Visuomotor control of steering: the artefact of the matter

An Investigation of Early Detection of Driver Drowsiness Using Ensemble Machine Learning Based on Hybrid Sensing

Drowsy driving is one of the main causes of traffic accidents. To reduce such accidents, early detection of drowsy driving is needed. In previous studies, it was shown that driver drowsiness affected driving performance, behavioral indices, and physiological indices. The purpose of this study is to investigate the feasibility of classification of the alert states of drivers, particularly the slightly drowsy state, based on hybrid sensing of vehicle-based, behavioral, and physiological indicators with consideration for the implementation of these identifications into a detection system. First, we measured the drowsiness level, driving performance, physiological signals (from electroencephalogram and electrocardiogram results), and behavioral indices of a driver using a driving simulator and driver monitoring system. Next, driver alert and drowsy states were identified by machine learning algorithms, and a dataset was constructed from the extracted indices over a period of 10 s. Finally, ensemble algorithms were used for classification. The results showed that the ensemble algorithm can obtain 82.4% classification accuracy using hybrid methods to identify the alert and slightly drowsy states, and 95.4% accuracy classifying the alert and moderately drowsy states. Additionally, the results show that the random forest algorithm can obtain 78.7% accuracy when classifying the alert vs. slightly drowsy states if physiological indicators are excluded and can obtain 89.8% accuracy when classifying the alert vs. moderately drowsy states. These results represent the feasibility of highly accurate early detection of driver drowsiness and the feasibility of implementing a driver drowsiness detection system based on hybrid sensing using non-contact sensors.

Visual control of steering in curve driving

This pair of studies investigated steering in the absence of continuous visual information. In a driving simulator, participants steered a curving path that was displayed either continuously or intermittently. Optic flow conditions were manipulated to alter the nature of the heading information with respect to the path being steered. Removing or biasing heading information had little effect on steering even during long and frequent path occlusions as long as turn rate was available. This demonstrates that participants can use intermittent views of the path to plan their steering actions and optic flow to accurately update vehicle turns with respect to that path.

What is the difference in driver's lateral control ability during naturalistic distracted driving and normal driving? A case study on a real highway

Driver distraction is widely recognized as a major contributor to traffic crashes. Although the effect of distraction on simulated driving performance has been studied extensively, comparatively little research based on field tests has been performed on the effects of high driving speeds on lateral driving performance during naturalistic distraction (the driver was unaware of the research topic). In this study, an instrumented vehicle is used to examine the impact of speed and naturalistic visual distraction (rear vehicle's velocity and relative distance estimation) on a driver's ability to keep in the lane. Similar to results from previous studies, visual distraction resulted in an impaired ability to keep in a lane compared to normal driving. Further investigation of steering control parameters showed an increase in steering wheel reversal rates (SRRs at 1.3° and 2.5° levels) and the standard deviation of steering wheel acceleration (SDSWA). The results of this study indicated that the standard deviation of lane positioning (SDLP) and trajectory offset (TO) increased as speed increased. As speed increased, the growth rates of SDLP and TO in the visual distraction task were the same as that in normal driving. Moreover, the SRRs and steering wheel acceleration (SWA) decreased with increased speed. As speed increased, the growth rates of SRRs and SWA during a visual distraction task were the same as that during normal driving. These results suggest that driving speed has a similar effect on driving performance during both distracted driving and normal driving.

Steering bends and changing lanes: The impact of optic flow and road edges on two point steering control

Successful driving involves steering corrections that respond to immediate positional errors while also anticipating upcoming changes to the road layout ahead. In popular steering models these tasks are often treated as separate functions using two points: the near region for correcting current errors, and the far region for anticipating future steering requirements. Whereas two-point control models can capture many aspects of driver behavior, the nature of perceptual inputs to these two "points" remains unclear. Inspired by experiments that solely focused on road-edge information (Land & Horwood, 1995), two-point models have tended to ignore the role of optic flow during steering control. There is recent evidence demonstrating that optic flow should be considered within two-point control steering models (Mole, Kountouriotis, Billington, & Wilkie, 2016). To examine the impact of optic flow and road edges on two-point steering control we used a driving simulator to selectively and systematically manipulate these components. We removed flow and/or road-edge information from near or far regions of the scene, and examined how behaviors changed when steering along roads where the utility of far-road information varied. While steering behaviors were strongly influenced by the road-edges, there were also clear contributions of optic flow to steering responses. The patterns of steering were not consistent with optic flow simply feeding into two-point control; rather, the global optic flow field appeared to support effective steering responses across the time-course of each trajectory.

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.

Identifying cognitive distraction using steering wheel reversal rates

The influence of driver distraction on driving performance is not yet well understood, but it can have detrimental effects on road safety. In this study, we examined the effects of visual and non-visual distractions during driving, using a high-fidelity driving simulator. The visual task was presented either at an offset angle on an in-vehicle screen, or on the back of a moving lead vehicle. Similar to results from previous studies in this area, non-visual (cognitive) distraction resulted in improved lane keeping performance and increased gaze concentration towards the centre of the road, compared to baseline driving, and further examination of the steering control metrics indicated an increase in steering wheel reversal rates, steering wheel acceleration, and steering entropy. We show, for the first time, that when the visual task is presented centrally, drivers' lane deviation reduces (similar to non-visual distraction), whilst measures of steering control, overall, indicated more steering activity, compared to baseline. When using a visual task that required the diversion of gaze to an in-vehicle display, but without a manual element, lane keeping performance was similar to baseline driving. Steering wheel reversal rates were found to adequately tease apart the effects of non-visual distraction (increase of 0.5° reversals) and visual distraction with offset gaze direction (increase of 2.5° reversals). These findings are discussed in terms of steering control during different types of in-vehicle distraction, and the possible role of manual interference by distracting secondary tasks.

Control order and visuomotor strategy development for joystick-steered underground shuttle cars

OBJECTIVE

In this simulator-based study, we aimed to quantify performance differences between joystick steering systems using first-order and second-order control, which are used in underground coal mining shuttle cars. In addition, we conducted an exploratory analysis of how users of the more difficult, second-order system changed their behavior over time.

BACKGROUND

Evidence from the visuomotor control literature suggests that higher-order control devices are not intuitive, which could pose a significant risk to underground mine personnel, equipment, and infrastructure.

METHOD

Thirty-six naive participants were randomly assigned to first- and second-order conditions and completed three experimental trials comprising sequences of 90 degrees turns in a virtual underground mine environment, with velocity held constant at 9 km/h(-1). Performance measures were lateral deviation, steering angle variability, high-frequency steering content, joystick activity, and cumulative time in collision with the virtual mine wall.

RESULTS

The second-order control group exhibited significantly poorer performance for all outcome measures. In addition, a series of correlation analyses revealed that changes in strategy were evident in the second-order group but not the first-order group.

CONCLUSION

Results were consistent with previous literature indicating poorer performance with higher-order control devices and caution against the adoption of the second-order joystick system for underground shuttle cars.

APPLICATION

Low-cost, portable simulation platforms may provide an effective basis for operator training and recruitment.

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

Anticipatory skills are a potential factor for novice drivers' curve accidents. Behavioural data show that steering and speed regulation are affected by forward planning of the trajectory. When approaching a curve, the relevant visual information for online steering control and for planning is located at different eccentricities, creating a need to disengage the gaze from the guidance of steering to anticipatory look-ahead fixations over curves. With experience, peripheral vision can be increasingly used in the visual guidance of steering. This could leave experienced drivers more gaze time to invest on look-ahead fixations over curves, facilitating the trajectory planning. Eighteen drivers (nine novices, nine experienced) drove an instrumented vehicle on a rural road four times in both directions. Their eye movements were analyzed in six curves. The trajectory of the car was modelled and divided to approach, entry and exit phases. Experienced drivers spent less time on the road-ahead and more time on the look-ahead fixations over the curves. Look-ahead fixations were also more common in the approach than in the entry phase of the curve. The results suggest that with experience drivers allocate greater part of their visual attention to trajectory planning.

Cycling around a curve: the effect of cycling speed on steering and gaze behavior

Although it is generally accepted that visual information guides steering, it is still unclear whether a curvature matching strategy or a ‘look where you are going’ strategy is used while steering through a curved road. The current experiment investigated to what extent the existing models for curve driving also apply to cycling around a curve, and tested the influence of cycling speed on steering and gaze behavior. Twenty-five participants were asked to cycle through a semicircular lane three consecutive times at three different speeds while staying in the center of the lane. The observed steering behavior suggests that an anticipatory steering strategy was used at curve entrance and a compensatory strategy was used to steer through the actual bend of the curve. A shift of gaze from the center to the inside edge of the lane indicates that at low cycling speed, the ‘look where you are going’ strategy was preferred, while at higher cycling speeds participants seemed to prefer the curvature matching strategy. Authors suggest that visual information from both steering strategies contributes to the steering system and can be used in a flexible way. Based on a familiarization effect, it can be assumed that steering is not only guided by vision but that a short-term learning component should also be taken into account.

The Effect of Visual Degradation on Anticipatory and Compensatory Steering Control

It has long been held that steering a vehicle is subserved by two distinct visual processes, a compensatory one for maintaining lane position and an anticipatory one for previewing the curvature of the upcoming road. In this study, we investigated the robustness of these two steering control processes by systematically degrading their visual inputs. Performance was measured at the level of vehicle position and at the level of the actions on the steering wheel. The results show that the compensatory process is more robust to visual degradation than the anticipatory process. The results are also consistent with the idea that steering is under the supervision of a combination of compensatory and anticipatory mechanisms, although they suggest that the quality of the sensory information will determine how information is combined.