Dropout during a driving simulator study: A survival analysis

IntroductionSimulator sickness is the occurrence of motion-sickness like symptoms that can occur during use of simulators and virtual reality technologies. This study investigated individual factors that contributed to simulator sickness and dropout while using a desktop driving simulator.MethodEighty-eight older adult drivers (mean age 72.82 ± 5.42 years) attempted a practice drive and two test drives. Participants also completed a battery of cognitive and visual assessments, provided information on their health and driving habits, and reported their experience of simulator sickness symptoms throughout the study.ResultsFifty-two participants dropped out before completing the driving tasks. A time-dependent Cox Proportional Hazards model showed that female gender (HR = 2.02), prior motion sickness history (HR = 2.22), and Mini-SSQ score (HR = 1.55) were associated with dropout. There were no differences between dropouts and completers on any of the cognitive abilities tests.ConclusionsOlder adults are a high-risk group for simulator sickness. Within this group, female gender and prior motion sickness history are related to simulator dropout. Higher reported experience of symptoms of simulator sickness increased rates of dropout.Practical applicationsThe results highlight the importance of screening and monitoring of participants in driving simulation studies. Older adults, females, and those with a prior history of motion sickness may be especially at risk.     

Improvement of driver active interventions during automated driving by displaying trajectory pointers—A driving simulator study

Abstract

Objective: The handover of vehicle control from automated to manual operation is a critical aspect of interaction between drivers and automated driving systems (ADS). In some cases, it is possible that the ADS may fail to detect an object. In this event, the driver must be aware of the situation and resume control of the vehicle without assistance from the system. Consequently, the driver must fulfill the following 2 main roles while driving: (1) monitor the vehicle trajectory and surrounding traffic environment and (2) actively take over vehicle control if the driver identifies a potential issue along the trajectory. An effective human–machine interface (HMI) is required that enables the driver to fulfill these roles. This article proposes an HMI that constantly indicates the future position of the vehicle.

Methods: This research used the Toyota Dynamic Driving Simulator to evaluate the effect of the proposed HMI and compares the proposed HMI with an HMI that notifies the driver when the vehicle trajectory changes. A total of 48 test subjects were divided into 2 groups of 24: One group used the HMI that constantly indicated the future position of the vehicle and the other group used the HMI that provided information when the vehicle trajectory changed.

The following instructions were given to the test subjects: (1) to not hold the steering wheel and to allow the vehicle to drive itself, (2) to constantly monitor the surrounding traffic environment because the functions of the ADS are limited, and (3) to take over driving if necessary.

The driving simulator experiments were composed of an initial 10-min acclimatization period and a 10-min evaluation period. Approximately 10?min after the start of the evaluation period, a scenario occurred in which the ADS failed to detect an object on the vehicle trajectory, potentially resulting in a collision if the driver did not actively take over control and manually avoid the object.

Results: The collision avoidance rate of the HMI that constantly indicated the future position of the vehicle was higher than that of the HMI that notified the driver of trajectory changes, χ² = 6.38, P < .05. The steering wheel hands-on and steering override timings were also faster with the proposed HMI (t test; P < .05).

Conclusions: This research confirmed that constantly indicating the position of the vehicle several seconds in the future facilitates active driver intervention when an ADS is in operation.     

Changes in driving performance after first and second eye cataract surgery: A driving simulator study

Introduction: This study investigated the separate impact of first eye and second eye cataract surgery on driving performance, as measured on a driving simulator. Method: Forty-four older drivers with bilateral cataract aged 55+ years, awaiting first eye cataract surgery participated in a prospective cohort study. They completed a questionnaire, visual tests and a driving simulator assessment at three time points: before first eye, after first eye, and after second eye cataract surgery. Generalized Estimating Equation Poisson or linear regression models were undertaken to examine the change in four driving outcomes of interest after adjusting for cataract surgery and other potential confounders. Results: The rate of crashes/near crashes decreased significantly by 36% (incidence rate ratio (IRR) 0.64, 95% CI 0.47–0.88, p = 0.01) after first eye surgery and 47% (IRR 0.53, 95% CI 0.35–0.78, p < 0.001) after second eye surgery, compared to before first eye cataract surgery, after accounting for confounders. The rate of crashes/near crashes also decreased with better contrast sensitivity (IRR 0.69, 95% CI 0.48–0.90, p = 0.041). A separate model found that time spent speeding 10 kilometers per hour or more over the limit after second eye surgery was significantly less (0.14 min, p = 0.002), compared to before first eye surgery, after accounting for confounders. As contrast sensitivity improved, the duration of speeding also decreased significantly by 0.46 min (p = 0.038). There were no statistically significant changes in lane excursions or speed variation. Practical applications: The findings highlight the importance of timely first and second eye cataract surgery to ensure driver safety, especially as older drivers wait for second eye cataract surgery. It also provides further evidence that contrast sensitivity is probably a better predictor of driving ability in older drivers with cataract than visual acuity, the measure on which driver licensing requirements are currently based, and should also be used when assessing fitness to drive.     

Relationships between frequency of driving under the influence of cannabis,self-reported reckless driving and risk-taking behavior observed in a driving simulator

IntroductionThe role of cannabis consumption in traffic crashes is unclear and the causal link between cannabis and collisions is still to be demonstrated. While cannabis use is very likely to impair driving ability, there is as yet no overwhelming evidence that cannabis use in isolation contributes more to collisions than other characteristics inherent to cannabis users. As noted in a growing body of literature, individuals driving under the influence of cannabis (DUIC) seem to exhibit a general reckless driving style putting them at higher risk to be involved in traffic crashes.MethodThis study aims at investigating the relationship between self-reported DUIC and reckless driving by means of self-reported measures and direct observations made in a driving simulator. Participants (n = 72) were required to be between 18 and 25 years of age, to hold a valid driver's license, and to drive at least twice a week. They completed standard driving simulation tasks recreating everyday on-road trivial conditions.ResultsResults show that people admitting that they commit more real-life dangerous driving behaviors reached higher maximum speed and demonstrated more reckless driving behaviors on the driving simulation tasks. Self-reported DUIC is associated with a risky driving style including a broad range of reckless on-road behaviors and support the problem driving behavior theory. Moreover, beyond confounding factors, both self-report DUIC and observed dangerous behaviors are associated with real-life traffic violations.Practical applicationsSince DUIC appears to be related to an overall reckless style of driving, it is proposed that public safety policies should be more holistic, simultaneously targeting multiple on-road dangerous behaviors for intervention.     

A simulator study of driving behavior and mental workload in mixed-use arterial road environments

Objectives: Mixed-use urban environments, such as arterial roads with adjacent commercial land uses, represent crash locations with the highest risk. These locations are often characterized by high volumes of motor vehicle traffic, on-street parking, and interactions with multiple road user groups such as pedestrians, cyclists, and public transportation. The objective of this study was to investigate previously identified crash risk factors for mixed-use urban environments and assess how parking occupancy, center medians, and cyclist volume influence performance and workload in a driving simulator study.

Methods: Thirty participants were recruited for the study. Participants completed 6 drives that presented different combinations of cyclist volume, median condition, and parking occupancy. Incorporated into the simulator drives was a secondary peripheral detection task (PDT) designed to measure mental workload. Participants provided subjective assessments of workload using the Rating Scale Mental Effort (RSME).

Results: Mean lateral lane position was found to significantly vary across the 3 independent variables of parking occupancy, cyclist volume, and median conditions. No significant changes were identified for mean speed across the conditions. Subjective and objective measures of workload identified changes due to the presence of cyclists with slower reaction times for the PDT task when cyclists were present.

Conclusion: The findings provide insight into the interaction of road design elements in mixed-use urban road environments and demonstrate that increasingly complex environments increase driver demand. This has important road design implications for mixed-use arterial roads, which are often characterized by complex interactions between multiple road user groups.     

Effects of time-gap settings of adaptive cruise control (ACC) on driving performance and subjective acceptance in a bus driving simulator

A study was conducted to investigate the effects of time-gap settings and contents of secondary tasks on a fix-based bus driving simulator on drivers’ performance while reclaiming control from ACC in a car-following scenario of emergency brake by the lead vehicle. Thirty professional bus drivers drove on the simulator with the scenario of highway traffic flow under 12 random time-gap settings: from 0.64 s to 2.40 s with the interval of 0.16 s. As for the effects of secondary tasks, subjects were evenly divided into three conditions: no secondary task interference, simple secondary task, and complex task. The results demonstrated that different safety demarcations of time-gaps on subjective acceptance and driving performance can be found out. The integrated demarcations separated time-gaps into divisions that represented different levels of danger. It revealed that the safer time-gaps for different situations were: longer than 1.60 s for none-secondary task distraction and longer than 2.08 s for being continuously distracted by secondary tasks. The demand for simple tasks is relatively high, so a larger time-gap is needed for the driver to remain safe. This research has implications for the time-gap selection of ACC and effects of secondary task distraction on buses. A next logical step will focus on determining time-gaps for lead vehicles on curves or slopes, when multiple vehicles are present ahead, and modeling driver behavior and performance with ACC for cars, buses, and other types of vehicles.     

The effect of driver eye height on speed choice, lane-keeping, and car-following behavior: results of two driving simulator studies

OBJECTIVE: Two simulator studies were conducted that assessed the effect of driver eye height on speed choice, lane-keeping, and car-following behavior. The effect of eye height on the subjective variables of mental workload, frustration, and confidence was also investigated, as was the contribution of drivers' aggression. METHODS: A total of 43 participants drove a simulated route while seated at two different eye heights: one that represented the view of the road from a large SUV and one that represented the view of the road from a small sports car. Driving scenarios were comprised of both open road and car-following segments. Dependent variables included driver-selected speed, speed variability, lane position, following distance to a slower-moving lead vehicle, and the subjective variables of frustration, confidence, and mental workload. RESULTS: When viewing the road from a high eye height, drivers drove faster, with more variability, and were less able to maintain a consistent position within the lane than when viewing the road from a low eye height. Driver eye height did not influence following distance to a slower-moving lead vehicle. Driver aggression had no effect on any of the dependent variables except level of frustration. CONCLUSIONS: The two studies demonstrate that, when they are not able to reference a speedometer, drivers choose to drive faster when they view the road from an eye height that is representative of a large SUV compared to that of a small sports car. There is a need to educate drivers of SUVs and other tall vehicles of this perceptual phenomenon in order to prevent collisions that may occur in conditions where it is impossible for drivers to base their speed selection solely on posted speed limits, such as in inclement weather.     

Examining drivers' eye glance patterns during distracted driving: Insights from scanning randomness and glance transition matrix

IntroductionVisual attention to the driving environment is of great importance for road safety. Eye glance behavior has been used as an indicator of distracted driving. This study examined and quantified drivers' glance patterns and features during distracted driving.MethodData from an existing naturalistic driving study were used. Entropy rate was calculated and used to assess the randomness associated with drivers' scanning patterns. A glance-transition proportion matrix was defined to quantity visual search patterns transitioning among four main eye glance locations while driving (i.e., forward on-road, phone, mirrors and others). All measurements were calculated within a 5 s time window under both cell phone and non-cell phone use conditions.ResultsResults of the glance data analyses showed different patterns between distracted and non-distracted driving, featured by a higher entropy rate value and highly biased attention transferring between forward and phone locations during distracted driving. Drivers in general had higher number of glance transitions, and their on-road glance duration was significantly shorter during distracted driving when compared to non-distracted driving.ConclusionsResults suggest that drivers have a higher scanning randomness/disorder level and shift their main attention from surrounding areas towards phone area when engaging in visual-manual tasks.Practical applicationsDrivers' visual search patterns during visual-manual distraction with a high scanning randomness and a high proportion of eye glance transitions towards the location of the phone provide insight into driver distraction detection. This will help to inform the design of in-vehicle human-machine interface/systems.     

The relationship between oxygen consumption rate and temperature during coal spontaneous combustion

Spontaneous combustion is a major natural disaster in coal production. In the process of exploring coal self-ignition, a series of hypotheses have been put forward, most scholars agree that the current coal-oxygen compound theory. Oxygen consumption rate reflects the status of coal spontaneous combustion, and it is also one of the parameters necessary for numerical simulation of coal spontaneous combustion. In this paper, a coal heating and oxidation experiment was designed, Experimental device consists of heating and oxidation furnace, gas chromatograph, temperature control and data acquisition systems and other equipment components. Three coal samples whose weight each is 5 g were selected for the study. By experiment, oxygen concentration at the inlet and outlet of temperature oxidation furnace was measured. Oxygen consumption rate is calculated in the heating process of coal according to air flow. In the Cartesian coordinate system, the temperature as abscissa and the oxygen consumption rate for the longitudinal coordinates, drawing the relationship between oxygen consumption rate and temperature plot. And then regression analysis was used to analyze the relationship between oxygen consumption rate and coal temperature during the heating and oxidation process of coal. The results show that the oxygen consumption rate and temperature of coal were linear relationships both before and after the critical temperature when the coal temperature is less than 180 °C. Before the critical temperature oxygen consumption rate is low, however it increases rapidly when coal temperature reaches a critical temperature. The result is important for the prevention and treatment of spontaneous combustion of coal.     

Deterioration of the useful visual field with ageing during simulated driving in traffic and its possible consequences for road safety

A previous study has shown that the useful visual field deteriorates in a simulated road traffic situation as a function of the driver’s age and of the vehicle’s speed under monotonous conditions [Rogé, J., Pébayle, T., Lambilliotte, E., Spitzenstetter, F., Giselbrecht, D., Muzet, A., 2004. Influence of age, speed and duration of monotonous driving task in traffic on the driver’s useful visual field. Vision Research 44 (23), 2737–2744]. The aim of this new experiment is to study the effects of traffic density and age on the useful visual field of the driver during a simulated driving task with controlled traffic characteristics (speed, number of cars) for all participants. In total, 10 young drivers (m = 28.2 years) and 10 older drivers (m = 51.2 years) followed a car in road traffic at an average speed of 126 km h⁻¹ during two 2 h sessions corresponding to two conditions of traffic (light traffic, with five vehicles around the participant; and heavy traffic, with nine vehicles). While following this vehicle, the driver had to detect changes in the colour of a signal located in the central part of his or her visual field and a signal that appeared at different eccentricities on the rear lights of other vehicles in the traffic. Analysis of the data indicated that age interacted with the location of the peripheral signal and density of traffic interacted with the duration of driving. The implications of these results are discussed in terms of road safety and in terms of models of deterioration of the useful visual field (general interference and tunnel vision).