Driving Simulator Test Research Articles

Optimization of the position layout of in-vehicle central information display based on genetic algorithm

In-vehicle central information display (CID) has become an essential part in the cockpit. It is of great theoretical significance and application value to optimize the position layout of CID, which help to improve driving safety and operating comfort. In this paper, the ergonomics experiment is designed and the driving simulation test method is used for the experiment. Based on the collected data for genetic algorithm, the fitness function is set, and the process of gene selection, crossover and mutation is simulated to obtain the optimized coordinates of the position layout of the central control screen. According to the results of optimization, ergonomics experiments are carried out again to verify the reliability of the optimization results. This paper has guiding significance for the development of digitalization in the cockpit.

User Preference of Different Artificial Intelligence Level in Vehicle System

With the development of artificial intelligence technology, the functional requirements of the vehicle central control panel becomes various and abundant. This work studies the preference degree of the user’s in different artificial intelligence level, which is of great significance to the application research of artificial intelligence technology in the car interaction design. This paper uses the driving simulation test method to conduct experiments. Through the qualitative research on 20 users, the Chinese users’ preference has been studied, which provides a new research content for the application of artificial intelligence technology in the driving process.

An investigation on coordination of lane departure warning based on driver behaviour characteristics

As an important part of Advanced Driver Assistance Systems (ADAS), Lane Departure Warning System (LDWS) plays a significant role in lane departure prevention and reducing traffic accidents caused by lane departure. In order to improve the warning effect of the system as well as driver acceptance, this paper describes an LDWS algorithm for personalised driving assistance. The proposed combination algorithm consists of a multi-mode Time to Lane Crossing (TLC) and a Future Offset Distance (FOD) based on driver behaviour characteristics. To detect driver's lane change intention, the steering behaviour has been developed incorporating vehicle states and road curvature. Driving simulator tests are conducted to validate the lane departure warning algorithm with multi-mode based on TLC and FOD under various driving situations. The obtained test results are consistent with the expected performance.

An investigation on coordination of lane departure warning based on driver behaviour characteristics

As an important part of Advanced Driver Assistance Systems (ADAS), Lane Departure Warning System (LDWS) plays a significant role in lane departure prevention and reducing traffic accidents caused by lane departure. In order to improve the warning effect of the system as well as driver acceptance, this paper describes an LDWS algorithm for personalised driving assistance. The proposed combination algorithm consists of a multi-mode Time to Lane Crossing (TLC) and a Future Offset Distance (FOD) based on driver behaviour characteristics. To detect driver's lane change intention, the steering behaviour has been developed incorporating vehicle states and road curvature. Driving simulator tests are conducted to validate the lane departure warning algorithm with multi-mode based on TLC and FOD under various driving situations. The obtained test results are consistent with the expected performance.

Cognitive dysfunction during hypoglycemia in an elderly subject without diabetes

The aim of the present study was to examine whether an elderly subject without diabetes experiences hypoglycemia during his daily life or after an oral glucose tolerance test (OGTT), and investigate whether hypoglycemic episodes affect cognitive function. The 85-year-old healthy subject, who is a sports enthusiast, showed lower than normal (< 80mg/dl) blood glucose levels on two occasions over 6days in the early morning. The subject also experienced hypoglycemic episodes and blood glucose levels of 65 and 74mg/dl, respectively, during the 6-h OGTT given after a 13-h fast. Cognitive function, as assessed using a numeracy test and a driving simulator test, deteriorated during the hypoglycemic episodes but recovered 0.5h after ingestion of a confectionary product (two pieces of Dorayaki containing 247kcal and 51.5g of carbohydrate each). Cognitive dysfunction caused by mild hypoglycemia can be involved in a part of traffic accidents in elderly drivers.

Effect of Music Listening on Physiological Condition, Mental Workload, and Driving Performance with Consideration of Driver Temperament.

This paper presents the study on the association between in-vehicle music listening, physiological and psychological response, and driving performance, using the driving simulator approach, with which personality (temperament) was considered. The performance indicators considered were the standard deviation of speed, lane crossing frequency, perceived mental workload, and mean and variability of heart rate. Additionally, effects of the presence of music and music genre (light music versus rock music) were considered. Twenty participants of different personalities (in particular five, four, seven, and four being choleric, sanguine, phlegmatic, and melancholic, respectively) completed a total of 60 driving simulator tests. Results of mixed analysis of variance (M-ANOVA) indicated that the effects of music genre and driver character on driving performance were significant. The arousal level perceived mental workload, standard deviation of speed, and frequency of lane crossing were higher when driving under the influence of rock music than that when driving under the influence of light music or an absence of music. Additionally, phlegmatic drivers generally had lower arousal levels and choleric drivers had a greater mental workload and were more likely distracted by music listening. Such findings should imply the development of cost-effective driver education, training, and management measures that could mitigate driver distraction. Therefore, the safety awareness and safety performance of drivers could be enhanced.

Examining the safety of trucks under crosswind at bridge-tunnel section: A driving simulator study

Bridge-tunnel section is the connecting section between bridges and tunnels, where strong crosswind is considered as one of the most important causes of traffic accidents, in particular for trucks. A driving simulator experiment has been carried out based on a box truck module, with the purpose of investigating the safety of the truck under crosswind at the bridge-tunnel section. Nineteen professional truck drivers participated in the driving simulator tests. The yawing rate and steering angle are selected as the indices of the dynamic response under crosswinds. The response characteristics of the truck entering a tunnel from crosswind region are also discussed particularly. The reference of yaw stability has been proposed based on the performance when the truck moves on the first tunnel section with no crosswind applied. The results indicate that the yaw stability of the moving truck becomes worse as the intensity of crosswind action increases and the lateral displacement resulted from the left-to-right crosswind is larger than that from the right-to-left. A transitional section at the entrance of the tunnel should be designed to prevent the possible accident induced by large lateral displacement under strong crosswind.

Mobile Telephone Use and Reaction Time in Drivers With Glaucoma

Combining mobile telephone use with driving is not unusual. However, distracted driving limits driving performance because of limited capacity for persons to divide attention. To investigate the frequency of mobile telephone use while driving and to assess whether patients with glaucoma had a disproportionate decrease in driving performance while conversing on a mobile telephone compared with healthy participants. Cross-sectional study of surveys collected from 112 patients with glaucoma and 70 control participants investigating mobile telephone use while driving. A randomly selected subgroup of 37 patients with glaucoma and 28 controls drove in a driving simulator to investigate peripheral event detection performance during distracted driving at the Visual Performance Laboratory, Duke University, Durham, North Carolina. Data collection was performed from December 1, 2016, through April 30, 2017. Participants answered a survey and submitted to a driving simulation test with and without mobile telephone use. Survey answers were collected, and distracted driving performance, assessed by reaction time to peripheral stimuli, was analyzed. Of the 182 participants who answered the survey, the 112 participants with glaucoma included 56 women (50.0%) and had a mean (SD) age of 73.6 (9.6) years. The 70 controls included 49 women (70.0%) and had a mean (SD) age of 68.4 (10.9) years. When asked about mobile telephone use while driving, 30 patients with glaucoma (26.8%) admitted rarely using and 2 (1.8%) sometimes using it. In the control group, 20 participants (28.6%) admitted rarely using and 2 (2.9%) sometimes using the telephone while driving (P = .80). Reaction times to peripheral stimuli were significantly longer among patients with glaucoma compared with controls during mobile telephone use (median [interquartile range], 1.86 [1.42-2.29] seconds vs 1.14 [0.98-1.59] seconds; P = .02). Compared with driving performance while not using a mobile telephone, the mean (SD) increase of 0.85 (0.60) second in reaction time while conversing on the mobile telephone among patients with glaucoma was significantly greater than the mean (SD) increase of 0.68 (0.83) second for controls (P = .03). This study's findings indicate that patients with glaucoma use mobile telephones while driving as frequently as healthy participants. However, the findings also suggest that patients with glaucoma may experience a greater decline than healthy participants in their ability to detect peripheral events while driving when also talking on a mobile telephone. Patients with glaucoma should be informed that they may have a higher driving risk that may be worsened by distractions, such as mobile telephone use.

Simulator and Field Study of Green Lights on Truck-Mounted Attenuators in Missouri during Mobile Operations

Mobile work zones for various types of moving operations (e.g., striping, pothole patching, sweeping) are an important component in highway maintenance activities which have particular safety issues. To help mitigate the risk and severity of collisions, a truck-mounted attenuator (TMA) is attached to a construction vehicle, typically equipped with amber/white lights. Despite these visible warnings, collisions involving TMAs and traffic still occur. In an effort to improve upon the traditional amber/white lights, the use of green lights on TMAs was investigated. The study included the evaluation of four light-color configurations: amber/white, green only, green/amber, and green/white. Driving simulator tests obtained various driver behavior measures, including the first blinker distance, merge distance, work zone and arrow direction recognition distance, and disability glare. Vehicle speeds were captured in both a simulator study and a field study. In the simulator study, the use of the amber/white combination led to the highest work zone visibility but also created the greatest concern with disability glare. Although the green-only configuration led to the lowest disability glare, it also resulted in low visibility. The results showed an inverse relationship between visibility (awareness of work zone) and arrow board recognition (easy on eyes). Other findings from the field study include lower traffic speeds for the green light TMA and lower vehicle speeds for lower TMA vehicle speeds. Overall, the study showed that the four configurations had various tradeoffs and none stood out as clearly superior in terms of the performance measures.

Intervention Comparative Effectiveness for Adult Cognitive Training (ICE-ACT) Trial: Rationale, design, and baseline characteristics

Age-related perceptual and cognitive declines are associated with difficulties performing everyday tasks required to remain independent. Encouraging improvements in cognitive abilities have been shown for various short-term interventions but there is little evidence for direct impact on independence. This project compares the effect of broad and directed (narrow) technology-based training on basic perceptual and cognitive abilities in older adults and on the performance of simulated tasks of daily living including driving and fraud avoidance. Participants (N = 230, Mean age = 72) were randomly assigned to one of four training conditions: broad training using either (1) a web-based brain game suite, Brain HQ, or (2) a strategy video game, Rise of Nations, or to directed training for (3) Instrumental Activities of Daily Living (IADL) training using web-based programs for both driving and fraud avoidance training, or (4) to an active control condition of puzzle solving. Training took approximately 15–20 h for each intervention condition across four weeks. Before training began, participants received baseline ability tests of perception, attention, memory, cognition, and IADL, including a driving simulator test for hazard perception, and a financial fraud recognition test. They were tested again on these measures following training completion (post-test). A one-year follow-up from training completion is also scheduled. The baseline results support that randomization was successful across the intervention conditions. We discuss challenges and potential solutions for using technology-based interventions with older adults. We also discuss how the current trial addressed methodological limitations of previous intervention studies. Trial registration numberNCT03141281

Temporal patterns of driving fatigue and driving performance among male taxi drivers in Hong Kong: A driving simulator approach

This study uses a questionnaire survey and a driving simulator test to investigate the temporal patterns of variations in driving fatigue and driving performance in 50 male taxi drivers in Hong Kong. Each driver visited the laboratory three times: before, during, and after a working shift. The survey contained a demographic questionnaire and the Brief Fatigue Inventory. A following-braking simulator test session was conducted at two speeds (50 and 80 km/h) by each driver at each of his three visits, and the driver’s performance in brake reaction, lane control, speed control, and steering control were recorded. A random-effects modeling approach was incorporated to address the unobserved heterogeneity caused by the repeated measures. In the results, a recovery effect and a lagging effect were defined for the driving fatigue and performance measures because their temporal patterns were concavely quadratic and had a 1-hour delay compared to the temporal patterns of occupied taxi trips and taxi crash risk in Hong Kong. Demographic variables, such as net income and driver age, also had significant effects on the measured driving fatigue and performance. Policies regarding taxi management and operation based on the modeling results are proposed to alleviate the taxi safety situation in Hong Kong and worldwide.

A Preliminary Investigation into the Impact of Connected Vehicle Human-Machine Interface on Driving Behavior

Abstract This paper developed a driving simulator testbed, which includes three simulation scenarios that can represent different real-world driving conditions, to investigate the impact of Connected Vehicle (CV) Human-Machine Interface (HMI) on driving behavior. A total number of 23 professional drivers were invited to participate in the driving simulator test; a comprehensive questionnaire was employed to collect the participant’s feedback of CV HMI. It was found that 96 percent of the participants stated that CV HMI provided them with improved road condition information and increased their safety while driving; 65 percent of the participants stated the CV applications and the display unit did not introduce significant distraction from the main driving task.

The study of driver’s brain activity and behaviour on DS test using fNIRS

Abstract In this study, according to Driving Simulator test, based on brain activity measuring using fNIRS, we tried to grasp the interaction between a driver’s reaction on sighting Variable Message Sign, and a driver’s behavior, such as the change of car speed and acceleration. As the result, we confirmed that Parietal association cortex and Prefrontal area activated in the case of a driver’s driving with recognition and judgment using the collecting information from an environment. Therefore, it was suggested that it needs to expand the measuring area to Parietal association cortex in the case of evaluating driver’s activity.

Field Evaluation of Vehicle to Infrastructure Communication-Based Eco-Driving Guidance and Eco-Signal System

In urban areas, the main factor causing excessive fuel consumption is stop-and-go, which is prevalent at urban intersections. To decrease fuel consumption at the intersections, various methods have been proposed and evaluated using simulation models and driving simulators. However, it is not known how reliable the driving simulator results would be when compared with those of the field test. In this paper, eco-driving guidance and eco-signal system based on vehicle-to-infrastructure communication are developed and tested in the field in a multi-vehicle environment. They were also tested using a driving simulator and the results were compared with those of the field test. This was intended to assess the reliability of driving simulator-based study. The field test results at an isolated intersection indicated that the eco-driving guidance could save the fuel consumption around 20%–40% and the eco-signal system could reduce the fuel consumption up to 45%. Although the absolute fuel consumptions between the driving simulator test and the field test did not match, the results from both tests confirmed better performance with eco-driving guidance and eco-signal system when compared with the base scenarios. This indicates that a driving simulator is an effective tool for assessing relative benefits of eco-driving guidance and eco-signal system.

Agreement of driving simulator and on-road driving performance in patients with binocular visual field loss.

On-road testing is considered the standard for assessment of driving performance; however, it lacks standardization. In contrast, driving simulators provide controlled experimental settings in a virtual reality environment. This study compares both testing conditions in patients with binocular visual field defects due to bilateral glaucomatous optic neuropathy or due to retro-chiasmal visual pathway lesions. Ten glaucoma patients (PG), ten patients with homonymous visual field defects (PH), and 20 age- and gender-matched ophthalmologically normal control subjects (CG and CH, respectively) participated in a 40-min on-road driving task using a dual brake vehicle. A subset of this sample (8 PG, 8 PH, 8 CG, and 7 CH) underwent a subsequent driving simulator test of similar duration. For both settings, pass/fail rates were assessed by a masked driving instructor. For on-road driving, hemianopia patients (PH) and glaucoma patients (PG) showed worse performance than their controls (CH and CG groups): PH 40%, CH 30%, PG 60%, CG 0%, failure rate. Similar results were obtained for the driving simulator test: PH 50%, CH 29%, PG 38%, CG 0%, failure rate. Twenty-four out of 31 participants (77%) showed concordant results with regard to pass/fail under both test conditions (p > 0.05; McNemar test). Driving simulator testing leads to results comparable to on-road driving, in terms of pass/fail rates in subjects with binocular (glaucomatous or retro-chiasmal lesion-induced) visual field defects. Driving simulator testing seems to be a well-standardized method, appropriate for assessment of driving performance in individuals with binocular visual field loss.

Driver-Assistance Lateral Motion Control for In-Wheel-Motor-Driven Electric Ground Vehicles Subject to Small Torque Variation

Electric ground vehicles driven by in-wheel-motors (IWMs) have control flexibility of easily generating external yaw moment, which is effective for vehicle lateral motion control without interfering driver steering maneuvers. However, IWMs small torque variation may introduce undesired yaw moment that causes vehicle trajectory drifts and affects lateral motion. This paper proposes a driver-assistance lateral motion control method specifically considering IWMs small torque variation. In driving conditions where a driver steering maneuver is not expected, the controller compensates for small torque variation to reduce the driver workload. However, for driving conditions that require steering input from the driver, the controller assists the driver to maintain the path when there is a tendency of lane departure. A gain-scheduling robust controller is designed to deal with a time-varying parameter and system uncertainty. The weighted ${H_\infty }$ performance and eigenvalue placement technique are employed to derive a suitable feedback gain. CarSim simulations are conducted to illustrate the control effectiveness for compensating small torque variation and prevent lane departure. Furthermore, human-in-the-loop tests are conducted to verify the effectiveness of the designed controller for human drivers. Both simulation results and human driving simulator tests show that the proposed controller can assist drivers with vehicle lateral motion control under different driving conditions subject to IWMs small torque variation.

An Ecolevel Estimation Method of Individual Driver Performance Based on Driving Simulator Experiment

Accurately acquiring the ecolevel of individual driver performance is the precondition for more targeted ecodriving behavior optimization. Because of obvious advantage in mining hidden relationship, machine learning was adopted to explore the complicated relationship between driver performance and vehicle fuel consumption and thus to predict the ecolevel of individual driver performance in this study. Based on driving simulator tests, data of driver performance and vehicle fuel consumption were collected. The ecolevel was indicated as the ecoscore corresponding to vehicle fuel consumption. The model input was designed as 10 feature indexes of driver performance (e.g., percentage number, mean value, standard deviation, and power of applying acceleration pedal). The output was treated as ecoscore. Taking a number of one hundred of data segments in vehicle starting process as training sample, the optimal structure, functions, and learning rate of a backpropagation neural network model with three layers were obtained, after repeated model simulation experiments. The validation test of 16 sample data items showed that the mean prediction accuracy of our developed model was 92.89%. In addition, comparative analysis displayed that the performance of backpropagation neural network based model was better than linear regression based model and random forest based model, from the aspects of elapsed time and prediction accuracy in estimating the ecolevel of driver performance. The study results provide an effective method to grasp the ecolevel of driver performance and further contribute to driving behavior optimization towards vehicle fuel consumption and emissions reduction.

Investigating the effectiveness of perceptual treatments on a crest vertical curve: A driving simulator study

Rural roads are characterized by a high percentage of run-off-the-road accidents and head-on collisions, mainly caused by inappropriate speeds and failure to maintain a proper lateral position along the roadway alignment. Among several road safety treatments, low-cost perceptual measures are considered an effective tool, as they generally increase the risk perceived by drivers, or even alter the drivers’ speed perception, and consequently tempting them to decrease their speeds. Their effectiveness has been widely recognized in a number of studies, especially with respect to road intersections and curves.The overall aim of this study is to investigate the effects of different perceptual treatments on driving speed, along a crest vertical curve of an existing two-lane rural road, in order to identify the most effective measure to reduce speed and define its subsequent implementation in the field. Three perceptual treatments were tested using a driving simulator: white peripheral transverse bars, red peripheral transverse bars and optical speed bars, with each one being painted along the approaching tangent to the crest vertical curve. The effects of these speed-reducing measures were investigated using a sample of forty-four participants, by comparing the driving speeds with those recorded under a baseline condition (without a treatment); these were also used to validate the driving simulator’s speed measurements with those found in the field. Moreover, subjective measures were collected, consisting of the driver’s static evaluation of the desired speed, risk perception and markings comprehension, based on screen shot pictures that represented the simulated configurations of the treatments.The findings demonstrated an overall effectiveness of the perceptual treatments, although only the red peripheral transverse bars were found to significantly reduce the driving speeds (−6 km/h). The analysis of the questionnaire yielded interesting information and demonstrated the importance of performing driving simulation tests for evaluating the effectiveness of perceptual treatments.Finally, the results confirmed the enormous potential of using driving simulators to pinpoint a number of speed-reducing measures, and consequently select the most effective one that reduces cost and promotes safety before its actual implementation in the field.

Relationship of Quality of Sleep in Adolescents and Young Adults to the Driving Performance

Introduction: Sleep deprivation is a major cause of motor vehicle accidents, and can impair the human brain as much as alcohol. It has been estimated that between 16% and 60% of all motor vehicle accidents are caused by sleep related problems. Adolescents and young adults frequently complain of sleep disorder symptoms and suffer from chronic sleep deprivation. There is an absence of evidence in existing literature regarding the impact of sleep disturbances on the driving function in young, novice drivers compared to that in young adults. Materials and Methods: This study is a prospective cohort study of two subject groups: young adults with driving experience of less than 36 months, and young adults with driving experience of greater than 36 months). Each subject served as its own control. The enrolled subjects are 16 – 26 years old, right-handed, with normalor corrected vision. Participants with a chronic or acute ongoing health condition which might affect the study results were excluded. Study procedures utilized were: polysomnography, multiple sleep latency test and driving simulator testing. Results: Repeated-measures MANCOVA revealed that driving experience, objective sleepiness (as measured by the Multiple Sleep Latency Test (MSLT)), interaction between driving experience and depressive symptoms (as measured by The Center for Epidemiologic Studies Depression Scale Revised (CESD-R)), and interaction between depressive symptoms and objective sleepiness had statistically significant effects on driving performance. Conclusion: Unexpectedly, more experienced drivers made more driving errors and were responsible for a greater number of accidents. Mood and ongoing sleep deprivation emerged as two key factors that impacted driving performance more than level of experience. This may represent the impact of a less-regulated post high school lifestyle, as compared to more structured high school schedule. The study findings aid in confirming that functional impairments related to sleepiness previously observed in adult study populations are also replicated in adolescents and young adults.

Aiding medical professionals in fitness-to-drive screenings for elderly drivers: development of an office-based screening tool.

The main objective of this study was to develop a fitness to drive screening tool for elderly drivers to be used in a doctor's office. Furthermore, this study investigated the additional value of driving simulator tests in the assessment of fitness to drive. Both screenings (functional abilities and driving simulator test) were benchmarked against the official Belgian fitness to drive licensing procedure. One-hundred thirty-six elderly drivers participated in a functional abilities screening, a driving simulator assessment and an on-road driving test. Sixty-five percent of the sample was considered fit to drive. Visual acuity, physical flexibility, and knowledge of road signs were found to be the best predictive set of tests for the on-road fitness to drive outcome. A performance based driving simulator assessment increased predictive accuracy significantly. The proposed screening procedure saves part of the at-risk elderly driver population from stressful and costly on-road driving evaluations. This procedure provides more information of an individual driver's specific driving parameters. This opens doors for personalized older driver training to maintain independent mobility in later life.