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.     

Exploring behavioral validity of driving simulator under time pressure driving conditions of professional drivers

Driving simulators have become an important tool in human factors research, given that they are appropriately validated. Therefore, this study aims to explore the behavioral (absolute and relative) validity of a fixed-base driving simulator by analyzing different driving behavior measures such as speed, longitudinal acceleration, lateral acceleration, and brake pedal force. Thirty professional drivers participated in the experiment and the data was collected in real and simulated worlds under No Time Pressure (NTP) and Time Pressure (TP) driving conditions. Initially, comparative analyses were conducted on different driving behavior measures using Wilcoxon-signed rank test to examine absolute validity of the driving simulator. Finally, Generalized Linear Mixed (GLM) models were developed for computing the effective distance between real and simulated worlds by quantifying the parameters and for establishing relative validity. In general, the continuous profiles of driving behavior measures followed similar trends in real and simulated worlds and comparative analyses indicated relative validity of the driving simulator. The GLM models showed significant interaction effect of driving environments (real-world and simulated world) and driving conditions (NTP and TP) where high driving speed, high brake pedal force, and low lateral acceleration were observed in simulated world under TP driving condition than real-world under TP driving condition. Overall, the statistical analyses showed qualitative correspondence (relative validity) of the driving behavior measures in between real and simulated worlds. The findings from the current study showed expediency of the driving simulator and its effectiveness in conducting research on human factors and driver safety.     

Comparing simulator sickness in younger and older adults during simulated driving under different multisensory conditions

Driving simulators are valuable tools for traffic safety research as they allow for systematic reproductions of challenging situations that cannot be easily tested during real-world driving. Unfortunately, simulator sickness (i.e., nausea, dizziness, etc.) is common in many driving simulators and may limit their utility. The experience of simulator sickness is thought to be related to the sensory feedback provided to the user and is also thought to be greater in older compared to younger users. Therefore, the present study investigated whether adding auditory and/or motion cues to visual inputs in a driving simulator affected simulator sickness in younger and older adults. Fifty-eight healthy younger adults (age 18–39) and 63 healthy older adults (age 65+) performed a series of simulated drives under one of four sensory conditions: (1) visual cues alone, (2) combined visual + auditory cues (engine, tire, wind sounds), (3) combined visual + motion cues (via hydraulic hexapod motion platform), or (4) a combination of all three sensory cues (visual, auditory, motion). Simulator sickness was continuously recorded while driving and up to 15 min after driving session termination. Results indicated that older adults experienced more simulator sickness than younger adults overall and that females were more likely to drop out and drove for less time compared to males. No differences between sensory conditions were observed. However, older adults needed significantly longer time to fully recover from the driving session than younger adults, particularly in the visual-only condition. Participants reported that driving in the simulator was least realistic in the visual-only condition compared to the other conditions. Our results indicate that adding auditory and/or motion cues to the visual stimulus does not guarantee a reduction of simulator sickness per se, but might accelerate the recovery process, particularly in older adults.     

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.     

Valid representation of a highly dynamic collision avoidance scenario in a driving simulator

In Germany the second-most frequent accidents in road traffic are rear-end collisions. For this reason rear-end collisions are quite important for accident research and the development of driving safety systems. To examine the functionality and to design the human–machine-interface of new driving safety systems, especially in the early development phase, subject tests are necessary. Because of the great hazard potential of such safety critical scenarios for the test persons, they are often conducted in a driving simulator (DS). Accordingly, validity is an important qualification to ensure that the findings collected in a simulated test environment can be directly transferred to the real world.This paper regards the question of driving behavior validity of DS in critical situations. There are hardly any validation studies which analyze the driving behavior in a specific collision avoidance situation.The validation study described in this paper aims to evaluate the behavioral validity of a fixed-base simulator in a collision avoidance situation. For this reason a field study from 2007 was replicated in a fixed-base simulator environment.The main questions of this validation study were if the driver can notice an active hazard braking system and if the driving behavior in a static simulator can be valid in such a critical situation.The key finding of the study states that there is no driving behavior validity in a static driving simulator for the tested dynamic scenario. The missing vestibular feedback causes a different behavior of the participants in field and simulator. The resulting absence of comparability leads to non-valid performance indicators. But these indicators are key parameters for analyzing the function and acceptance of active braking systems. So the question arises, which motion performance does a motion base have to provide in order to achieve valid acceleration simulation of such a highly dynamic collision avoidance scenario. The DS’s performance is measured in workspace, velocity and acceleration.     

Driving simulation sickness and the sense of presence: Correlation and contributing factors

Driving simulators are useful and effective tools for conducting studies in the field of traffic safety. Simulation sickness (SS) and the sense of presence (SP) are two well-known factors that could affect the results of the driving simulator experiments. This study investigated the relationship between SP and SS in a medium-fidelity driving simulator. Additionally, the impact of the road environment (urban arterials or rural expressways) on these subscales was investigated. Data was collected by means of self-reported questionnaires, which were conducted after the participants have driven the simulation scenarios in a fixed-base medium-fidelity driving simulator. A total of 125 drivers participated in this study. Results showed that females reported significantly higher SS scores than males. An increasing trend in the SS was observed with the increase of age. Importantly, designing buildings that replicate a real-world environment could increase SP and decrease SS. Moreover, designing high quality and resolution scenarios could also increase SP, thus decreasing the severity of SS symptoms. The results of this study can help researchers using medium-fidelity driving simulators to know the influencing factors for each subscale of SP on SS. Adjustments in the driving simulator and scenario settings as well as additional training exercises for higher speed scenarios can be beneficial in reducing the severity of SS.     

The potential of gamification for user education in partial and conditional driving automation: A driving simulator study

Drivers must establish adequate mental models to ensure safe driver-vehicle interaction in combined partial and conditional driving automation. To achieve this, user education is considered crucial. Since gamification has previously shown positive effects on learning motivation and performance, it could serve as a measure to enhance user education on automated vehicles. We developed a tablet-based instruction involving gamified elements and compared it to instruction without gamification and a control group receiving a user manual. After instruction, participants (N = 57) experienced a 30-minute automated drive on a motorway in a fixed-base driving simulator. Participants who received the gamified instruction reported a higher level of intrinsic motivation to learn the provided content. The results also indicate that gamification promotes mental model formation and trust during the automated drive. Taken together, including gamification in user education for automated driving is a promising approach to enhance safe driver-vehicle interaction.     

Driving simulator validation with hazard perception

How should we assess the comparability of driving on a road and “driving” in a simulator? If similar patterns of behaviour are observed, with similar differences between individuals, then we can conclude that driving in the simulator will deliver representative results and the advantages of simulators (controlled environments, hazardous situations) can be appreciated. To evaluate a driving simulator here we compare hazard detection while driving on roads, while watching short film clips recorded from a vehicle moving through traffic, and while driving through a simulated city in a fully instrumented fixed-base simulator with a 90 degree forward view (plus mirrors) that is under the speed/direction control of the driver. In all three situations we find increased scanning by more experienced and especially professional drivers, and earlier eye fixations on hazardous objects for experienced drivers. This comparability encourages the use of simulators in drivers training and testing.     

The utility of the AusEd driving simulator in the clinical assessment of driver fatigue

Several driving simulators have been developed which range in complexity from PC based driving tasks to advanced "real world" simulators. The AusEd driving simulator is a PC based task, which was designed to be conducive to and test for driver fatigue. This paper describes the AusEd driving simulator in detail, including the technical requirements, hardware, screen and file outputs, and analysis software. Some aspects of the test are standardized, while others can be modified to suit the experimental situation. The AusEd driving simulator is sensitive to performance decrement from driver fatigue in the laboratory setting, potentially making it useful as a laboratory or office based test for driver fatigue risk management. However, more research is still needed to correlate laboratory based simulator performance with real world driving performance and outcomes.     

Young adult drivers' sensitivity to changes in speed and driving mode in a simple vehicle simulator

The study was done to check replication of changes in sensitivity with a simple simulator as had been obtained in an experiment using the real road situation. Another purpose was to control simulator sickness which could have confounded data from testing with a simulator or in actual driving. Sensitivity of the drivers (72 healthy young adults, M age = 24 yr., SD = 5) while performing the driving task was measured in terms of subjective ratings of simulator sickness and affect, and physiological measures (i.e., galvanic skin responses and skin temperature) at different driving speeds and in driving mode conditions, using a simple vehicle simulator. Analysis showed measures of drivers' state, including simulator sickness, physiological indices, and subjective reports, increased with driving speed (30 --> 90 -->120 km/hr.) and driving mode change from the regular speed to sudden increasing to sudden decreasing speeds. Particularly, the results suggest that the increased autonomic nervous activation induces increase of rated simulator sickness. Based upon the same tendency in change of the simulator sickness and physiological state with driving speed and driving mode conditions, it was concluded that, if the results obtained from the simulator experiment can be generalized to the real situation, the simulator sickness must be considered a confounding factor. The results also suggest that the changes in human sensitivity are dependent upon aspects related to speed of a vehicle and driving mode.     

Driving errors,estimated performance and individual characteristics under simulated and real road traffic conditions – A validation study

BackgroundThe suitability of driving simulators for the prediction of driving behaviour in road traffic has been able to be confirmed in respect of individual assessment parameters. However, there is a need for overarching approaches that take into account the interaction between various influencing factors in order to establish proof of validity. The aim of this study was to explore the validity of our driving simulator in respect of its ability to predict driving behaviour based on participants‘ observed driving errors and driver’s individual characteristics.Method41 healthy participants were assessed both in a Smart-Realo-Simulator and on the road. By means of linear modelling, the correlation between observed driving errors was investigated. In addition, the influence of self-reported and externally assessed driving behaviour as well as individual parameters (education and training; driving history) were analysed.ResultsBy including these factors, 58% of the variance could be explained. For observed driving errors, a relative validity was established. For self-reported and externally assessed driving behaviour, an absolute to relative validity emerged. The amount of time spent in education and training proved to have a significant influence on driving performance in the simulator, but not on the road.DiscussionIn general, our results confirmed the validity of our driving simulator with regard to observed and self-reported driving behaviour. It emerged that education and training as potential indicators of cognitive resources played a differential role regarding the study conditions. Since real road driving is considerably automated in experienced drivers, this result suggests that simulation-related behavioural regulation is challenged by additional cognitive demands as opposed to behavioural regulation extending to real road driving. However, the source of these additional cognitive demands remains currently elusive and may form the subject of future research.     

Utilizing driving simulators for persons with multiple sclerosis: A scoping review

ObjectiveThis scoping review synopsized and mapped the evidence on the utility of driving simulators for drivers with Multiple Sclerosis (MS) including participant characteristics (e.g., demographic, clinical) suited to simulator use; and driving scenario environments, maneuvers, and outcomes reflective of driving performance.Data SourcesThe research team searched six databases for English studies on driving simulator performance in drivers with MS.Study SelectionFour reviewers independently screened 976 unique titles, 148 abstracts, and 18 full-text sources for study inclusion or exclusion. Inclusion criteria ensured that studies utilized measures of driving simulator performance in adults 18 years or older with MS.Data ExtractionReviewers independently charted, verified, and achieved consensus on 100% of the data in the extraction table.Data SynthesisThe scoping review included thirteen studies (twelve assessment, one intervention), published between 2001 and 2021. Studies included small samples (N = 11–50) of adults (M age = 36–50 years; 40–91% female), mostly with a relapsing-remitting (53–100%) diagnosis and low to moderate physical disability (Expanded Disability Status Scale score < 6.0). The assessment studies utilized driving scenarios to assess pre-driving (n = 1) or driving abilities (n = 2), responses to hazardous events in suburban (n = 1) or urban environments (n = 4), or the ability to maintain speed or lateral lane positioning during monotonous highway drives (n = 7), with four scenarios also including responses to secondary divided attention tasks. The intervention study utilized driving simulation as a training program to improve driving-related skills.ConclusionsThe evidence on the utility of driving simulators for adults with MS is limited to assessment of driving performance, mostly during monotonous highway drives. Further research should consider exploring how driving simulators can be utilized to assess driving performance in other environments or for intervention. Gender should be examined to support gender diverse populations.     

Visual attention as a predictor of on-road driving performance of older drivers

With increasing numbers of older drivers on Australian roads, it is important to determine the functional abilities most closely related to driving ability among older adults. To this end, 90 drivers aged from 60 to 91 completed a battery of psychological, visual, physical and cognitive tests, and a standardised on-road driving test. A computerised test of visual attention, devised specifically for the study, was the best predictor of on-road driving performance. Other abilities that made independent contributions to the prediction of driving performance were contrast sensitivity and visuospatial memory. These functional abilities provided a better prediction of driving performance than chronological age, reinforcing the argument that drivers should only have their driving tested when their functional abilities decline, rather than when they reach a particular age.     

Risk profiles in novice road users: Relation between moped riding simulator performance,on-road aberrant behaviors and dangerous driving

The aim of this study was to compare the scores obtained by an Italian sample of novice drivers/riders on an adapted version of the Driver Behaviour Questionnaire (DBQ) and the Dula Dangerous Driving Index (DDDI) with their performance in a moped-riding simulator. Cluster analysis on the indexes extracted by the simulator were used to identify two groups with opposite riding styles: Prudent riders and Imprudent riders.Using the DBQ, our data not only confirmed data in the literature indicating that females reported more driving Errors than males, and that males reported higher Intended Violation scores than females, but also showed that gender effects are modulated by riding style (as measured by the simulator) and driving exposure. Differences between males’ and females’ DBQ scores were only apparent for Imprudent riders, while the reported Errors, Slips and Lapses, and Violations were lower the higher the driving exposure.As for the DDDI, males scored higher than females for Risky Driving, and the Aggressive Driving scores were higher the greater the driving exposure, but only for Imprudent riders.These results provide crucial information for the use of DBQ and DDDI questionnaires in the Italian population. They also confirm that a multidimensional approach, supported by the use of driving simulators, may facilitate a more detailed assessment of riding abilities.     

Personality factors are associated with simulated driving outcomes across the driving lifespan

Research has shown that personality factors are related to driving safety. However, the majority of existing studies rely on self-report measures of driving behaviour and sample drivers from limited age ranges. This study sought to examine the relationship between personality and objective driving outcomes as assessed by a driving simulator in a sample of young, mid-aged, and older adults. A total of 114 active drivers completed personality questionnaires as well as a simulated driving assessment protocol. The results showed that: (1) Extraversion and neuroticism were significantly associated with driving simulator performance; (2) conscientiousness was significantly associated with driving performance among middle-aged adults; (3) sensation seeking was an important personality factor primarily for young drivers and was positively correlated with driving speed in the simulator. These results provide further support for the link between personality factors and driving performance, and suggest certain directions for future research.     

A simulation sickness study on a driving simulator equipped with a vibration platform

Simulator sickness is a well-known side effect of driving simulation which may reduce the passenger well-being and performance due to its various symptoms, from pallor to vomiting. Numerous reducing countermeasures have been previously tested; however, they often have undesirable side effects. The present study investigated the possible effect of seat vibrations on simulator sickness. Three configurations were tested: no vibrations, realistic ones and some that might affect the proprioception. Twenty-nine participants were exposed to the three configurations on a four-minute long automated driving in a simulator equipped with a vibration platform. Simulator sickness was estimated thanks to the Simulator Sickness Questionnaire (SSQ) and to a postural instability measure. Results showed that vibrations help to reduce the sickness. Our findings demonstrate that some specific vibration configurations may have a positive impact on the sickness, thus confirming the usefulness of devices reproducing the road vibrations in addition to creating more immersion for the driver.     

A meta-analysis of the n-back task while driving and its effects on cognitive workload

This study investigates the effect of the n-back task on cognitive workload while driving. Results of 20 studies with over 800 participants in total show a moderate to high mean effect size. That means the n-back task varies cognitive load while driving in a substantial matter. Further analysis reveals several moderator variables: experiments conducted in a driving simulator showed larger effect sizes than on-road studies. This effect decreases with increasing driving simulator fidelity. Furthermore, the specific driving task assignment moderates the effect: lane change task scenarios result in higher effects than other situations. Regarding the different measurement methods of cognitive workload, subjective questionnaires seem to have very high sensitivity. In contrast, n-back performance measures, detection response task measures, and physiological measurements result in moderate effect sizes, and driving performance measures show reduced sensitivity. Regarding different implementations of the n-back task itself, surprisingly, no moderators are found. Overall, the findings highlight the suitability of the n-back task as a method of inducing cognitive load in transportation research. The moderator analysis gives an overview of different methodological designs and how these designs will affect effect sizes.     

Head-mounted displays for clinical virtual reality applications: pitfalls in understanding user behavior while using technology.

The use of virtual environments with head-mounted displays (HMDs) offers unique assets to the evaluation and therapy of clinical populations. However, research examining the effects of this technology on clinical populations is sparse. Understanding how wearers interact with the HMD is vital. Discomfort leads to altered use of the HMD that could confound performance measures; the very measures which might be used as tools for clinical decision making. The current study is a post-hoc analysis of the relationship between HMD use and HMD comfort. The analysis was conducted to examine contributing factors for a high incidence of simulator sickness observed in an HMD-based driving simulator. Pearson correlation analysis was used to evaluate objective and subjective measures of HMD performance and self-reported user comfort ratings. The results indicated weak correlations between these variables, indicating the complexity of quantifying user discomfort and HMD performance. Comparison of two case studies detailing user behavior in the virtual environment demonstrates that selected variables may not capture how individuals use the HMD. The validity and usefulness of the HMD-based virtual environments must be understood to fully reap the benefits of virtual reality (VR) in rehabilitation medicine.     

A comprehensive systematic review of the laboratory-based research investigating the influence of alcohol on driving behaviour

In the past thirty years, alcohol influence on drivers has been widely researched using driving simulators across the world. However, a critical evaluation of the existing evidence is required to project the current status and provide directions for future investigations. The present study conducts a comprehensive systematic review of the research examining the effects of alcohol on simulated driving performance. The literature search was conducted in academic databases such as Google Scholar, SCOPUS, Transportation Research Information Database (TRID), PubMed, and Web of science. In total, 1015 articles were identified from the initial database search along with 14 additional articles from other sources (Articles Plus, Cochrane Library, Medline, National Technical Information Services, National Highway Traffic Safety Administration, and Medline Grey Literature Report), out of which 110 articles were included in the systematic review. The majority of the studies were conducted in the United States of America (45%), followed by Australia (15%). These studies were reviewed based on the following aspects: type of driving simulator, study design, Blood Alcohol Concentration (BAC) or alcohol dose used in the experiments, driving environment characteristics, driving performance measures, data analysis techniques, and additional factors affecting driver behaviour under the influence of alcohol. Overall, the evidence regarding driving performance under the influence of alcohol shows that the majority of the previous studies have found a significant impact of alcohol on the various aspects of driving behaviour. The systematic review highlighted the methodological limitations observed in the previous driving simulator studies which should be acknowledged in future research.