Effect of driving experience on anticipatory look-ahead fixations in real curve driving

Targeted nudging for speeding behavior: The influence of interpersonal characteristics on responses to in-vehicle road nudges

Road carnage is one of the most fatal and expensive global issues today. Many solutions have been implemented to minimize it, but most are costly and unreliable. Therefore, in this study, nudges were used as a reliable and inexpensive tool to affect safe driving behavior which, in turn, may reduce road fatalities. To optimize the use of nudges, we suggested that responses to nudges - in a similar manner to responses to other stimuli - may vary by interpersonal characteristics, so that different nudges may lead to more accurate and reliable reactions in different sub-populations in a predictable manner. To test these assertions, we collected a sample of 200 participants, both men and women, ages 17.5 to 83 years. We measured different interpersonal characteristics that included both demographic information (e.g., age, gender, years with a driver's license) and different personality traits. We then assessed responses to nudges using a simulator that was specially designed for this study, in which participants are asked to adjust their speed as they see fit while they watched a video shot from a driver's perspective of the forward roadway. Over the course of the video, a different nudge was displayed for each subject and their response latency and speeds were recorded for further analysis. We were able to observe several interesting phenomena: responses to a reminder nudge and a negative reinforcement nudge were faster than responses to a social norm nudge. However, the latter showed a longer-term impact. The responses to the social norm interventions were also more variable, demonstrating that high neuroticism is linked to decreased response to social norm nudges, a picture that is repeated in men compared to women. Contrarily, conscientiousness was linked to a faster and more reliable response to the social norm nudge, and the gender effect was eliminated for men with high conscientiousness. Moreover, parenthood was found to increase the response to all nudges and was protective against the effects of high sensation-seeking, which led to more road violations. These findings may be tested using modern technology, which can facilitate the measurements of personal traits and verify the reliability of responses to nudges. Therefore, the current study suggests nudge personalization may be beneficial in improving the use of nudges on the road.

Prospective control of steering through multiple waypoints

Some locomotor tasks involve steering at high speeds through multiple waypoints within cluttered environments. Although in principle actors could treat each individual waypoint in isolation, skillful performance would seem to require them to adapt their trajectory to the most immediate waypoint in anticipation of subsequent waypoints. To date, there have been few studies of such behavior, and the evidence that does exist is inconclusive about whether steering is affected by multiple future waypoints. The present study was designed to address the need for a clearer understanding of how humans adapt their steering movements in anticipation of future goals. Subjects performed a simulated drone flying task in a forest-like virtual environment that was presented on a monitor while their eye movements were tracked. They were instructed to steer through a series of gates while the distance at which gates first became visible (i.e., lookahead distance) was manipulated between trials. When gates became visible at least 1-1/2 segments in advance, subjects successfully flew through a high percentage of gates, rarely collided with obstacles, and maintained a consistent speed. They also approached the most immediate gate in a way that depended on the angular position of the subsequent gate. However, when the lookahead distance was less than 1-1/2 segments, subjects followed longer paths and flew at slower, more variable speeds. The findings demonstrate that the control of steering through multiple waypoints does indeed depend on information from beyond the most immediate waypoint. Discussion focuses on the possible control strategies for steering through multiple waypoints.

Early Eye Disengagement Is Regulated by Task Complexity and Task Repetition in Visual Tracking Task

Understanding human actions often requires in-depth detection and interpretation of bio-signals. Early eye disengagement from the target (EEDT) represents a significant eye behavior that involves the proactive disengagement of the gazes from the target to gather information on the anticipated pathway, thereby enabling rapid reactions to the environment. It remains unknown how task difficulty and task repetition affect EEDT. We aim to provide direct evidence of how these factors influence EEDT. We developed a visual tracking task in which participants viewed arrow movement videos while their eye movements were tracked. The task complexity was increased by increasing movement steps. Every movement pattern was performed twice to assess the effect of repetition on eye movement. Participants were required to recall the movement patterns for recall accuracy evaluation and complete cognitive load assessment. EEDT was quantified by the fixation duration and frequency within the areas of eye before arrow. When task difficulty increased, we found the recall accuracy score decreased, the cognitive load increased, and EEDT decreased significantly. The EEDT was higher in the second trial, but significance only existed in tasks with lower complexity. EEDT was positively correlated with recall accuracy and negatively correlated with cognitive load. Performing EEDT was reduced by task complexity and increased by task repetition. EEDT may be a promising sensory measure for assessing task performance and cognitive load and can be used for the future development of eye-tracking-based sensors.

Drivers' gaze patterns when resuming control with a head-up-display: Effects of automation level and time budget

The removal of drivers' active engagement in driving tasks can lead to erratic gaze patterns in SAE Level 2 (L2) and Level 3 (L3) automation, which has been linked to their subsequential degraded take-over performance. To further address how changes in gaze patterns evolve during the take-over phase, and whether they are influenced by the take-over urgency and the location of the human-machine interface, this driving simulator study used a head-up display (HUD) to relay information about the automation status and conducted take-over driving experiments where the ego car was about to exit the highway with variations in the automation level (L2, L3) and time budget (2 s, 6 s). In L2 automation, drivers were required to monitor the environment, while in L3, they were engaged with a visual non-driving related task. Manual driving was also embodied in the experiments as the baseline. Results showed that, compared to manual driving, drivers in L2 automation focused more on the HUD and Far Road (roadway beyond 2 s time headway ahead), and less on the Near Road (roadway within 2 s time headway ahead); while in L3, drivers' attention was predominantly allocated on the non-driving related task. After receiving take-over requests (TORs), there was a gradual diversion of attention from the Far Road to the Near Road in L2 take-overs. This trend changed nearly in proportion to the time within the time budget and it exaggerated given a shorter time budget of 2 s. While in L3, drivers' gaze distribution was similar in the early stage of take-overs for both time budget conditions (2 s vs. 6 s), where they prioritized their early glances to Near Road with a gradual increase in attention towards Far Road. The HUD used in the present study showed the potential to maintain drivers' attention around the road center during automation and to encourage drivers to glance the road earlier after TORs by reducing glances to the instrument cluster, which might be of significance to take-over safety. These findings were discussed based on an extended conceptual gaze control model, which advances our understanding of gaze patterns around control transitions and their underlying gaze control causations. Implications can be contributed to the design of autonomous vehicles to facilitate the transition of control by guiding drivers' attention appropriately according to drivers' attentional state and the take-over urgency.

Peripheral vision in real-world tasks: A systematic review

Peripheral vision is fundamental for many real-world tasks, including walking, driving, and aviation. Nonetheless, there has been no effort to connect these applied literatures to research in peripheral vision in basic vision science or sports science. To close this gap, we analyzed 60 relevant papers, chosen according to objective criteria. Applied research, with its real-world time constraints, complex stimuli, and performance measures, reveals new functions of peripheral vision. Peripheral vision is used to monitor the environment (e.g., road edges, traffic signs, or malfunctioning lights), in ways that differ from basic research. Applied research uncovers new actions that one can perform solely with peripheral vision (e.g., steering a car, climbing stairs). An important use of peripheral vision is that it helps compare the position of one’s body/vehicle to objects in the world. In addition, many real-world tasks require multitasking, and the fact that peripheral vision provides degraded but useful information means that tradeoffs are common in deciding whether to use peripheral vision or move one’s eyes. These tradeoffs are strongly influenced by factors like expertise, age, distraction, emotional state, task importance, and what the observer already knows. These tradeoffs make it hard to infer from eye movements alone what information is gathered from peripheral vision and what tasks we can do without it. Finally, we recommend three ways in which basic, sport, and applied science can benefit each other’s methodology, furthering our understanding of peripheral vision more generally.

Self-Assessed Driving Skills and Risky Driver Behaviour Among Young Drivers: A Cross-Sectional Study

The first few years of driving is a critical period when driving skills develop and the driving style is established. While the actual driving skills improve during the first few years of driving, a novice driver's view of himself/herself as a safe and/or skilful driver also develops rapidly. The aim of this study was to investigate self-evaluated driver safety and perceptual-motor skills among different age groups of young drivers, along with the relationships between self-evaluated skills and driving behaviour. The sample consisted of a stratified random sample of 18-25-year-old drivers from the Finnish driving licence register. The questionnaires, which included the Driver Skill Inventory (DSI), Driver Behaviour Questionnaire (DBQ) and background information, were completed and returned by a total of 1,058 participants. While female drivers assessed their safety skills to be higher than their perceptual-motor skills, the opposite was true for males. In both sexes, perceptual-motor skills increased, and safety skills decreased with experience. Perceptual-motor skills correlated negatively with safety skills, lapses and errors, but positively with aggressive and ordinary violations. Safety skills correlated negatively with all DBQ variables. Safety orientation seems to be most clearly reflected in deliberate aberrant driving behaviours. Sex differences were observed in the development of behaviours and skills, perceptual-motor skills only increased with age among males, while safety skills decreased through experience among both men and women. Results showed that driving experience was strongly related to both driving style (violations, errors) and the drivers' view of their skills (safety orientation), highlighting the importance of the first few years of driving.

Gaze Strategies in Driving-An Ecological Approach

Human performance in natural environments is deeply impressive, and still much beyond current AI. Experimental techniques, such as eye tracking, may be useful to understand the cognitive basis of this performance, and "the human advantage." Driving is domain where these techniques may deployed, in tasks ranging from rigorously controlled laboratory settings through high-fidelity simulations to naturalistic experiments in the wild. This research has revealed robust patterns that can be reliably identified and replicated in the field and reproduced in the lab. The purpose of this review is to cover the basics of what is known about these gaze behaviors, and some of their implications for understanding visually guided steering. The phenomena reviewed will be of interest to those working on any domain where visual guidance and control with similar task demands is involved (e.g., many sports). The paper is intended to be accessible to the non-specialist, without oversimplifying the complexity of real-world visual behavior. The literature reviewed will provide an information base useful for researchers working on oculomotor behaviors and physiology in the lab who wish to extend their research into more naturalistic locomotor tasks, or researchers in more applied fields (sports, transportation) who wish to bring aspects of the real-world ecology under experimental scrutiny. Part of a Research Topic on Gaze Strategies in Closed Self-paced tasks, this aspect of the driving task is discussed. It is in particular emphasized why it is important to carefully separate the visual strategies driving (quite closed and self-paced) from visual behaviors relevant to other forms of driver behavior (an open-ended menagerie of behaviors). There is always a balance to strike between ecological complexity and experimental control. One way to reconcile these demands is to look for natural, real-world tasks and behavior that are rich enough to be interesting yet sufficiently constrained and well-understood to be replicated in simulators and the lab. This ecological approach to driving as a model behavior and the way the connection between "lab" and "real world" can be spanned in this research is of interest to anyone keen to develop more ecologically representative designs for studying human gaze behavior.

The Influence of Visual-Manual Distractions on Anticipatory Driving

OBJECTIVE

The aim of this study is to investigate how anticipatory driving is influenced by distraction.

BACKGROUND

The anticipation of future events in traffic can allow potential gains in recognition and response times. Anticipatory actions (i.e., control actions in preparation for potential traffic changes) have been found to be more prevalent among experienced drivers in simulator studies when driving was the sole task. Despite the prevalence of visual-manual distractions and their negative effects on road safety, their influence on anticipatory driving has not yet been investigated beyond hazard anticipation.

METHODS

A simulator experiment was conducted with 16 experienced and 16 novice drivers. Half of the participants were provided with a self-paced visual-manual secondary task presented on a dashboard display.

RESULTS

More anticipatory actions were observed among experienced drivers; experienced drivers also exhibited more efficient visual scanning behaviors as indicated by higher glance rates toward and percent times looking at cues that facilitate the anticipation of upcoming events. Regardless of experience, those with the secondary task displayed reduced anticipatory actions and paid less attention toward anticipatory cues. However, experienced drivers had lower odds of exhibiting long glances toward the secondary task compared to novices. Further, the inclusion of glance duration on anticipatory cues increased the accuracy of a model predicting anticipatory actions based on on-road glance durations.

CONCLUSION

The results provide additional evidence to existing literature supporting the role of driving experience and distraction engagement in anticipatory driving.

APPLICATION

These findings can guide the design of in-vehicle systems and guide training programs to support anticipatory driving.

Motor skill learning decreases movement variability and increases planning horizon

We investigated motor skill learning using a path tracking task, where human subjects had to track various curved paths at a constant speed while maintaining the cursor within the path width. Subjects' accuracy increased with practice, even when tracking novel untrained paths. Using a "searchlight" paradigm, where only a short segment of the path ahead of the cursor was shown, we found that subjects with a higher tracking skill differed from the novice subjects in two respects. First, they had lower movement variability, in agreement with previous findings. Second, they took a longer section of the future path into account when performing the task, i.e. had a longer planning horizon. We estimate that between one third and one half of the performance increase in the expert group was due to the longer planning horizon. An optimal control model with a fixed horizon (receding horizon control) that increases with tracking skill quantitatively captured the subjects' movement behaviour. These findings demonstrate that human subjects not only increase their motor acuity but also their planning horizon when acquiring a motor skill.

The Multiple Object Avoidance (MOA) task measures attention for action: Evidence from driving and sport

Performance in everyday tasks, such as driving and sport, requires allocation of attention to task-relevant information and the ability to inhibit task-irrelevant information. Yet there are individual differences in this attentional function ability. This research investigates a novel task for measuring attention for action, called the Multiple Object Avoidance task (MOA), in its relation to the everyday tasks of driving and sport. The aim in Study 1 was to explore the efficacy of the MOA task to predict simulated driving behaviour and hazard perception. Whilst also investigating its test-retest reliability and how it correlates to self-report driving measures. We found that superior performance in the MOA task predicted simulated driving performance in complex environments and was superior at predicting performance compared to the Useful Field of View task. We found a moderate test-retest reliability and a correlation between the attentional lapses subscale of the Driving Behaviour Questionnaire. Study 2 investigated the discriminative power of the MOA in sport by exploring performance differences in those that do and do not play sports. We also investigated if the MOA shared attentional elements with other measures of visual attention commonly attributed to sporting expertise: Multiple Object Tracking (MOT) and cognitive processing speed. We found that those that played sports exhibited superior MOA performance and found a positive relationship between MOA performance and Multiple Object Tracking performance and cognitive processing speed. Collectively, this research highlights the utility of the MOA when investigating visual attention in everyday contexts.

Speed behaviour upon approaching freeway curves

The actual speed behaviour when drivers approach a curve is very relevant to assess the road design and safety but is mostly overlooked in the scientific literature. Most research into curve driving behaviour is focussed at the behaviour inside the curve, although the speed selection is done before curve entry. The main objective of this research is to identify which freeway characteristics play a role in driving speed selection. High Frequency Floating Car Data, detailed reconstruction of the curves and their surroundings, as well as three dimensional sight distance analysis, were used to analyse individual speed profiles on 153 Dutch freeway curves. By defining the positions where the acceleration approaches 0 m/s² before and after a curve starts, the positions when the driver started and stopped decelerating upon curve entry were defined. Further correlation and regression analysis of those positions revealed that the radius of the curve is indeed a main explaining variable, as well as the speed driven before deceleration starts. Sight distances and cross section characteristics play a further role in determining the position where deceleration starts. Deceleration ends at approximately 135 m after curve start, and the speed in a curve is also correlated with the deflection angle and length of a curve. Sight distances do not play a role in selecting the speed in a curve based on this research. Overall, the findings indicate a non-constant nature and variability of speed behaviour upon curve entry. This can be used for safer freeway curve design and to assess traffic safety based on actual speed behaviour.

Dynamic scan paths investigations under manual and highly automated driving

Active visual scanning of the scene is a key task-element in all forms of human locomotion. In the field of driving, steering (lateral control) and speed adjustments (longitudinal control) models are largely based on drivers’ visual inputs. Despite knowledge gained on gaze behaviour behind the wheel, our understanding of the sequential aspects of the gaze strategies that actively sample that input remains restricted. Here, we apply scan path analysis to investigate sequences of visual scanning in manual and highly automated simulated driving. Five stereotypical visual sequences were identified under manual driving: forward polling (i.e. far road explorations), guidance, backwards polling (i.e. near road explorations), scenery and speed monitoring scan paths. Previously undocumented backwards polling scan paths were the most frequent. Under highly automated driving backwards polling scan paths relative frequency decreased, guidance scan paths relative frequency increased, and automation supervision specific scan paths appeared. The results shed new light on the gaze patterns engaged while driving. Methodological and empirical questions for future studies are discussed.

Theoretical interpretation of drivers' gaze strategy influenced by optical flow

Driver analysis, particularly revealing where drivers gaze, is a key factor in understanding drivers’ perception. Several studies have examined drivers’ gaze behavior and the two main hypotheses that have been developed are Tangent Point (TP) and Future Path Point (FP). TP is a point on the inner side of the lane, where the driver’s gaze direction becomes tangential with the lane edge. FP is an arbitrary single point on the ideal future path for an individual driver on the road. The location of this single point is dependent on the individual driver. While these gaze points have been verified and discussed by various psychological experiments, it is unclear why drivers gaze at these points. Therefore, in this study, we used optical flow theory to understand drivers’ gaze strategy. Optical flow theory is a method to quantify the extent to which drivers can perceive the future path of the vehicle. The results of numerical simulations demonstrated that optical flow theory can potentially estimate drivers’ gaze behavior. We also conducted an experiment in which the observed driver gaze behavior was compared to calculated gaze strategy based on optical flow theory. The experimental results demonstrate that drivers’ gaze can be estimated with an accuracy of 70.8% and 65.1% on circular and straight paths, respectively. Thus, these results suggest that optical flow theory can be a determining factor in drivers’ gaze strategy.

Drivers use active gaze to monitor waypoints during automated driving

Automated vehicles (AVs) will change the role of the driver, from actively controlling the vehicle to primarily monitoring it. Removing the driver from the control loop could fundamentally change the way that drivers sample visual information from the scene, and in particular, alter the gaze patterns generated when under AV control. To better understand how automation affects gaze patterns this experiment used tightly controlled experimental conditions with a series of transitions from 'Manual' control to 'Automated' vehicle control. Automated trials were produced using either a 'Replay' of the driver's own steering trajectories or standard 'Stock' trials that were identical for all participants. Gaze patterns produced during Manual and Automated conditions were recorded and compared. Overall the gaze patterns across conditions were very similar, but detailed analysis shows that drivers looked slightly further ahead (increased gaze time headway) during Automation with only small differences between Stock and Replay trials. A novel mixture modelling method decomposed gaze patterns into two distinct categories and revealed that the gaze time headway increased during Automation. Further analyses revealed that while there was a general shift to look further ahead (and fixate the bend entry earlier) when under automated vehicle control, similar waypoint-tracking gaze patterns were produced during Manual driving and Automation. The consistency of gaze patterns across driving modes suggests that active-gaze models (developed for manual driving) might be useful for monitoring driver engagement during Automated driving, with deviations in gaze behaviour from what would be expected during manual control potentially indicating that a driver is not closely monitoring the automated system.

On the nature of eye-hand coordination in natural steering behavior

Eyes and hand movements are known to be coordinated during a variety of tasks. While steering a vehicle, gaze was observed to be tightly linked with steering wheel angle changes over time, with the eyes leading the hands. In this experiment, participants were asked to drive a winding road composed of bends with systematically manipulated radii of curvature, under regular and automatic steering conditions. With automatic steering, the vehicle followed the road, but the steering wheel and participants hands did not move. Despite the absence of physical eye-hand coordination in that condition, the eye and [what the hands should have done] to produce the action on the steering wheel were found to be coordinated, as under regular steering. This result brings a convincing piece of evidence that eye movements do more than just guiding the hands. In addition, eye-hand coordination was also found to be intermittent, context and person-dependant.

Modeling crash risk of horizontal curves using large-scale auto-extracted roadway geometry data

Highway horizontal curves (H-curves) provide a smooth transition between two tangent sections of roadways. They allow vehicles to adjust their travel directions gradually. However, the geometry changes of the highway sections with H-curves often raise safety concerns. In order to deploy effective safety countermeasures, a critical task is to understand the risk factors associated with H-curves. Existing studies have made efforts to probe the safety issues associated with H-curves, whereas they were limited to relatively small-scale examinations because of the challenges in identifying H-curves from large road networks. In addition, due to the lack of well-archived traffic and roadway information, gathering other data associated with the H-curves is also difficult. Regarding to these gaps, this study aims to leverage open-source data to analyze the crash risk of highway sections with H-curves. In particular, the present study highlights itself from two main aspects: (i) a H-curve extraction tool was developed to facilitate large-scale curve data collection through the analytics of different open source data; and (ii) a crash modeling framework was developed to quantify H-curve crash risk. A case study based on a statewide road network was performed to test the developed crash risk models with the collected curve data. The results show the opportunities of using the developed tool for large-scale data collection and analyze the safety impacts of H-curve geometric properties, elevation change, traffic exposure, among others. Findings of this study provide insights into the improvement of H-curve data collection and safety evaluation.

How does drivers' visual search change as a function of experience? A systematic review and meta-analysis

Novice drivers are statistically over-represented in reported road crashes, with recent evidence suggesting that some of this increased crash involvement may be a result of limitations in their cognitive processing. Such processing has typically been measured by recording drivers' patterns of eye movements, however, the exact ways in which eye movements are reported and interpreted varies substantially between different studies in the literature. Therefore, the objective of this systematic review was to investigate whether novice drivers and experienced drivers do differ in clear and reproducible ways in their visual search. Studies were identified through searches of Web of Science, Medline, TRID Database, and the TRB Research in Progress Database, with no restrictions on publication status. Studies were included if they compared the visual search of a novice driver group (<3 years driving experience) and an experienced driver group (>3 years driving experience) using an eye tracking method and reported at least one of the following four visual search outcomes: fixation durations, horizontal spread of search, vertical spread of search and number of fixations. Two reviewers independently screened searches and assessed the full texts of potentially included studies. Of the 235 studies initially identified 18 were included in the review, with 13 studies reporting sufficient data to be included in the meta-analysis for at least one outcome measure. Given that the included studies deployed a range of method types, additional sub-group analyses were conducted using this factor. Sensitivity analyses were also conducted by temporarily removing extreme experience groups (e.g. driving instructors and learner drivers) in order to test the effect of different levels of experience and training. The meta-analyses, along with support from results discussed narratively, revealed that novice drivers have a narrower horizontal spread of search compared to experienced drivers, however, there were no overall differences in fixation durations, vertical spread of search or number of fixations when the studies were pooled together. These findings have important primary implications for the development of novice training interventions, with novice drivers needing to develop a broader horizontal spread of visual search, but not to necessarily learn to fixate further down the road. Subgroup analyses also provided considerations for future research studies in terms of the experience of the driver groups, and the method type used.

Looking at the Road When Driving Around Bends: Influence of Vehicle Automation and Speed

When negotiating bends car drivers perform gaze polling: their gaze shifts between guiding fixations (GFs; gaze directed 1–2 s ahead) and look-ahead fixations (LAFs; longer time headway). How might this behavior change in autonomous vehicles where the need for constant active visual guidance is removed? In this driving simulator study, we analyzed this gaze behavior both when the driver was in charge of steering or when steering was delegated to automation, separately for bend approach (straight line) and the entry of the bend (turn), and at various speeds. The analysis of gaze distributions relative to bend sections and driving conditions indicate that visual anticipation (through LAFs) is most prominent before entering the bend. Passive driving increased the proportion of LAFs with a concomitant decrease of GFs, and increased the gaze polling frequency. Gaze polling frequency also increased at higher speeds, in particular during the bend approach when steering was not performed. LAFs encompassed a wide range of eccentricities. To account for this heterogeneity two sub-categories serving distinct information requirements are proposed: mid-eccentricity LAFs could be more useful for anticipatory planning of steering actions, and far-eccentricity LAFs for monitoring potential hazards. The results support the idea that gaze and steering coordination may be strongly impacted in autonomous vehicles.

Effects of an Active Visuomotor Steering Task on Covert Attention

In complex dynamic tasks such as driving it is essential to be aware of potentially important targets in peripheral vision. While eye tracking methods in various driving tasks have provided much information about drivers’ gaze strategies, these methods only inform about overt attention and provide limited grounds to assess hypotheses concerning covert attention. We adapted the Posner cue paradigm to a dynamic steering task in a driving simulator. The participants were instructed to report the presence of peripheral targets while their gaze was fixed to the road. We aimed to see whether and how the active steering task and complex visual stimulus might affect directing covert attention to the visual periphery. In a control condition, the detection task was performed without a visual scene and active steering. Detection performance in bends was better in the control task compared to corresponding performance in the steering task, indicating that active steering and the complex visual scene affected the ability to distribute covert attention. Lower targets were discriminated slower than targets at the level of the fixation circle in both conditions. We did not observe higher discriminability for on-road targets. The results may be accounted for by either bottom-up optic flow biasing of attention, or top-down saccade planning.

Humans Use Predictive Gaze Strategies to Target Waypoints for Steering

A major unresolved question in understanding visually guided locomotion in humans is whether actions are driven solely by the immediately available optical information (model-free online control mechanisms), or whether internal models have a role in anticipating the future path. We designed two experiments to investigate this issue, measuring spontaneous gaze behaviour while steering, and predictive gaze behaviour when future path information was withheld. In Experiment 1 participants (N = 15) steered along a winding path with rich optic flow: gaze patterns were consistent with tracking waypoints on the future path 1–3 s ahead. In Experiment 2, participants (N = 12) followed a path presented only in the form of visual waypoints located on an otherwise featureless ground plane. New waypoints appeared periodically every 0.75 s and predictably 2 s ahead, except in 25% of the cases the waypoint at the expected location was not displayed. In these cases, there were always other visible waypoints for the participant to fixate, yet participants continued to make saccades to the empty, but predictable, waypoint locations (in line with internal models of the future path guiding gaze fixations). This would not be expected based upon existing model-free online steering control models, and strongly points to a need for models of steering control to include mechanisms for predictive gaze control that support anticipatory path following behaviours.

Adverse effects of anxiety on attentional control differ as a function of experience: A simulated driving study

This study tested whether adverse effects of state anxiety on attention and performance may be modulated by experience. Sixteen experienced and eleven inexperienced drivers drove in a simulator under low- and high-stress conditions. Anxiety was manipulated by competition, the presence of an evaluator, external video camera, and traffic noise. Most drivers showed greater anxiety scores and higher mean heart rates following manipulation. In both groups increased state anxiety decreased car speed control and caused more collisions, accompanied by fewer fixations of longer duration towards the driving lane across a horizontally narrower region. Inexperienced drivers increased the number of short fixations towards cars, while experienced drivers increased the number of short fixations on the speedometer. Although anxiety impairs processing efficiency and performance effectiveness for both groups, attentional changes differ as a function of experience. Inexperienced drivers tended to shift attention to threatening stimuli, while experienced drives were more likely to consciously monitor task goal.

Gaze doesn't always lead steering

In car driving, gaze typically leads the steering when negotiating curves. The aim of the current study was to investigate whether drivers also use this gaze-leads-steering strategy when time-sharing between driving and a visual secondary task. Fourteen participants drove an instrumented car along a motorway while performing a secondary task: looking at a specified visual target as long and as much as they felt it was safe to do so. They made six trips, and in each trip the target was at a different location relative to the road ahead. They were free to glance back at the road at any time. Gaze behaviour was measured with an eye tracker, and steering corrections were recorded from the vehicle's CAN bus. Both in-car 'Fixation' targets and outside 'Pursuit' targets were used. Drivers often used a gaze-leads-steering strategy, glancing at the road ahead 200-600 ms before executing steering corrections. However, when the targets were less eccentric (requiring a smaller change in glance direction relative to the road ahead), the reverse strategy, in which glances to the road ahead followed steering corrections with 0-400 ms latency, was clearly present. The observed use of strategies can be interpreted in terms of predictive processing: The gaze-leads-steering strategy is driven by the need to update the visual information and is therefore modulated by the quality/quantity of peripheral information. Implications for steering models are discussed.

When flow is not enough: evidence from a lane changing task

Humans are able to estimate their heading on the basis of optic flow information and it has been argued that we use flow in this way to guide navigation. Consistent with this idea, several studies have reported good navigation performance in flow fields. However, one criticism of these studies is that they have generally focused on the task of walking or steering towards a target, offering an additional, salient directional cue. Hence, it remains a matter of debate as to whether humans are truly able to control steering in the presence of optic flow alone. In this study, we report a set of maneuvers carried out in flow fields in the absence of a physical target. To do this, we studied the everyday task of lane changing, a commonplace multiphase steering maneuver which can be conceptualized without the need for a target. What is more (and here is the crucial quirk), previous literature has found that in the absence of visual feedback, drivers show a systematic, asymmetric steering response, resulting in a systematic final heading error. If optic flow is sufficient for controlling navigation through our environment, we would expect this asymmetry to disappear whenever optic flow is provided. However, our results show that this asymmetry persisted, even in the presence of a flow field, implying that drivers are unable to use flow to guide normal steering responses in this task.

Expert - Non-expert differences in visual behaviour during alpine slalom skiing

The aim of this study was to investigate visual behaviour of expert and non-expert ski athletes during an alpine slalom. Fourteen non-experts and five expert slalom skiers completed an alpine slalom course in an indoor ski slope while wearing a head-mounted eye tracking device. Experts completed the slalom clearly faster than non-experts, but no significant difference was found in timing and position of the turn initiation. Although both groups already looked at future obstacles approximately 0,5s before passing the upcoming pole, the higher speed of experts implied that they shifted gaze spatially earlier in the bend than non-experts. Furthermore, experts focussed more on the second next pole while non-expert slalom skiers looked more to the snow surface immediately in front of their body. No difference was found in the fixation frequency, average fixation duration, and quiet eye duration between both groups. These results suggest that experts focus on the timing of their actions while non-experts still need to pay attention to the execution of these actions. These results also might suggest that ski trainers should instruct non-experts and experts to focus on the next pole and, shift their gaze to the second next pole shortly before reaching it. Based on the current study it seems unadvisable to instruct slalom skiers to look several poles ahead during the actual slalom. However, future research should test if these results still hold on a real outdoor slope, including multiple vertical gates.

Learning game for training child bicyclists' situation awareness

Encouraging more children to bicycle would produce both environmental and health benefits, but bicycling accidents are a major source of injuries and fatalities among children. One reason for this may be children's less developed hazard perception skills. We assume that children's situation awareness could be trained with a computer based learning game, which should also improve their hazard perception skills. In this paper, we present a prototype for such a game and pilot it with 8-9year old children. The game consisted of videos filmed from a bicyclist's perspective. Using a touchscreen, the player's task was to point out targets early enough to gain points. The targets were either overt (other visible road users on a potentially conflicting course) or covert (occlusions, i.e. locations where other road users could suddenly emerge). If a target was missed or identified too late, the video was paused and feedback was given. The game was tested with 49 children from the 2nd grade of primary school (aged 8-9). 31 young adults (aged 22-34) played the game for comparison. The effect of the game on situation awareness was assessed with situation awareness tests in a crossover design. Similar videos were used in the tests as in the game, but instead of pointing out the targets while watching, the video was suddenly masked and participants were asked to locate all targets which had been present just before the masking, choosing among several possible locations. Their performance was analyzed using Signal Detection Theory and answer latencies. The game decreased answer latency and marginally changed response bias in a less conservative direction for both children and adults, but it did not significantly increase sensitivity for targets. Adults performed better in the tests and in the game, and it was possible to satisfactorily predict group membership based on the scores. Children found it especially difficult to find covert targets. Overall, the described version of the learning game cannot be regarded as an effective tool for situation awareness/hazard perception training, but ways to improve the game are discussed.

Dynamic Speed Adaptation for Path Tracking Based on Curvature Information and Speed Limits

A critical concern of autonomous vehicles is safety. Different approaches have tried to enhance driving safety to reduce the number of fatal crashes and severe injuries. As an example, Intelligent Speed Adaptation (ISA) systems warn the driver when the vehicle exceeds the recommended speed limit. However, these systems only take into account fixed speed limits without considering factors like road geometry. In this paper, we consider road curvature with speed limits to automatically adjust vehicle’s speed with the ideal one through our proposed Dynamic Speed Adaptation (DSA) method. Furthermore, ‘curve analysis extraction’ and ‘speed limits database creation’ are also part of our contribution. An algorithm that analyzes GPS information off-line identifies high curvature segments and estimates the speed for each curve. The speed limit database contains information about the different speed limit zones for each traveled path. Our DSA senses speed limits and curves of the road using GPS information and ensures smooth speed transitions between current and ideal speeds. Through experimental simulations with different control algorithms on real and simulated datasets, we prove that our method is able to significantly reduce lateral errors on sharp curves, to respect speed limits and consequently increase safety and comfort for the passenger.

Systematic Observation of an Expert Driver's Gaze Strategy-An On-Road Case Study

In this paper we present and qualitatively analyze an expert driver's gaze behavior in natural driving on a real road, with no specific experimental task or instruction. Previous eye tracking research on naturalistic tasks has revealed recurring patterns of gaze behavior that are surprisingly regular and repeatable. Lappi (2016) identified in the literature seven “qualitative laws of gaze behavior in the wild”: recurring patterns that tend to go together, the more so the more naturalistic the setting, all of them expected in extended sequences of fully naturalistic behavior. However, no study to date has observed all in a single experiment. Here, we wanted to do just that: present observations supporting all the “laws” in a single behavioral sequence by a single subject. We discuss the laws in terms of unresolved issues in driver modeling and open challenges for experimental and theoretical development.

Mobile Eye Tracking During Real-World Night Driving: A Selective Review of Findings and Recommendations for Future Research

We exhaustively review the published research on eye movements during real-world night driving, which is an important field of research as fatal road traffic accidents at night out-number fatal accidents during the daytime. Eye tracking provides a unique window into the underlying cognitive processes. The studies were interpreted and evaluated against the back-ground of two descriptions of the driving task: Gibson and Crooks’ description of driving as the visually guided selection of a driving path through the unobstructed field of safe travel; and Endsley’s situation awareness model, highlighting the influence of drivers’ interpreta-tions and mental capacities (e.g., cognitive load, memory capacity, etc.) for successful task performance. Our review unveiled that drivers show expedient looking behavior, directed to the boundaries of the field of safe travel and other road users. Thus, the results indicated that controlled (intended) eye movements supervened, but some results could have also reflected automatic gaze attraction by salient but task-irrelevant distractors. Also, it is not entirely certain whether a wider dispersion of eye fixations during daytime driving (compared to night driving) reflected controlled and beneficial strategies, or whether it was (partly) due to distraction by stimuli unrelated to driving. We concluded by proposing a more fine-grained description of the driving task, in which the contribution of eye movements to three different subtasks is detailed. This model could help filling an existing gap in the reviewed research: Most studies did not relate eye movements to other driving performance measurements for the evaluation of real-world night driving performance.

Game-based situation awareness training for child and adult cyclists

Safe cycling requires situation awareness (SA), which is the basis for recognizing and anticipating hazards. Children have poorer SA than adults, which may put them at risk. This study investigates whether cyclists' SA can be trained with a video-based learning game. The effect of executive working memory on SA was also studied. Thirty-six children (9-10 years) and 22 adults (21-48 years) played the game. The game had 30 video clips filmed from a cyclist's perspective. Each clip was suddenly masked and two or three locations were presented. The player's task was to choose locations with a potential hazard and feedback was given for their answers. Working memory capacity (WMC) was tested with a counting span task. Children's and adults' performance improved while playing the game, which suggests that playing the game trains SA. Adults performed better than children, and they also glanced at hazards more while the video was playing. Children expectedly had a lower WMC than adults, but WMC did not predict performance within the groups. This indicates that SA does not depend on WMC when passively viewing videos.

Training driving ability in a traumatic brain-injured individual using a driving simulator: a case report

Background

Traumatic brain injury (TBI) causes functional deficits that may significantly interfere with numerous activities of daily living such as driving. We report the case of a 20-year-old woman having lost her driver’s license after sustaining a moderate TBI.

Objective

We aimed to evaluate the effectiveness of an in-simulator training program with automated feedback on driving performance in a TBI individual.

Methods

The participant underwent an initial and a final in-simulator driving assessment and 11 in-simulator training sessions with driving-specific automated feedbacks. Driving performance (simulation duration, speed regulation and lateral positioning) was measured in the driving simulator.

Results

Speeding duration decreased during training sessions from 1.50 ± 0.80 min (4.16 ± 2.22%) to 0.45 ± 0.15 min (0.44 ± 0.42%) but returned to initial duration after removal of feedbacks for the final assessment. Proper lateral positioning improved with training and was maintained at the final assessment. Time spent in an incorrect lateral position decreased from 18.85 min (53.61%) in the initial assessment to 1.51 min (4.64%) on the final assessment.

Conclusion

Driving simulators represent an interesting therapeutic avenue. Considerable research efforts are needed to confirm the effectiveness of this method for driving rehabilitation of individuals who have sustained a TBI.

Drivers' Visual Behavior-Guided RRT Motion Planner for Autonomous On-Road Driving

This paper describes a real-time motion planner based on the drivers’ visual behavior-guided rapidly exploring random tree (RRT) approach, which is applicable to on-road driving of autonomous vehicles. The primary novelty is in the use of the guidance of drivers’ visual search behavior in the framework of RRT motion planner. RRT is an incremental sampling-based method that is widely used to solve the robotic motion planning problems. However, RRT is often unreliable in a number of practical applications such as autonomous vehicles used for on-road driving because of the unnatural trajectory, useless sampling, and slow exploration. To address these problems, we present an interesting RRT algorithm that introduces an effective guided sampling strategy based on the drivers’ visual search behavior on road and a continuous-curvature smooth method based on B-spline. The proposed algorithm is implemented on a real autonomous vehicle and verified against several different traffic scenarios. A large number of the experimental results demonstrate that our algorithm is feasible and efficient for on-road autonomous driving. Furthermore, the comparative test and statistical analyses illustrate that its excellent performance is superior to other previous algorithms.

Effects of fog, driver experience and gender on driving behavior on S-curved road segments

Driving on curved roads has been recognized as a significant safety issue for many years. However, driver behavior and the interactions among variables that affect driver performance on curves is complicated and not well understood. Previous studies have investigated various factors that influence driver performance on right- or left-turn curves, but have paid little attention to the effects of foggy weather, driver experience and gender on driver performance on complex curves. A driving simulator experiment was conducted in this study to evaluate the relationships between driving behavior on a continuous S-curve and foggy weather, driver experience and gender. The process of negotiating a curve was divided into three stages consisting of a straight segment, the transition from the straight segment to the S-curve and the S-curve. The experimental results indicated that drivers tended to drive more cautiously in heavy fog, but the driving risk was still increased, especially in the transition stage from the straight segment to the S-curve. The non-professional (NP) drivers were less sensitive to the impending change in the road geometry, and less skilled in both longitudinal and lateral vehicle control than the professional drivers. The NP female drivers in particular were found to be the most vulnerable group in S-curve driving.

On-road experiment to assess drivers' detection of roadside targets as a function of headlight system, target placement, and target reflectance

Adaptive headlights swivel with steering input to keep the beams on the roadway as drivers negotiate curves. To assess the effects of this feature on driver's visual performance, a field experiment was conducted at night on a rural, unlit, and unlined two-lane road during which 20 adult participant drivers searched a set of 60 targets. High- (n=30) and low- (n=30) reflectance targets were evenly distributed on straight road sections and on the inside or outside of curves. Participants completed three target detection trials: once with adaptive high-intensity discharge (HID) headlights, once with fixed HID headlights, and once with fixed halogen headlights. Results indicated the adaptive HID headlights helped drivers detect targets that were most difficult to see (low reflectance) at the points in curves found by other researchers to be most crucial for successful navigation (inside apex). For targets placed on straight stretches of road or on the outside of curves, the adaptive feature provided no significant improvement in target detection. However, the pattern of results indicate that HID lamps whether fixed or adaptive improved target detection somewhat, suggesting that part of the real world crash reduction measured for this adaptive system (Highway Loss Data Institute (HLDI), 2012a) may be due to the differences in the light source (HID vs. halogen). Depending on the scenario, the estimated benefits to driver response time associated with the tested adaptive (swiveling HID) headlights ranged from 200 to 380ms compared with the fixed headlight systems tested.