Drivers Of Different Ages Research Articles

Multigroup invariance of measure for angry drivers (MAD) scale using a representative sample of drivers in Australia

Introduction: Driver anger and aggression have been linked to crash involvement and injury outcomes. Improved road safety outcomes may be achieved through understanding the causes of driver anger, and interventions designed to reduce this anger or prevent it from becoming aggression. Scales to measure anger propensities will be an important tool in this work. The measure for angry drivers (MAD; Stephens et al., 2019) is a contemporary scale designed to measure tendencies for anger across three types of driving scenarios: perceived danger from others, travel delays, and hostility or aggression from other drivers. Method: This study aimed to validate MAD using a representative sample of Australian drivers, stratified across age, gender, and location. Participants completed a 10-minute online survey that included MAD, sought demographic information (age, gender, driving purpose, crash history), as well as the frequency of aggressive driving. Multigroup confirmatory factor analyses (MGCFA) assessed how stable the structure of the MAD was across drivers of different ages, gender, purposes for driving and those who do or do not display anger aggressively. MAD was invariant across all groups, showing that all drivers interpreted and responded to MAD in the same way. Results: A comparison of latent means showed anger tendencies were higher for men compared to women, for younger drivers compared to older drivers, and for those who drive mainly for work compared to those who mainly drive for other reasons. When controlling for driver factors, driving anger was associated with increased odds of being aggressive while driving. Practical Applications: Overall, this study demonstrated that MAD is an appropriate scale to measure anger tendencies and can be used to support interventions, and evaluation of interventions, to reduce anger and aggressive driving.

Bus Drivers’ Behavioral Intention to Comply with Real-Time Control Instructions: An Empirical Study from China

Developing intelligent bus control systems is crucial for fostering the sustainability of urban transportation. Control instructions are produced in real time by the bus control system; these are important technical commands to stabilize the order in which buses operate and improve service reliability. Understanding the behavioral intention of bus drivers to comply with these instructions will help improve the effectiveness of intelligent bus control system implementation. We have developed a psychological model that incorporates decomposed variables of the theory of planned behavior (TPB) and other influencing variables to explain the micromechanisms that determine bus drivers’ behavioral intention to comply with real-time control instructions during both peak and off-peak-hour scenarios. A total of 258 responses were obtained and verified for analysis. The results showed that the influential factors in the peak- and off-peak-hour scenarios were not identical. Female drivers had greater off-peak-hour behavior intention to comply than male drivers, and there were significant differences in peak-hour behavior intention among drivers of different ages. In both peak and off-peak-hour scenarios, perceived benefit positively and perceived risk negatively affected behavioral intention. Perceived controllability positively affected behavioral intention only during peak hours. Self-efficacy only negatively affected behavioral intention during off-peak hours. Three antecedent variables (i.e., trust, mental workload, and line infrastructure support) influenced drivers’ behavioral intentions indirectly via the decomposed variables of TPB. These results provide profound insights for the improvement and implementation of real-time control technology for bus services, thereby facilitating the development of smart and sustainable urban public transport systems.

К ВОПРОСУ ОБ ИЗМЕНЕНИИ ВРЕМЕНИ РЕАКЦИИ ВОДИТЕЛЯ В ТРАНСПОРТНОМ ПОТОКЕ ВЫСОКОЙ ПЛОТНОСТИ

This article considers the problem of determining the reaction time of sanguine drivers of different age categories in the city's transport system in conditions of high-density traffic flow, close to congestion. Prolonged exposure to high-density traffic leads to a deterioration in the functional state of the driver and to an increase in his psycho-emotional tension. A change in the functional state causes fatigue in the driver, which in turn leads to an increase in his reaction time, which affects road safety. The assessment of the driver's fatigue level was carried out by measuring an electrocardiogram and analyzing the unevenness of cardiac intervals, which are a universal response to all types of loads. A model for estimating changes in the reaction time of a sanguine driver based on a regression model of changes in his fatigue level is proposed. The graphs show the changes in the reaction time of drivers of different ages during their stay in traffic congestion. It was revealed that the reaction time of the driver in the first minutes of being in a traffic jam changes slightly, due to the presence of reserve compensatory capabilities of the body, however, after the fifth to sixth minute, an objective process of deterioration of the functional state begins. It was found that the change in the reaction time of a sanguine driver in a traffic jam primarily depends on the initial level of fatigue. When the driver stays in a high-density traffic flow with the initial state of optimal voltage of the regulatory systems, the change in his reaction time by the end of the jam reaches the greatest value. It was also revealed that the greatest changes in the reaction time of a sanguine driver occur in older drivers.

Temporal instability and age differences of determinants affecting injury severities in nighttime crashes

Driving at nighttime may make drivers more likely to be involved in fatal crashes. To investigate the temporal instability and age differences of contributors determining different injury severity levels in nighttime crashes, this paper estimates three groups of random parameters logit models with heterogeneity in the means and variances (young/middle-age/old groups). Nighttime single-vehicle crashes in this study are gathered over four years in California, from January 1, 2014, to December 31, 2017, provided by Highway Safety Information System, including single-vehicle crashes occurring under dark, dawn, and dusk lighting conditions. Simultaneously, to investigate the temporal instability and transferability of nighttime crash severity relating to drivers of different ages, three disaggregate groups are defined: young drivers (15–29 years old), middle-age drivers (30–49 years old), old drivers (over 49 years old). Three injury-severity categories are determined as outcome variables: severe injury, minor injury, and no injury, while multiple factors are investigated as explanatory variables, including driver characteristics, vehicle characteristics, roadway characteristics, environmental characteristics, crash characteristics, and temporal characteristics. Two series of likelihood ratio tests are undertaken to unveil the contributors determining nighttime crash injury severities varying among drivers of different ages over time. Besides, the current study also compares the differences between out-of-sample and within-sample predictions. The results indicate the unstable direction of predictions across different age groups over time and underscore the necessity to adequately accommodate the temporal instability and age differences in accident prediction. More studies can be conducted to accommodate the self-selectivity issue and the out-of-sample prediction differences between using the parametric models and non-parametric models.

Effects of Automation and Fatigue on Drivers from Various Age Groups

This study explores how drivers are affected by automation when driving in rested and fatigued conditions. Eighty-nine drivers (45 females, 44 males) aged between 20 and 85 years attended driving experiments on separate days, once in a rested and once in a fatigued condition, in a counterbalanced order. The results show an overall effect of automation to significantly reduce drivers’ workload and effort. The automation had different effects, depending on the drivers’ conditions. Differences between the manual and automated mode were larger for the perceived time pressure and effort in the fatigued condition as compared to the rested condition. Frustration was higher during manual driving when fatigued, but also higher during automated driving when rested. Subjective fatigue and the percentage of eye closure (PERCLOS) were higher in the automated mode compared to manual driving mode. PERCLOS differences between the automated and manual mode were higher in the fatigued condition than in the rested condition. There was a significant interaction effect of age and automation on drivers’ PERCLOS. These results are important for the development of driver-centered automation because they show different benefits for drivers of different ages, depending on their condition (fatigued or rested).

Benefits or Risks: What Influences Novice Drivers Regarding Adopting Smart Cars?

Level 4 autonomous vehicles (AVs) are smart vehicles that can move between two different points without any human interference. In 2018, the Saudi Arabian ban on female drivers was finally lifted, resulting in a large number of novice women drivers of different ages. The Kingdom might therefore be considered a risky place to drive, but AVs would help novices to reduce their fear of driving and reduce accidents. Previous studies focused narrowly on those who already had sufficient driving experience and held a valid driving license, but there were no studies on the adoption of smart cars by novice drivers. Based on a literature search, no studies had used a net valence model (NVM) for the adoption of AVs to understand their benefits/risks. Therefore, this study proposed an adoption model for AVs using an NVM to identify the benefit and risk factors that have an impact on beginner drivers’ adoption of autonomous vehicles. A survey method was applied using the purposive sampling technique. Data were collected from 1400 female Saudi novice drivers who had experience with driving AVs. Data analysis was performed using Smart PLS Version 3. The results showed that individuals tended to ignore potential risks and focus instead on the potential benefits of using AVs. Performance expectancy, enjoyment, and effort expectancy were found to be positively related to the perceived advantages. On the other hand, the perceived risk as a construct did not have an impact on beginner drivers’ adoption of autonomous vehicles. Therefore, the major theoretical contribution of this study was the formation of a new NVM model by incorporating three more constructs, which were social influence, personal innovativeness, and alternatives. Finally, the enhanced NVM model could assist AV developers in identifying the expected benefits and drawbacks of AV adoption.

Intraindividual variability in driving simulator parameters of healthy drivers of different ages

Intraindividual variability is a fundamental behavioural characteristic of aging but has been examined to a very limited extent in driving. This study investigated intraindividual variability in driving simulator measures in healthy drivers of different ages using the coefficient of variation (COV) as a variability measure. Participants were healthy volunteers who were regular drivers, who were divided into a “young” group, a “middle-aged” group, and an “old” group. They drove in two environments (rural, 72 drivers; urban, 60 drivers), under conditions of moderate and high traffic load, without and with distraction (conversation). Significant differences in COV were observed in the rural condition for headway distance and lateral position as a function of traffic load, with high traffic (without and with distraction) resulting in increased COV of headway and decreased COV of lateral position. Significant differences in COV were observed in the urban condition for headway distance only, with high traffic (without and with distraction) resulting in increased COV of headway. No age effects were found for any of the driving conditions. The results indicate that traffic load affected headway distance and lateral position in opposite directions in all three age groups: high traffic resulted in increased variability of headway in both rural and urban conditions but in decreased variability of lateral position in the rural conditions compared to moderate traffic irrespective of distraction. The study indicates that driving conditions affect the intraindividual variability of driving measures in selective ways, which may be linked to the extent of automatization of the driving variables and to adaptive changes to traffic condition challenges.

RETRACTED ARTICLE: Investigation of automotive digital mirrors ergonomics through laser shadowgraphy and driver’s real-road test questionnaire

This paper studied the effect of replacing automotive reflection mirrors with digital mirrors (DM) on the driver’s safety and comfort. In this perspective, a new classification for DMs was proposed in appendance with a brief overview of driver’s visual ergonomics, associated with comparison and criticism of automotive DM design causality. Automotive laser shadowgraphy from car interior was performed to measure the obscuration in the driver’s direct field of view, due to the presence of DM displays at nine different obscuration positions. The driver’s off-road glances time toward DM displays was measured using a digital video recorder system. The eye glances of thirty drivers of different ages during different traffic conditions and their opinion about each display position through a simple questionnaire were statistically analyzed. Some pilot solutions were also proposed to reduce the expected drawbacks of such technology.

Predictors of accidents in people with mild cognitive impairment, mild dementia due to Alzheimer's disease and healthy controls in simulated driving.

To examine the driving variables that predict accident probability in mild dementia due to Alzheimer's disease (AD), mild cognitive impairment (MCI) and healthy older control drivers in simulated driving. To compare the three groups in mean performance and in frequency of scores exceeding 1.5 SD from the mean. Participants were 37 drivers with MCI, 16 drivers with AD, and 21 control drivers over the age of 52. Driving measures were derived from four rural driving conditions: moderate traffic without and with distraction and high traffic without and with distraction. The measures were z-transformed based on the performance of 90 control drivers of different ages. Two unexpected incidents occurred per condition, requiring the sudden breaking to avoid an accident. Drivers with AD showed significantly lower average speed, speed variability, greater headway distance, headway variability and average reaction time (RT) than control drivers. Drivers with MCI showed significantly lower average speed, greater headway distance and average RT than control drivers in the two conditions of distraction. No differences were found in accident probability. Drivers with AD had more deviant scores than both control drivers and drivers with MCI in most comparisons. Predictors of accident probability were average RT, speed variability and lateral position variability but MCI and AD status were not significant predictors in any of the regression models. Despite significant differences in performance, drivers with MCI and AD did not differ in accident probability from control drivers. An individualized approach of examining individual driving performance is recommended.

Determination of Risk Perception of Drivers Using Fuzzy-Clustering Analysis for Road Safety

This study aims at investigating drivers' risk perception ability. To achieve this objective, the risk sensitivity and risk judgment thresholds of drivers of different ages were calculated. Five scenarios of intersections with risks were established for the driving simulator experiment. The driving behavior data of fourteen younger drivers and fourteen elderly drivers during the risky event and the subjective evaluation of risk by an expert driver were collected. The expert driver's conflict degree and subjective feeling were combined to classify the risk level of driving scene; then, fuzzy signal detection was used to calculate the driver's risk sensitivity (d') and judgment threshold (β). The β with the greatest difference was selected for cluster analysis and drivers were divided into four types according to the threshold. Finally, a driver classification discriminant model was constructed based on Fisher discriminant analysis. The results show that d' and β of younger drivers are both better than those of elderly drivers, younger drivers can detect and respond risks in time, while elderly drivers need be closer to risks and have intuitive feelings to make judgments. The results of the cluster analysis showed that younger drivers account for a large proportion of the sensitive type, indicating that younger drivers can find risks more sensitively in risk scenarios than elderly drivers, while elderly drivers easily ignore risks due to physical and psychological weakness. The correlation analysis showed that age, saccade amplitude and heart rate are the main factors that affect the risk judgment threshold.

Riding the Adolescence: Personality Subtypes in Young Moped Riders and Their Association With Risky Driving Attitudes and Behaviors.

The aim of the present study was to identify sub-types of moped riders based on a cluster analysis of specific personality characteristics (i.e., driving anger, anxiety, angry hostility, excitement-seeking, altruism, normlessness, and driving locus of control) within a large sample of Italian adolescents. The study had also the aim to compare the emerged sub-types of moped riders on measures of attitudes toward safe driving, risky driving behaviors (e.g., rule’s violations and speeding, not using helmet, drinking and driving, etc.), and self-reported tickets and accident involvement. One thousand two hundred seventy-three Italian high school students aged from 13 to 19 years (meanage = 15.43, SD = 0.98) with a valid driving license for moped participated to the study. Results revealed three sub-types of moped riders (namely risky, worried and careful moped riders), which differ significantly for risky driving behaviors, attitudes toward traffic safety, risk perception, and self-reported accident involvement. Importantly, the results of the present study showed that the personality and behavioral characteristics of the three sub-groups of moped riders substantially resembled those identified by previous studies with vehicle drivers of different ages; thus, empirically supporting the notion that certain combinations of personality characteristics are associated with risk driving tendencies and behaviors in both young moped riders and car drivers. Safe driving interventions can tackle risky driving beliefs and behavioral tendencies in young moped riders and car drivers by tailoring their messages according to the personality sub-types of the target groups.

Association between cellphone use while driving legislation and self-reported behaviour among adult drivers in USA: a cross-sectional study

ObjectivesCellphone use behaviours can vary demographically in the USA. This study examined whether legislation restricting cellphone use while driving was associated with lower self-reported hand-held cellphone conversations or texting behaviours...

Operating speed models of two-lane rural state roads developed on continuous speed data

This paper presents models for predicting operating speeds on tangent sections and curves of two-lane rural roads developed on continuous speed data. The data corresponds to 20 drivers of different ages and driving experiences, driving their own cars along an 18 km long section of a state road. The data were first used for determination of minimum operating speeds on curves and maximum operating speeds on tangents and their comparison with speeds in the middle of curves and tangents i.e. speed data used in most of the operating speed studies. There was no significant difference between speed models developed using speed data in the middle of tangents and curves and models developed using maximum and minimum operating speeds on tangents and curves. Models developed on continuous data have higher coefficient of determination than models developed on spot speed data. It can be concluded that the method of measuring has more significant impact on the quality of speed model than the location of measurement.

Young females at risk while driving with a small child

IntroductionPrevious research suggests that young mothers with little driving experience are at risk when driving with a small child passenger. In this study we examined the prevalence, characteristics and risk of fatal motor vehicle crashes involving an infant passenger under the age of one among female drivers of different ages. MethodsWe used crash data from the US Fatality Analysis Reporting System for 1994–2013. The prevalence of fatal crashes involving infants was examined by age of female drivers and compared to the number of births among mothers of a similar age. The essential characteristics of the crashes were described, and the odds of being at fault were determined for young (16–24-year-olds) and older female drivers (25–39-year-olds) with an infant passenger or with no passengers. ResultsThe prevalence of fatal crashes involving infant passengers was higher among young female drivers in relation to the number of births among mothers of a similar age than among older females. Young female drivers with an infant passenger were more often at fault than older drivers (aOR=1.83, 95%, CI=1.52, 2.20). Their vehicles were older and smaller and they used proper safety seats for infants less often than the older drivers. In addition, young female drivers with an infant passenger but with no adult passenger in the vehicle were more often at fault than young female drivers with no passengers (aOR=1.27, 95% CI=1.06, 1.51).Both young and older female drivers’ crashes involving an infant passenger typically occurred in ordinary driving conditions, but these drivers with infant passengers were more often reported as having fallen asleep or inattentive than those with no passengers. The presence of an adult passenger in addition to an infant passenger lowered female drivers’ odds of being at fault, regardless of the driver’s age. ConclusionsYoung females driving with an infant passenger, probably most often mothers, are at an elevated risk of a fatal crash, especially when they drive alone with an infant. The protective effect of an adult passenger suggests that another adult in the vehicle can assist the driver by taking care of the infant and enabling the driver to focus on driving.

Hand-held cell phone use while driving legislation and observed driver behavior among population sub-groups in the United States

BackgroundCell phone use behaviors are known to vary across demographic sub-groups and geographic locations. This study examined whether universal hand-held calling while driving bans were associated with lower road-side observed hand-held cell phone conversations across drivers of different ages (16–24, 25–59, ≥60 years), sexes, races (White, African American, or other), ruralities (suburban, rural, or urban), and regions (Northeast, Midwest, South, and West).MethodsData from the 2008–2013 National Occupant Protection Use Survey were merged with states’ cell phone use while driving legislation. The exposure was presence of a universal hand-held cell phone ban at time of observation. Logistic regression was used to assess the odds of drivers having a hand-held cell phone conversation. Sub-groups differences were assessed using models with interaction terms.ResultsWhen universal hand-held cell phone bans were effective, hand-held cell phone conversations were lower across all driver demographic sub-groups and regions. Sub-group differences existed among the sexes (p-value, <0.0001) and regions (p-value, 0.0003). Compared to states without universal hand-held cell phone bans, the adjusted odds ratio (aOR) of a driver hand-held phone conversation was 0.34 [95% confidence interval (CI): 0.28, 0.41] for females versus 0.47 (CI 0.40, 0.55) for males and 0.31 (CI 0.25, 0.38) for drivers in Western states compared to 0.47 (CI 0.30, 0.72) in the Northeast and 0.50 (CI 0.38, 0.66) in the South.ConclusionsThe presence of universal hand-held cell phone bans were associated lower hand-held cell phone conversations across all driver sub-groups and regions. Hand-held phone conversations were particularly lower among female drivers and those from Western states when these bans were in effect. Public health interventions concerning hand-held cell phone use while driving could reasonably target all drivers.

Distinguishing patterns in drivers’ visual attention allocation using Hidden Markov Models

Driving is an intricate task where different demands compete for the driver’s attention. Current interface designs present novel multi-modal interactions that extend beyond traditional visual-manual modalities. These new interaction paradigms have given rise to additional subtask elements which call upon varying degrees of cognitive, auditory, vocal, visual, and manual resources. The draw on a larger number of resources has made demand assessment and optimization challenging. How these elements impact the driver’s visual behavior may provide insight into the degree to which a vehicle’s user interface influences attentional focus. This report addresses this question by approaching the problem from a computationally predictive perspective. Data were drawn from two studies that captured visual behaviors of drivers during a series of radio tuning tasks using a traditional manual interface and a multi-modal voice enabled interface during highway driving. Manual annotations of glance times and targets were compiled for each task period and then used to train a predictive model. A statistical machine learning approach (Hidden Markov Model) showed that manual radio tuning, voice-based radio tuning, and “just driving” behaviors result in fundamentally and predictably different strategies of visual attention allocation. We report classification accuracies of over 95% for detecting the correct task modality within a 3 class classification framework, extending prior work to show that time series of glance allocations contain highly descriptive information that generalizes well across drivers of different ages, genders, and driving experience. Results suggest that differences in glance allocation strategies serve as an effective evaluator of the visual demand of a vehicle interface, providing an objective methodology for demonstrating that voice-based technologies allow drivers to maintain a broader distribution of visual attention than the traditional manual interface.

The licensing and safety of older drivers in Britain

Driving licence holding in Britain is increasing for older people, particularly older women. Licence holding by men aged 40–69 has saturated at about 90%, and for women aged 30–59 at about 78%. Drivers begin to surrender licences after age 70. By age 90, 38% of women and 25% of men who held a licence at age 70 have surrendered their licences.The paper shows the numbers of car drivers of different ages killed and injured in accidents since 1975 and the fatality and casualty rates per driver and per mile driven. The safety of older drivers is improving faster than that of younger age groups. The number of car driver fatalities aged 70 and over was highest between 1990 and 2004, and has subsequently reduced by almost 40%. For drivers aged 80 and over, the peak was in 2004 and the number has subsequently reduced by almost 50%.The paper uses demographic projections, forecast licence holding and the trends in fatality rates to project the numbers of fatalities for drivers of different ages in Britain. This shows that fatalities among older drivers aged are likely to continue to reduce.Fatality rates for older road users are increased by the fragility of older persons. This disguises the fact that the accident involvement rate for older drivers does not increase with age until after age 75 or 80.

Older drivers do not have a high crash risk—A replication of low mileage bias

The widespread claim that older drivers are overly involved in crashes has apparent support from crash data, especially when distance travelled is used as the exposure measure. However, independent of age, drivers travelling more kilometres will typically have lower crash rates per kilometre than those driving fewer kilometres. This paper uses Dutch travel survey data from a large sample of respondents to confirm previous research findings concerning the association between annual mileages driven and crash involvement. When the crash rates of drivers of different ages were compared after being matched for yearly driving distance, most drivers aged 75 years and above were indicatively safer than all other drivers. Only older drivers travelling less than 3000 km per year (just over 10% of all older drivers in the survey) gave any indication of elevated crash rates.

Occupational therapy assessment of open-road driving performance: validity of directed and self-directed navigational instructional components.

The purpose of this study was to validate an assessment tool used by occupational therapists to evaluate on-road driving performance. The driving assessment was conducted over a 15-km route that consisted of a range of traffic situations and contained both directed and self-directed navigational instruction. The driving performance of four groups of drivers of different ages and visual characteristics was assessed independently by an occupational therapist and driving instructor using a range of scoring criteria. The occupational therapist scores were significantly affected by the drivers' age and visual characteristics (directed navigation, F(3,133) = 6.05, p = 0.001; self-directed navigation, F(3,133) = 5.04, p < 0.002), and these group differences were greater for self-directed navigational instruction. The occupational therapist scores were highly correlated with the driving instructor's global driver safety rating (r = 0.76, p < 0.001). The driving assessment instrument was a valid measure of on-road driving performance relative to an independent global driving safety evaluation. The instrument provided detailed information regarding driving performance and highlighted areas of difficulty, particularly when drivers followed self-navigational instruction.

Looming Detection Among Drivers of Different Ages

Rear-end collisions make up about 25 percent of all automobile crashes, 27 percent of crashes resulting in injuries, and 5 percent of all fatal car crashes in the U.S. We believe that one factor in these crashes is that some people are less able to detect when they are closing in on another car, and that this ability can be measured. Thirty participants in three age groups participated in this study. Testing included the detection of size change (looming), estimation of change in looming, manual lateral tracking, synthetic tail-following, and low-fidelity driving. Participants' visual and cognitive abilities were also tested. Results indicated that the looming detection task possessed a respectable amount of retest reliability and yielded a measure that provided stable data after one session. The results further indicated that the loom tests showed minimal relationships with other temporal visual functions, indicating that looming detection is a separate function. Finally, a clear relationship between age and looming detection was shown, but neither gender nor handedness appeared to have an effect.