Effects of visual and cognitive load in real and simulated motorway driving

As part of the HASTE European Project, effects of visual and cognitive demand on driving performance and driver state were systematically investigated by means of artificial, or surrogate, In-vehicle Information Systems (S-IVIS). The present paper reports results from simulated and real motorway driving. Data were collected in a fixed base simulator, a moving base simulator and an instrumented vehicle driven in real traffic. The data collected included speed, lane keeping performance, steering wheel movements, eye movements, physiological signals and self-reported driving performance. The results show that the effects of visual and cognitive load affect driving performance in qualitatively different ways. Visual demand led to reduced speed and increased lane keeping variation. By contrast, cognitive load did not affect speed and resulted in reduced lane keeping variation. Moreover, the cognitive load resulted in increased gaze concentration towards the road centre. Both S-IVIS had an effect on physiological signals and the drivers’ assessment of their own driving performance. The study also investigated differences between the three experimental settings (static simulator, moving base simulator and field). The results are discussed with respect to the development of a generic safety test regime for In-vehicle Information Systems.     

Using a multi-user driving simulator system to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits

Vehicle fleet rear-end collisions (FRECs) are an extremely fatal type of traffic collisions on freeway and they usually occur in foggy weather. This study aimed to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits on freeway. A multi-user driving simulator system was used to conduct the experiment and the driving behavior data were collected from eight participants. The experimental results showed that as the fog density increased, the length of vehicle fleet decreased significantly, and drivers tended to keep a more stable car-following distance. The fog weather and short vehicle gap prompted drivers to react faster and brake harder in respond to the leading vehicle’s brake. In spite of the compensational behaviors, more FRECs were observed under heavy fog condition. Lowering speed limit can significantly reduce the FRECs under foggy conditions. As the speed limits reduced, drivers’ brake response time and speed variance significantly reduced. The study also found that drivers’ brake response time was negatively correlated with their positions in the fleet. Drivers in the front positions of the fleet had a longer response time than drivers in the back positions and thus were more likely to encounter collisions. The study generated a better understanding of drivers’ behavioral pattern in a vehicle fleet and the patterns of vehicle fleet rear-end collisions occurrence. The findings also shed lights on the design of driver assistance system for complex driving situations such as freeway driving under adverse weather.     

The implications of situation and route familiarity for driver-pedestrian interaction at uncontrolled mid-block crosswalks

Most routine daily trips take place along the same route, a fact that previous studies have not investigated together with the repeated situation of conflicting with other road users. Consequently, our study addresses driver behaviour by separating the driving experience into three categories: (i) drivers unfamiliar with the route, (ii) those route-familiar, and (iii) situation-familiar drivers. The specific case of driver-pedestrian interaction at uncontrolled mid-block crosswalks is investigated. A multi-level factorial experiment including (i) crosswalk design (linear sidewalk and curb extension), (ii) driver familiarity, and (iii) pedestrian time gap acceptance (4, 6, and 8 s) was conducted using a driving simulator. Fifty-two participants were divided into four groups and stratified by age, gender, and driving experience. The minimum instantaneous time to collision, post-encroachment time, maximum car deceleration, and maximum car speed were all used as surrogate safety measures (SSM).Route-familiarity led to higher speed, while situation-familiarity positively affected driving behaviour making drivers more inclined to decrease their speed at circa 100 m before a crosswalk. The curb extension layout enhanced pedestrian safety and mitigated any adverse effects due to familiarity, with a particularly relevant impact on SSM at low accepted time gaps for pedestrians. Situation- and route-familiarity treatment protocols lead to different behaviours among drivers, indicating a clear need to account for these two familiarity levels in experiments on safety-related countermeasures.     

Driving simulator validation with hazard perception

How should we assess the comparability of driving on a road and “driving” in a simulator? If similar patterns of behaviour are observed, with similar differences between individuals, then we can conclude that driving in the simulator will deliver representative results and the advantages of simulators (controlled environments, hazardous situations) can be appreciated. To evaluate a driving simulator here we compare hazard detection while driving on roads, while watching short film clips recorded from a vehicle moving through traffic, and while driving through a simulated city in a fully instrumented fixed-base simulator with a 90 degree forward view (plus mirrors) that is under the speed/direction control of the driver. In all three situations we find increased scanning by more experienced and especially professional drivers, and earlier eye fixations on hazardous objects for experienced drivers. This comparability encourages the use of simulators in drivers training and testing.     

Investigating the effectiveness of perceptual treatments on a crest vertical curve: A driving simulator study

Rural roads are characterized by a high percentage of run-off-the-road accidents and head-on collisions, mainly caused by inappropriate speeds and failure to maintain a proper lateral position along the roadway alignment. Among several road safety treatments, low-cost perceptual measures are considered an effective tool, as they generally increase the risk perceived by drivers, or even alter the drivers’ speed perception, and consequently tempting them to decrease their speeds. Their effectiveness has been widely recognized in a number of studies, especially with respect to road intersections and curves.The overall aim of this study is to investigate the effects of different perceptual treatments on driving speed, along a crest vertical curve of an existing two-lane rural road, in order to identify the most effective measure to reduce speed and define its subsequent implementation in the field. Three perceptual treatments were tested using a driving simulator: white peripheral transverse bars, red peripheral transverse bars and optical speed bars, with each one being painted along the approaching tangent to the crest vertical curve. The effects of these speed-reducing measures were investigated using a sample of forty-four participants, by comparing the driving speeds with those recorded under a baseline condition (without a treatment); these were also used to validate the driving simulator’s speed measurements with those found in the field. Moreover, subjective measures were collected, consisting of the driver’s static evaluation of the desired speed, risk perception and markings comprehension, based on screen shot pictures that represented the simulated configurations of the treatments.The findings demonstrated an overall effectiveness of the perceptual treatments, although only the red peripheral transverse bars were found to significantly reduce the driving speeds (−6 km/h). The analysis of the questionnaire yielded interesting information and demonstrated the importance of performing driving simulation tests for evaluating the effectiveness of perceptual treatments.Finally, the results confirmed the enormous potential of using driving simulators to pinpoint a number of speed-reducing measures, and consequently select the most effective one that reduces cost and promotes safety before its actual implementation in the field.     

Effects of directional auditory and visual warnings at intersections on reaction times and speed reduction times

Intersection collision warning systems (ICWSs) have an important impact on driving safety because making the potential collision at intersection predictable, allow reducing the probability and severity of accidents. Among the several types of alarms to alert the driver of an imminent collision, those most used concerning the auditory and the visual stimulus. However, it is unclear whether is more effective an audio or a visual warning. In addition, no study compared the effects on drivers’ behavior induced by an acoustic and a visual directional warning. The main objective of the present study was to assess, in response to a potential conflict event at the intersections, the effects of directional auditory and visual warnings on driving performance.A driving simulator experiment was carried out to collect drivers’ behavior in response to a vehicle that failed to stop at the intersection. The parameters reaction time and speed reduction time were used for the evaluation of the effects on driving performance. These duration variables were modeled following the survival analysis, by the use of the accelerated failure time duration model with a Weibull distribution.Results showed that when the directional warning system (auditory or visual) was present, the drivers were able to detect earlier the violator vehicle. This effect led to a more comfortable braking maneuver and, thus, less possibilities of an unexpected maneuver for the following vehicle, avoiding the car – following collisions. The effectiveness of ICWSs was more evident for the directional auditory speech message; for this condition, in fact, the lower reaction time and the longer speed reduction time were obtained.The outcomes of the present study provide useful suggestions about the most effective collision warning systems that the automotive industry should develop and equip on vehicles.     

Decreasing driver speeding with feedback and a token economy

On-road research suggests that driver feedback combined with a token economy (a system of delayed reinforcement whereby tokens or points are distributed following a desired behaviour and are later exchanged for desired items) can reduce speeding, and that an incentive system without feedback may be sufficient to achieve this reduction. In two studies, we investigated the necessary and sufficient conditions required for this intervention to reduce speeding, and the efficacy of conducting such research using a driving simulator. Study 1 served to validate the simulator procedure. Participants completed a simulated drive while receiving feedback on their speed and a speed-based token economy. The intervention decreased their speeding compared with that of a control group. Study 2 investigated the amount of speed reduction that could be achieved with just one intervention component (i.e., feedback alone or a token economy alone) compared with feedback and a token economy combined or a control condition. Participants completed a 30-min simulated drive. Overall, drivers who received feedback combined with a token economy spent the least amount of time driving above the speed limit, had the slowest mean speed, and had the smallest standard deviation of speed. Drivers exposed to a token economy alone showed similar speed reductions. However, drivers exposed to feedback alone drove at speeds similar to control participants. Replicating these results under more realistic operating conditions could inform policy-makers and car manufacturers. Furthermore, the simulator proved a cost-effective and efficient means for examining the intervention.     

Effects of different non-driving-related-task display modes on drivers’ eye-movement patterns during take-over in an automated vehicle

Highly automated vehicles relieve drivers from driving tasks, allowing them to engage in non-driving-related-tasks (NDRTs). However, drivers are required to take over control in certain circumstances due to the limitations of highly automated vehicles. This study focused on drivers’ eye-movement patterns during take-overs when an NDRT (watching videos) was presented via a head-up-display (HUD) and a mobile device display (MDD), compared to no NDRT as the baseline. The experiment was conducted in a high-fidelity driving simulator with real-world driving videos scenarios. Forty-six participants took part in the experiment by completing three drives in three counterbalanced conditions (HUD, MDD and baseline). A take-over-request was issued towards the end of automated driving requesting drivers to stop the NDRT and take over control. Eye-movement data including pupil diameter, blinks, glance duration and number of AOI (Area of Interest) were collected and analysed. The results show that during automated driving, drivers were more engaged in the MDD NDRT with smaller pupil diameter and shorter glance duration on the front scenario compared to the HUD and baseline modes. The number of AOI was reduced during automated driving in both MDD and HUD modes. The take-over-request redirected drivers’ visual attention back to the driving task from NDRT by increasing drivers’ pupil diameter, glance duration and number of AOI. However, the effect of MDD NDRT on pupil diameter and glance duration continued even after the take-over-request when the NDRT was terminated. The study demonstrated HUD is a better display to help maintain drivers’ attention on the road.     

Analyzing driver's response to the yellow onset at signalized intersections

Intersections are critical points within the highway system at which the risk of crashes increases. This study seeks to better understand drivers’ behavior at an intersection by examining the relationship between their observed driving behavior, psychological attributes and decision to proceed through an intersection. A driving simulator and self-report questionnaire were used to understand driver decision-making at the onset of the yellow phase across several signalized intersections. The simulator measured driving outcomes such as speed, braking, and throttle as drivers cross through four increasingly difficult intersections. The questionnaires measured demographics, psychological traits including mindfulness and impulsiveness along with self-reported driving behaviors. A total of 102 participants completed the questionnaire as well as the driving simulator experiment. Hierarchical clustering served to classify drivers into four groups on the basis of their observed driving in the simulator: the safest drivers, safe drivers, speed demons, and aggressive drivers. These driving styles moderated the relationship between the drivers’ psychological traits and their decision to stop or proceed at each intersection. Results showed that mindfulness was highly related to the safest drivers’ decision to stop at the first intersection, while impulsiveness and anxiety were related to the speed demons’ decision to stop at the third intersection. These findings lay a strong foundation for developing progressive educational campaigns incorporating driver psychology in their methodology. Findings also provide support for research linking driving performance and psychological traits with implications for intersection design.     

Identification of driving simulator sessions of depressed drivers: A comparison between aggregated and time-series classification

Depression has been found to significantly increase the probability of risky driving and involvement in traffic collisions. The majority of studies correlating depressive symptoms with driving, pursue to predict the differences in driving behavior if the driver has already been diagnosed. Little evidence can be found, however, on how mental and psychological disorders can be identified from driving data, and usually analyses utilize simple models and aggregated data. This study aims at utilizing microscopic data from a driving simulator to detect sessions belonging to “depressed” drivers by utilizing powerful machine learning classifiers. Driving simulator sessions from 11 older drivers with symptoms of depression and 65 healthy drivers were utilized towards that aim. Random Forests, an ensemble classifier, with proven efficiency among transportation applications, are then trained on highly disaggregated data describing the mean and standard deviation of speed and lateral or longitudinal acceleration of drivers in the simulator. The kinematic data were aggregated in 30-seconds, 1-minute and 5-minute intervals, but the corresponding time-series of the measurements were also taken into account. Furthermore, classifiers were treated with imbalanced learning techniques to address the scarcity of depressed drivers among the healthy. Time-series of mean speed and the standard deviation of longitudinal acceleration even with a duration of 30-seconds have proven to be the best predictors of driving sessions belonging to depressed drivers with a very low rate of false alarms. The results outperform previous approaches, and indicate that naturalistic driving data or deep learning could prove even more efficient in detecting depression.     

Effectiveness of the compensatory strategy adopted by older drivers: Difference between professional and non-professional drivers

It has been a controversial issue for the effect of ageing population on driving safety. Apparently, drivers’ physiological and cognitive performances deteriorate with age. However, older drivers may compensate for the elevated risk by adjusting their behaviors, known as compensatory strategy. Despite the extensive research on this topic, the compensatory strategy of older professional drivers is not well understood since many studies focused on the differences in compensatory behavior between older and young drivers. Professional drivers tend to be more skillful and able to cope with the unfavorable driving environments, thus presenting a higher capability to mitigate the risk. This study attempts to examine the compensatory behavior and its safety effect amongst older professional drivers, as compared to those of older non-professional drivers, using the driving simulator approach. In the driving simulator experiment, participants were asked to follow a leading vehicle for one hour, and two sudden brake events were presented. 41 (mid-aged and older) drivers completed the driving tests. Each participant was required to complete a car-following test, either under high or low traffic flow conditions. Performance indicators include driving capability (i.e. lateral control, longitudinal control, and brake reaction time) and compensatory behavior (i.e. average speed, and time headway). Additionally, two modified traffic conflict measures: time exposed time-to-collision (TET) and time integrated time-to-collision (TIT) are applied to indicate the traffic conflict risk. The random parameter Tobit models were estimated to measure the association between conflict risk and driver attributes, and random intercept models were used to assess other driving performance indicators. Results show that despite the impaired lateral control performance and longer brake reaction time of older drivers, the likelihood of severe traffic conflict of older drivers is lower than that of mid-aged drivers. Furthermore, though both older professional and older non-professional drivers adopted longer time headway, the reduction in the risk of severe traffic conflict is more profound among the older professional drivers. Such findings suggest that older professional drivers are more capable of mitigating the possible collision risk by adopting the compensatory strategy, as compared to older non-professional drivers. This justifies the existence of compound effect by the compensatory strategy of older driver and better driving skills of professional driver. This research provides useful insights into driver training and management strategies for employers, as older drivers would become a major cohort in the transportation industry.     

Effects of hands-free cellular phone conversational cognitive tasks on driving stability based on driving simulation experiment

Driver distraction due to cellular phone usage is a major contributing factor to road crashes. This study compares the effects of conversational cognitive tasks using hands-free cellular phone on driving performance under three distraction conditions: (1) no distraction (no cellular conversation), (2) normal conversation (non-emotional cellular conversation), and (3) seven-level mathematical calculations. A car-following scenario was implemented using a driving simulator. Thirty young drivers with an average age of 24.1 years maintained a constant speed and distance between the subject vehicle and a leading vehicle on the driving simulator, and then respond to the leading vehicle’s emergency stop. The driving performances were assessed by collecting and statistically analyzing several variables of maneuver stability: the drivers’ brake reaction times, driving speed fluctuation, car-following distance undulation, and car-following time-headway undulation. The results revealed that normal conversation on a hands-free cellular phone impaired driving performance. The degree of impairment caused by normal calculation was equivalent to the distraction caused by Level 3 mathematical calculations according to the seven-level calculation baseline. The calculation difficulty of Level 3 is one double-digit figure plus a single-digit figure, and non-carry addition mental arithmetic is required, e.g., 44 + 4. The results indicated that an increase in the level of complexity of the calculation task was associated with an increase in brake reaction time. The seven-level calculation-task baseline could be applied to measure additional distraction effects on driving performance for further comparison.     

Anticipatory and control processes in the interaction with secondary tasks while driving

The paper describes an experiment where anticipatory processes in the interaction with secondary tasks while driving could be explicitly identified and contrasted to control processes during the engagement in the secondary task. A special experimental set-up in a driving simulator environment was created that allows drivers to deliberately decide whether they want to be distracted or not depending on the driving situation and the expected development of that situation. As indicators for a situation-adaptive interaction with secondary tasks parameters from driving behaviour, secondary task performance and visual behaviour were analyzed. A study with 24 test drivers revealed that drivers are, in general, able to interact with a secondary task in a situation-aware manner. For example, drivers rejected more secondary tasks in already highly demanding situations or tried to delay the beginning of the task. During secondary task performance drivers observed the situational development with short control glances back to the road and adapted their speed. The analysis of driving errors revealed that rejecting a task in an already highly demanding driving situation is an effective strategy to maintain an adequate level of driving safety. However, some critical factors were identified that might hinder the driver from executing such strategies. Several recommendations for supporting the driver on this issue are given.     

Field operational test of a seatbelt reminder system: Effects on driver behaviour and acceptance

The long-term effects on driver behaviour and acceptance of a seatbelt reminder system were examined in an on-road study. The system was capable of detecting seatbelt use in all seating positions and produced a two-stage visual and auditory warning if occupants were unrestrained. The effects of this system were evaluated alone and in combination with two other intelligent transport systems: intelligent speed adaptation and a following distance warning system. Twenty-three fleet car drivers drove an instrumented vehicle (SafeCar) for at least 16,500 km as part of their everyday driving. The results revealed that driver and passenger interaction with the seatbelt reminder system led to large and significant decreases in the percentage of trips where occupants were unbelted, in the percentage of total driving time spent unbelted, and in the time taken to fasten a seatbelt in response to system warnings. The seatbelt reminder system was rated by drivers as being useful, effective and socially acceptable, and led to a decrease in drivers’ subjective workload. These results were found even though the baseline pre-exposure seatbelt wearing compliance rates among participants were high.     

Compensating for failed attention while driving

While operating a motor vehicle, drivers must pay attention to other moving vehicles and the roadside environment in order to detect and process critical information related to the driving task. Using a driving simulator, this study investigated the effects of an unexpected event on driver performance in environments of more or less clutter and under situations of high attentional load. Attentional load was manipulated by varying the number of neighboring vehicles participants tracked for lane changes. After baseline-driving behavior was established, the unexpected event occurred: a pedestrian ran into the driver’s path. Tracking-accuracy, brake initiation, swerving, and verbal report of the unexpected pedestrian were used to assess driver performance. All participants verbally reported noticing the pedestrian. However, analyses of driving behavior revealed differences in the reactions to the pedestrian: drivers braked faster and had significantly less deviation in their steering heading with a lower attentional load, and participants in low clutter environments had a larger overall change in velocity. This research advances the understanding of how drivers allocate attention between various stimuli and the trade-offs between a driver’s focus on an assigned task and external objects within the roadway environment. Moreover, the results of this research lend insight into how to construct roadway environments that encourage driver attention toward the most immediate and relevant information to reduce both vehicle-to-vehicle and vehicle-to-pedestrian interactions.     

Can infrastructure improvements mitigate unsafe traffic safety culture: A driving simulator study exploring cross cultural differences

This paper presents the results of a cross-cultural study to investigate the influence of traffic safety culture and infrastructure improvements on driver behaviour. To achieve this, the driving style of UK drivers was compared with that of Nigerians with and without experience of driving in the UK. A driving simulator experiment compared the actual driving style of these three groups of drivers in different safety critical scenarios. The simulated road environment varied depending on how much infrastructure was provided (low or high infrastructure). In addition, the Driver Behaviour Questionnaire was used to collect self-reported data on violations, errors and lapses. It was hypothesised that Nigerian drivers with no experience of driving in a UK road system would report and engage in more unsafe driving behaviour compared to the other two groups, and that increasing infrastructure would have little positive benefit. Overall, the results supported these hypotheses, indicating that the behaviours of drivers are interpretable in relation to their traffic safety culture, compared to changes in their driving environment.     

Should drivers be informed about the equipment of drivers with green light optimal speed advisory (GLOSA)?

Previous research demonstrated that green light optimal speed advisory (GLOSA) affects driving behavior at signalized intersections: On the one hand, drivers assisted with GLOSA show more energy-efficient and eco-friendly driving. Following unequipped vehicles’ drivers (UVDs) also adapt their driving behavior to the assisted one. On the other hand, safety issues can be found in encounters with UVDs who also perceive assisted driving behavior negatively. Therefore, in a multi-driver simulator study (N = 60 participants sorted in groups of n = 2 UVDs), we tested whether informing UVDs about the GLOSA of an assisted driver results in more behavioral adaptation of UVDs to the assisted driving behavior, less safety issues, and less frustration of UVDs. Two UVDs followed a lead vehicle driven by a confederate. The confederate was equipped with GLOSA and knew when traffic lights switched from green to red and, consequently, slowed down when approaching a green traffic light. The degree of information UVDs received was manipulated: The group “no information” did not receive any information. The group “information” knew about the equipment of the assisted confederate with GLOSA and the group “detailed information” received additional information about its functionality and benefit. Results show that UVDs of the group “detailed information” adapted their driving behavior to the assisted driver. However, these UVDs also showed smaller minimum time-to-collision (TTC) values indicating safety issues. Results are discussed and implications made with regard to providing information to UVDs and to further investigate these challenges in the context of autonomous vehicles.     

Effects of hazard exposure and roadway complexity on young and older driver situation awareness and performance

Few previous studies of driver situation awareness (SA) have focused on behavior in hazard negotiation. The objective of this research was to assess the effect of hazard exposure on driver SA and interactions with age and roadway complexity. Ten young (18–25 yrs) and ten older (65–81 yrs) participants drove in a simulator under two levels of environment complexity (simple – rural vs. complex – city) with two types of hazard exposure (static vs. dynamic). Situation awareness was measured using real-time probes posed by a confederate passenger. Driving performance was assessed in terms of lane maintenance and speed control. Results revealed hazards to cause degradations in high level of driver SA and speed control or to trigger adaptation, and vulnerability to hazard type was dependent on driver age. Older drivers exhibited greater speed reduction in response to dynamic hazards; whereas, young driver maintained higher speed, as compared to normal driving, when confronted with static hazards. In addition, increased roadway environment complexity compounded decrements in performance caused by hazard exposure. These findings are applicable to modeling driver behavior and SA under hazardous conditions and may support the design of new in-vehicle assistive technologies for hazard avoidance.     

Dynamic traffic management on a familiar road: Failing to detect changes in variable speed limits

Variable speed limits (VSL) are used more commonly around the globe lately. Although on a macroscopic level positive effects of VSLs have been reported, the caveat is that the impact of VSLs is very sensitive to the level of driver compliance. Thus far it is unknown whether all individual drivers are actually able to notice when a speed limit changes into another speed limit; a prerequisite for purposeful speed limit compliance in the first place. To simulate regular driving conditions, twenty-four participants were familiarised with a particular route by driving the same route in a driving simulator nineteen times on five separate days. Part of the route consisted of a motorway where VSL signs were regularly displayed above every driving lane. At drive nineteen, speed limits changed from 80 km/h to 100 km/h on four out of eight consecutive signs. After passing all signs, one expects 6.25% of the participants still to be unaware that the speed limit had increased (based on chance), while the results showed most participants had failed to notice the speed limit change (58.3%). Instead, they saw what they expected to see: a speed limit of 80 km/h. If the speed change had been vice versa, in other words from 100 km/h to 80 km/h, this would immediately result in speed offences, though not deliberately at all.