Driving Simulator Test Research Articles

Acute Cannabis Administration Transiently Reduces Mitochondrial DNA in Young Adults: Findings from a Secondary Analysis of a Double-Blind, Placebo-Controlled, Randomized Clinical Trial.

Background: Cannabis is one of the world's most commonly used substances; however, many questions remain unanswered as to how cannabis impacts the body. Recently, there has been a resurgence of research into the effects of plant-derived cannabinoids on mitochondrial health. In particular, a number of studies implicate mitochondrial-Δ9-tetrahydrocannabinol (Δ9-THC) interactions with altered memory, metabolism, and catalepsy in mice. Although the research in this field is expanding rapidly, there is little known about the effects of cannabis on mitochondria health in human subjects either in acute or chronic term use. Methods: Blood samples were obtained from a double-blind, placebo-controlled, parallel-group randomized clinical trial in which adults who regularly use cannabis (1-4 days/week) aged 19-25 years were randomized 2:1 to receive either an active (12.5% Δ9-THC) cigarette or placebo (<0.01% Δ9-THC) cigarette containing 750 mg of cannabis before driving simulator testing. DNA was extracted from whole blood using commercial spin columns, followed by measurement of mt-ND1, mt-ND4, and β2M using quantitative polymerase chain reaction. One-way repeated measures analysis of variance (ANOVA) followed by Dunnett's multiple comparisons test was used to observe changes in mitochondrial DNA (mtDNA) copy number over time. A two-tailed Pearsons R test was used to assess correlations between mtDNA copy number and cannabinoid levels (Δ9-THC and metabolites) in blood. Results: We found that exposure to active cannabis containing Δ9-THC, as opposed to placebo, was associated with an acute reduction in mitochondrial DNA copy number in whole blood at 15 min and 1 h after smoking. The observed decrease in mtDNA copy number negatively correlated with blood concentrations of 11-hydroxy-Δ9-tetrahydrocannabinol (11-OH-THC) and 11-Nor-9-carboxy-Δ9-tetrahydrocannabinol (THC-COOH), the two primary metabolites of Δ9-THC, but not Δ9-THC itself. Further, the negative correlation between 11-OH THC and THC-COOH concentrations and mtDNA copy number was found in only a subgroup of participants who use cannabis infrequently, suggesting a tolerance effect. Conclusions: These results illuminate mitochondrial alterations attributed to Δ9-THC consumption, which may be mediated by metabolites. These results appear to suggest stronger effects in individuals who consume cannabis less frequently, suggesting some form of tolerance to the effects of Δ9-THC and its metabolites on mtDNA content in whole blood. Keywords: Mitochondria; mtDNA; cannabis; THC; THC metabolites; blood; THC-COOH; 11-OH-THC.

Analysis and regulation of driving behavior in the entrance zone of freeway tunnels: Implementation of visual guidance systems in China

In China, visual guidance systems are commonly used in tunnels to optimize the visual reference system. However, studies focusing specifically on visual guidance systems in the tunnel entrance zone are limited. Hence, a driving simulation test is performed in this study to quantitatively evaluate the effectiveness of (i) visual guidance devices at different vertical positions (pavement and roadside) and (ii) a multilayer visual guidance system for regulating driving behavior in the tunnel entrance zone. Furthermore, the characteristics of driving behavior and their effects on traffic safety in the tunnel entrance zone are examined. Data such as the vehicle position, area of interest (AOI), throttle position, steering wheel angle, and lane center offset are obtained using a driving simulation platform and an eye-tracking device. As indicators, the first fixation position (FP), starting deceleration position (DP), average throttle position (TPav), number of deceleration stages (N|DS), gradual change degree of the vehicle trajectory (G|VT), and average steering wheel angle (SWAav) are derived. The regulatory effect of visual guidance devices on driving performance is investigated. First, high-position roadside visual guidance devices effectively reduce decision urgency and significantly enhance deceleration and lane-keeping performance. Specifically, the advanced deceleration performance (AD), smooth deceleration performance (SD), trajectory gradualness (TG), and trajectory stability (TS) in the tunnel entrance zone improve by 63%, 225%, 269%, and 244%, respectively. Additionally, the roadside low-position visual guidance devices primarily target the trajectory gradualness (TG), thus resulting in improvements by 80% and 448% in the TG and TS, respectively. Meanwhile, the pavement visual guidance devices focus solely on enhancing the TS and demonstrates a relatively lower improvement rate of 99%. Finally, the synergistic effect of these visual guidance devices facilitates the multilayer visual guidance system in enhancing the deceleration and lane-keeping performance. This aids drivers in early detection and deceleration at the tunnel entrance zone, reduces the urgency of deceleration decisions, promotes smoother deceleration, and improves the gradualness and stability of trajectories.

Study of Road Accidents by Analysis of Effects of Driving Parameters On Stopping Distance Using the Experimental Design Method and Driving Simulator

This paper aims to investigate the key factors contributing to road accidents and their interplay. A significant proportion of road accidents can be attributed to non-compliance with speed regulations, in conjunction with vehicle braking components (such as grip, road conditions, ..), as well as weather conditions. We conducted a speed measurement campaign on peri-urban roads in multiple Algerian cities to examine driving behavior and adherence to speed limits. To comprehensively understand the impact of speed, anti-lock systems, weather conditions, grip, and their interactions on a vehicle's braking distance, we employed an experimental design methodology. This approach was complemented with driving simulator tests. We expanded the experimental design to cover a range of speed variations, from 70 to 130 km/h, enabling us to explore the influence of various driving parameters on braking distance. Through statistical analysis of influence coefficients from 16 driving simulator tests, we established a model that represents the relationship between "objective functions" and "influence factors." This mathematical model was validated using simulator results. Our study revealed that braking distance is primarily affected by speed and weather conditions. Notably, the analysis of the road speed measurement campaign demonstrated that 55% of road users fail to adhere to speed limits.

State Estimation of Drive-by-Wire Chassis Vehicle Based on Dual Unscented Particle Filter Algorithm

Accurate vehicle dynamic information plays an important role in vehicle driving safety. However, due to the characteristics of high mobility and multiple controllable degrees of freedom of drive-by-wire chassis vehicles, the current mature application of traditional vehicle state estimation algorithms can not meet the requirements of drive-by-wire chassis vehicle state estimation. This paper proposes a state estimation method for drive-by-wire chassis vehicle based on the dual unscented particle filter algorithm, which make full use of the known advantages of the four-wheel drive torque and steer angle parameters of the drive-by-wire chassis vehicle. In the dual unscented particle filter algorithm, two unscented particle filter transfer information to each other, observe the vehicle state information and the tire force parameter information of the four wheels respectively, which reduce the influence of parameter uncertainty and model parameter changes on the estimation accuracy during driving. The performance with the dual unscented particle filter algorithm, which is analyzed in terms of the time-average square error, is superior of the unscented Kalman filter algorithm. The effectiveness of the algorithm is further verified by driving simulator test. In this paper, a vehicle state estimator based on dual unscented particle filter algorithm was proposed for the first time to improve the estimation accuracy of vehicle parameters and states.

Statistical Risk and Performance Analyses on Naturalistic Driving Trajectory Datasets for Traffic Modeling

The development of autonomous driving technology has made simulation testing one of the most important tools for evaluating system performance. However, there is a lack of systematic methods for analyzing and assessing naturalistic driving trajectory datasets. Specifically, there is a lack of comprehensive analyses on data diversity and balance in machine learning-oriented research. This study presents a comprehensive assessment of existing highway scenario datasets in the context of traffic modeling in autonomous driving simulation tests. In order to clarify the level of traffic risk, we design a systematic risk index and propose an index describing the degree of data scatter based on the principle of Euclidean distance quantization. By comparing several datasets, including NGSIM, highD, INTERACTION, CitySim, and our self-collected Highway dataset, we find that the proposed metrics can effectively quantify the risk level of the dataset while helping to gain insight into the diversity and balance differences of the dataset.

Algorithm Optimization of Computer Simulation Vehicle Driving Simulation System Based on Virtual Reality Technology

The traditional automobile driving simulation system has the problems of low calculation efficiency and lack of realism. The traditional automobile driving simulation system with low computational efficiency and lack of realism limits the learning effect. Through virtual reality technology, vehicle driving can be simulated. By optimizing the algorithm of simulating vehicle driving simulation system, the preference of testers for driving style is investigated and the driver's preference style is determined. Finally, through the automatic driving simulation test method based on genetic algorithm, the key scenes can be divided into 11 different types, and the Euclidean distance of these 11 types is analyzed. Most drivers prefer a more conservative autonomous driving style. When analyzing 11 key scenario types, the Euclidean distance between scenario 2 and scenario 3 is the smallest, which is 33 m, and the maximum Euclidean distance between scenario 6 and scenario 11 is 91 m. The difference between scene 2 and scene 3 is the smallest, while the difference between scene 6 and scene 11 is the largest, and there are differences between each scene. Through virtual reality technology and algorithm optimization, the performance and user experience of driving simulation system are improved.

Identifying the effects of driving parameters on stopping distance to reduce accident risks

The object of the research is the most important factors causing road accidents. This paper aimed to study the effects of this factors and their interactions on the stopping distance function. Understanding this function through simulation and comparing the results with mathematical models and experimental tests will help to reduce the number of road accidents. A large part of road accidents is linked to non-compliance with regulatory speed associated with vehicle braking system (grip, road and tires) and weather conditions. A speed measurement campaign on peri-urban roads was carried out to study driving behavior and compliance with speed limits in several Algerian cities. An experimental modelling of speed, anti-lock system, weather, grip and their interaction effects on the stopping distance of a vehicle using the experimental design method, combined with driving simulator tests was been conducted. The developments of experimental design with speed variation ranges (70 and 130 km/h) were necessary to study the influence of the various driving parameters on stopping distance. The mathematical model developed has been validated by the results obtained on the simulator. The experimental design method and simulator results were used to identify and define the important parameters that influence the braking distance. The results show that the stopping distance (SD) is mainly influenced by the vehicle speed (S), the weather conditions (M), and their interaction. The increase due to speed leads to an increase in the stopping distance with an estimated effect of 54.30 m. When the speed varies between its lower experimental level (70 km/h) and its higher level (130 km/h), it is estimated that the stopping distance will increase by 54.30 m. The analysis of the road speed measurement campaign, 55 % of road users do not obey the speed limits. The results obtained in this study can be applied to other countries, only the parameters need to be adjusted.

Validation of a computerized driving simulator test of cognitive abilities for fitness-to-drive assessments.

Driving requires a series of cognitive abilities, many of which are affected by age and medical conditions. The psychosocial importance of continued driving ushers the need for valid measurements in fitness-to-drive assessments. A driving simulator test could prove useful in these assessments, having greater face validity than other off-road tests and being more cost-effective and safer than ordinary on-road testing. The aim of this study was to validate a driving simulator test for assessment of cognitive ability in fitness-to-drive assessments. The study included 67 healthy participants. Internal consistency of the simulator subtests was estimated. A correlation analysis between results on the simulator and the cognitive tests Trail Making Test (TMT) A and B and the Useful field of View test (UFOV) and multiple regression analysis were conducted. Finally, a comparison of results between age groups (>65 years) and (<65 years) was done. Results showed good internal consistency. Significant and moderate correlations were found for all reaction time in the simulator's subtests and UFOV 3, and all but two with TMT A. Lane positioning in the simulator showed significant and low to moderate correlations with UFOV 3 in all subtests. Reaction time and Double reaction time on subtest 3 were significantly correlated with UFOV 2 and UFOV 3 and TMT A, respectively. Test on Centerline (position) in subtest 3 as dependent variable was significantly correlated with UFOV 3. Significant means differences and large effect sizes between the age groups were found for all reaction time and lane positioning tests. The findings of concurrent validity, especially with TMT A and UFOV 3 and its sensitivity for age-related differences, indicate potential for the simulator to be used as a complement in fitness-to-drive assessments. However, a clinical study is necessary to further examine its usefulness for patients with cognitive deficits.

Research on Specific Scenario Generation Methods for Autonomous Driving Simulation Tests

In this paper, we propose a method for the generation of simulated test scenarios for autonomous driving. Based on the requirements of standard regulatory test scenarios, we can generate virtually simulated scenarios and functional scenario libraries for autonomous driving, which can be used for the simulated verification of different ADAS functions. Firstly, the operational design domain (ODD) of a functional scenario is selected, and the weight values of the ODD elements are calculated. Then, a combination test algorithm based on parameter weights is improved to generate virtually simulated autonomous driving test cases for the ODD elements, which can effectively reduce the number of generated test cases compared with the traditional combination test algorithm. Then, the traffic participant elements in each test case are sampled and clustered so as to obtain hazard-specific scenarios. Then, the values of the subelements under the traffic participant element in each test case are sampled and clustered to obtain hazard-specific scenarios. Finally, the specific scenarios are applied to the automatic emergency braking (AEB) system on the model-in-the-loop (MIL) testbed to verify the effectiveness of this scenario generation method.

Exploring the impact of the passenger's display on driver workload and driving performance

New production vehicles equipped with multiple screens have various functions and technologies at the user's fingertips that create informative and immersive cockpits not only for the driver but also for the passenger. Despite the growing popularity of the co-pilot display, surprisingly little is known about the impact of its engagement on drivers. Engagement, in the context of this paper, is defined as visual, auditory, and mental involvement but no manual involvement. The present study sought to investigate the effects of co-pilot display engagement on drivers' visual workload, cognitive workload, and driving performance and offered a deeper insight into the design factors and task involvement of the co-pilot display. The study involved a driving simulator testing of 25 participants in five automobiles with a co-pilot display. Our analysis found increased driver visual workload and cognitive workload in the conditions of co-pilot display engagement. Participants exhibited more erratic driving behavior (standard deviation of speed and standard deviation of lane position) while the front passenger was watching a video. Furthermore, five linear mixed models were built to further analyze the effects of task type, screen size, screen layout, and task involvement on dependent measures. Potential applications of this research include refinements to the co-pilot display and workload estimation of co-pilot display engagement.

How Does an Extra-Long Freeway Tunnel Influence Driving Performance? A Comparative Study of Driving Simulation

Extra-long tunnels have adverse effects on driving performance since drivers will be affected by the enclosed, dimly lit, and monotonous environment for a longer time. In the context of the increasing number of extra-long tunnels, this study aims to investigate the effects of extra-long freeway tunnels with a length of 20 km on driving performance using driving simulation tests. Factors including the tunnel environment, driving time, traffic flow, and gender were considered as influencing factors. Performance indicators including the brake reaction time, standard deviation of driving speed, and standard deviation of lateral position were collected. A total of 60 drivers were recruited for the driving simulation study, and the relationships between the driving performance indicators and influencing factors were analyzed by establishing linear mixed models with random intercept. The results demonstrate that driving performance significantly degraded after 5 – 6 min of driving in the extra-long tunnel although drivers were more cautious and presented a better performance when just entering the tunnel. Moderately higher traffic flow could improve driving performance in the extra-long tunnel but not on the open road. Meanwhile, female drivers had better lateral and longitudinal stability in the extra-long tunnel, while no significant difference was witnessed in reaction ability and driving performance on the open road.

Drivers’ behaviour when overtaking cyclists on rural roads: Driving simulator validation using naturalistic data

Driving simulator is a useful tool for obtaining data on driver behaviour efficiently and quickly. However, to ensure the reliability of the data gathered by the simulator, it is necessary to check the differences between drivers’ behaviour in the simulator and in reality. In this study, an existing two-lane rural road was replicated on the driving simulator under the same traffic conditions of groups of cyclists and oncoming motorised vehicles. For this purpose, a naturalistic field data collection was developed on the real road using instrumented bicycles and static video recordings. A total of 30 volunteers participated in the driving simulator tests. The objective validation of the driving simulator was based on three operational variables: average travel speed, overtaking vehicle speed, and lateral clearance. As a result, higher average travel speeds and lower lateral clearances were obtained in the real world compared to those observed in the simulator. It was also found that overtaking vehicle speed depends on the group of cyclists. Overall, the data obtained in the field and in the driving simulator did not present statistically significant differences. The analysis of drivers’ perception in the simulator tests concluded that the simulator reflected reality in an accurate way, achieving the subjective validation of the driving simulator. Thus, this study validates the driving simulator for bicycle safety research on rural roads.

Risk Assessment of Distracted Driving Behavior Based on Visual Stability Coefficient

Cell phone call operations during driving can lead to distraction and cause potential safety hazards. In order to quantitatively characterize the influence of cell phone call mode on the driver’s visual behavior in different traffic conditions and to analyze the risk level of distracted driving from the visual level, a distracted driving simulation test was carried out based on a driving simulator and eye tracker. The eye movement data of drivers during normal driving, hands-free call, and video call under two typical traffic conditions of free flow and congested flow on the urban expressway were collected. Firstly, four visual characteristics indicators that were highly sensitive to traffic conditions and driving states were selected in terms of visual field range, visual recognition, visual search, and visual load, which were the information entropy of fixation area (IEFA), saccade amplitude, peak-to-average ratio of saccade velocity (PARSV), and relative change intensity of pupil area (RCPA). Then, based on the improved CRITIC method, the visual stability coefficient (VSC) was constructed as a new indicator to comprehensively assess the risk level of the driving state, and the assessment criteria were divided. Finally, the grey correlation analysis method was introduced to verify the assessment effect of VSC. The results show that different cell phone call modes increased driving risk in both traffic conditions. Among them, the negative influence of video calls on driving safety was significantly higher than that of hands-free calls, with a significant decrease in VSC, and the drivers’ VSC in the free flow scenario was more sensitive to the impact of cell phone call operation, and the driving risk increased significantly during distracted driving. The VSC can quantitatively assess driving risk from the perspective of visual psychological safety and contributes to the development of corresponding early warning and control measures.

Visual characteristics of drivers in different directions and lengths of gradual landscape zones in extra-long highway tunnels

Owing to the tightness and monotonicity of the tunnels, the number of traffic accidents caused by driving through them for a long time is positively correlated to their length. To improve driving safety, a landscape zone with the function of awakening the driver and relieving their fatigue has been adopted in an increasing number of extra-long highway tunnels. However, the sharp contrast between the landscape and ordinary zones often makes drivers uncomfortable. Therefore, a gradual landscape zone is proposed in this study. Through driving simulation tests, the eye movement and pupil index were used to study the attractiveness, direction, and length of the gradual landscape zone in an extra-long highway tunnel. The results show that there is no risk of causing excessive distraction to drivers in the “blue sky and white clouds” landscape zone of the tunnel vault, and the gradual landscape zone in the approach direction has a significant influence on the change rate of the pupil diameter range of drivers. In contrast, the gradual landscape zone in the driving direction has little influence. For a longer length of the gradual landscape zone in the approach direction, drivers require a longer adaptation time at the descent stage of the pupil diameter, and the change rate of the pupil diameter range is smaller. Therefore, a longer gradual zone in the approach direction is helpful in improving the adaptability of drivers when passing through the landscape zone.

Comparing Eye-tracking System Effectiveness in Field and Driving Simulator Studies

Background: Several studies have been conducted by combining the benefits of eye-tracking systems with driving simulators to simultaneously investigate driving behavior and the potential source of distraction. However, little effort has been made in terms of eye-tracking validation in the driving simulator environment. Objective: The overall aim of this study is to validate an eye-tracking system within the context of a driving simulation environment by considering a specific urban context application. Methods: A field survey and a driving simulation experiment were conducted for a case study in Rome, Italy. The selected real road sections and events were reproduced on the driving simulator system. An eye-tracking system was used to record eye movements both on a real vehicle and the simulator. The eye movements of 14 participants in the field survey and 18 participants in the driving simulation tests, as well as their driving performances, were collected while approaching an urban intersection in relation to two specific road events: i) the presence of a speed limit sign and ii) the presence of a crossing pedestrian. Results: Eye tracker parameters and driving performances were compared between the real driving tests and driving simulator experiments in order to validate the eye-tracking system. It was validated for both events in terms of duration and distance of the eye fixation. Conclusion: The results demonstrated that an eye-tracking system is an effective tool for studies and applications in a virtual reality environment.

Automatic travelling of agricultural support robot for a fruit farm -Verification of effectiveness of RTK-GNSS and developed simulator for specification design

Labour shortages and fatal accidents in agricultural work have recently emerged as critical problems in Japan, necessitating productivity enhancement, workload reduction, and safety assurance. Therefore, in Japan and countries with similar agricultural environments, the use of small and inexpensive agricultural robots that can be used in mountain farms and orchards is desirable. In this study, a dynamic positioning test was performed in orchards in a mountainous region to verify the positioning accuracy and stability of the Global Navigation Satellite System (GNSS) and real time kinematic (RTK)-GNSS. In addition, a simulator for an agricultural robot that could consider the environmental information of orchards was developed, and driving tests were conducted using the GNSS data acquired in the simulation. The error of the GNSS module was set to be higher than that for the measured value, and robot travelling in the orchard was simulated. The results of GNSS positioning tests in an orchard near a mountainous area indicate that in the specific environmental conditions, the RTK-GNSS and stand-alone (SA)-GNSS can attain a positioning accuracy with an order of tens of centimetres and few metres, respectively. Moreover, the simulation results based on the GNSS positioning results indicate that a vehicle implementing RTK-GNSS and a simple obstacle detection sensor can travel autonomously in a farmyard without colliding with the tree rows. In contrast, a vehicle implementing SA-GNSS and a simple obstacle detection sensor cannot drive autonomously in an orchard and must realise self-positioning using a more accurate sensor. Therefore, the proposed approach of realising simulations of autonomous agricultural robots based on GNSS data from a real orchard can facilitate the evaluation of practical agricultural robots and confirming safety traveling root. The results demonstrate the possibility of development of small agricultural robot for orchards. We conducted the GNSS positioning test in an orchard at an altitude of approximately 830 m, and a similar performance can be expected under similar agricultural situations because the error of the GNSS module was set to be higher than the measured value in driving simulation test.

RHONN-Modeling-Based Predictive Safety Assessment and Torque Vectoring for Holistic Stabilization of Electrified Vehicles

Improving vehicle safety and reducing traffic accidents have always been of cardinal importance in vehicle dynamics control fields. A reasonable and comprehensive safety index that characterizes the vehicle's safe region is the most challenging aspect of research. With the linear dynamics model as the benchmark, this article uses the deviation of yaw rate and vehicle sideslip angle from the corresponding linear response as the lateral stability indices. Meanwhile, the maximum slip ratio of the driven wheels is selected as the longitudinal stability index. The <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">safety indicator</i> , a quantitative index featuring the safety degree of vehicle planar motions, is then inferred by a fuzzy inference system using the lateral and longitudinal stability indices. As such, the recurrent high-order neural network model predicts the vehicle states. Based on the predicted states, a safety indicator is then derived by using fuzzy inference system, which can assess the safety of a driver's control commands. In the case of an improper driving torque demand given by the driver, the torque correction process is immediately conducted to maintain the vehicle in a safe region. Finally, two typical scenarios—slippery curves and double lane changes in low friction roads—are simulated on the MATLAB/Simulink-CarSim cosimulation platform. The hardware-in-the-loop experiments are also conducted on a driving simulator test rig, validating the performance of the developed algorithms. The holistic stability performance of the in-wheel motor driven vehicle is thoroughly analyzed and compared using three existing methods. The simulation and experimental results validate the effectiveness and feasibility of the proposed method.

Correlating driving behavior with safety performance: from the heart to the pedals with a driving simulator

Driving behavior significantly affects road safety, pollutant emissions, and fuel consumption, and an in-depth analysis is crucial for any accurate evaluation of a transport system. To develop a comprehensive study, it is important to consider different variables and traffic conditions, the presence of vulnerable road users, road singularities, as well as driving behavior profiles (e.g., gear-shift strategy, acceleration style). In this research, fixed-based driving simulation tests were carried out to allow a global evaluation of driving behavior under two different traffic conditions (urban and highway). The main objective is to understand driver-road interaction and associated impacts in terms of the adopted gear-shift strategy, vehicle dynamics profile, driving volatility profile (a safety-related indicator), driver's heart rate monitoring (a driving comfort-related variable), and pollutant emissions modeling. Drivers’ performance was assessed for each case study and a database was created for different segment types and considering different drivers, using statistical data mining models. This work is relevant for a better understanding of driving behavior both from the viewpoint of policymaking as well as for driver awareness about the relative impact associated with his/her driving behavior.

Dangerous Driving Behavior Recognition Based on Hand Trajectory

Dangerous driving behaviors in the process of driving will produce road traffic safety hazards, and even cause traffic accidents. Common dangerous driving behavior includes: eating, smoking, fetching items, using a handheld phone, and touching a control monitor. In order to accurately identify the dangerous driving behaviors, this study first uses the hand trajectory data to construct the dangerous driving behavior recognition model based on the dynamic time warping algorithm (DTW) and the longest common sub-sequence algorithm (LCS). Secondly, 45 subjects’ hand trajectory data were obtained by driving simulation test, and 30 subjects’ hand trajectory data were used to determine the dangerous driving behavior label. The matching degree of hand trajectory data of 15 subjects was calculated based on the dangerous driving behavior recognition model, and the threshold of dangerous driving behavior recognition was determined according to the calculation results. Finally, the dangerous driving behavior recognition algorithm and neural network algorithm are compared and analyzed. The dangerous driving behavior recognition algorithm has a fast calculation speed, small memory consumption, and simple program structure. The research results can be applied to dangerous driving behavior recognition and driving distraction warning based on wrist wearable devices.

The Effects of Visual Field Loss from Stroke on Performance in a Driving Simulator.

Visual field loss is a common consequence of stroke and often precludes driving. However, legal visual requirements for drivers' licenses are largely without scientific basis. This study aimed to examine the effects of different types of homonymous visual field loss after stroke on simulated driving. Data on performance and safety from a traffic simulator test for 153 participants with withdrawn drivers' licenses due to visual field loss from stroke were retrospectively compared with data from 83 healthy individuals without visual deficits in a cross-sectional study. The 93 individuals in the stroke group who regained their driving licenses after a successful simulator test were then followed in a national accident database. Sixty-five percent of the stroke participants passed the simulator test (95% confidence interval, 57 to 72%). Younger patients were more successful than older. However, classification by neither type of homonymous visual field loss nor side of visual field loss was predictive of driver safety. Participants with hemianopia had their lateral lane position dislocated to the nonaffected side of the visual field. None of the participants with a regained license were involved in motor vehicle accidents 3 to 6 years after the test. In this large cohort, driver safety could not be predicted from the type of homonymous visual field loss. Even individuals with severe visual field loss might be safe drivers. Therefore, it seems reasonable to provide an opportunity for individualized assessments of practical fitness to drive in circumstances of licensing issues. This study demonstrates the potential of using a standardized driving simulator test for such assessments of fitness to drive.