The effects of on-street parking and road environment visual complexity on travel speed and reaction time

On-street parking is associated with elevated crash risk. It is not known how drivers’ mental workload and behaviour in the presence of on-street parking contributes to, or fails to reduce, this increased crash risk. On-street parking tends to co-exist with visually complex streetscapes that may affect workload and crash risk in their own right. The present paper reports results from a driving simulator study examining the effects of on-street parking and road environment visual complexity on driver behaviour and surrogate measures of crash risk. Twenty-nine participants drove a simulated urban commercial and arterial route. Compared to sections with no parking bays or empty parking bays, in the presence of occupied parking bays drivers lowered their speed and shifted their lateral position towards roadway centre to compensate for the higher mental workload they reported experiencing. However, this compensation was not sufficient to reduce drivers’ reaction time on a safety-relevant peripheral detection task or to an unexpected pedestrian hazard. Compared to the urban road environments, the less visually complex arterial road environment was associated with speeds that were closer to the posted limit, lower speed variability and lower workload ratings. These results support theoretical positions that proffer workload as a mediating variable of speed choice. However, drivers in this study did not modify their speed sufficiently to maintain safe hazard response times in complex environments with on-street parking. This inadequate speed compensation is likely to affect real world crash risk.     

Does attention capacity moderate the effect of driver distraction in older drivers?

With age, a decline in attention capacity may occur and this may impact driving performance especially while distracted. Although the effect of distraction on driving performance of older drivers has been investigated, the moderating effect of attention capacity on driving performance during distraction has not been investigated yet. Therefore, the aim was to investigate whether attention capacity has a moderating effect on older drivers’ driving performance during visual distraction (experiment 1) and cognitive distraction (experiment 2). In a fixed-based driving simulator, older drivers completed a driving task without and with visual distraction (experiment 1, N = 17, mean age 78 years) or cognitive distraction (experiment 2, N = 35, mean age 76 years). Several specific driving measures of varying complexity (i.e., speed, lane keeping, following distance, braking behavior, and crashes) were investigated. In addition to these objective driving measures, subjective measures of workload and driving performance were also included. In experiment 1, crash occurrence increased with visual distraction and was negatively related to attention capacity. In experiment 2, complete stops at stop signs decreased, initiation of braking at pedestrian crossings was later, and crash occurrence increased with cognitive distraction. Interestingly, for a measure of lane keeping (i.e., standard deviation of lateral lane position (SDLP)), effects of both types of distraction were moderated by attention capacity. Despite the decrease of driving performance with distraction, participants estimated their driving performance during distraction as good. These results imply that attention capacity is important for driving. Driver assessment and training programs might therefore focus on attention capacity. Nonetheless, it is crucial to eliminate driver distraction as much as possible given the deterioration of performance on several driving measures in those with low and high attention capacity.     

EEG alpha spindles and prolonged brake reaction times during auditory distraction in an on-road driving study

Driver distraction is responsible for a substantial number of traffic accidents. This paper describes the impact of an auditory secondary task on drivers’ mental states during a primary driving task. N = 20 participants performed the test procedure in a car following task with repeated forced braking on a non-public test track. Performance measures (provoked reaction time to brake lights) and brain activity (EEG alpha spindles) were analyzed to describe distracted drivers. Further, a classification approach was used to investigate whether alpha spindles can predict drivers’ mental states.     

Where do novice and experienced drivers direct their attention on approach to urban rail level crossings?

Crashes at rail level crossings (RLXs) remain a persistent but ill-defined safety issue. In urban areas, RLXs are typically located in areas of high workload and visual clutter, such as busy shopping strips. Despite this, the impact of such environments on driver behaviour and compliance with RLX controls is not well understood. This study sought to examine where drivers direct their attention on approach to urban RLXs located in busy shopping strip areas, and whether this differs between novice and experienced drivers. Participants drove an instrumented vehicle around a pre-defined urban route containing several active (flashing light with boom barriers) RLXs. Drivers’ visual scanning behaviour and cognitive processes were examined on approach to RLXs. The results suggest that RLXs were not a key focus of drivers’ attention. Further, rather than actively scanning, participants were over-reliant on RLX warning signals and the behaviour of surrounding vehicles to alert them to the presence of both trains and RLXs. This study provides important insights into drivers’ visual and cognitive behaviour on approach to urban RLXs located in areas of high visual demand.     

Driver's visual attention as a function of driving experience and visibility. Using a driving simulator to explore drivers’ eye movements in day, night and rain driving

Road crashes are the main cause of death of young people in the developed world. The reasons that cause traffic crashes are numerous; however, most researchers agree that a lack of driving experience is one of the major contributing factors. In addition it has been demonstrated that environmental factors such as driving during night and rain increases the risk of a crash. Both of these factors may be related to drivers’ visual search strategies that become more efficient with increased experience.In the present study we recorded the eye movements of driving instructors and learner drivers while they drove three virtual routes that included day, night and rain routes in a driving simulator.The results showed that driving instructors had an increased sampling rate, shorter processing time and broader scanning of the road than learner drivers. This broader scanning of the road could be possibly explained by the mirror inspection pattern which revealed that driving instructors fixated more on the side mirrors than learner drivers. Also it was found that poor visibility conditions, especially rain, decrease the effectiveness of drivers’ visual search. The lack of interaction between driving experience and visibility suggests that some aspects of visual search are affected by general rather than situation specific driving experience.The present findings support the effect of driving experience in modifying eye movement strategies. The high accident risk of night and rain driving could be partly explained by the decrement in visual search strategies during these conditions. Finally it is argued that the use of driving simulators can provide valuable insights regarding driving safety.     

Exploring precrash maneuvers using classification trees and random forests

Taking evasive actions vis-à-vis critical traffic situations impending to motor vehicle crashes endows drivers an opportunity to avoid the crash occurrence or at least diminish its severity. This study explores the drivers, vehicles, and environments’ characteristics associated with crash avoidance maneuvers (i.e., evasive actions or no evasive actions). Rear-end collisions, head-on collisions, and angle collisions are analyzed separately using decision trees and the significance of the variables on the binary response variable (evasive actions or no evasive actions) is determined. Moreover, the random forests method is employed to rank the importance of the drivers/vehicles/environments characteristics on crash avoidance maneuvers. According to the exploratory analyses’ results, drivers’ visibility obstruction, drivers’ physical impairment, drivers’ distraction are associated with crash avoidance maneuvers in all three types of accidents. Moreover, speed limit is associated with rear-end collisions’ avoidance maneuvers and vehicle type is correlated with head-on collisions and angle collisions’ avoidance maneuvers. It is recommended that future research investigates further the explored trends (e.g., physically impaired drivers, visibility obstruction) using driving simulators which may help in legislative initiatives and in-vehicle technology recommendations.     

The effect of the learner license Graduated Driver Licensing components on teen drivers’ crashes

Background

Most studies evaluating the effectiveness of Graduated Driver Licensing (GDL) have focused on the overall system. Studies examining individual components have rarely accounted for the confounding of multiple, simultaneously implemented components. The purpose of this paper is to quantify the effects of a required learner license duration and required hours of supervised driving on teen driver fatal crashes.

Methods

States that introduced a single GDL component independent of any other during the period 1990–2009 were identified. Monthly and quarterly fatal crash rates per 100,000 population of 16- and 17-year-old drivers were analyzed using single-state time series analysis, adjusting for adult crash rates and gasoline prices. Using the parameter estimates from each state's time series model, the pooled effect of each GDL component on 16- and 17-year-old drivers’ fatal crashes was estimated using a random effects meta-analytic model to combine findings across states.

Results

In three states, a six-month minimum learner license duration was associated with a significant decline in combined 16- and 17-year-old drivers’ fatal crash rates. The pooled effect of the minimum learner license duration across all states in the sample was associated with a significant change in combined 16- and 17-year-old driver fatal crash rates of −.07 (95% Confidence Interval [CI] −.11, −.03). Following the introduction of 30 h of required supervised driving in one state, novice drivers’ fatal crash rates increased 35%. The pooled effect across all states in the study sample of having a supervised driving hour requirement was not significantly different from zero (.04, 95% CI −.15, .22).

Conclusion

These findings suggest that a learner license duration of at least six-months may be necessary to achieve a significant decline in teen drivers’ fatal crash rates. Evidence of the effect of required hours of supervised driving on teen drivers’ fatal crash rates was mixed.     

The effects of age,gender, and crash types on drivers’ injury-related health care costs

There are many studies that evaluate the effects of age, gender, and crash types on crash related injury severity. However, few studies investigate the effects of those crash factors on the crash related health care costs for drivers that are transported to hospital. The purpose of this study is to examine the relationships between drivers’ age, gender, and the crash types, as well as other crash characteristics (e.g., not wearing a seatbelt, weather condition, and fatigued driving), on the crash related health care costs. The South Carolina Crash Outcome Data Evaluation System (SC CODES) from 2005 to 2007 was used to construct six separate hierarchical linear regression models based on drivers’ age and gender. The results suggest that older drivers have higher health care costs than younger drivers and male drivers tend to have higher health care costs than female drivers in the same age group. Overall, single vehicle crashes had the highest health care costs for all drivers. For males older than 64-years old sideswipe crashes are as costly as single vehicle crashes. In general, not wearing a seatbelt, airbag deployment, and speeding were found to be associated with higher health care costs. Distraction-related crashes are more likely to be associated with lower health care costs in most cases. Furthermore this study highlights the value of considering drivers in subgroups, as some factors have different effects on health care costs in different driver groups. Developing an understanding of longer term outcomes of crashes and their characteristics can lead to improvements in vehicle technology, educational materials, and interventions to reduce crash-related health care costs.     

How realistic are older drivers’ ratings of their driving ability?

One strategy that can be used by older drivers to guard against age-related declines in driving capability is to regulate their driving. This strategy presumes that self-judgments of driving capability are realistic. We found no significant relationships between older drivers’ hazard perception skill ratings and performance on an objective and validated video-based hazard perception test, even when self-ratings of performance on specific scenarios in the test were used. Self-enhancement biases were found across all components of driving skill, including hazard perception. If older drivers’ judgments of their driving capability are unrealistic, then this may compromise the effectiveness of any self-restriction strategies to reduce crash risk.     

Concealing their communication: Exploring psychosocial predictors of young drivers’ intentions and engagement in concealed texting

Making a conscious effort to hide the fact that you are texting while driving (i.e., concealed texting) is a deliberate and risky behaviour involving attention diverted away from the road. As the most frequent users of text messaging services and mobile phones while driving, young people appear at heightened risk of crashing from engaging in this behaviour. This study investigated the phenomenon of concealed texting while driving, and utilised an extended Theory of Planned Behaviour (TPB) including the additional predictors of moral norm, mobile phone involvement, and anticipated regret to predict young drivers’ intentions and subsequent behaviour. Participants (n = 171) were aged 17–25 years, owned a mobile phone, and had a current driver's licence. Participants completed a questionnaire measuring their intention to conceal texting while driving, and a follow-up questionnaire a week later to report their behavioural engagement. The results of hierarchical multiple regression analyses showed overall support for the predictive utility of the TPB with the standard constructs accounting for 69% of variance in drivers’ intentions, and the extended predictors contributing an additional 6% of variance in intentions over and above the standard constructs. Attitude, subjective norm, PBC, moral norm, and mobile phone involvement emerged as significant predictors of intentions; and intention was the only significant predictor of drivers’ self-reported behaviour. These constructs can provide insight into key focal points for countermeasures including advertising and other public education strategies aimed at influencing young drivers to reconsider their engagement in this risky behaviour.     

Impact of traffic states on freeway crash involvement rates

Freeway traffic accidents are complicated events that are influenced by multiple factors including roadway geometry, drivers’ behavior, traffic conditions and environmental factors. Among the various factors, crash occurrence on freeways is supposed to be strongly influenced by the traffic states representing driving situations that are changed by road geometry and cause the change of drivers’ behavior. This paper proposes a methodology to investigate the relationship between traffic states and crash involvements on the freeway. First, we defined section-based traffic states: free flow (FF), back of queue (BQ), bottleneck front (BN) and congestion (CT) according to their distinctive patterns; and traffic states of each freeway section are determined based on actual measurements of traffic data from upstream and downstream ends of the section. Next, freeway crash data are integrated with the traffic states of a freeway section using upstream and downstream traffic measurements. As an illustrative study to show the applicability, we applied the proposed method on a 32-mile section of I-880 freeway. By integrating freeway crash occurrence and traffic data over a three-year period, we obtained the crash involvement rate for each traffic state. The results show that crash involvement rate in BN, BQ, and CT states are approximately 5 times higher than the one in FF. The proposed method shows promise to be used for various safety performance measurement including hot spot identification and prediction of the number of crash involvements on freeway sections.     

Elderly drivers’ everyday behavior as a predictor of crash involvement—Questionnaire responses by drivers’ family members

When or whether elderly drivers stop driving is concerning not only to the drivers themselves but also to their family members. Therefore, it is important for family members to take the initiative if they wish to obtain information on the likelihood of the drivers’ involvement in crashes. On the basis of the older drivers’ Everyday Behavior Questionnaire (EBQ) developed in this paper, we attempt to predict drivers’ involvement in crashes using the responses given by their family members. The results revealed that this 14-item questionnaire has a sufficient level of internal consistency as well as a significant correlation (r = 0.29) with the experience of involvement in crashes in the last three years (p < 0.01). Although the EBQ is a proxy-reported questionnaire and does not include items directly related to driving behaviors, the correlation between the EBQ and crash involvement is stronger than that of the self-reported Driver Behavior Questionnaire reported in deWinter and Dodou (2010), who conducted a meta-analysis and estimated the overall correlation among samples of earlier studies. In addition, logistic regression analysis showed that the EBQ score and the exposure to driving risks, measured by the frequency of driving, are significant predictors of involvement in crashes.     

Reliability of drivers in urban intersections

The concept of human reliability has been widely used in industrial settings by human factors experts to optimise the person-task fit. Reliability is estimated by the probability that a task will successfully be completed by personnel in a given stage of system operation. Human Reliability Analysis (HRA) is a technique used to calculate human error probabilities as the ratio of errors committed to the number of opportunities for that error. To transfer this notion to the measurement of car driver reliability the following components are necessary: a taxonomy of driving tasks, a definition of correct behaviour in each of these tasks, a list of errors as deviations from the correct actions and an adequate observation method to register errors and opportunities for these errors. Use of the SAFE-task analysis procedure recently made it possible to derive driver errors directly from the normative analysis of behavioural requirements. Driver reliability estimates could be used to compare groups of tasks (e.g. different types of intersections with their respective regulations) as well as groups of drivers’ or individual drivers’ aptitudes. This approach was tested in a field study with 62 drivers of different age groups. The subjects drove an instrumented car and had to complete an urban test route, the main features of which were 18 intersections representing six different driving tasks. The subjects were accompanied by two trained observers who recorded driver errors using standardized observation sheets. Results indicate that error indices often vary between both the age group of drivers and the type of driving task. The highest error indices occurred in the non-signalised intersection tasks and the roundabout, which exactly equals the corresponding ratings of task complexity from the SAFE analysis. A comparison of age groups clearly shows the disadvantage of older drivers, whose error indices in nearly all tasks are significantly higher than those of the other groups. The vast majority of these errors could be explained by high task load in the intersections, as they represent difficult tasks. The discussion shows how reliability estimates can be used in a constructive way to propose changes in car design, intersection layout and regulation as well as driver training.     

Older drivers' insight into their hazard perception ability

Even though the driving ability of older adults may decline with age, there is evidence that some individuals attempt to compensate for these declines using strategies such as restricting their driving exposure. Such compensatory mechanisms rely on drivers’ ability to evaluate their own driving performance. This paper focuses on one key aspect of driver ability that is associated with crash risk and has been found to decline with age: hazard perception. Three hundred and seven drivers, aged 65–96, completed a validated video-based hazard perception test. There was no significant relationship between hazard perception test response latencies and drivers’ ratings of their hazard perception test performance, suggesting that their ability to assess their own test performance was poor. Also, age-related declines in hazard perception latency were not reflected in drivers’ self-ratings. Nonetheless, ratings of test performance were associated with self-reported regulation of driving, as was self-rated driving ability. These findings are consistent with the proposal that, whileself-assessments of driving ability may be used by drivers to determine the degree to which they restrict their driving, the problem is that drivershave little insight into their own driving ability. This may impact on the potential road safety benefits of self-restriction of driving because drivers may not have the information needed to optimally self-restrict. Strategies for addressing this problem are discussed.     

A brief peripheral motion contrast threshold test predicts older drivers’ hazardous behaviors in simulated driving

Our research group has previously demonstrated that the peripheral motion contrast threshold (PMCT) test predicts older drivers’ self-report accident risk, as well as simulated driving performance. However, the PMCT is too lengthy to be a part of a battery of tests to assess fitness to drive. Therefore, we have developed a new version of this test, which takes under two minutes to administer. We assessed the motion contrast thresholds of 24 younger drivers (19–32) and 25 older drivers (65–83) with both the PMCT-10 min and the PMCT-2 min test and investigated if thresholds were associated with measures of simulated driving performance. Younger participants had significantly lower motion contrast thresholds than older participants and there were no significant correlations between younger participants’ thresholds and any measures of driving performance. The PMCT-10 min and the PMCT-2 min thresholds of older drivers’ predicted simulated crash risk, as well as the minimum distance of approach to all hazards. This suggests that our tests of motion processing can help predict the risk of collision or near collision in older drivers. Thresholds were also correlated with the total lane deviation time, suggesting a deficiency in processing of peripheral flow and delayed detection of adjacent cars. The PMCT-2 min is an improved version of a previously validated test, and it has the potential to help assess older drivers’ fitness to drive.     

Understanding commercial truck drivers’ decision-makin process concerning distracted driving

A concurrent mixed methods design was used to explore personal and workplace factors, informed by the Theory of Planned Behavior, that affect truck drivers’ decision-making about distracted driving on the job. Qualitative data were collected via semi-structured interviews with experts in truck safety and distracted driving, and quantitative data were collected via online survey of truck drivers in the United States. Findings from the interviews illustrated how drivers perceived distractions and the importance of supervisors enforcing organizational distracted driving policies. Survey results found that behavioral intentions were most important in regards to texting and crash and near-crash outcomes, while perceived norms from management best described the correlation between dispatch device use and negative crash-related outcomes. By using a mixed methods design, rather than two separate studies, these findings revealed nuanced differences into the influence of supervisors on distracted driving.     

Comprehension and acceptability of on-board traffic information: Beliefs and driving behaviour

Co-Drive on-board traffic information system is a complementary tool providing a dynamic management of transportation infrastructure and traffic as well as the diffusion of accurate real-time information about the road environment and motorists’ driving behaviour. The aim of this study was to examine drivers’ acceptability of Co-Drive by investigating the impact of traffic information provided via on-board display devices on motorists’ beliefs and behaviour.     

Velocity,safety, or both? How do balance and strength of goal conflicts affect drivers’ behaviour,feelings and physiological responses?

Motivational models of driving behaviour agree that choice of speed is modulated by drivers’ goals. Whilst it is accepted that some goals favour fast driving and others favour safe driving, little is known about the interplay of these conflicting goals. In the present study, two aspects of this interplay are investigated: the balance of conflict and the strength of conflict. Thirty-two participants completed several simulated driving runs in which fast driving was rewarded with a monetary gain if the end of the track was reached. However, unpredictably, some runs ended with the appearance of a deer. In these runs, fast driving was punished with a monetary loss. The ratio between the magnitudes of gains and losses varied in order to manipulate the balance of conflict. The absolute magnitudes of both gains and losses altered the strength of conflict. Participants drove slower, reported an increase in anxiety-related feelings, and showed indications of physiological arousal if there was more money at stake. In contrast, only marginal effects of varying the ratio between gains and losses were observed. Results confirm that the strength of a safety–velocity conflict is an important determinant of drivers’ behaviour, feelings, and physiological responses. The lack of evidence for the balance of conflict playing a role suggests that in each condition, participants subjectively weighted the loss higher than the gain (loss aversion). It is concluded that the interplay of the subjective values that drivers attribute to objective incentives for fast and safe driving is a promising field for future research. Incorporating this knowledge into motivational theories of driving behaviour might improve their contribution to the design of adequate road safety measures.     

Young driver crash rates by licensing age,driving experience,and license phase

Background

Few studies have concurrently assessed the influence of age and experience on young driver crashes, in particular in the post-Graduated Driver Licensing (GDL) era. Further, little attention is given to the transition from intermediate to full licensure. We examined the independent and joint contributions of licensing age, driving experience, and GDL license phase on crash rates among the population of young New Jersey (NJ) drivers.

Methods

From a unique linked database containing licensing and crash data, we selected all drivers who obtained their NJ intermediate license at 17–20 years old from 2006–2009 (n = 410,230). We determined the exact age at which each driver obtained an intermediate and full license and created distinct, fixed cohorts of drivers based on their age at intermediate licensure. For each cohort, we calculated and graphed observed monthly crash rates over the first 24 months of licensure. Further, we examined crash rates by age at licensure, driving experience (i.e., time since licensure), and license phase.

Results

First-month crash rates were higher among the youngest drivers (licensed at 17y0m). Drivers who were licensed later experienced a reduced “steepness” in the slope of their crash rates in the critical initial months of driving, but there did not appear to be any incremental benefit of later licensure once drivers had six months of driving experience. Further, at each age, those with more driving experience had lower crash rates; however, the benefit of increased experience was greatest for the substantial proportion of teens licensed immediately after becoming eligible (at 17y0m). Finally, independent of age and experience, teen drivers’ crash risk increased substantially at the point of transition to a full license, while drivers of a similar age who remained in the intermediate phase continued to experience a decline in crash rates.

Conclusion

Age and driving experience interact to influence crash rates. Further, independent of these two factors, there is an abrupt increase in crash risk at the point of transition from intermediate to full licensure. Future studies should investigate whether this increase is accounted for by a change in driving exposure, driving behaviors, and/or other factors.     

Young drivers' optimism bias for accident risk and driving skill: Accountability and insight experience manipulations

This study aimed to determine whether two brief, low cost interventions would reduce young drivers’ optimism bias for their driving skills and accident risk perceptions. This tendency for such drivers to perceive themselves as more skilful and less prone to driving accidents than their peers may lead to less engagement in precautionary driving behaviours and a greater engagement in more dangerous driving behaviour. 243 young drivers (aged 17–25 years) were randomly allocated to one of three groups: accountability, insight or control. All participants provided both overall and specific situation ratings of their driving skills and accident risk relative to a typical young driver. Prior to completing the questionnaire, those in the accountability condition were first advised that their driving skills and accident risk would be later assessed via a driving simulator. Those in the insight condition first underwent a difficult computer-based hazard perception task designed to provide participants with insight into their potential limitations when responding to hazards in difficult and unpredictable driving situations. Participants in the control condition completed only the questionnaire. Results showed that the accountability manipulation was effective in reducing optimism bias in terms of participants’ comparative ratings of their accident risk in specific situations, though only for less experienced drivers. In contrast, among more experienced males, participants in the insight condition showed greater optimism bias for overall accident risk than their counterparts in the accountability or control groups. There were no effects of the manipulations on drivers’ skills ratings. The differential effects of the two types of manipulations on optimism bias relating to one's accident risk in different subgroups of the young driver sample highlight the importance of targeting interventions for different levels of experience. Accountability interventions may be beneficial for less experienced young drivers but the results suggest exercising caution with the use of insight type interventions, particularly hazard perception style tasks, for more experienced young drivers typically still in the provisional stage of graduated licensing systems.