction-related factors. Besides, exogenous factors including weather, visual obstruction, lighting condition, traffic density, and intersection presence and endogenous factors including driver age and gender were considered.ResultsThere was an association between driver distraction and reaction time in the sample freeway rear-end events from SHRP 2 NDS database. Distraction duration, the distracted status when a leader braked, and secondary task type were related to reaction time, while all other factors showed no significant effect on reaction time.ConclusionsThe analysis showed that driver distraction duration is the primary direct cause of the increase in reaction time, with other factors having indirect effects mediated by distraction duration. Longer distraction duration, the distracted status when a leader braked, and engaging in auditory-visual-manual secondary task tended to result in longer reaction times.Practical applicationsGiven drivers will be distracted occasionally, countermeasures which shorten distraction duration or avoid distraction presence while a leader vehicle brakes are worth considering. This study helps better understand the mechanism of freeway rear-end events in car-following situations, and provides a methodology that can be adopted to study the association between driver behavior and driving features.     

The role of off-path glances: A quantitative analysis of rear-end conflicts involving Chinese professional truck drivers as the striking partners

Introduction: Rear-end crashes are one of the most frequent crash types in China, leading to significant economic and societal losses. The development of active safety systems – such as Automatic Emergency Braking System (AEBS) – could avoid or mitigate the consequences of these crashes in Chinese traffic situations. However, a clear understanding of the crash causation mechanisms is necessary for the design of these systems. Method: Manually coded variables were extracted from a naturalistic driving study conducted with commercial vehicles in Shanghai. Quantitative analyses of rear-end crashes and near crashes (CNC) were conducted to assess the prevalence, duration, and location of drivers’ off-path glances, the influence of lead vehicle brake lights on drivers’ last off-path glance, and driver brake onset, and the influence of off-path glances and kinematic criticality on drivers’ response to conflicts. Results: The results indicate that the Chinese truck drivers in our study rarely engage in distracting activities involving a phone or other handheld objects while driving. Instead, they direct their off-path glances mainly toward the mirrors, and the duration of off-path glances leading to critical situations are shorter compared to earlier analyses performed in Western countries. The drivers also often keep small margins. Conclusions: Overall, the combination of short time headway with off-path glances directed toward the mirror originates visual mismatches which, associated to a rapid change in the kinematic situation, cause the occurrence of rear-end CNC. When drivers look back toward the road after an off-path glance, a fast response seems to be triggered by lower values of looming compared to previous studies, possibly because of the short time headways. Practical Application: The results have practical implications for the development of driver models, for the design of active safety systems and automated driving, and for the design of campaigns promoting safe driving.     

How do drivers avoid collisions? A driving simulator-based study

Introduction: Drivers' collision avoidance performance in an impending collision situation plays a decisive role for safety outcomes. This study explored drivers' collision avoidance performances in three typical collision scenarios that were right-angle collision, head-on collision, and collision with pedestrian. Method: A high-fidelity driving simulator was used to design the scenarios and conduct the experiment. 45 participants took part in the simulator experiment. Drivers' longitudinal/lateral collision avoidance performances and collision result were recorded. Results: Experimental results showed that brake only was the most common response among the three collision scenarios, followed by brake combining swerve in head-on and pedestrian collision scenarios. In right-angle collision scenario with TTC (time to collision) largest among three scenarios, no driver swerved, and meanwhile drivers who showed slow brake reaction tended to compensate the collision risk by taking a larger maximum deceleration rate within a shorter time. Swerve-toward-conflict was a prevalent phenomenon in head-on and pedestrian collision scenarios and significantly associated with collision risk. Drivers that swerved toward the conflict object had a shorter swerve reaction time than drivers that swerved away from conflict. Conclusions: Long brake reaction time and wrong swerve direction were the main factors leading to a high collision likelihood. The swerve-toward-conflict maneuver caused a delay in brake action and degraded subsequent braking performances. The prevalent phenomenon indicated that drivers tended to use an intuitive (heuristic) way to make decisions in critical traffic situations. Practical applications: The study generated a better understanding of collision development and shed lights on the design of future advanced collision avoidance systems for semi-automated vehicles. Manufactures should also engage more efforts in developing active steering assistance systems to assist drivers in collision avoidance.     

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.     

Brazilian adaptation of the driving anger expression inventory: testing its psychometrics properties and links between anger behavior,risky behavior,sensation seeking,and hostility in a sample of Brazilian undergraduate students

Introduction: In Brazil, driver aggressiveness in road traffic is a critical issue and could be an important contributing factor to the high number of traffic accidents. Because no instruments are available in Portuguese to register driving aggressiveness or driving anger in Brazil, we adapted English instruments into the Brazilian context. The aims of this study were to provide a Brazilian adaptation of the Driving Anger Expression Inventory (DAX) and to try to validate it by testing its psychometric properties and investigating its relationships with risky driving behaviors (DBQ), road accidents, driving sensation seeking, and hostility. Method: The Brazilian adaptations of the DAX, DBQ, the Driving Sensation Seeking Scale (DSSS) and the hostility Scale were administered to a sample of 512 undergraduate students (with a mean age of 23.7 years, 52.1% men). Results: Confirmatory factor analysis of the Brazilian DAX (DAX-BR) items yielded a four-factor solution with 43 items, which obtained the best goodness-of-fit to the data. Cronbach’s alpha for the DAX-BR factors ranged from 0.69 to 0.88. Other results on validity were a positive correlation (range 0.39–0.59) between the factors of the DAX-BR, DSSS, and DBQ. Conclusion: DAX-BR as the same structure as the original and is a reliable instrument for use with young drivers. Other studies should be conducted to further validate the DAX-BR in different types of populations such as older and more experienced drivers, professional drivers, and traffic regulation offenders whose driver's license has been taken away. Practical applications: This Brazilian version can be recommended for the assessment of driving anger expression in Brazil among young drivers in view of helping them driver more safely, and in particular to reduce traffic violations.     

Assessing the impacts of signal coordination on the crash risks of various driving cohorts

Introduction: Signal coordination has been wildly implemented on urban arterials to improve traffic efficiency. The impacts of signal coordination on traffic safety, however, are largely overlooked, particularly on crash propensities of driver–vehicle cohorts, which will vary due to changing traffic flow patterns. Method: The paper aims to compare crash risks of various driving cohorts (measured by relative crash involvement ratio) on arterials with and without signal coordination with quasi-induced exposure technique, which has been well developed in estimating crash risks for driver–vehicle characteristics (i.e., driver age, gender, and vehicle type). Michigan traffic crash data (2000–2014) are retrieved for the case study. Results: The results indicate that: (a) when signal coordination is implemented, young, male drivers, and pickups are associated with more crash responsibilities; (b) crash propensities vary for different disaggregated situations, e.g., young drivers may experience the rapid increase in crash risks during the peak hours; and (c) more hazardous actions (e.g., failing to stop in assured clear distance) are witnessed for the high-risk driving cohorts on the coordinated arterials than non-coordinated ones. Conclusions and practical applications: The findings highlight the importance of safety impact analysis of signal coordination, and serve to guide the potential improvements of safety operation and management of signal coordinated arterials.     

Cycle Aware: Piloting a module for novice drivers

Introduction: In low-cycling countries, motor-vehicle traffic and driver behavior are well known barriers to the uptake of bicycles, particularly for utility cycling. Lack of separation between cyclists and faster-moving traffic is one key issue, while attitudes of drivers toward and/or harassment of cyclists is another. Cyclist-related driver education has been recommended as a means to improve driver-cyclist interactions. Methods: The driver licensing process provides an opportunity for such education. The Cycle Aware module was developed to test and enhance novice drivers’ knowledge of interacting safely with cyclists. It was piloted across three Australian jurisdictions targeting both novice and experienced drivers. Participants were asked to complete the Cycle Aware module and an accompanying survey. A total of 134 novice and 97 experienced drivers completed the survey with 42 novice and 50 experienced drivers going on to complete the module. Results: Both groups of drivers scored equally well in the module but the very youngest and very oldest participants were more likely to have some incorrect responses. We did not find any relationship between correct module scores and attitudes toward cyclists. Survey results showed both novice and experienced drivers had somewhat positive attitudes toward cyclists. The two cohorts differed on several attitude questions. Sixty percent (60%) of novices compared to 30% of experienced drivers reported feeling concerned when sharing the road with cyclists, and novices were less likely to agree that cyclists had a right to use the roads. Conclusions and practical applications: The analysis suggests novices need to be better equipped to share roads confidently with cyclists and to recognize cyclists as legitimate traffic participants.     

Comparative judgements of crash risk and driving ability for speeding behaviours

Introduction: Preliminary research has indicated that numerous drivers perceive their risk of traffic crash to be less than other drivers, while perceiving their driving ability to be better. This phenomenon is referred to as ‘comparative optimism’ (CO) and may prove to inhibit the safe adoption of driving behaviors and/or dilute perceptions of negative outcomes. The objective of this study was to investigate comparative judgments regarding crash risk and driving ability, and how these judgments relate to self-reported speeding. Method: There were 760 Queensland motorists comprised of 51.6% males and 48.2% females, aged 16–85 (M = 39.60). Participants completed either a paper or online version of a survey. Judgments of crash risk and driving ability were compared to two referents: the average same-age, same-sex driver, and the average same-age, same-sex V8 supercar champion. Results: Drivers displayed greater optimism when comparing their crash risk and driving ability to the average same-age, same- sex driver (respectively, 72%, 72.4%), than when comparing to a V8 supercar champion (respectively, 60%, 32.9%). When comparing judgements of crash risk and driving ability to a similar driver, it appears that participants in the present study are just about as optimistic about their risk of crash (i.e. 72%) as they are optimistic about their driving ability (i.e. 74.2%).     

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.     

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.     

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.     

Impact of medical fitness to drive policies in preventing property damage,injury, and death from motor vehicle collisions in Ontario,Canada

Introduction: Drivers with medical conditions and functional impairments are at increased collision risk. A challenge lies in identifying the point at which such risk becomes unacceptable to society and requires mitigating measures. This study models the road safety impact of medical fitness-to-drive policy in Ontario. Method: Using data from 2005 to 2014, we estimated the losses to road safety incurred during the time medically-at-risk drivers were under review, as well as the savings to road safety accrued as a result of licensing decisions made after the review process. Results: While under review, drivers with medical conditions had an age- and sex-standardized collision rate no different from the general driver population, suggesting no road safety losses occurred (RR = 1.02; 95% CI: 0.93–1.12). Licensing decisions were estimated to have subsequently prevented 1,211 (95% CI: 780–1,730) collisions, indicating net road safety savings resulting from medical fitness to drive policies. However, more collisions occurred than were prevented for drivers with musculoskeletal disorders, sleep apnea, and diabetes. We theorize on these findings and discuss its multiple implications. Conclusions: Minimizing the impact of medical conditions on collision occurrence requires robust policies that balance fairness and safety. It is dependent on efforts by academic researchers (who study fitness to drive); policymakers (who set driver medical standards); licensing authorities (who make licensing decisions under such standards); and clinicians (who counsel patients on their driving risk and liaise with licensing authorities). Practical Applications: Further efforts are needed to improve understanding of the effects of medical conditions on collision risk, especially for the identified conditions and combinations of conditions. Results reinforce the value of optimizing the processes by which information is solicited from physicians in order to better assess the functional impact of drivers’ medical conditions on driving and to take suitable licensing action.     

Exploring relationships between microscopic kinetic parameters of tires under normal driving conditions,road characteristics and accident types

IntroductionFreeway accidents are a leading cause of death in China, which also triggers substantial economic loss and an emotional burden to society. However, the internal mechanism of how microscopic kinetic parameters of vehicles influenced by road characteristics determine the occurrence of different types of accidents has not been explicitly studied. This research aimed to explore the “link role” of tire microscopic kinetic parameters in road characteristic variables and traffic accidents to aid in facilitating the traffic design and management, and thus to prevent traffic accident. Method: A mountain freeway in Zhejiang Province, China was used as the research object and the data used in this paper were obtained through a real-time vehicle experiment. Multiple estimation models, including the standard ordered logit (SOL) model, fixed parameters logit (FPL) model, and random parameters logit (RPL) model were established. Results: The findings show that road characteristics will affect the longitudinal kinetic characteristics of the vehicle and, consequently, map the level of risk of rear-end accidents. Driving compensation effects were also identified in this paper (i.e., the drivers tend to be more cautious in complicated driving circumstances). Another finding relating to the mountain freeway is that different tunnel characteristics (e.g., tunnel entrance and tunnel exit) have different effects on different types of traffic accidents. Practical Applications: The framework proposed in this article can provide new insight for researchers to enlarge the research subjects of both explanatory and outcome variables in accident analysis. Future research could be implemented to consider more driving conditions.     

Driver licensing,motor-vehicle crashes,and moving violations among older adults

IntroductionDriving is important for well-being among older adults, but age-related conditions are associated with driving reduction or cessation and increased crash risk for older drivers. Our objectives were to describe population-based rates of older drivers’ licensing and per-driver rates of crashes and moving violations.Methods: We examined individual-level statewide driver licensing, crash, and traffic citation data among all New Jersey drivers aged ≥ 65 and a 35- to 54-year-old comparison group during 2010–2014. Rate ratios (RR) of crashes and moving violations were estimated using Poisson regression.Results: Overall, 86% of males and 71% of females aged ≥ 65 held a valid driver’s license. Older drivers had 27% lower per-driver crash rates than middle-aged drivers (RR: 0.73, 95% CI: 0.73, 0.74)—with appreciable differences by sex—but 40% higher fatal crash rates (RR: 1.40 [1.24, 1.58]). Moving violation rates among older drivers were 72% lower than middle-aged drivers (RR: 0.28 [0.28, 0.28]).Conclusion: The majority of older adults are licensed, with substantial variation by age and sex. Older drivers have higher rates of fatal crashes but lower rates of moving violations compared with middle-aged drivers.Practical applications: Future research is needed to understand the extent to which older adults drive and to identify opportunities to further reduce risk of crashes and resultant injuries among older adults.     

Driving anger and its expressions: further evidence of validity and reliability for the Driving Anger Expression Inventory French adaptation

Introduction: The aims of this study were to provide further evidence of validity and reliability for the Driving Anger Expression Inventory (DAX) French adaptation (Villieux & Delhomme, 2008, Le Travail Humain, 71(4), 359-384) and to investigate the relationships between driving anger, how people express their anger while driving, and traffic violations among young drivers in France. Method: The French adaptations of the DAX, of the Driving Anger Scale (DAS), and of the Extended Violations Scale were administered to a sample of 314 drivers. Results: Confirmatory factor analysis of the French DAX items yielded a three factors solution with 11 items, which obtained better goodness-of-fit to the data. Cronbach α reliabilities for DAX factors ranged from .71 to .79. Aggressive forms of anger expression correlated positively with driving anger and traffic violations whereas the 'Adaptive/Constructive Expression' factor correlated negatively with these variables. Discussion: Globally, our results replicated earlier findings and showed that DAX factors are useful predictors of self reported violations and complement established measures like the DAS. Impact on Industry: Implications for driver education and interventions were examined.