The effects of driver identity on driving safety in a retrospective feedback system

Background

Retrospective feedback that provides detailed information on a driver's performance in critical driving situations at the end of a trip enhances his/her driving behaviors and safe driving habits. Although this has been demonstrated by a previous study, retrospective feedback can be further improved and applied to non-critical driving situations, which is needed for transportation safety.

Objectives

To propose a new retrospective feedback system that uses driver identity (i.e., a driver's name) and to experimentally study its effects on measures of driving performance and safety in a driving simulator.

Method

We conducted a behavioral experimental study with 30 participants. “Feedback type” was a between-subject variable with three conditions: no feedback (control group), feedback without driver identity, and feedback with driver identity. We measured multiple aspects of participants’ driving behavior. To control for potential confounds, factors that were significantly correlated with driving behavior (e.g., age and driving experience) were all entered as covariates into a multivariate analysis of variance. To examine the effects of speeding on collision severity in driving simulation studies, we also developed a new index – momentum of potential collision – with a set of equations.

Results

Subjects who used a feedback system with driver identity had the fewest speeding violations and central-line crossings, spent the least amount of time speeding and crossing the central line, had the lowest speeding and central-line crossing magnitude, ran the fewest red lights, and had the smallest momentum of potential collision compared to the groups with feedback without driver identity and without feedback (control group).

Conclusions

The new retrospective feedback system with driver identity has the potential to enhance a person's driving safety (e.g., speeding, central-line crossing, momentum of potential collision), which is an indication of the valence of one's name in a feedback system design.     

Differences in state drug testing and reporting by driver type in U.S. fatal traffic crashes

IntroductionDriving under the influence of drugs, including marijuana, has become more prevalent in recent years despite local, state, and federal efforts to prevent such increases. The Fatality Analysis Reporting System (FARS) is the primary source of drugged driving data for fatal crashes in the United States but lacks the completeness required to calculate unbiased estimates of drug use among drivers involved in fatal crashes.MethodsThis article uses the 2013 FARS dataset to present differences in state drug testing rates by driver type, driver fault type, and state-level factors; discusses limitations related to analysis and interpretation of drugged driving data; and offers suggestions for improvements that may enable appropriate use of FARS drug testing data in the future.ResultsResults showed that state drug testing rates were highest among drivers who died at the scene of the crash (median = 70.8%) and drivers who died and were at fault in the crash (median = 64.4%). The lowest testing rates were seen among surviving drivers who were not transported to a hospital (median = 14.0%) and surviving drivers who were not at fault in the crash (median = 10.0%). Drug testing rates differed by state blood alcohol content (BAC) testing rate across all driver types and driver fault types, and in general, states that tested a higher percentage of drivers for BAC had higher drug testing rates.DiscussionTesting rates might be increased through standardization and mandatory testing policies. FARS data users should continue to be cautious about the limitations of using currently available data to quantify drugged driving. More efforts are needed to improve drug testing and reporting practices, and more research is warranted to establish drug concentration levels at which driving skills become impaired.     

How to identify the key factors that affect driver perception of accident risk. A comparison between Italian and Spanish driver behavior

Road crashes can be caused by different factors, including infrastructure, vehicles, and human variables. Many research studies have focused solely on identifying the key factors that cause road crashes. From these studies, it emerged that human factors have the most relevant impact on accident severity. More specifically, accident severity depends on several factors related directly to the driver, i.e., driving experience, driver's socio-economic characteristics, and driving behavior and attitudes. In this paper, we investigate driver behaviors and attitudes while driving and specifically focus on different methods for identifying the factors that most affect the driver's perception of accident risk. To this end, we designed and conducted a survey in two different European contexts: the city of Cosenza, which is located in the south of Italy, and the city of Granada, which is located in the south of Spain. Samples of drivers were contacted for their opinions on certain aspects of driving rules and attitudes while driving, and different types of questions were addressed to the drivers to assess their judgments of these aspects. Consequently, different methods of data analysis were applied to determine the aspects that heavily influence driver perception of accident risk. An experiment based on the stated preferences (SP) was carried out with the drivers, and the SP data were analyzed using an ordered probit (OP) model. Interesting findings emerged from different analyses of the data and from the comparisons among the data collected in the two different territorial contexts. We found that both Italian and Spanish drivers consider driving in an altered psychophysical state and violating the overtaking rules to be the most risky behaviors.     

A human factors perspective on automated driving

ABSTRACT

Automated driving can fundamentally change road transportation and improve quality of life. However, at present, the role of humans in automated vehicles (AVs) is not clearly established. Interviews were conducted in April and May 2015 with 12 expert researchers in the field of human factors (HFs) of automated driving to identify commonalities and distinctive perspectives regarding HF challenges in the development of AVs. The experts indicated that an AV up to SAE Level 4 should inform its driver about the AV's capabilities and operational status, and ensure safety while changing between automated and manual modes. HF research should particularly address interactions between AVs, human drivers and vulnerable road users. Additionally, driver-training programmes may have to be modified to ensure that humans are capable of using AVs. Finally, a reflection on the interviews is provided, showing discordance between the interviewees’ statements – which appear to be in line with a long history of HFs research – and the rapid development of automation technology. We expect our perspective to be instrumental for stakeholders involved in AV development and instructive to other parties.     

Real-time driver drowsiness feedback improves driver alertness and self-reported driving performance

Driver drowsiness has been implicated as a major causal factor in road accidents. Tools that allow remote monitoring and management of driver fatigue are used in the mining and road transport industries. Increasing drivers’ own awareness of their drowsiness levels using such tools may also reduce risk of accidents. The study examined the effects of real-time blink-velocity-derived drowsiness feedback on driver performance and levels of alertness in a military setting. A sample of 15 Army Reserve personnel (1 female) aged 21–59 (M = 41.3, SD = 11.1) volunteered to being monitored by an infra-red oculography-based Optalert Alertness Monitoring System (OAMS) while they performed their regular driving tasks, including on-duty tasks and commuting to and from duty, for a continuous period of 4–8 weeks. For approximately half that period, blink-velocity-derived Johns Drowsiness Scale (JDS) scores were fed back to the driver in a counterbalanced repeated-measures design, resulting in a total of 419 driving periods under “feedback” and 385 periods under “no-feedback” condition. Overall, the provision of real-time feedback resulted in reduced drowsiness (lower JDS scores) and improved alertness and driving performance ratings. The effect was small and varied across the 24-h circadian cycle but it remained robust after controlling for time of day and driving task duration. Both the number of JDS peaks counted for each trip and their duration declined in the presence of drowsiness feedback, indicating a dynamic pattern that is consistent with a genuine, entropy-reducing feedback mechanism (as distinct from random re-alerting) behind the observed effect. Its mechanisms and practical utility have yet to be fully explored. Direct examination of the alternative, random re-alerting explanation of this feedback effect is an important step for future research.     

The effects of range versus nonrange driver training on the accident and conviction frequencies of young drivers

The sample consisted of 2,057 high school students from five California high schools who were assigned randomly either to a traditional driver training program (N = 918) or to an experimental program utilizing a driving range (N = 1,139). Aspects of their performance during driver training were measured, as well as performance on tests required for driver licensing and number of days between training and licensing. In addition, Department of Motor Vehicles files supplied information on their accident and conviction records within the year following the beginning of driver training. Results showed that nonrange students performed significantly better on the following training variables: knowledge posttest (p < 0.01), simulator score (p < 0.01), and driver course grade (p < 0.05). There were no significant differences between range and nonrange students on driver licensing test scores or in the amount of time spent in becoming licensed. However, range students had fewer total accidents than nonrange students (p < 0.05) in the year following the beginning of training. Time spent on the range during training was not related to frequency of accidents or convictions for range students. Cost-benefit aspects of range training were discussed. Range training is operationally less expensive than traditional training, but costs of constructing a driving range may vary appreciably.     

Drivers’ behavioral responses to combined speed and red light cameras

BackgroundNumerous signalized intersections worldwide have been equipped with enforcement cameras in order to tackle red light running and often also to enforce speed limits. However, various impact evaluation studies of red light cameras (RLCs) showed an increase of rear-end collisions (up to 44%).ObjectiveThe principal objective of this study is to provide a better insight in possible explaining factors for the increase in rear-end collisions that is caused by placing combined speed and red light cameras (SRLCs).MethodReal-world observations and driving simulator-based observations are combined. Video recordings at two signalized intersections where SRLCs were about to be installed are used to analyze rear-end conflicts, interactions and driver behavior in two conditions (i.e., with and without SRLC). Furthermore, one of these intersections was rebuilt in a driving simulator equipped with an eye tracking system. At this location, two test conditions (i.e., SRLC and SRLC with a warning sign) and one control condition (i.e., no SRLC) are examined. The data of 63 participants were used to estimate the risk of rear-end collisions by means of a Monte Carlo Simulation.ResultsThe results of the on-site observation study reveal decreases in the number of red and yellow light violations, a shift (i.e., closer to the stop line) in the dilemma zone and a time headway reduction after the installation of the SRLC. Based on the driving simulator data, the odds of rear-end collisions (compared to the control condition) for the conditions with SRLC and SRLC + warning sign is 6.42 and 4.01, respectively.ConclusionThe real-world and driving simulator observations indicate that the risk of rear-end collisions increases when SRLCs are installed. However, this risk might decrease when a warning sign is placed upstream.     

Occupational driver safety: Conceptualising a leadership-based intervention to improve safe driving performance

Occupational driving crashes are the most common cause of death and injury in the workplace. The physical and psychological outcomes following injury are also very costly to organizations. Thus, safe driving poses a managerial challenge. Some research has attempted to address this issue through modifying discrete and often simple target behaviours (e.g., driver training programs). However, current intervention approaches in the occupational driving field generally consider the role of organizational factors in workplace safety. This study adopts the A–B–C framework to identify the contingencies associated with an effective exchange of safety information within the occupational driving context. Utilizing a sample of occupational drivers and their supervisors, this multi-level study examines the contingencies associated with the exchange of safety information within the supervisor–driver relationship. Safety values are identified as an antecedent of the safety information exchange, and the quality of the leader–member exchange relationship and safe driving performance is identified as the behavioural consequences. We also examine the function of role overload as a factor influencing the relationship between safety values and the safety information exchange. Hierarchical linear modelling found that role overload moderated the relationship between supervisors’ perceptions of the value given to safety and the safety information exchange. A significant relationship was also found between the safety information exchange and the subsequent quality of the leader–member exchange relationship. Finally, the quality of the leader–member exchange relationship was found to be significantly associated with safe driving performance. Theoretical and practical implications of these results are discussed.     

An analysis of driving and working hour on commercial motor vehicle driver safety using naturalistic data collection

Current hours-of-service (HOS) regulations prescribe limits to commercial motor vehicle (CMV) drivers’ operating hours. By using naturalistic-data-collection, researchers were able to assess activities performed in the 14-h workday and the relationship between safety-critical events (SCEs) and driving hours, work hours, and breaks. The data used in the analyses were collected in the Naturalistic Truck Driving Study and included 97 drivers and about 735,000 miles of continuous driving data. An assessment of the drivers’ workday determined that, on average, drivers spent 66% of their shift driving, 23% in non-driving work, and 11% resting. Analyses evaluating the relationship between driving hours (i.e., driving only) and SCE risk found a time-on-task effect across hours, with no significant difference in safety outcomes between 11th driving hour and driving hours 8, 9 or 10. Analyses on work hours (i.e., driving in addition to non-driving work) found that risk of being involved in an SCE generally increased as work hours increased. This suggests that time-on-task effects may not be related to driving hours alone, but implies an interaction between driving hours and work hours: if a driver begins the day with several hours of non-driving work, followed by driving that goes deep into the 14-h workday, SCE risk was found to increase. Breaks from driving were found to be beneficial in reducing SCEs (during 1-h window after a break) and were effective in counteracting the negative effects of time-on-task.     

Getting the driver back into the loop: the quality of manual vehicle control following long and short non-critical transfer-of-control requests: TI:NS

ABSTRACT

Specific vehicle automation use-cases such as traffic jams will be the first level 3 functions on the market. When the ‘traffic jam pilot’ nears its limits in non-critical situations, control needs to be handed back to the driver, enabling appropriate situation awareness (SA) and vehicle handling. According to previous research, operational vehicle stabilisation can be achieved within a transfer-of-control (TOC) of a few seconds in simple traffic environments, but tactical level decisions benefit from longer hand-over times. To date, the effects of non-critical TOCs have not been studied using set time frames. To investigate the impact of short (unplanned, 5 seconds) and long (planned, 50 seconds) TOC requests, while playing/not playing an engaging tablet game, a simulator experiment was conducted with 16 participants. Comparisons of the 60-second-period of manual driving following automation suggest better longitudinal vehicle control as well as more appropriate SA following the long TOC request, and automation periods without the game. However, following no engaging game, lateral performance was worse during the first 10 seconds of manual driving. Control-level visual search patterns did not change with TOC time or the game. Future research needs to consider support for drivers’ SA maintenance and readiness to drive following high automation.     

Prevalence of teen driver errors leading to serious motor vehicle crashes

Objectives

Motor vehicle crashes are the leading cause of adolescent deaths. Programs and policies should target the most common and modifiable reasons for crashes. We estimated the frequency of critical reasons for crashes involving teen drivers, and examined in more depth specific teen driver errors.

Methods

The National Highway Traffic Safety Administration's (NHTSA) National Motor Vehicle Crash Causation Survey collected data at the scene of a nationally representative sample of 5470 serious crashes between 7/05 and 12/07. NHTSA researchers assigned a single driver, vehicle, or environmental factor as the critical reason for the event immediately leading to each crash. We analyzed crashes involving 15–18 year old drivers.

Results

822 teen drivers were involved in 795 serious crashes, representing 335,667 teens in 325,291 crashes. Driver error was by far the most common reason for crashes (95.6%), as opposed to vehicle or environmental factors. Among crashes with a driver error, a teen made the error 79.3% of the time (75.8% of all teen-involved crashes). Recognition errors (e.g., inadequate surveillance, distraction) accounted for 46.3% of all teen errors, followed by decision errors (e.g., following too closely, too fast for conditions) (40.1%) and performance errors (e.g., loss of control) (8.0%). Inadequate surveillance, driving too fast for conditions, and distracted driving together accounted for almost half of all crashes. Aggressive driving behavior, drowsy driving, and physical impairments were less commonly cited as critical reasons. Males and females had similar proportions of broadly classified errors, although females were specifically more likely to make inadequate surveillance errors.

Conclusions

Our findings support prioritization of interventions targeting driver distraction and surveillance and hazard awareness training.     

Safety improvements and driver perception

The paper deals with potential influences of engineering standards on driver perception. The argument is advanced that, in certain cases, the common belief that simplification of the driving task increases safety might be misleading. This might be the situation following engineering improvements. Driver confidence in the system may then be increased and driving task difficulties may be underestimated. As a result, decision criteria will be biased and driver attention level decreased. The overall effect is a degradation in driver performance which is due to a poorer detection of relevant cues and to poorer criteria. This degradation ultimately leads to an increase in accidents. The challenge of road engineering, therefore, should be to find the optimal balance between environmental demands (e.g. engineering standards and design levels) and drivers' perception of task difficulties.     

Thematic issue: driving automation and autonomy

ABSTRACT

Automated driving has the potential to support drivers, freeing them up to do other things, such as work, rest or play. The problem is that in the present instantiation, automated driving requires the driver to perform a monitoring function and be ready to intervene if required. This is the worst of all worlds of automation. The monitoring task can be (if performed properly) more demanding than manual driving and the driver is not freed up to do other things. Worse still, is that the monitoring task cannot be sustained for long and, on occasions, led to a vehicle collisions because the driver cannot intervene in a timely manner. One of the first studies conducted over twenty years shows this to be the case and there really has not been any improvements since. This special issue reports on the latest development in vehicle automation and points to future directions that research should be directed.     

Statistical implications of using moving violations to determine crash responsibility in young driver crashes

Traditional methods for determining crash responsibility – most commonly moving violation citations – may not accurately characterize at-fault status among crash-involved drivers given that: (1) issuance may vary by factors that are independent of fault (e.g., driver age, gender), and (2) these methods do not capture driver behaviors that are not illegal but still indicative of fault. We examined the statistical implications of using moving violations to determine crash responsibility in young driver crashes by comparing it with a method based on crash-contributing driver actions. We selected all drivers in police-reported passenger-vehicle crashes (2010–2011) that involved a New Jersey driver <21 years old (79,485 drivers < age 21, 61,355 drivers ≥ age 21). For each driver, crash responsibility was determined from the crash report using two alternative methods: (1) issuance of a moving violation citation; and (2) presence of a driver action (e.g., failure to yield, inattention). Overall, 18% of crash-involved drivers were issued a moving violation while 50% had a driver action. Only 32.2% of drivers with a driver action were cited for a moving violation. Further, the likelihood of being cited given the presence of a driver action was higher among certain driver subgroups—younger drivers, male drivers, and drivers in single-vehicle and more severe crashes. Specifically among young drivers, those driving at night, carrying peer passengers, and having a suspended or no license were more often cited. Conversely, fatally-injured drivers were almost never cited. We also demonstrated that using citation data may lead to statistical bias in the characterization of at-fault drivers and of quasi-induced exposure measures. Studies seeking to accurately determine crash responsibility should thoughtfully consider the potential sources of bias that may result from using legal culpability methods. For many studies, determining driver responsibility via the identification of driver actions may yield more accurate characterizations of at-fault drivers.     

The effects of texting on driving performance in a driving simulator: The influence of driver age

Distracted driving is a significant contributor to motor vehicle accidents and fatalities, and texting is a particularly significant form of driver distraction that continues to be on the rise. The present study examined the influence of driver age (18–59 years old) and other factors on the disruptive effects of texting on simulated driving behavior. While ‘driving’ the simulator, subjects were engaged in a series of brief text conversations with a member of the research team. The primary dependent variable was the occurrence of Lane Excursions (defined as any time the center of the vehicle moved outside the directed driving lane, e.g., into the lane for oncoming traffic or onto the shoulder of the road), measured as (1) the percent of subjects that exhibited Lane Excursions, (2) the number of Lane Excursions occurring and (3) the percent of the texting time in Lane Excursions. Multiple Regression analyses were used to assess the influence of several factors on driving performance while texting, including text task duration, texting skill level (subject-reported), texting history (#texts/week), driver gender and driver age. Lane Excursions were not observed in the absence of texting, but 66% of subjects overall exhibited Lane Excursions while texting. Multiple Regression analysis for all subjects (N = 50) revealed that text task duration was significantly correlated with the number of Lane Excursions, and texting skill level and driver age were significantly correlated with the percent of subjects exhibiting Lane Excursions. Driver gender was not significantly correlated with Lane Excursions during texting. Multiple Regression analysis of only highly skilled texters (N = 27) revealed that driver age was significantly correlated with the number of Lane Excursions, the percent of subjects exhibiting Lane Excursions and the percent of texting time in Lane Excursions. In contrast, Multiple Regression analysis of those drivers who self-identified as not highly skilled texters (N = 23) revealed that text task duration was significantly correlated with the number of Lane Excursions. The present studies confirm past reports that texting impairs driving simulator performance. Moreover, the present study demonstrates that for highly skilled texters, the effects of texting on driving are actually worse for older drivers. Given the increasing frequency of texting while driving within virtually all age groups, these data suggest that ‘no texting while driving’ education and public service messages need to be continued, and they should be expanded to target older drivers as well.     

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.     

Mitigating driver distraction with retrospective and concurrent feedback

OBJECTIVES: An experiment was conducted to assess the effects of retrospective and combined retrospective and concurrent feedback on driver performance and engagement in distracting activities. BACKGROUND: A previous study conducted by the authors showed that concurrent (or real time) feedback can help drivers better modulate their distracting activities. However, research also shows that concurrent feedback can pose additional distractions due to the limited time and resources available during driving. Retrospective feedback, which is presented at the end of a trip (i.e., post-drive), can include additional information on safety critical situations during a trip and help the driver learn safe driving habits. METHOD: A driving simulator study was conducted with 48 participants and 3 conditions: retrospective feedback, combined feedback (both retrospective and concurrent), and no feedback (baseline case). RESULTS: The feedback conditions (retrospective and combined) resulted in faster response to lead vehicle braking events as depicted by shorter accelerator release times. Moreover, combined feedback also resulted in longer glances to the road. CONCLUSIONS: The results suggest that both feedback types have potential to improve immediate driving performance and driver engagement in distractions. APPLICATION: Combined feedback holds the most promise for mitigating the effects of distraction from in-vehicle information systems.     

An outcome evaluation of the ‘Skipper’ designated driver program

The general aim of designated driver programs is to reduce the level of drink driving by encouraging potential drink drivers to travel with a driver who has abstained from (or at least limited) consuming alcohol. Designated driver programs appear to be quite widespread around the world, however a limited number have been subject to rigorous evaluation. This paper reports results from an outcome evaluation of a designated driver program called ‘Skipper’, which was trialled in a provincial city in Queensland, Australia. The outcome evaluation included surveys three weeks prior to (baseline), four months following (1st follow-up), and 16 months following (2nd follow-up) the commencement of the trial in both the ‘intervention area’ (baseline, n = 202; 1st follow-up, n = 211; 2nd follow-up, n = 200) and a ‘comparison area’(baseline, n = 203; 1st follow-up, n = 199; 2nd follow-up, n = 201); and a comparison of random breath testing and crash data before and after the trial. The survey results indicate that awareness of the program in the intervention area was quite high four months following its introduction and that this was maintained at 16 months. The results also suggest that the ‘Skipper’ program and the related publicity had positive impacts on behaviour with an increase in the proportion of people participating in designated driver as a passenger. It is less clear, however, whether the ‘Skipper’ program impacted on other behaviours of interest, such as drink driving or involvement in alcohol-related crashes. Suggestions for further research and program improvement are discussed as well as limitations of the research.     

The driver,the road,the rules … and the rest? A systems-based approach to young driver road safety

The persistent overrepresentation of young drivers in road crashes is universally recognised. A multitude of factors influencing their behaviour and safety have been identified through methods including crash analyses, simulated and naturalistic driving studies, and self-report measures. Across the globe numerous, diverse, countermeasures have been implemented; the design of the vast majority of these has been informed by a driver-centric approach. An alternative approach gaining popularity in transport safety is the systems approach which considers not only the characteristics of the individual, but also the decisions and actions of other actors within the road transport system, along with the interactions amongst them. This paper argues that for substantial improvements to be made in young driver road safety, what has been learnt from driver-centric research needs to be integrated into a systems approach, thus providing a holistic appraisal of the young driver road safety problem. Only then will more effective opportunities and avenues for intervention be realised.