Should I Stay or Should I Go? Cognitive Modeling of Left-Turn Gap Acceptance Decisions in Human Drivers.

OBJECTIVE: We aim to bridge the gap between naturalistic studies of driver behavior and modern cognitive and neuroscientific accounts of decision making by modeling the cognitive processes underlying left-turn gap acceptance by human drivers. BACKGROUND: Understanding decisions of human drivers is essential for the development of safe and efficient transportation systems. Current models of decision making in drivers provide little insight into the underlying cognitive processes. On the other hand, laboratory studies of abstract, highly controlled tasks point towards noisy evidence accumulation as a key mechanism governing decision making. However, it is unclear whether the cognitive processes implicated in these tasks are as paramount to decisions that are ingrained in more complex behaviors, such as driving. RESULTS: The drivers' probability of accepting the available gap increased with the size of the gap; importantly, response time increased with time gap but not distance gap. The generalized drift-diffusion model explained the observed decision outcomes and response time distributions, as well as substantial individual differences in those. Through cross-validation, we demonstrate that the model not only explains the data, but also generalizes to out-of-sample conditions. CONCLUSION: Our results suggest that dynamic evidence accumulation is an essential mechanism underlying left-turn gap acceptance decisions in human drivers, and exemplify how simple cognitive process models can help to understand human behavior in complex real-world tasks. APPLICATION: Potential applications of our results include real-time prediction of human behavior by automated vehicles and simulating realistic human-like behaviors in virtual environments for automated vehicles.

Drivers of partially automated vehicles are blamed for crashes that they cannot reasonably avoid.

People seem to hold the human driver to be primarily responsible when their partially automated vehicle crashes, yet is this reasonable? While the driver is often required to immediately take over from the automation when it fails, placing such high expectations on the driver to remain vigilant in partially automated driving is unreasonable. Drivers show difficulties in taking over control when needed immediately, potentially resulting in dangerous situations. From a normative perspective, it would be reasonable to consider the impact of automation on the driver's ability to take over control when attributing responsibility for a crash. We, therefore, analyzed whether the public indeed considers driver ability when attributing responsibility to the driver, the vehicle, and its manufacturer. Participants blamed the driver primarily, even though they recognized the driver's decreased ability to avoid the crash. These results portend undesirable situations in which users of partially driving automation are the ones held responsible, which may be unreasonable due to the detrimental impact of driving automation on human drivers. Lastly, the outcome signals that public awareness of such human-factors issues with automated driving should be improved.

Should Steering Settings be Changed by the Driver or by the Vehicle Itself?

INTRODUCTION: Cars are increasingly computerized, and vehicle settings such as steering gain (SG) can now be altered during driving. However, it is unknown whether transitions in SG should be adaptable (i.e., triggered by driver input) or adaptive (i.e., triggered automatically). We examined this question for road segments expected to require different SG. OBJECTIVE: This paper aimed to investigate whether SG mode changes should be made by the driver or automatically. METHODS: Twenty-four participants drove under four conditions in a simulator: fixed low gain (FL), fixed high gain (FH), a machine-initiated steering system, which switched between the two SG levels at predetermined locations (MI), and a driver-initiated steering system, in which the SG level could be changed by pressing a button on the steering wheel (DI). RESULTS: Participants showed poorer lane-keeping and reported higher effort for FH compared to FL on straights, while the opposite held true on curved roads. On curved roads, the MI condition yielded better lane-keeping and lower subjective effort than the DI condition. However, a substantial portion of the drivers gave low preference rankings to the MI system. CONCLUSION: Drivers prefer and benefit from a steering system with a variable rather than fixed gain. Furthermore, although automatic SG transitions reduce effort, some drivers reject this concept. APPLICATION: As the state of technology advances, MI transitions are becoming increasingly feasible, but whether drivers would want to delegate their decision-making authority to a machine remains a moot point.

Haptic Lane-Keeping Assistance for Truck Driving: A Test Track Study.

OBJECTIVE: This study aims to compare the effectiveness and subjective acceptance of three designs for haptic lane-keeping assistance in truck driving. BACKGROUND: Haptic lane-keeping assistance provides steering torques toward a reference trajectory, either continuously or only when exceeding a bandwidth. These approaches have been previously investigated in driving simulators, but it is unclear how these generalize toward real-life truck driving. METHOD: Three haptic lane-keeping algorithms to assist truck drivers were evaluated on a 6.3-km-long oval-shaped test track: (1) a single-bandwidth (SB) algorithm, which activated assistance torques when the predicted lateral deviation from lane center exceeded 0.4 m; (2) a double-bandwidth (DB) algorithm, which activated as SB, but deactivated after returning within 0.15 m lateral deviation; and (3) an algorithm providing assistance torques continuously (Cont) toward the lane center. Fifteen participants drove four trials each, one trial without and one for each haptic assistance design. Furthermore, participants drove with and without a concurrent visually distracting task. RESULTS: Compared to unsupported driving, all three assistance systems provided similar safety benefits in terms of decreased absolute lateral position and number of lane departures. Participants reported higher satisfaction and usability for Cont compared to SB. CONCLUSION: The continuous assistance was better accepted than bandwidth assistance, a finding consistent with prior driving simulator research. Research is still needed to investigate the long-term effects of haptic assistance on reliance and after-effects. APPLICATION: The present results are useful for designers of haptic lane-keeping assistance, as driver acceptance and performance are determinants of reliance and safety, respectively.

Human-like driving behaviour emerges from a risk-based driver model.

Current driving behaviour models are designed for specific scenarios, such as curve driving, obstacle avoidance, car-following, or overtaking. However, humans can drive in diverse scenarios. Can we find an underlying principle from which driving behaviour in different scenarios emerges? We propose the Driver's Risk Field (DRF), a two-dimensional field that represents the driver's belief about the probability of an event occurring. The DRF, when multiplied with the consequence of the event, provides an estimate of the driver's perceived risk. Through human-in-the-loop and computer simulations, we show that human-like driving behaviour emerges when the DRF is coupled to a controller that maintains the perceived risk below a threshold-level. The DRF model predictions concur with driving behaviour reported in literature for seven different scenarios (curve radii, lane widths, obstacle avoidance, roadside furniture, car-following, overtaking, oncoming traffic). We conclude that our generalizable DRF model is scientifically satisfying and has applications in automated vehicles.

Which parts of the road guide obstacle avoidance? Quantifying the driver's risk field.

Gibson and Crooks (1938) argued that a 'field of safe travel' could qualitatively explain drivers' steering behavior on straights, curved roads, and while avoiding obstacles. This study aims to quantitatively explain driver behavior while avoiding obstacles on a straight road, and quantify the 'Driver's Risk Field' (DRF). In a fixed-based driving simulator, 77 (7 longitudinal and 11 lateral) positions of the obstacles were used to quantify the subjectively perceived and objectively (maximum absolute steering angle) measured DRF for eight participants. The subjective response was a numerical answer to the question "How much steering do you think you need at this moment in time?" The results show that the propagation of the width of the DRF, along the longitudinal distance, resembled an hourglass shape, and all participants responded to obstacles that were placed beyond the width of the car. This implies that the Driver's Risk Field is wider than the car width.

Perception and control of low cable operation forces in voluntary closing body-powered upper-limb prostheses.

Operating a body-powered prosthesis can be painful and tiring due to high cable operation forces, illustrating that low cable operation forces are a desirable design property for body-powered prostheses. However, lower operation forces might negatively affect controllability and force perception, which is plausible but not known. This study aims to quantify the accuracy of cable force perception and control for body-powered prostheses in a low cable operation force range by utilizing isometric and dynamic force reproduction experiments. Twenty-five subjects with trans-radial absence conducted two force reproduction tasks; first an isometric task of reproducing 10, 15, 20, 25, 30 or 40 N and second a force reproduction task of 10 and 20 N, for cable excursions of 10, 20, 40, 60 and 80 mm. Task performance was quantified by the force reproduction error and the variability in the generated force. The results of the isometric experiment demonstrated that increasing force levels enlarge the force variability, but do not influence the force reproduction error for the tested force range. The second experiment showed that increased cable excursions resulted in a decreased force reproduction error, for both tested force levels, whereas the force variability remained unchanged. In conclusion, the design recommendations for voluntary closing body-powered prostheses suggested by this study are to minimize cable operation forces: this does not affect force reproduction error but does reduce force variability. Furthermore, increased cable excursions facilitate users with additional information to meet a target force more accurately.

Haptic Assistance Improves Tele-Manipulation With Two Asymmetric Slaves.

Tele-manipulation of heavy loads typically requires the simultaneous use of two asymmetric slaves: a crane for vertical weight support and a robot for accurate lateral positioning. The industrial standard prescribes a pair of operators for such tasks (one operator to control each slave), although in principle one operator might control both slaves with a single, hybrid interface. Accurate and safe co-operative handling of the expensive and fragile heavy components is difficult, presumably due to problems in the coordination of the subtasks and the lack of mutual awareness between the two operators. This study proposes a novel haptic assistance system to improve subtask coordination and task performance. Its novelty consists of haptically linking operators/interfaces through the joint task environment. The system's efficacy is evaluated with 15 pairs of co-operators and 15 individual uni-manual operators who maneuvered a heavy load through a bounded path in Virtual Reality. Haptic assistance improves task completion time for both groups. It also reduces control activity and self-reported workload without affecting a number of critical errors made by the operators. Moreover, without haptic assistance, uni-manual operators perform worse than co-operators, but this difference between the interfaces was not found with haptic assistance.

Reliance on Haptic Assistance Reflected in Haptic Cue Weighting.

When using an automated system, user trust in the automation is an important factor influencing performance. Prior studies have analyzed trust duringsupervisory control of automation, and how trust influences reliance: the behavioral correlate of trust. Here, we investigated how reliance on haptic assistance affects performance during shared control with an automated system. Subjects made reaches towards a hidden target using a visual cue and haptic cue (assistance from the automation). We sought to influence reliance by changing the variability of trial-by-trial random errors in the haptic assistance. Reliance was quantified in terms of the subject's position at the end of the reach relative to the two cues. Our results show that subjects aimed more towards the visual cue when the variability of the haptic cue errors increased, resembling cue weighting behavior. Similar behavior was observed both when subjects had explicit knowledge about the haptic cue error variability, as well as when they had only implicit knowledge (from experience). However, the group with explicit knowledge was able to more quickly adapt their reliance on the haptic assistance. The method we introduce here provides a quantitative way to study user reliance on the information provided by automated systems with shared control.

What determines drivers' speed? A replication of three behavioural adaptation experiments in a single driving simulator study.

We conceptually replicated three highly cited experiments on speed adaptation, by measuring drivers' experienced risk (galvanic skin response; GSR), experienced task difficulty (self-reported task effort; SRTE) and safety margins (time-to-line-crossing; TLC) in a single experiment. The three measures were compared using a nonparametric index that captures the criteria of constancy during self-paced driving and sensitivity during forced-paced driving. In a driving simulator, 24 participants completed two forced-paced and one self-paced run. Each run held four different lane width conditions. Results showed that participants drove faster on wider lanes, thus confirming the expected speed adaptation. None of the three measures offered persuasive evidence for speed adaptation because they failed either the sensitivity criterion (GSR) or the constancy criterion (TLC, SRTE). An additional measure, steering reversal rate, outperformed the other three measures regarding sensitivity and constancy, prompting a further evaluation of the role of control activity in speed adaptation. Practitioner Summary: Results from a driving simulator experiment suggest that it is not experienced risk, experienced effort or safety margins that govern drivers' choice of speed. Rather, our findings suggest that steering reversal rate has an explanatory role in speed adaptation.

Feel-Good Robotics: Requirements on Touch for Embodiment in Assistive Robotics.

The feeling of embodiment, i.e., experiencing the body as belonging to oneself and being able to integrate objects into one's bodily self-representation, is a key aspect of human self-consciousness and has been shown to importantly shape human cognition. An extension of such feelings toward robots has been argued as being crucial for assistive technologies aiming at restoring, extending, or simulating sensorimotor functions. Empirical and theoretical work illustrates the importance of sensory feedback for the feeling of embodiment and also immersion; we focus on the the perceptual level of touch and the role of tactile feedback in various assistive robotic devices. We critically review how different facets of tactile perception in humans, i.e., affective, social, and self-touch, might influence embodiment. This is particularly important as current assistive robotic devices - such as prostheses, orthoses, exoskeletons, and devices for teleoperation-often limit touch low-density and spatially constrained haptic feedback, i.e., the mere touch sensation linked to an action. Here, we analyze, discuss, and propose how and to what degree tactile feedback might increase the embodiment of certain robotic devices, e.g., prostheses, and the feeling of immersion in human-robot interaction, e.g., in teleoperation. Based on recent findings from cognitive psychology on interactive processes between touch and embodiment, we discuss technical solutions for specific applications, which might be used to enhance embodiment, and facilitate the study of how embodiment might alter human-robot interactions. We postulate that high-density and large surface sensing and stimulation are required to foster embodiment of such assistive devices.

Tele-Manipulation with Two Asymmetric Slaves: Two Operators Perform Better Than One.

Certain tele-manipulation tasks require manipulation by two asymmetric slaves, for example, a crane for hoisting and a dexterous robotic arm for fine manipulation. It is unclear how to best design human-in-the-loop control over two asymmetric slaves. The goal of this paper is to quantitatively compare the standard approach of two co-operating operators that each control a single subtask, to a single operator performing bi-manual control over the two subtasks, and a uni-manual control approach. In a human factors experiment, participants performed a heavy load maneuvering and mounting task using a vertical crane and a robotic arm. We hypothesize that bi-manual control yields worse task performance and control activity compared to co-operation, because of conflicting spatial and temporal constraints. Literature suggests that uni-manual operators should perform better than co-operation, as co-operators critically depend on each other's actions. However, other literature provides evidence that individual operators have limited capabilities in controlling asymmetric axes of two dynamic systems. The results show that the two co-operators perform the maneuvering and mounting task faster than either bi- or uni-manual operators. Compared to co-operators, uni-manual operators required more control activity for the vertical crane and less for the robotic arm. In conclusion, this study suggests that when controlling two asymmetric slaves, a co-operating pair of operators performs better than a single operator.

Trust in haptic assistance: weighting visual and haptic cues based on error history.

To effectively interpret and interact with the world, humans weight redundant estimates from different sensory cues to form one coherent, integrated estimate. Recent advancements in physical assistance systems, where guiding forces are computed by an intelligent agent, enable the presentation of augmented cues. It is unknown, however, if cue weighting can be extended to augmented cues. Previous research has shown that cue weighting is determined by the reliability (inversely related to uncertainty) of cues within a trial, yet augmented cues may also be affected by errors that vary over trials. In this study, we investigate whether people can learn to appropriately weight a haptic cue from an intelligent assistance system based on its error history. Subjects held a haptic device and reached to a hidden target using a visual (Gaussian distributed dots) and haptic (force channel) cue. The error of the augmented haptic cue varied from trial to trial based on a Gaussian distribution. Subjects learned to estimate the target location by weighting the visual and augmented haptic cues based on their perceptual uncertainty and experienced errors. With both cues available, subjects were able to find the target with an improved or equal performance compared to what was possible with one cue alone. Our results show that the brain can learn to reweight augmented cues from intelligent agents, akin to previous observations of the reweighting of naturally occurring cues. In addition, these results suggest that the weighting of a cue is not only affected by its within-trial reliability but also the history of errors.

High Cable Forces Deteriorate Pinch Force Control in Voluntary-Closing Body-Powered Prostheses.

BACKGROUND: It is generally asserted that reliable and intuitive control of upper-limb prostheses requires adequate feedback of prosthetic finger positions and pinch forces applied to objects. Body-powered prostheses (BPPs) provide the user with direct proprioceptive feedback. Currently available BPPs often require high cable operation forces, which complicates control of the forces at the terminal device. The aim of this study is to quantify the influence of high cable forces on object manipulation with voluntary-closing prostheses. METHOD: Able-bodied male subjects were fitted with a bypass-prosthesis with low and high cable force settings for the prehensor. Subjects were requested to grasp and transfer a collapsible object as fast as they could without dropping or breaking it. The object had a low and a high breaking force setting. RESULTS: Subjects conducted significantly more successful manipulations with the low cable force setting, both for the low (33% more) and high (50%) object's breaking force. The time to complete the task was not different between settings during successful manipulation trials. CONCLUSION: High cable forces lead to reduced pinch force control during object manipulation. This implies that low cable operation forces should be a key design requirement for voluntary-closing BPPs.

Admittance-Adaptive Model-Based Approach to Mitigate Biodynamic Feedthrough.

Biodynamic feedthrough (BDFT) refers to the feedthrough of vehicle accelerations through the human body, leading to involuntary control device inputs. BDFT impairs control performance in a large range of vehicles under various circumstances. Research shows that BDFT strongly depends on adaptations in the neuromuscular admittance dynamics of the human body. This paper proposes a model-based approach of BDFT mitigation that accounts for these neuromuscular adaptations. The method was tested, as proof-of-concept, in an experiment where participants inside a motion simulator controlled a simulated vehicle through a virtual tunnel. Through evaluating tracking performance and control effort with and without motion disturbance active and with and without cancellation active, the effectiveness of the cancellation was evaluated. Results show that the cancellation approach is successful: the detrimental effects of BDFT were largely removed.

Movement Strategy Discovery during Training via Haptic Guidance.

Haptic guidance has previously been investigated to facilitate motor skill training, whereupon a robotic device assists a trainee in executing the desired movement. However, many studies have reported a null or even detrimental effect of haptic guidance on training compared to unassisted practice. While prior studies have focused on using haptic guidance to refine a movement strategy, our study explores its effect on the discovery of a new strategy. Subjects learned to manipulate a virtual under-actuated system via a haptic device either with or without haptic guidance (and without haptic feedback of system dynamics). The guidance enabled subjects to experience a range of successful movements, rather than strictly enforcing one trajectory. Subjects who trained with guidance adopted a strategy that involved faster reaches, required greater control of the system's degrees of freedom, and increased the potential for faster task completion. However, overall improvement of task performance was limited with the new strategy.

The Effect of Trial-by-Trial Adaptation on Conflicts in Haptic Shared Control for Free-Air Teleoperation Tasks.

Haptic shared control can improve execution of teleoperation and driving tasks. However, shared control designs may suffer from conflicts between individual human operators and constant haptic assistance when their desired trajectories differ, leading to momentarily increased forces, discomfort, or even deteriorated performance. This study investigates ways to reduce conflicts between individual human operators and a haptic shared controller by modifying supported trajectories. Subjects (n=12) performed a repetitive movement task in an abstract environment with varying spatio-temporal constraints, both during manual control and while supported by haptic shared control. Four types of haptic shared control were compared, combining two design properties: the initial supported trajectory (either the centerline of the environment or an individualized trajectory based on manual control trials), and trial-by-trial adaptation of guidance towards previously performed trajectories (either present or absent). Trial-by-trial adaptation of guidance reduced conflicts compared to non-adaptive guidance, whether the initial trajectory was individualized or not. Without trial-by-trial adaptation, individualized trajectories also reduced conflicts, but not completely: when guided, operators adapt their preferred trajectories. In conclusion, trial-by-trial adaptation is the most promising approach to mitigate conflicts during repetitive motion tasks.

The Effect of Haptic Support Systems on Driver Performance: A Literature Survey.

A large number of haptic driver support systems have been described in the scientific literature. However, there is little consensus regarding the design, evaluation methods, and effectiveness of these systems. This literature survey aimed to investigate: (1) what haptic systems (in terms of function, haptic signal, channel, and supported task) have been experimentally tested, (2) how these haptic systems have been evaluated, and (3) their reported effects on driver performance and behaviour. We reviewed empirical research in which participants had to drive a vehicle in a real or simulated environment, were able to control the heading and/or speed of the vehicle, and a haptic signal was provided to them. The results indicated that a clear distinction can be made between warning systems (using vibrations) and guidance systems (using continuous forces). Studies typically used reaction time measures for evaluating warning systems and vehicle-centred performance measures for evaluating guidance systems. In general, haptic warning systems reduced the reaction time of a driver compared to no warnings, although these systems may cause annoyance. Guidance systems generally improved the performance of drivers compared to non-aided driving, but these systems may suffer from after-effects. Longitudinal research is needed to investigate the transfer and retention of effects caused by haptic support systems.

Haptic Shared Control in Tele-Manipulation: Effects of Inaccuracies in Guidance on Task Execution.

Haptic shared control is a promising approach to improve tele-manipulated task execution, by making safe and effective control actions tangible through guidance forces. In current research, these guidance forces are most often generated based on pre-generated, errorless models of the remote environment. Hence such guidance forces are exempt from the inaccuracies that can be expected in practical implementations. The goal of this research is to quantify the extent to which task execution is degraded by inaccuracies in the model on which haptic guidance forces are based. In a human-in-the-loop experiment, subjects (n = 14) performed a realistic tele-manipulated assembly task in a virtual environment. Operators were provided with various levels of haptic guidance, namely no haptic guidance (conventional tele-manipulation), haptic guidance without inaccuracies, and haptic guidance with translational inaccuracies (one large inaccuracy, in the order of magnitude of the task, and a second smaller inaccuracy). The quality of natural haptic feedback (i.e., haptic transparency) was varied between high and low to identify the operator's ability to detect and cope with inaccuracies in haptic guidance. The results indicate that haptic guidance is beneficial for task execution when no inaccuracies are present in the guidance. When inaccuracies are present, this may degrade task execution, depending on the magnitude and the direction of the inaccuracy. The effect of inaccuracies on overall task performance is dominated by effects found for the Constrained Translational Movement, due to its potential for jamming. No evidence was found that a higher quality of haptic transparency helps operators to detect and cope with inaccuracies in the haptic guidance.

Should drivers be operating within an automation-free bandwidth? Evaluating haptic steering support systems with different levels of authority.

OBJECTIVE: The aim of this study was to compare continuous versus bandwidth haptic steering guidance in terms of lane-keeping behavior, aftereffects, and satisfaction. BACKGROUND: An important human factors question is whether operators should be supported continuously or only when tolerance limits are exceeded. We aimed to clarify this issue for haptic steering guidance by investigating costs and benefits of both approaches in a driving simulator. METHODS: Thirty-two participants drove five trials, each with a different level of haptic support: no guidance (Manual); guidance outside a 0.5-m bandwidth (Band1); a hysteresis version of Band1, which guided back to the lane center once triggered (Band2); continuous guidance (Cont); and Cont with double feedback gain (ContS). Participants performed a reaction time task while driving. Toward the end of each trial, the guidance was unexpectedly disabled to investigate aftereffects. RESULTS: All four guidance systems prevented large lateral errors (>0.7 m). Cont and especially ContS yielded smaller lateral errors and higher time to line crossing than Manual, Band1, and Band2. Cont and ContS yielded short-lasting aftereffects, whereas Band1 and Band2 did not. Cont yielded higher self-reported satisfaction and faster reaction times than Band1. CONCLUSIONS: Continuous and bandwidth guidance both prevent large driver errors. Continuous guidance yields improved performance and satisfaction over bandwidth guidance at the cost of aftereffects and variability in driver torque (indicating human-automation conflicts). APPLICATION: The presented results are useful for designers of haptic guidance systems and support critical thinking about the costs and benefits of automation support systems.