Merging into heavy motorway traffic by young and elderly drivers

An increase in the number of Heavy Goods Vehicles on motorways may lead to additional problems in the interaction with an increased number of elderly drivers. Elderly drivers suffer from reduced information processing speed and capacity, and in general effectively compensate for this by taking more time. However, this strategy, regulating task demands by slowing down will make merging into motorway traffic actually more difficult.In an experiment performed in a driving simulator, young and elderly drivers merged into motorway traffic. Driver behaviour and mental workload were studied while the following factors were manipulated: type of traffic and density of Heavy Goods Vehicles on the main road, the length of the acceleration lane, presence of a slowly driving lead car, and presence of a driver support system that encouraged the drivers to speed up if their speed was too low.Results show that the effects of an increased number of Heavy Goods Vehicles on the main road were not more adverse for elderly than for the young participants, with the exception that elderly drivers merged at a lower speed. This lower speed could make the manoeuvre more risky in real traffic. The support system and an extended acceleration lane facilitated merging, while a slowly driving lead car impeded completion of the manoeuvre.     

Drivers' reactions to sudden braking by lead car under varying workload conditions; towards a driver support system

At urban intersections drivers handle multiple tasks simultaneously, making urban driving a complex task. An advanced driver assistance system may support drivers in this specific driving task, but the design details of such a system need to be determined before they can be fully deployed. A driving simulator experiment was conducted to determine the relationship between different subtasks of driving at urban intersections. Participants completed four drives, each comprising 20 comparable intersections with different traffic situations and encountered one unexpected braking event during the experiment. The effects of varying levels of event urgency on the relationship between different driving subtasks were studied. Furthermore, the influence of workload on this relationship was determined by giving half of the subjects an additional cognitive task. After the lead car braked unexpectedly, participants reduced speed and increased headway depending on the urgency of the braking event. Depending on the workload, participants returned to the normal speed and headway again after a number of intersections. Participants experiencing a high-workload drove more smoothly, except for those who had experienced the most urgent unexpected event. High workload additionally affected the length of the adjustments to the unexpected event.     

The consequences of an increase in heavy goods vehicles for passenger car drivers' mental workload and behaviour: a simulator study

The effects of an increase in Heavy Goods Vehicles (HGVs) on merging behaviour and on mental workload of motorists during filtering in and out of traffic were studied. Participants drove in a driving simulator in a total of 12 conditions; twice in each of two weather conditions and in three traffic conditions. The weather conditions were clear weather and foggy weather. The traffic conditions were without HGVs (i.e. only private cars), the current mix of HGVs and private cars, and a condition with a 70% increase of HGVs leading to an HGV column in the slow lane. The focus of the study was on assessing effects on behaviour and mental workload during filtering into traffic, and during exiting from the motorway. During the experiment driving performance was registered, behaviour was observed, self reports were collected, and the participant's heart rate was recorded. The results showed that directly after filtering into traffic the variation in driving speed increased and the minimum time headway decreased with an increase in the proportion of HGVs. Joining motorway traffic was considered to involve greater effort and risk in the condition with a column of HGVs. The effects of the conditions on heart rate are less clear, although the moment when the participants joined the traffic is clearly visible. The effects of weather conditions were limited, drivers adapting their driving behaviour in adverse weather by reducing speed. To exit the motorway is not a difficult manoeuvre. For that reason the lane change from the left hand to the right hand lane that preceded the exit was analysed. Although increased mental effort was reported and the lane change was visible in the heart rate record, no critical changes as a result of increase in proportion of HGVs were found for this manoeuvre. However, in the condition with a column of HGVs, the exit that had to be taken was most frequently missed as HGVs obstructed the view of the exit signs. It is concluded that an increase in HGVs will make merging into traffic more mentally demanding and will decrease safety margins.     

Efficient driver drowsiness detection at moderate levels of drowsiness

Previous research on driver drowsiness detection has focused primarily on lane deviation metrics and high levels of fatigue. The present research sought to develop a method for detecting driver drowsiness at more moderate levels of fatigue, well before accident risk is imminent. Eighty-seven different driver drowsiness detection metrics proposed in the literature were evaluated in two simulated shift work studies with high-fidelity simulator driving in a controlled laboratory environment. Twenty-nine participants were subjected to a night shift condition, which resulted in moderate levels of fatigue; 12 participants were in a day shift condition, which served as control. Ten simulated work days in the study design each included four 30-min driving sessions, during which participants drove a standardized scenario of rural highways. Ten straight and uneventful road segments in each driving session were designated to extract the 87 different driving metrics being evaluated. The dimensionality of the overall data set across all participants, all driving sessions and all road segments was reduced with principal component analysis, which revealed that there were two dominant dimensions: measures of steering wheel variability and measures of lateral lane position variability. The latter correlated most with an independent measure of fatigue, namely performance on a psychomotor vigilance test administered prior to each drive. We replicated our findings across eight curved road segments used for validation in each driving session. Furthermore, we showed that lateral lane position variability could be derived from measured changes in steering wheel angle through a transfer function, reflecting how steering wheel movements change vehicle heading in accordance with the forces acting on the vehicle and the road. This is important given that traditional video-based lane tracking technology is prone to data loss when lane markers are missing, when weather conditions are bad, or in darkness. Our research findings indicated that steering wheel variability provides a basis for developing a cost-effective and easy-to-install alternative technology for in-vehicle driver drowsiness detection at moderate levels of fatigue.     

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.     

Effects of steering demand on lane keeping behaviour, self-reports, and physiology. A simulator study

In this study a driving simulator was used to determine changes in mental effort in response to manipulations of steering demand. Changes in mental effort were assessed by using subjective effort ratings, physiology, and the standard deviation of the lateral position. Steering demand was increased by exposure to narrow lane widths and high density oncoming traffic while speed was fixed in all conditions to prevent a compensatory reaction. Results indicated that both steering demand factors influence mental effort expenditure and using multiple measures contributes to effort assessment. Application of these outcomes for adaptive automation is envisaged.     

Validating a driving simulator using surrogate safety measures

Traffic crash statistics and previous research have shown an increased risk of traffic crashes at signalized intersections. How to diagnose safety problems and develop effective countermeasures to reduce crash rate at intersections is a key task for traffic engineers and researchers. This study aims at investigating whether the driving simulator can be used as a valid tool to assess traffic safety at signalized intersections. In support of the research objective, this simulator validity study was conducted from two perspectives, a traffic parameter (speed) and a safety parameter (crash history). A signalized intersection with as many important features (including roadway geometries, traffic control devices, intersection surroundings, and buildings) was replicated into a high-fidelity driving simulator. A driving simulator experiment with eight scenarios at the intersection were conducted to determine if the subjects' speed behavior and traffic risk patterns in the driving simulator were similar to what were found at the real intersection. The experiment results showed that speed data observed from the field and in the simulator experiment both follow normal distributions and have equal means for each intersection approach, which validated the driving simulator in absolute terms. Furthermore, this study used an innovative approach of using surrogate safety measures from the simulator to contrast with the crash analysis for the field data. The simulator experiment results indicated that compared to the right-turn lane with the low rear-end crash history record (2 crashes), subjects showed a series of more risky behaviors at the right-turn lane with the high rear-end crash history record (16 crashes), including higher deceleration rate (1.80+/-1.20 m/s(2) versus 0.80+/-0.65 m/s(2)), higher non-stop right-turn rate on red (81.67% versus 57.63%), higher right-turn speed as stop line (18.38+/-8.90 km/h versus 14.68+/-6.04 km/h), shorter following distance (30.19+/-13.43 m versus 35.58+/-13.41 m), and higher rear-end probability (9/59=0.153 versus 2/60=0.033). Therefore, the relative validity of driving simulator was well established for the traffic safety studies at signalized intersections.     

The effects of visibility conditions,traffic density,and navigational challenge on speed compensation and driving performance in older adults

Research on how older drivers react to natural challenges in the driving environment is relevant for both the research on mental workload and that on age-related compensation. Older adults (M age = 70.8 years) were tested in a driving simulator to assess the impact of three driving challenges: a visibility challenge (clear day, fog), a traffic density challenge (low density, high density) and a navigational challenge (participants followed the road to arrive at their destination, participants had to use signs and landmarks). The three challenge manipulations induced different compensatory speed adjustments. This complicated interpretation of the other measures of driving performance. As a result, speed adjustment indices were calculated for each condition and participant and composite measures of performance were created to correct for speed compensation. (These speed adjustment indices correlated with vision test scores and subscales of the Useful Field of View^®.) When the composite measures of driving performance were analyzed, visibility × density × navigational challenge interactions emerged for hazard RT and SD of lane position. Effects were synergistic: the impact of the interaction of challenge variables was greater than the sum of independent effects. The directions of the effects varied depending on the performance measure in question though. For hazard RT, the combined effects of high-density traffic and navigational challenge were more deleterious in good visibility conditions than in fog. For or SD of lane position, the opposite pattern emerged: combined effects of high-density traffic and navigational challenge were more deleterious in fog than in clear weather. This suggests different aspects of driving performance tap different resources.     

Texting while driving using Google Glass™: Promising but not distraction-free

Texting while driving is risky but common. This study evaluated how texting using a Head-Mounted Display, Google Glass, impacts driving performance. Experienced drivers performed a classic car-following task while using three different interfaces to text: fully manual interaction with a head-down smartphone, vocal interaction with a smartphone, and vocal interaction with Google Glass. Fully manual interaction produced worse driving performance than either of the other interaction methods, leading to more lane excursions and variable vehicle control, and higher workload. Compared to texting vocally with a smartphone, texting using Google Glass produced fewer lane excursions, more braking responses, and lower workload. All forms of texting impaired driving performance compared to undistracted driving. These results imply that the use of Google Glass for texting impairs driving, but its Head-Mounted Display configuration and speech recognition technology may be safer than texting using a smartphone.     

Impact of distracted driving on safety and traffic flow

Studies have documented a link between distracted driving and diminished safety; however, an association between distracted driving and traffic congestion has not been investigated in depth. The present study examined the behavior of teens and young adults operating a driving simulator while engaged in various distractions (i.e., cell phone, texting, and undistracted) and driving conditions (i.e., free flow, stable flow, and oversaturation). Seventy five participants 16–25 years of age (split into 2 groups: novice drivers and young adults) drove a STISIM simulator three times, each time with one of three randomly presented distractions. Each drive was designed to represent daytime scenery on a 4 lane divided roadway and included three equal roadway portions representing Levels of Service (LOS) A, C, and E as defined in the 2000 Highway Capacity Manual. Participants also completed questionnaires documenting demographics and driving history. Both safety and traffic flow related driving outcomes were considered. A Repeated Measures Multivariate Analysis of Variance was employed to analyze continuous outcome variables and a Generalized Estimate Equation (GEE) Poisson model was used to analyze count variables. Results revealed that, in general more lane deviations and crashes occurred during texting. Distraction (in most cases, text messaging) had a significantly negative impact on traffic flow, such that participants exhibited greater fluctuation in speed, changed lanes significantly fewer times, and took longer to complete the scenario. In turn, more simulated vehicles passed the participant drivers while they were texting or talking on a cell phone than while undistracted. The results indicate that distracted driving, particularly texting, may lead to reduced safety and traffic flow, thus having a negative impact on traffic operations. No significant differences were detected between age groups, suggesting that all drivers, regardless of age, may drive in a manner that impacts safety and traffic flow negatively when distracted.     

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.     

A simulator study of the effects of singing on driving performance

This study aimed to investigate how singing while driving affects driver performance. Twenty-one participants completed three trials of a simulated drive concurrently while performing a peripheral detection task (PDT); each trial was conducted either without music, with participants listening to music, or with participants singing along to music. It was hypothesised that driving performance and PDT response times would be impaired, and that driver subjective workload ratings would be higher, when participants were singing to music compared to when there was no music or when participants were listening to music. As expected, singing while driving was rated as more mentally demanding, and resulted in slower and more variable speeds, than driving without music. Listening to music was associated with the slowest speeds overall, and fewer lane excursions than the no music condition. Interestingly, both music conditions were associated with slower speed-adjusted PDT response times and significantly less deviation within the lane than was driving without music. Collectively, results suggest that singing while driving alters driving performance and impairs hazard perception while at the same time increasing subjective mental workload. However, singing while driving does not appear to affect driving performance more than simply listening to music. Further, drivers’ efforts to compensate for the increased mental workload associated with singing and listening to music by slowing down appear to be insufficient, as evidenced by relative increases in PDT response times in these two conditions compared to baseline.     

The effect of chevron alignment signs on driver performance on horizontal curves with different roadway geometries

To develop a practicable and clear guideline for implementing Chevrons on China’s highways, it is necessary to understand the effect of Chevrons on driving performance in different roadway geometries.Using a driving simulator, this study tests the effect of China’s Chevrons on vehicle speed and lane position on two-lane rural highway horizontal curves with different roadway geometries.The results showed a significant effect of Chevrons on speed reduction, and this function was not significantly affected by curve radius but was statistically affected by curve direction. The speed reduction caused by Chevrons was also significant at the approach of curve, middle of curve and point of tangent. The 85th percentile speed was also markedly lower when Chevrons were present. We also found a significant effect of Chevrons in encouraging participants to drive the vehicle with a more proper lane position at the first half of curves; and this function was slightly affected by curve radius. Meanwhile, the effect of Chevrons on keeping drivers staying in a more stable lane position was also statistically significant at the second half of curves. In sharp curves, the function of Chevrons to make drivers keep a stable lane position was lost. Besides, the impact of curve direction on the function of Chevrons on lane position was always present, and drivers would drive slightly away from Chevrons.Regardless of the curve radius, China’s Chevrons at horizontal curves provide an advance warning, speed control and lane position guide for traffic on the nearside of Chevrons. Besides, combing with the function of Chevrons on preventing excessive speed and the benefit to make drivers keep a more proper lane position, China’s Chevrons appear to be of great benefit to reduce crashes (e.g., run-off-road) in curves.     

A simulator study on the impact of traffic calming measures in urban areas on driving behavior and workload

This study examined the impact of traffic calming measures (TCM) on major roads in rural and urban areas. More specifically we investigated the effect of gate constructions located at the entrance of the urban area and horizontal curves within the urban area on driving behavior and workload. Forty-six participants completed a 34 km test-drive on a driving simulator with eight thoroughfare configurations, i.e., 2 (curves: present, absent) × 2 (gates: present, absent) × 2 (peripheral detection task (PDT): present, absent) in a within-subject design.     

Emotional states of drivers and the impact on speed,acceleration and traffic violations—A simulator study

Maladjusted driving, such as aggressive driving and delayed reactions, is seen as one cause of traffic accidents. Such behavioural patterns could be influenced by strong emotions in the driver. The causes of emotions in traffic are divided into two distinct classes: personal factors and properties of the specific driving situation. In traffic situations, various appraisal factors are responsible for the nature and intensity of experienced emotions. These include whether another driver was accountable, whether goals were blocked and whether progress and safety were affected. In a simulator study, seventy-nine participants took part in four traffic situations which each elicited a different emotion. Each situation had critical elements (e.g. slow car, obstacle on the street) based on combinations of the appraisal factors. Driving parameters such as velocity, acceleration, and speeding, together with the experienced emotions, were recorded. Results indicate that anger leads to stronger acceleration and higher speeds even for 2 km beyond the emotion-eliciting event. Anxiety and contempt yielded similar but weaker effects, yet showed the same negative and dangerous driving pattern as anger. Fright correlated with stronger braking momentum and lower speeds directly after the critical event.     

Self-report measures of distractibility as correlates of simulated driving performance

The present study investigated the relationship between self-reported measures pertaining to attention difficulties and simulated driving performance while distracted. Thirty-six licensed drivers participated in a simulator driving task while engaged in a cell phone conversation. The participants completed questionnaires assessing their tendency toward boredom, cognitive failures, and behaviors associated with attention deficit and hyperactivity. Scores on these measures were significantly correlated with various driving outcomes (e.g., speed, lane maintenance, reaction time). Significant relationships were also found between one aspect of boredom proneness (i.e., inability to generate interest or concentrate) and self-reports of past driving behavior (moving violations). The current study may aid in the understanding of how individual differences in driver distractibility may contribute to unsafe driving behaviors and accident involvement. Additionally, such measures may assist in the identification of individuals at risk for committing driving errors due to being easily distracted. The benefits and limitations of conducting and interpreting simulation research are discussed.     

Driving strategies in overtaking

Over 400 overtaking manoeuvres were observed on a two lane British “A” carriageway with a maximum speed limit of 100 km/hr. It was found that 14% of overtaking drivers use a gap size too small (i.e. less than 400 m) to comfortably accommodate vehicles closing on each other at normally assumed driving speeds. Acceptance of a small gap for overtaking increased the incidence of lane sharing (overtaking partially in both lanes) and cutting in (precipitous return to the driving lane). When only a small gap was available, there was an increase in both lane sharing and cutting in, usually only one of the above options was utilised with a tendency for piggy-backers (two or more simultaneous overtakers) to prefer lane sharing while non-piggy-backers preferred to cut in. Flying overtakers (overtaking without pause), accelerative overtakers (overtaking after a pause), piggy-backers, non piggy-backers and drivers not braking to follow before overtaking, all cut in more in small gaps than in large gaps. Only drivers braking to follow failed to cut-in more in small gaps. In addition, accelerative overtakers, piggy-backers, non piggy-backers, drivers braking and drivers not braking to follow, lane shared more in small gaps than large gaps. Only flying overtakers failed to lane share more in small gaps than in large gaps, but this was because they did a lot of lane sharing in both large and small gaps. Finally, flying overtakers, piggy-backers and drivers who braked in order to follow before overtaking, were more likely to accept a small gap for overtaking than were accelerative overtakers, non piggy-backers and drivers who did not brake to follow. Policy and research implications of these findings are discussed.     

Driving simulator for speed research on two-lane rural roads

The paper reports on a validation study of the interactive fixed-base driving simulator of Inter-University Research Center for Road Safety (CRISS) that was effectuated in order to verify the CRISS driving simulator's usefulness at a tool for speed research on two-lane rural roads. Speeds were recorded at eleven measurement sites with different alignment configurations on a two-lane rural road near Rome. The real world was reproduced in the CRISS driving simulator. Forty drivers drove the simulator. The results of the comparative and statistical analysis established the relative validity and also revealed that absolute validity was obtained in nine measurements sites. Only in two non-demanding configurations, were the speeds in simulator significantly higher than those recorded in the field. In these sites the mean speed in simulator was equal to or greater than 94 km/h. For these configurations, the higher speeds recorded in simulator appeared to stem from the different risk perception on the simulated road as opposed to that on the real road. The study's results should be considered for driving speed behavior research, in which simulator equipment with similar features of the CRISS driving simulator is used.     

Sleepy driving on the real road and in the simulator—A comparison

Sleepiness has been identified as one of the most important factors contributing to road crashes. However, almost all work on the detailed changes in behavior and physiology leading up to sleep related crashes has been carried out in driving simulators. It is not clear, however, to what extent simulator results can be generalized to real driving. This study compared real driving with driving in a high fidelity, moving base, driving simulator with respect to driving performance, sleep related physiology (using electroencephalography and electrooculography) and subjective sleepiness during night and day driving for 10 participants. The real road was emulated in the simulator. The results show that the simulator was associated with higher levels of subjective and physiological sleepiness than real driving. However, both for real and simulated driving, the response to night driving appears to be rather similar for subjective sleepiness and sleep physiology. Lateral variability was more responsive to night driving in the simulator, while real driving at night involved a movement to the left in the lane and a reduction of speed, both of which effects were absent in the simulator. It was concluded that the relative validity of simulators is acceptable for many variables, but that in absolute terms simulators cause higher sleepiness levels than real driving. Thus, generalizations from simulators to real driving must be made with great caution.     

Age differences in simulated driving performance: Compensatory processes

In the context of driving, the reported experiment examines compensatory processes for age-related declines in cognitive ability. Younger (26–40 years) and older (60+ years) participants (n = 22 each group) performed a car following task in a driving simulator. Several performance measures were recorded, including assessments of anticipation of unfolding traffic events. Participants also completed a range of measures of cognitive ability – including both fluid and crystallised abilities. Three examples of age-related compensation are reported: (i) older drivers adopted longer headways than younger drivers. Data were consistent with this being compensation for an age-related deficit in complex reaction time; (ii) older drivers with relatively higher cognitive ability anticipated traffic events more frequently, whereas the reverse pattern was found for younger drivers; and, (iii) older drivers with greater crystallised ability were less reliant on spatial ability to maintain lane position. Consistent with theories of ‘cognitive reserve’, interactions between crystallised ability and age for self-report workload suggested that compensation for age-related cognitive ability deficits required investment of additional effort. Results are considered in the context of the prospects of further assessment of older drivers.