Jerky driving--An indicator of accident proneness?

This study uses continuously logged driving data from 166 private cars to derive the level of jerks caused by the drivers during everyday driving. The number of critical jerks found in the data is analysed and compared with the self-reported accident involvement of the drivers. The results show that the expected number of accidents for a driver increases with the number of critical jerks caused by the driver. Jerk analyses make it possible to identify safety critical driving behaviour or “accident prone” drivers. They also facilitate the development of safety measures such as active safety systems or advanced driver assistance systems, ADAS, which could be adapted for specific groups of drivers or specific risky driving behaviour.     

The contribution of family climate for road safety and social environment to the reported driving behavior of young drivers

Two studies examined the contribution of the new concept of “family climate for road safety” and several aspects of the social environment to the driving behavior of young drivers. Study 1 (n = 120) investigated the effect of the seven dimensions of the family climate for road safety – Modeling, Feedback, Communication, Monitoring, Noncommitment, Messages, and Limits – as well as a general tendency to conform to authority, and peer pressure. Study 2 (n = 154) examined the dimensions of family climate for road safety and perceived popularity of reckless driving among peers. The findings indicate associations both between the familial and the social aspects, and between these variables and driving styles, willingness to take risks while driving, reckless driving habits, and personal commitment to safe driving. Positive aspects of the parent–child relationship and high levels of conformity to authority were related to greater endorsement of the careful driving style, whereas family's noncommitment to safety, higher peer pressure, and lower conformity to authority were associated with greater endorsement of the reckless driving style. In addition, positive aspects of the family climate for road safety and lower perceived popularity of reckless driving among friends were associated with more personal commitment to safe driving and a lower tendency for risky driving. The discussion stresses the need to look at the complex set of antecedents of reckless driving among young drivers and addresses the practical implications of the findings for road safety.     

The development,factor structure and psychometric properties of driving self-regulation scales for older adults: Has self-regulation evolved in the last 15 years?

The term driving self-regulation is typically used to describe the practice of drivers who avoid driving in situations that they regard as unsafe because of perceived physical impairment. Older adults report using this strategy to improve safety while retaining mobility. Self-regulation is typically assessed using the driving avoidance items from the driving habits questionnaire (DHQ) and the driver mobility questionnaire (DMQ-A). However, the psychometric properties of these measures are not well understood. Using data from 277 older drivers, exploratory factor analysis was used to test the homogeneity of three driving self-regulation scales: the DHQ, DMQ-A, and an extended DMQ-A. Good internal consistency for each of the scales was identified (all αs ≥ .9). A one factor solution was identified for two of the measures (DHQ, DMQ-A) and a two factor solution accounting for over 70% of the score variance was identified for the third measure. The two factors assessed situations that may be avoided while driving because of the “external” (e.g., weather-related) or “internal” (e.g., passenger-related) driving environments, respectively. The findings suggest that the interpretation of an overall summated scale score, or single-item interpretations, may not be appropriate. Instead, driving self-regulation may be a multifaceted construct comprised of distinct dimensions that have not been identified previously but can be reliably measured. These data have implications for our understanding of driving self-regulation by older adults and the way in which this behavior is measured.     

Impact of mobile phone use on car-following behaviour of young drivers

Multitasking, such as the concurrent use of a mobile phone and operating a motor vehicle, is a significant distraction that impairs driving performance and is becoming a leading cause of motor vehicle crashes. This study investigates the impact of mobile phone conversations on car-following behaviour. The CARRS-Q Advanced Driving Simulator was used to test a group of young Australian drivers aged 18–26 years on a car-following task in three randomised phone conditions: baseline (no phone conversation), hands-free and handheld. Repeated measure ANOVA was applied to examine the effect of mobile phone distraction on selected car-following variables such as driving speed, spacing, and time headway. Overall, drivers tended to select slower driving speeds, larger vehicle spacings, and longer time headways when they were engaged in either hands-free or handheld phone conversations, suggesting possible risk compensatory behaviour. In addition, phone conversations while driving influenced car-following behaviour such that variability was increased in driving speeds, vehicle spacings, and acceleration and decelerations. To further investigate car-following behaviour of distracted drivers, driver time headways were modelled using Generalized Estimation Equation (GEE). After controlling for various exogenous factors, the model predicts an increase of 0.33 s in time headway when a driver is engaged in hands-free phone conversation and a 0.75 s increase for handheld phone conversation. The findings will improve the collective understanding of distraction on driving performance, in particular car following behaviour which is most critical in the determination of rear-end crashes.     

Thrill and Adventure Seeking as a modifier of the relationship of perceived risk with risky driving among young drivers

Risky driving contributes to road trauma, a leading cause of mortality among young people. Health-relevant behaviour models suggest a negative relationship between risky driving and perceived risk of its outcomes. However, high sensation seekers may value the “thrill” of the risk, and positive associations between sensation seeking and risky driving have been observed. This is the first study to examine whether aspects of sensation seeking modify the relationship between perceived risk and risky driving. Young drivers in metropolitan Sydney and rural New South Wales [NSW] (n = 797) completed a survey relating to one of the four risky driving behaviours (speeding, drink-driving, driving while fatigued, and failing to wear a seatbelt). Results suggest that the Thrill and Adventure Seeking subscale of Zuckerman's (1994) Sensation Seeking Scale moderate the relationship of perceived risk with risky driving – indicating a negative relationship for low-scores, but not high-scorers, on the TAS subscale. Thus, road safety campaigns that emphasize the riskiness of a particular behaviour may be of limited benefit to thrill and adventure seekers.     

“I drove after drinking alcohol” and other risky driving behaviours reported by young novice drivers

Background: Volitional risky driving behaviours such as drink- and drug-driving (i.e. substance-impaired driving) and speeding contribute to the overrepresentation of young novice drivers in road crash fatalities, and crash risk is greatest during the first year of independent driving in particular. Aims: To explore the: (1) self-reported compliance of drivers with road rules regarding substance-impaired driving and other risky driving behaviours (e.g., speeding, driving while tired), one year after progression from a Learner to a Provisional (intermediate) licence; and (2) interrelationships between substance-impaired driving and other risky driving behaviours (e.g., crashes, offences, and Police avoidance). Methods: Drivers (n = 1076; 319 males) aged 18–20 years were surveyed regarding their sociodemographics (age, gender) and self-reported driving behaviours including crashes, offences, Police avoidance, and driving intentions. Results: A relatively small proportion of participants reported driving after taking drugs (6.3% of males, 1.3% of females) and drinking alcohol (18.5% of males, 11.8% of females). In comparison, a considerable proportion of participants reported at least occasionally exceeding speed limits (86.7% of novices), and risky behaviours like driving when tired (83.6% of novices). Substance-impaired driving was associated with avoiding Police, speeding, risky driving intentions, and self-reported crashes and offences. Forty-three percent of respondents who drove after taking drugs also reported alcohol-impaired driving. Discussion and Conclusions: Behaviours of concern include drink driving, speeding, novice driving errors such as misjudging the speed of oncoming vehicles, violations of graduated driver licensing passenger restrictions, driving tired, driving faster if in a bad mood, and active punishment avoidance. Given the interrelationships between the risky driving behaviours, a deeper understanding of influential factors is required to inform targeted and general countermeasure implementation and evaluation during this critical driving period. Notwithstanding this, a combination of enforcement, education, and engineering efforts appear necessary to improve the road safety of the young novice driver, and for the drink-driving young novice driver in particular.     

Confirmatory factor analysis of the Behaviour of Young Novice Drivers Scale (BYNDS)

Purpose

The greatly increased risk of being killed or injured in a car crash for the young novice driver has been recognised in the road safety and injury prevention literature for decades. Risky driving behaviour has consistently been found to contribute to traffic crashes. Researchers have devised a number of instruments to measure this risky driving behaviour. One tool developed specifically to measure the risky behaviour of young novice drivers is the Behaviour of Young Novice Drivers Scale (BYNDS) (Scott-Parker et al., 2010). The BYNDS consists of 44 items comprising five subscales for transient violations, fixed violations, misjudgement, risky driving exposure, and driving in response to their mood. The factor structure of the BYNDS has not been examined since its development in a matched sample of 476 novice drivers aged 17–25 years.

Method

The current research attempted to refine the BYNDS and explore its relationship with the self-reported crash and offence involvement and driving intentions of 390 drivers aged 17–25 years (M = 18.23, SD = 1.58) in Queensland, Australia, during their first 6 months of independent driving with a Provisional (intermediate) driver's licence. A confirmatory factor analysis was undertaken examining the fit of the originally proposed BYNDS measurement model.

Results

The model was not a good fit to the data. A number of iterations removed items with low factor loadings, resulting in a 36-item revised BYNDS which was a good fit to the data. The revised BYNDS was highly internally consistent. Crashes were associated with fixed violations, risky driving exposure, and misjudgement; offences were moderately associated with risky driving exposure and transient violations; and road-rule compliance intentions were highly associated with transient violations.

Conclusions

Applications of the BYNDS in other young novice driver populations will further explore the factor structure of both the original and revised BYNDS. The relationships between BYNDS subscales and self-reported risky behaviour and attitudes can also inform countermeasure development, such as targeting young novice driver non-compliance through enforcement and education initiatives.     

Street racing video games and risk-taking driving: An Internet survey of automobile enthusiasts

Purpose

The purpose of this study was to examine the relationships among risky driving attitudes, self-perceptions as a risky driver, playing of “drive’em up” (which rewarded players for frequent traffic and other violations) and “circuit” racing video games as well as self-reported risky driving through a web-based survey of car and racing club members in relation to a socio-cognitive model of the effects of racing video game playing.

Method

An Internet questionnaire was developed and included: (1) self-perceptions as a risky driver scales (Driver Thrill Seeking and Competitive Attitude Toward Driving); (2) attitudes regarding street racing; (3) street racing video game playing, and (4) self-reported risky driving (Risk-Taking Driving Scale). A sequential logistic regression was performed entering age and driving exposure as control variables in the first block, self-perceptions as a risky driver in the second block, attitudes in the third block and playing “drive’em up” and “circuit” racing games in the last block to examine their effects on self-reported risk-taking driving.

Results

A total of 503 survey respondents were included in the analyses and only 20% reported any risk-taking driving. Higher score on the Competitive Attitude Toward Driving Scale, more positive attitudes toward street racing, and more frequent reported playing of “drive’em up” video games were associated with higher odds on the self-reported Risk-Taking Driving Scale. However, the Driver Thrill Seeking Scale and “circuit” video game playing failed to predict self-reported risk-taking driving.

Conclusions

Self-perceptions as a risky driver, positive attitudes toward risky driving and “drive’em up” street-racing games, but not “circuit” racing games, are associated with increased risk-taking driving. These findings are congruent with experimental studies in which games that reward driving violations increased risk taking, suggesting that risk taking may be a function of type of street racing game played by affecting self-perceptions as a risky driver.     

Exposure and experience are a confounded nuisance in research on driver behaviour

Road accidents are usually the outcome of multicausal interface problems. Statistical controls therefore need to be equally complex, if accident analyses are to produce understanding of causal factors and lead to correction of contributory errors in driver behaviour. Crude control of accident data for distance travelled, time of day, etc. may identify high-risk groups. However, such controls could produce misleading results from research on individual differences in liability to error, because driving is basically self-paced and purposeful. Certain individuals will thus exhibit characteristically raised levels of risk exposure within the driving task, often as a result of pressures extrinsic to the traffic system. If the errors made by these individuals are to be identified, accident data must be corrected for such self-induced risk exposure, instead of this factor merely being used to “explain” accidents. This need seems most acute in experimental studies, where self-imposed demands and purposes of driving change over time and effects of exposure and experience are thus statistically confounded in accident data. However, control for self-induced risk exposure also seems important in studies of professional drivers' accidents and its neglect calls into question one of the basic assumptions of the “induced exposure” method of interpreting accident data.     

The impact of childhood symptoms of conduct disorder on driver aggression in adulthood

Background

Despite limited empirical investigation, existing scientific literature suggests that individuals with a history or current diagnosis of conduct disorder (CD) may be more likely to demonstrate reckless and aggressive driving. Much of the limited research in this field examines the impact of childhood CD on driver behaviour and collision risk in young adults. Few if any, studies assess the impact of this disorder on driver behaviour beyond age 21 years. The current research is a population-based study of the impact of CD symptoms during childhood on the risk of engaging in driver aggression during adulthood.

Methods

Data are based on telephone interviews with 5230 respondents who reported having driven in the past year. Data are derived from the 2011–2013 cycles of the CAMH Monitor, an ongoing cross-sectional survey of adults in Ontario, Canada aged 18 years and older. A binary logistic regression analysis of self-reported driver aggression in the previous 12 months was conducted, consisting of measures of demographic characteristics, driving exposure, problem substance use, alcohol- and drug-impaired driving, symptoms of attention deficit hyperactivity disorder, and childhood (before age 15) symptoms of CD.

Results

When entered with demographic characteristics, driving exposure, and other potential confounders, childhood symptoms of CD increased the odds of reporting driver aggression more than two-fold (adjusted OR = 2.12). Exploratory analyses of the interaction between childhood symptoms of CD and age was not a significant predictor of driver aggression.

Conclusions

Results suggest that symptoms of CD during childhood are associated with significantly increased odds of self-reported driver aggression during adulthood. Limitations and future directions of the research are discussed.     

Induced exposure

Induced exposure “in the narrow sense” refers to exposure to vehicular collision only, and is modelled by a scheme which equates the proportion of single vehicle collisions experienced by a category of driver/vehicles to the proportion of double vehicle collisions in which that driver/vehicle combination was guilty, and which equates the exposure for the category to the proportion not guilty in double vehicle collisions. Induced exposure “in the wide sense” refers to all types of hazard, and separates the data into four categories by a hypothesis that factors relating to an accident are either internal or external for each of the two driver/vehicle combinations involved, where, for single car collisions, one of the “driver/ vehicle” categories is the type of accident, with the restriction that internal factors do not exist in the case where driver/vehicle represents type of single vehicle accident.     

A meta-analysis of the effects of texting on driving

Text messaging while driving is considered dangerous and known to produce injuries and fatalities. However, the effects of text messaging on driving performance have not been synthesized or summarily estimated. All available experimental studies that measured the effects of text messaging on driving were identified through database searches using variants of “driving” and “texting” without restriction on year of publication through March 2014. Of the 1476 abstracts reviewed, 82 met general inclusion criteria. Of these, 28 studies were found to sufficiently compare reading or typing text messages while driving with a control or baseline condition. Independent variables (text-messaging tasks) were coded as typing, reading, or a combination of both. Dependent variables included eye movements, stimulus detection, reaction time, collisions, lane positioning, speed and headway. Statistics were extracted from studies to compute effect sizes (r_c). A total sample of 977 participants from 28 experimental studies yielded 234 effect size estimates of the relationships among independent and dependent variables. Typing and reading text messages while driving adversely affected eye movements, stimulus detection, reaction time, collisions, lane positioning, speed and headway. Typing text messages alone produced similar decrements as typing and reading, whereas reading alone had smaller decrements over fewer dependent variables. Typing and reading text messages affects drivers’ capability to adequately direct attention to the roadway, respond to important traffic events, control a vehicle within a lane and maintain speed and headway. This meta-analysis provides convergent evidence that texting compromises the safety of the driver, passengers and other road users. Combined efforts, including legislation, enforcement, blocking technologies, parent modeling, social media, social norms and education, will be required to prevent continued deaths and injuries from texting and driving.     

Specific sleepiness symptoms are indicators of performance impairment during sleep deprivation

Drivers are not always aware that they are becoming impaired as a result of sleepiness. Using specific symptoms of sleepiness might assist with recognition of drowsiness related impairment and help drivers judge whether they are safe to drive a vehicle, however this has not been evaluated. In this study, 20 healthy volunteer professional drivers completed two randomized sessions in the laboratory – one under 24 h of acute sleep deprivation, and one with alcohol. The Psychomotor Vigilance Task (PVT) and a 30 min simulated driving task (AusEdTM) were performed every 3–4 h in the sleep deprivation session, and at a BAC of 0.00% and 0.05% in the alcohol session, while electroencephalography (EEG) and eye movements were recorded. After each test session, drivers completed the Karolinska Sleepiness Scale (KSS) and the Sleepiness Symptoms Questionnaire (SSQ), which includes eight specific sleepiness and driving performance symptoms. A second baseline session was completed on a separate day by the professional drivers and in an additional 20 non-professional drivers for test–retest reliability. There was moderate test–retest agreement on the SSQ (r = 0.59). Significant correlations were identified between individual sleepiness symptoms and the KSS score (r values 0.50–0.74, p < 0.01 for all symptoms). The frequency of all SSQ items increased during sleep deprivation (χ² values of 28.4–80.2, p < 0.01 for all symptoms) and symptoms were related to increased subjective sleepiness and performance deterioration. The symptoms “struggling to keep your eyes open”, “difficulty maintaining correct speed”, “reactions were slow” and “head dropping down” were most closely related to increased alpha and theta activity on EEG (r values 0.49–0.59, p < 0.001) and “nodding off to sleep” and “struggling to keep your eyes open” were related to slow eye movements (r values 0.67 and 0.64, p < 0.001). Symptoms related to visual disturbance and impaired driving performance were most accurate at detecting severely impaired driving performance (AUC on ROC curve of 0.86–0.91 for detecting change in lateral lane position greater than the change at a BAC of 0.05%). Individual sleepiness symptoms are related to impairment during acute sleep deprivation and might be able to assist drivers in recognizing their own sleepiness and ability to drive safely.     

A psychosocial model of young adult passengers’ intervening in unsafe driving of their friends

Young adults are over-represented in motor vehicle crashes and the carrying of same passengers puts them at greater risk of crashing. The current study examined characteristics of the passengers who might play a positive role in reducing friends’ crashes by actively engaging in strategies to protect such friends. A psychosocial theoretical model of prosocial behaviour including self-process and contextual cues explained intervening behaviour among primarily novice driver college students (n = 242) with the exception of the self-process, perspective taking. The results of this study provide support for countermeasure development that accounts for the positive role of peers to increase road safety, and reduce the incidence of crashes, among young adults.     

Older driver distraction: A naturalistic study of behaviour at intersections

This study examined older driver engagement in distracting behaviours (secondary activities) at intersections using naturalistic driving data from a larger study based in Melbourne, Australia. Of interest was whether engagement in secondary activities at intersections was influenced by factors such as driver gender and situational variables, in particular, those relating to the complexity of the driving environment. Specifically we expected that when making left/right turns, older drivers would reduce the proportion of time engaged in secondary behaviours at intersections which required gap judgements (partly controlled or uncontrolled) compared with intersections that were fully controlled by traffic signals. Consideration was given to engagement in secondary activity with hands off the wheel and when the vehicle was moving versus stationary. Older drivers aged between 65 and 83 years drove an instrumented vehicle (IV) on their regular trips for approximately two weeks. The IV was equipped with a video camera system, enabling recording of the road environment and driver and a data acquisition unit, enabling recording of trip distance, vehicle speed, braking, accelerating, steering and indicator use. Driving experience and demographics were collected and functional abilities were assessed using the Useful Field of View (UFOV), Trail Making Test B, Mini Mental Status Examination (MMSE), visual acuity and contrast sensitivity. The study yielded a total of 371 trips with 4493 km (99.8 h) of naturalistic driving data including 1396 left and right turns. Trips were randomly selected from the dataset and in-depth analysis was conducted on 200 intersection manoeuvres (approximately 50% left turns, 50% right turns). The most frequently observed secondary activities were scratching/grooming (42.5%), talking/singing (30.2%) and manipulating the vehicle control panel (12.2%). Glances “off road” 2 s or longer were associated with reading, reaching and manipulation of the vehicle control panel. Hands off the wheel was associated with reading. Key parameters associated with the percent of intersection time that drivers engaged in secondary activities were intersection complexity, vehicle status (moving vs. stationary) and traffic density. In conclusion, older drivers appeared to engage selectively in secondary activities according to roadway/driving situations, supporting the notion that drivers self-regulate by engaging in secondary tasks less frequently when the driving task is more challenging compared with less challenging manoeuvres.     

Texting while driving: Psychosocial influences on young people's texting intentions and behaviour

Despite the dangers and illegality, there is a continued prevalence of texting while driving amongst young Australian drivers. The present study tested an extended theory of planned behaviour (TPB) to predict young drivers’ (17-24 years) intentions to [1] send and [2] read text messages while driving. Participants (n = 169 university students) completed measures of attitudes, subjective norm, perceived behavioural control, intentions, and the additional social influence measures of group norm and moral norm. One week later, participants reported on the number of texts sent and read while driving in the previous week. Attitude predicted intentions to both send and read texts while driving, and subjective norm and perceived behavioural control determined sending, but not reading, intentions. Further, intention, but not perceptions of control, predicted both texting behaviours 1 week later. In addition, both group norm and moral norm added predictive ability to the model. These findings provide support for the TPB in understanding students’ decisions to text while driving as well as the inclusion of additional normative influences within this context, suggesting that a multi-strategy approach is likely to be useful in attempts to reduce the incidence of these risky driving behaviours.     

Adolescent exposure to drink driving as a predictor of young adults’ drink driving

The purpose of this study was to investigate the influence of exposure to others’ drink driving during adolescence on self-reported driving under the influence (DUI) of alcohol in young adulthood. Data were drawn from 1956 participants with a driving license enrolled in the International Youth Development Study from Victoria, Australia. During 2003 and 2004, adolescents in Grades 7, 9 and 10 (aged 12–17) completed questionnaires examining whether they had ridden in a vehicle with a driver who had been drinking, as well as other demographic, individual, peer and family risk factors for DUI. In 2010, the same participants (aged 18–24) then reported on their own DUI behaviour. 18% of young adults with a driving license reported DUI in the past 12 months. Exposure to others’ drink driving during adolescence was associated with an increased likelihood of DUI as a young adult (OR = 2.13, 95% CI 1.68–2.69). This association remained after accounting for the effects of other potential confounding factors from the individual, peer and family domains (OR = 1.62, 95% CI 1.23–2.13). Observing the drink driving behaviours of others during adolescence may increase the likelihood of DUI as a young adult. Strategies to reduce youth exposure to drink driving are warranted.     

Revisiting the concept of the ‘problem young driver’ within the context of the ‘young driver problem’: Who are they?

For decades there have been two young driver concepts: the ‘young driver problem’ where the driver cohort represents a key problem for road safety; and the ‘problem young driver’ where a sub-sample of drivers represents the greatest road safety problem. Given difficulties associated with identifying and then modifying the behaviour of the latter group, broad countermeasures such as graduated driver licensing (GDL) have generally been relied upon to address the young driver problem. GDL evaluations reveal general road safety benefits for young drivers, yet they continue to be overrepresented in fatality and injury statistics. Therefore it is timely for researchers to revisit the ‘problem young driver’ concept to assess its potential countermeasure implications. This is particularly relevant within the context of broader countermeasures that have been designed to address the ‘young driver problem’ Personal characteristics, behaviours and attitudes of 378 Queensland novice drivers aged 17–25 years were explored during their pre-, Learner and Provisional 1 (intermediate) licence as part of a larger longitudinal project. Self-reported risky driving was measured by the Behaviour of Young Novice Drivers Scale (BYNDS), and five subscale scores were used to cluster the drivers into three groups (high risk n = 49, medium risk n = 163, low risk n = 166). High risk ‘problem young drivers’ were characterised by greater self-reported pre-Licence driving, unsupervised Learner driving, and speeding, driving errors, risky driving exposure, crash involvement, and offence detection during the Provisional period. Medium risk drivers were also characterised by more risky road use than the low risk group. Interestingly problem young drivers appear to have some insight into their high-risk driving, since they report significantly greater intentions to bend road rules in future driving. The results suggest that tailored intervention efforts may need to target problem young drivers within the context of broad countermeasures such as GDL which address the young driver problem in general. Experiences such as crash-involvement could be used to identify these drivers as a preintervention screening measure.     

Young drivers’ attitudes toward accompanied driving: A new multidimensional measure

Four studies were conducted in order to develop and validate a multidimensional instrument to assess attitudes toward accompanied driving among young drivers. Study 1 (n = 841) focused on developing the Attitudes Toward Accompanied Driving Scale (ATADS), a self-report scale based on five previously conceptualized domains of attitudes. Factor analysis revealed the five hypothesized factors: Tension, Relatedness, Disapproval, Avoidance, and Anxiety. In addition, significant associations were found between these factors and gender, age, and the assessment of reckless driving as risky. Study 2 (n = 651) adopted a developmental approach, comparing the attitudes of participants in various stages of licensure. Disapproval and Tension were found to be higher, and Relatedness lower, among participants who had not yet begun driving instruction than among those who were taking driving lessons or had already obtained a license. Study 3 (n = 160) revealed associations between the five ATADS factors and perceived driving costs and benefits. In Study 4 (n = 193), associations were found between these factors and driver's self-image, with a combination of ATADS factors, self-image, and gender contributing to the explained variance of two outcome variables: driving self-efficacy, and reported frequency of reckless driving. The discussion focuses on the validity and utility of the new measure of young drivers’ attitudes toward accompanied driving, stressing its practical implications for road safety.     

Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK

This paper analyses driving behaviour in car-following conditions, based on extensive individual vehicle data collected during experimental field surveys carried out in Italy and the UK. The aim is to contribute to identify simple evidence to be exploited in the ongoing process of driving assistance and automation which, in turn, would reduce rear-end crashes. In particular, identification of differences and similarities in observed car-following behaviours for different samples of drivers could justify common tuning, at a European or worldwide level, of a technological solution aimed at active safety, or, in the event of differences, could suggest the most critical aspects to be taken into account for localisation or customisation of driving assistance solutions. Without intending to be exhaustive, this paper moves one step in this direction. Indeed, driving behaviour and human errors are considered to be among the main crash contributory factors, and a promising approach for safety improvement is the progressive introduction of increasing levels of driving automation in next-generation vehicles, according to the active/preventive safety approach. However, the more advanced the system, the more complex will be the integration in the vehicle, and the interaction with the driver may sometimes become unproductive, or risky, should the driver be removed from the driving control loop. Thus, implementation of these systems will require the interaction of human driving logics with automation logics and then an enhanced ability in modelling drivers’ behaviour. This will allow both higher active-safety levels and higher user acceptance to be achieved, thus ensuring that the driver is always in the control loop, even if his/her role is limited to supervising the automatic logic. Currently, the driving mode most targeted by driving assistance systems is longitudinal driving. This is required in various driving conditions, among which car-following assumes key importance because of the huge number of rear-end crashes.The increased availability of lower-cost information and communication technologies (ICTs) has enhanced the possibility of collecting copious and reliable car-following individual vehicle data. In this work, data collected from three different experiments, two carried out in Italy and one in the UK, are analysed and compared. The experiments involved 146 drivers (105 Italian drivers and 41 UK drivers). Data were collected by two instrumented vehicles.Our analysis focused on inter-vehicular spacing in equilibrium car-following conditions. We observed that (i) the adopted equilibrium spacing can be fitted using lognormal distributions, (ii) the adopted equilibrium spacing increases with speed, and (iii) the dispersion between drivers increases with speed. In addition, according to different headway thresholds (up to 1 second) a significant number of potentially dangerous behaviours is observed.Three different car-following paradigms are also applied to each of the experiments, and modelling parameters are calibrated and compared to obtain indirect confirmation about the observed similarities and differences in driving behaviour.