The relationship between simulator sickness and driving performance in a high-fidelity simulator

Driving simulators are highly valuable tools for various applications such as research, training, and rehabilitation. However, they are also known to cause simulator sickness, a special form of traditional motion sickness. Common side effects of simulator sickness include nausea, headache, dizziness, eye-strain, and/or disorientation, all symptoms which may negatively impact driving performance. The goal of the present study was to investigate the relationship between simulator sickness and driving performance obtained in a high-fidelity driving simulator. Twenty-one healthy participants were engaged in a simulated driving task containing rural, city, and highway sections for approx. 25 min. Participants were asked to drive naturally while obeying traffic rules and completing common driving maneuvers (including reactions to sudden events). Driving performance was evaluated based on various driving measures, such as lane positioning, speed measures, following distance, or the number of steering reversals. Simulator sickness was measured before, during, and after the simulated drive using a combination of the Simulator Sickness Questionnaire and the Fast Motion Sickness scale. Overall, correlations between the level of simulator sickness and driving performance measures were low to moderate (r’s from -0.37 to 0.40) and were not significant. Additionally, participants who reported higher levels of simulator sickness did not differ with regards to their driving performance from those who reported lower simulator sickness scores. Our results suggest that the presence of simulator sickness is not strongly related to performance in a driving simulator.     

An evaluation of the effectiveness of countermeasures for improving the safety of dilemma zones: A driving simulator study

The main objective of this driving simulator study is to analyze the behavior of the driver at the start of the yellow signal of a signalized rural intersection and identify the most effective countermeasures for tackling the dilemma zone, namely an area on the intersection approach where vehicles at the start of the yellow phase can neither safely stop before the stop line nor cross the intersection. The following countermeasures were tested in the study on a sample of 48 drivers: green signal countdown timers, GSCT (C₁); a new pattern of vertical and horizontal warning signs (C₂); and an advanced on-board driver assistance system based on augmented reality (AR) and connected vehicle technologies (C₃). These countermeasures were tested and compared to a baseline condition (B) where no countermeasures were applied. Based on the results of this study, the C₂ and C₃ countermeasures have proven to be valid tools for reducing driver indecision when approaching signalized intersections at the start of the yellow signal. In fact, using C₂ and C₃, the length of the dilemma zone was equal to 30 m and 36 m, respectively, with a reduction of about 50%, as compared to the baseline condition (B). Moreover, a reduced number of false behaviors was recorded, as well as a greater consistency in driver decision-making behaviors. Conversely, the C₁ countermeasure did not lead to a significant improvement in the dilemma zone: an unnecessary increase in early stop rates was recorded, resulting in reduced intersection efficiency and operations.     

The effects of adaptive cruise control (ACC) headway time on young-experienced drivers' overtaking tendency in a driving simulator

The preference to maintain a certain desired speed is perhaps the most prevalent explanation for why a driver of a manually driven car decides to overtake a lead vehicle. Still, the motivation for overtaking is also affected by other factors such as aggressiveness, competitiveness, or sensation-seeking caused by following another vehicle. Whether such motivational factors for overtaking play a role in partially automated driving is yet to be determined. This study had three goals: (i) to investigate whether and how a driver's tendency to overtake a lead vehicle changes when driving a vehicle equipped with an adaptive cruise control (ACC) system. (ii) To study how such tendencies change when the headway time configuration of the ACC system varies. (iii) To examine how the manipulation of the speed and speed variance of the lead vehicle affect drivers' tendencies to overtake a lead vehicle. We conducted two different experiments, where the second experiment followed the first experiment's results. In each experiment, participants drove three 10–12 min simulated drives under light traffic conditions in a driving simulator under manual and level one (L1) automation driving conditions. The automation condition included an ACC with two headway time configurations. In the first experiment, it was 1 sec and 3 secs, and in the second, it was 1 sec and 2 secs. Each drive included six passing opportunities representing three different speeds of the lead vehicle (−3 km/h, +3 km/h, +6 km/h relative to the participant), with or without speed variance. Results show that drivers tended to overtake a lead vehicle more often in manual mode than in automated driving modes. In the first experiment, ACC with a headway time of 1 sec led to more overtaking events than ACC with 3 secs headway time. In addition, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies. In the second experiment, the relative speed of the lead vehicle and its speed variability affected overtaking tendencies only when interacting with each other and with driving configuration. When the speed of the lead vehicle was +3 km/h and included variability, more overtaking events occurred in manual mode than both automation modes. This work has shown that driving with ACC might help reduce overtaking frequencies and more considerable when the headway time is set to 3 secs.     

Denoting and Disquoting

Fregeans hold that predicates denote things, albeit things different in kind from what singular terms denote. This leads to a familiar problem: it seems impossible to say what any given predicate denotes. One strategy for avoiding this problem reduces the Fregean position to form of nominalism. I develop an alternative strategy that lets the Fregean hold on to the view that predicate denote things by reconceiving the nature of singular denotation and of Fregean objects.     

A validation study of driving errors using a driving simulator

BackgroundDriving simulators have become an important research tool in road safety. They provide a safer environment to test driving performance and have the capacity to manipulate and control situations that are not possible on-road.AimTo validate a laboratory-based driving simulator in measuring on-road driving performance by type and mean driving errors.MethodsParticipants were instructed to drive a selected route on-road. The same route was programmed in the driving simulator using the UC/Win-road software. All participants completed a background questionnaire. On-road driving behaviours of participants and driving behaviours in the simulator were assessed by an occupational therapist and two trained researchers using an assessment form. Interclass correlations were calculated to assess the inter-rater agreement between the researchers on driving behaviours. Paired t-tests were used to assess differences in driving performance between the simulator and on-road assessments.ResultsA convenience sample of 47 drivers aged 18–69 years who held a current Western Australian class C licence (passenger vehicle) were recruited into the study. The mean age was 34.80 years (SD: 13.21) with twenty-six males (55.32%) and 21 females (44.68%) completing the study. There was no statistical difference between the on-road assessment and the driving simulator for mirror checking, left, right and forward observations, speed at intersections, maintaining speed, obeying traffic lights and stop signs.ConclusionThe preliminary results provide early support for the relative validity of the driving simulator which may be used for a variety of road safety outcomes with reduced risk of harm to participants.     

Towards testing auditory–vocal interfaces and detecting distraction while driving: A comparison of eye-movement measures in the assessment of cognitive workload

Recently, there has been a growing need among researchers to understand the problem of cognitive workload induced by auditory–verbal–vocal tasks while driving in realistic conditions. This is due to the fact that we need (a) valid methods to evaluate in-vehicle electronic devices using voice control systems and (b) experimental data to build more reliable driver state monitoring systems. In this study, we examined the effects of cognitive workload induced by the delayed digit recall task (n-back) while driving. We used a high-fidelity driving simulator and a highway scenario with moderate traffic to study eye movements in realistic driving conditions. This study included 46 participants, and the results indicate that a change in pupil size is most sensitive for measuring changes in cognitive demand in auditory–verbal–vocal tasks. Less sensitive measures included changes in fixation location and blink rate. Fixation durations and the driving performance metrics did not provide sensitive measures of graded levels of cognitive demand.     

Capturing the effects of texting on young drivers behaviour based on copula and Gaussian Mixture Models

This research effort aims to investigate the impact of texting on young drivers' behavior and safety based on data from driving simulator experiments, for different driving contexts, like motorways, urban and rural roads, during daytime and night, and for alternative weather conditions (‘clear sky’ and rain). The study offers a complete and comprehensive investigation of the effects of texting on driving behavior, able to provide evidence on policy-making. For the purposes of this study, a driving simulator experiment was carried out where 34 young participants drove predefined driving scenarios. Initially, multivariate copula analysis was used in order to explore statistical inferences among variables, especially since it retains a parametric specification for bivariate dependencies and allows testing of several parametric structures to characterize them. Secondly, alternative copula configurations were tested, which showed that texting and other road and environmental characteristics affect young drivers behavior and in particular more than one outcome can occur at the same time. Finally, Gaussian Mixture Modeling (GMM) was employed, demonstrating that the variables' pairs that presented the strongest correlations were lane departure and speed, as well as speed and reaction time. GMMs application showed that drivers using mobile phones who were involved in a collision presented a different driving behavior compared to the drivers who were occupied but were not involved in a collision.     

Synchronising self-displacement with a cross-traffic gap: How does the size of traffic vehicles impact continuous speed regulations?

In this article, we investigated what visual information is used by drivers at a road crossing when they want to synchronize their displacement with that of an incoming traffic train. We made the hypothesis that synchronizing self-displacement with that of a traffic gap shares the same perceptual-motor basis as interception tasks. While a large body of literature demonstrates that bearing angle is used to control interception, another range of studies points to optical size and expansion as playing a critical role in collision avoidance. In order to test the hypothesis of the exclusive use of bearing angle in road crossing task, we manipulated the optical size and expansion of oncoming traffic elements independently of bearing angle variations. We designed a driving simulator study in which participants were to adjust their approach speed in order to cross a road junction within a moving traffic gap. We manipulated the initial offset of participants with the traffic gap, the geometry of the road junction and the way optical size of oncoming traffic elements evolves over the course of a trial. Our results showed an effect of optical size and optical expansion manipulations eventhough, we also found similar displacement profiles as in interception studies. This demonstrates that bearing angle could not explain alone the control of such a complex perceptual-motor task. We discuss these results with regard to similar results in other fields of literature.     

Instruction-prompted objective behaviors as proxy for subjective measures in a driving simulator

Interactions with other road users and interpretations of traffic situations are important aspects of driving safety. Self-reports are often used to study drivers’ perceptions and attitudes but self-reports can be inaccurate and biased because of socially desirable responding. Driving simulators offer objective measures of driver behaviors but have limited ability to elicit natural behaviors. To address this issue, we tested a driving simulator-based approach that combined realistic driving scenarios including potentially frustrating forward obstacles and delays in travel time with two different types of instructions. Participants' vehicle control behaviors and subjective perception of traffic delays were compared. Results demonstrated that behaviors collected following instructions to drive safely did not have significant associations with participants’ perceptions of the traffic delays while participants following instructions to drive quickly demonstrated behaviors that were predictive of their subjective perceptions of the traffic delays. The findings suggest that vehicle control behaviors can be used as a proxy for subjective perceptions of traffic delays. We conclude that driving simulator methodology combining instructions, realistic traffic scenarios, and adaptive analytical methods is appropriate for studying drivers’ behaviors and interactions with other road users and can minimize the need to rely on subjective self-reports.     

Make this detour and be unselfish! Influencing urban route choice by explaining traffic management

Traffic management policies aim to improve traffic flow by influencing the route choice of drivers, therefore preventing traffic jams in crowded cities. With respect to a system-optimum of the traffic network, drivers might have to make small-scale detours. The aim of this article is to encourage unselfish route choice behaviour in an urban context by informing drivers in advance about the objectives of traffic management. Two studies were conducted: (1) an online survey (N = 244) and (2) a driving simulation study (N = 48). The first study focussed on the general effect of recommendations for routes with longer travel times (system-optimal routes) when traffic management is explained. Other route choice attributes (travel time, red-light duration, time pressure) were analysed as well. Drivers were randomly confronted with 35 route choice scenarios consisting of a main route with certain red-light duration and an alternative route without. Results showed that the compliance with system-optimal routes is increased by around 10 percentage points when comparing the group with recommendation to the group without. This effect occurred independently of the variation of other route choice attributes. The second study aimed to determine if the compliance can be increased even more if drivers receive in-depth information about traffic management and experience ‘good’ as well as ‘bad’ recommendations in a driving simulator. Results showed no further effect of these manipulations on route choice. Only decision-making times and subjective evaluation were influenced by in-depth information compared to basic information. Altruism was partly correlated with decision-making. This article shows a novel approach to encouraging drivers to select routes with longer travel times for the benefit of the common good. Drivers’ knowledge gap regarding traffic management needs to be closed in order to enhance their understanding of traffic regulations. Finally, results of this research should be transferred to driver models within traffic simulations to estimate the effects on traffic networks.