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BACKGROUND: Return to driving after an acquired brain injury (ABI) has been positively associated with return to employment, maintenance of social relationships, and engagement in recreational and other community activities. Safe driving involves multiple cognitive abilities in a dynamic environment, and cognitive dysfunction resulting from ABI can negatively impact driving performance. OBJECTIVE: This manuscript examines the post-injury return-to-driving process, including performances on the in-office and on-road assessments, and the role of a rehabilitation neuropsychologist in helping patients resume driving. METHOD: In this study, 39 of 200 individuals (approximately 20%) treated at an outpatient neurorehabilitation facility, who performed satisfactorily on a pre-driving cognitive screening, completed a behind-the-wheel driving test. RESULTS: Of the 200 individuals, 34 (87%) passed the road test. Among the remaining five individuals who did not pass the road test, primary reasons for their failure included inability to follow or retain examiner directions primarily about lane position, speed, and vehicle control. The errors were attributable to cognitive difficulties with information processing, memory, attention regulation, and dual tasking. CONCLUSION The rehabilitation neuropsychologist contributed to the process by assessing cognition, facilitating self-awareness and error minimization, providing education about driving regulations and safety standards, and preparing for the road test and its outcomes.

Cilj ove aplikacije je korištenjem Vue.js framework-a pružiti korisniku što lakše sučelje za svladavanja gradiva teorijskog dijela vozačkog ispita. Glavni dio aplikacije sastavljen je od 4 komponente Teorije, Pitanja, Kvizova te Znakova. Teorija pruža setove pitanja i odgovora po poglavljima priloženim na jednom mjestu. Komponenta Pitanja pruža korisniku samoprovjeru naučenih pitanja također po poglavljima. Kvizovi omogućuju korisniku pripremu za kviz teorijskog dijela vozačkog ispita. Kvizovi su sastavljeni kao pravi kvizovi, odnosno sastoje se od 38 pitanja, sadržavaju 120 bodova, imaju vremensko ograničenje i tako dalje. Spremanjem riješenih kvizova u SQLite bazu podataka pomoću Express.js i Sequelize-a, korisniku pružamo uvid u rezultate svih njegovih riješenih kvizova. Svi ti dijelovi pružaju korisniku veću mogućnost prolaska teorijskog dijela vozačkog ispita. The goal of this application is to use the Vue.js framework to provide the user with the easiest possible interface for mastering the theoretical part of the driving test. The main part of the application is composed of 4 components: Theory, Questions, Quizzes and Signs. Theory provides sets of questions and answers by chapters attached in one place. The Questions component provides the user with a self-evaluation of learned questions also by chapter. Quizzes prepare the user for theoretical part of the driving test quiz. They are composed like real quizzes, i.e. they consist of 38 questions, contain 120 points, have a time limit and so on. By saving the solved quizzes in the SQLite database using Express.js and Sequelize, we provide the user with insight into the results of all his solved quizzes. All these parts provide the user with a greater possibility of passing the theoretical part of the driving test.

Equestrianism is a special sport. Equestrian sports have become popular in people’s lives and have also developed rapidly in our country, becoming a trend. This paper aims to study the equestrian sports posture information detection and information service resource aggregation system based on mobile edge computing. The research of equestrian sports can greatly promote future development. For this reason, we use the power of science and technology to study the equestrian sports posture and make an equestrian sports posture information detection system. The system is designed to feed back the riding posture in real time and can provide equestrian athletes with a more scientific and healthier equestrian training posture. In order to fully verify the practicability of the system, at the end of the forum, the performance of the entire monitoring platform was tested, and three tests were designed, respectively: packet loss rate test, driving test, and riding test. The driving test proves the validity of data transmission, and the riding test proves the practicability of the monitoring platform’s functions. The test results show that the maximum data packet loss rate is 0.6%, which can fully confirm that the monitoring platform has sufficient technical practicability, no problems have been found in practical applications, and it has good market and application prospects.

International audience; Car manufacturers expect driving simulators to be reliable research and development tools. Questions arise, however, as to whether drivers’ behavior on simulators exactly matches that observed when they are driving real cars. Drivers’ performances and their subjective feelings about their driving were compared between two groups during a 40-min driving test on the same circuit in a real car (n = 20) and a high-fidelity dynamic simulator (n = 27). Their speed and its variability, the braking force and the engine revolutions per minute (rpm) were recorded five times on a straight line and three times on a curve. The differences observed in these measurements between circuit driving (CD) and simulator driving (SD) from the 6th to 40th minute showed no significant changes during the drive. The drivers also completed the NASA Raw Task Load Index (NASA RTLX) questionnaire and the Simulator Sickness Questionnaire (SSQ) and estimated the ease and standard of their own driving performances. These subjective feelings differed significantly between the two groups throughout the experiment. The SD group’s scores on the NASA RTLX and SSQ questionnaires increased with time and the CD group’s perceived driving quality and ease increased with time, reaching non-significantly different levels from their usual car driving standards by the end of the drive. These findings show the existence of a fairly good match between real-life and simulated driving, which stabilized six minutes after the start of the test, regardless of whether the road was straight or curved. These objective findings and subjective assessments suggest possible ways of improving the match between drivers’ performances on simulators and their real-life driving behavior.

The paper sums up the requirements and demands for the driver training in Czech lands from the early 20th century to 1989. This period is associated with several political changes that were reflected also in the training of drivers. In this context, the paper focuses on the driving schools and their legal status, the entitlements for obtaining a driving license and the individual groups of these driving licenses. Since the obligation to undergo a driving test before driving had been implemented (1905), the content and difficulty of the driver training as well as other requirements (such as medical or professional) had been discussed. Particular attention is paid to the transformation of involvement of the state and the role it played in the trainings. The text of the article is largely based on the analysis of various legislations. To reveal the reality of the driver training and driving schools’ activities, relevant archive sources and partly contemporary literature were used.

Background Little is known about the lived experiences of individuals with tic disorders when driving vehicles or trying to obtain a driving license. Objective To survey the driving-related experiences of adults with tic disorders. Methods A global survey was disseminated via social media, international patient organizations, and experts between April 27, 2020 and July 20, 2020. Results Participants were 228 adult individuals self-reporting a confirmed diagnosis of Tourette syndrome or chronic tic disorder. Of these, 183 (87.7%) had a driver's license. A minority (9%) reported that they had found it hard to pass the driving test. Tics only interfered with driving "a bit" (58.5%) or "not at all" (33%). A majority of participants reported being able to suppress their tics (39.5%) or that their tics are unchanged (28.5%) while driving. Nearly half of the participants (46.5%) had been involved in accidents, but only a negligible percentage (3.2%) considered that these were linked to the tics. Participants without a driver's license (n = 28, 12.3%) reported significantly more severe tics, compared to those with a license. The majority of these (60.7%) identified their tics as the main reason for not having a license and 64.3% said that they would like to receive support to obtain one. Conclusions The majority of surveyed participants with chronic tic disorders reported minimal difficulties with driving. However, a non-negligible minority of more severe cases struggle with driving or refrain from driving altogether and would benefit from additional support. The results have implications for clinicians and vehicle licensing agencies.

This study aimed to examine the content validity of on-road tests in real traffic environments over 4 phases. Phase 1: Extracted on-road test items from the previous study. Phase 2: Conducted a sem...

The ride comfort of bus passengers is a critical factor that is recognized to attract greater ridership towards a sustainable public transport system. However, it is challenging to predict bus passenger comfort due to the complex non-linear interaction among various factors. In an application-based study, 18 real driving tests were conducted to analyze the correlation between factors induced by motion sickness and the driving status of the vehicle. We used the user’s feedback module (UFM) to record the feelings of passengers, and the six degrees of freedom (6-df) motion parameters were obtained by the accelerometer in the micro electro mechanical system (MEMS) of the smartphone. Then, the data were discriminated and analyzed, and thresholds of the variables affecting the discomfort of passengers in different conditions were obtained. Finally, we established a prediction model of motion sickness duration based on the driving status of vehicles. The result shows that passenger’s comfort is most sensitive to vertical acceleration changes when the vehicle is decelerated, and the duration of motion sickness (DMS) can be effectively predicted (79.8%) by the vehicle’s lateral acceleration, roll, and pitch angular velocity indicators. The findings of this study provide insights into the potential theoretical basis for policymakers to improve the adjustment of the driving strategies and path trajectory of city buses.

The objective of the study was to evaluate predictor variables stemming from different assessment approaches (medical documentation, neuropsychological assessment, and Mediatester driving assessment) on patient's ability to drive (passing the practical driving test with a qualified instructor) following a TBI (traumatic brain injury) or a stroke. The study included 63 participants (54 males), aged 20 to 80 years (M = 44.4; SD = 16.7). Majority of participants suffered a TBI and 18 participants were included after an ischemic stroke. Patients who passed a driving test had significantly higher composite index on Comprehensive Trail- Making Test (medium or large effect size) compared to those who did not pass a driving test, or those who passed the driving test with limitations. The results on the 18-light reaction test (18 LRT) suggest that the reaction time could also play a role in predicting the ability to drive. The model with these two predictors, along with Glasgow Coma Scale, successfully classified 90 % of participants in two respectful groups; passed vs. did not pass a driving test/passed the driving test with limitations. The results suggest that neuropsychological and driving assessments that measure a range of cognitive abilities are better predictors of regaining the ability to drive after a TBI or stroke than separate cognitive abilities.

This study developed a control algorithm of torque vectoring system to improve the handling performance of a green-car and evaluate the performance of vehicle dynamics to improve the controllability and stability. Firstly, this study configured the control algorithm with the supervisory controller that decides the control mode by checking the current driving status of a vehicle, target yawrate calculator that reflects the steady-state and transient-state response characteristics according to the control mode, as well as the reference yawrate calculation, desired yaw moment calculation and transferred torque calculation. The control mode consists of the agile mode that controls the torque vectoring to improve the controllability and the safe mode that controls the torque vectoring to improve stability. Secondly, this study performed the modeling of the dual motor type torque vectoring system and an EV AWD vehicle. Lastly, this study defined the driving test scenario and evaluation method as well as the quantitative performance index for each vehicle test and established the co-simulation environment for the handling test evaluation. This study found that when a vehicle is controlled by applying the torque vectoring system, handling performance was improved according to controllability and safe mode by verifying the simulation.

Motor vehicle crashes remain the leading cause of adolescent mortality and injury in the United States. For young drivers, crash risk peaks immediately after licensure and declines during the next two years, making the point of licensure an important safety intervention opportunity. Legislation in Ohio established a unique health-transportation partnership among the State of Ohio, Children's Hospital of Philadelphia, and Diagnostic Driving, Inc., to identify underprepared driver license applicants through a virtual driving assessment system. The system, a computer-based virtual driving test, exposes drivers to common serious crash scenarios to identify critical skill deficits and is delivered in testing centers immediately before the on-road examination. A pilot study of license applicants who completed it showed that the virtual driving assessment system accurately predicted which drivers would fail the on-road examination and provided automated feedback that informed drivers on their skill deficits. At this time, the partnership's work is informing policy changes around integrating the virtual driving assessment system into licensing and driver training with the aim of reducing crashes in the first months of independent driving. The system can be developed to identify deficits in safety-critical skills that lead to crashes in new drivers and to address challenges that the coronavirus disease 2019 pandemic has introduced to driver testing and training.

This paper presents the development of a Virtual Simulation Environment (VSE) and a Digital Twin (DT) of an autonomously driving truck for a distribution center. While autonomous driving on public roads still faces various technical and legal challenges, within a distribution center, which is a confined area, some of these restrictions do not apply. Therefore, distribution centers can be the first environment where the autonomous driving of trucks is possible. A distribution center is a closed environment with no, or minimal generic traffic, where the trucks have relatively low speeds, short stopping distance and layout precisely known. Dedicated sensors locate the trucks. This paper addresses the mentioned aspects of driving in the distribution centers describing the necessary steps taken for the design, implementation, and testing of a VSE for a distribution center, and a DT of an autonomously driving truck. The development of the VSE is based on the integration of a SysML modeling tool – IBM Rhapsody, MATLAB Simulink, and Unity Game Engine using a Model-Based System Engineering approach. The paper also presents the test and the validation of a driving scenario used in a distribution center, using the TruckLab setup of the Eindhoven University of Technology, The Netherlands. The VSE and the DT showed considerable potential as testing and validation tools for automotive engineers, making it possible to define driving test scenarios for different types of tractor and trailer combinations.

The development of automated driving is an ongoing process; nonetheless, certain problems remain unresolved. One of them is the question when the automated vehicle control system should hand over the control to a human driver and whether this can be done in a safe way. What happens if a driver is not ready to take over? Can the system somehow estimate the status of the driver? The WACHsens simulator study was designed with the aim to gain more knowledge about when and how drivers are getting sleepy with special focus on automated driving.The overall goal of the project was to merge data from vegetative vigilance, camera observation and driving behaviour. This article describes the process of the driving behaviour observation and the evaluation of the data collected during the observation. An enhanced observation scheme made it possible to determine, at any point in time of the 30 minutes drives, in which posture the test person is and in what degree of drowsiness the test person is. It is based on the variables and scales which have been used in other studies such as ORD (Observer Rating of Drowsiness) and ORS (Observer Rated Sleepiness). They were linked to the observation method of the Vienna driving test to allow continuous observation. 197 simulator test drives from 50 test persons were analyzed by the observers. Four different scenarios were evaluated for all test subjects: tired/manual, tired/automatic, rested/manual, and rested/automatic. The aim of the observation analysis was to investigate differences in body movements and activities according to personal characteristics (age, gender, driving experience, experience with assistance systems) and regarding the different scenarios. The categorization of the drowsiness level of the test persons by the observers corresponds very well with the subjective assessment of the test subjects (measured by the Karolinska sleepiness scale KSS). A comparison of the different scenarios shows that most of the signs of sleepiness or situations in which the test subjects fell asleep were observed during the tired/automated trips. But even during the rested/automated drive over 40% of the test persons showed signs of tiredness, roughly the same number actually fell asleep as in the tired/manual drive. No significant differences between the personal characteristics (gender, age, and experience with assistance systems) regarding the number of body movements (change of position and activities) or sleepiness levels could be found. A significant difference was found between the different scenarios and the comparisons between the tired/rested trips and the manual/automated trips regarding the moment in which the test persons showed first signs of tiredness. During the automated trips and/or if the test subjects showed signs of progressing weariness, the first signs of tiredness were registered significantly earlier than during the trips in which the test subjects drove manually and/or were rested. The results show that the mode of operation - manual or automated driving - impacts the time course and level of sleepiness while driving. This sheds light on the importance to carefully evaluate driving automation systems that assume a driver as emergency fallback. Further research is recommended to investigate safe modes of control hand over in automated driving.

Fatigue driving is one of the main reasons for fatal crashes and highway accidents for drivers. Driving fatigue detection method based on monitoring psychological indicators is an effective method to avoid traffic accidents. The driver’s heart rate (HR) and blood oxygen saturation (SpO2) data were obtained in low-voltage and hypoxia plateau area by driving fatigue test, that is, field driving fatigue test and drug intervention fatigue driving test. SPSS software was used to process the analysis data and combined with the driver’s subjective response, which can figure out the correlation between parameters and driving fatigue. This paper figures out that HR can be used as an effective indicator to determine the degree of driver fatigue, and SpO2 can only be used as an auxiliary indicator. The time spent driving to fatigue increased after taking the intervention drug, indicating that the intervention drug has the ability to resist driving fatigue and delay fatigue in low-voltage and hypoxia plateau environment. This study provides theoretical basis and new research fields for further research on low-voltage and hypoxia plateau areas to alleviate driving fatigue, ensure driving safety and design of fatigue warning devices.

What is known and objective Tolperisone is a centrally acting muscle relaxant under development in the United States as a treatment for acute and painful symptoms of muscle spasms. The objective of this three‐way, randomized, blinded, three‐period crossover study was to assess the safety and cognitive effects of tolperisone compared to placebo and the widely used muscle relaxant cyclobenzaprine in healthy volunteers. Methods Subjects were randomized to 1 of 3 treatment arms to receive tolperisone (150 mg), cyclobenzaprine (10 mg) or placebo 3 times per day (TID) in 3 separate study periods. Subjects completed a driving test on the Cognitive Research Corporation's Driving Simulator (CRCDS Mini‐Sim), a validated driving simulator, on day 1 at time to maximum plasma concentration, on day 2 before the morning dose of study drug and on day 3 at steady state following the morning dose. Subjects were assessed on various driving parameters and on a computer‐administered digit‐symbol substitution test (CogScreen symbol digit coding test). The driving scenario is a monotonous 100 km highway route on which subjects are instructed to maintain speed and lane position. Results and discussion The performance of subjects who had received tolperisone was not significantly different from those who had received placebo in terms of the primary end point: standard deviation of lateral position, a measure of weaving. Subjects who had received tolperisone also performed comparably to those who had received placebo on a range of secondary measures assessing driving ability, cognition and psychomotor performance. In contrast, subjects who had received cyclobenzaprine showed significant impairment compared to placebo (P, Tolperisone is a centrally acting muscle relaxant under development for the treatment of acute and painful symptoms of muscle spasm. In this study of driving ability and cognitive effects, subjects who received tolperisone experienced no impact on measures of driving, self‐reported sleepiness, or cognition compared to placebo, in contrast to those who received the widely used muscle relaxant cyclobenzaprine.

Weaving turbulence on freeways significantly increases the demand for complex driving maneuvers, leading to high driver stress. This study explored the impact of freeway weaving segment configuration designs on drivers’ stress attributed to complex vehicle maneuvers in dynamic traffic. An on-road driving test was conducted to measure healthy, young drivers’ heart rate variability, a biomarker of driving stress, while they performed various freeway weaving maneuvers under different traffic conditions. Statistical analyses were conducted to identify specific weaving maneuvers that triggered high- and medium-level driver stress. The probability distributions of the heart rate variability were estimated and the probabilities of high- and medium driving-stress were determined. Results indicate that intense demand of vehicle maneuvers significantly increases drivers’ stress, especially in the driving scenarios, where two-lane changes were required and the base length of weaving segments were shorter than 400 m or longer than 700 m under medium traffic, or the non-weaving segments were under medium traffic. The baseline driver stress probability is 3.34%. This grew dramatically to more than 60% under the driving scenarios. The results of the study concluded that two-sided weaving segment type, the shorter base length of weaving segments, and medium traffic, are the determinants for a higher likelihood of the driving stress.

This paper proposes an on-line advice eco-driving assistance system (EDAS) for providing the optimal velocity profile to improve fuel economy. The EDAS employs a driver-in-the-loop (DIL) framework, where an adviser is designed to provide high-level driving mode suggestions while the low-level control commands such as throttle and brake, are left to the driver to implement. A simplified dynamic model is developed in the adviser excluding continuous-time control variables such as the engine torque and engine brake torque. The adviser employs an event-triggered model predictive control (MPC) algorithm to provide suggestions in realtime using predictive road and traffic information. On-line computational cost for the MPC has been significantly reduced using an efficient mixed-integer optimal control (MIOC) algorithm. To demonstrate the efficiency and effectiveness of the proposed EDAS, a numerical study and a simulation using measured data from a real-life driving test is conducted. Comparisons are made between the proposed EDAS and an eco-driving controller considering both high and low level control inputs without a driver.

Background and Objectives: Nearly 16,000 people are killed in driving accidents in Iran each year. The purpose of this study was, therefore, to determine the effect of age on driving performance, using a driving simulator. Methods: This cross-sectional study was carried out on 16 young drivers, 16 middle-aged drivers, and 16 elderly drivers in Tehran. Driving simulators were used to check the drivers' performances. The main scenario was driving on a freeway at an average speed of 50 km/h, when pedestrians suddenly appeared at a distance of 40 m and the drivers had to brake immediately after noticing the pedestrian. The time interval between the emergence of the pedestrian and stepping on the brake pedal was continuously recorded as the reaction time and the amount of vehicle deviation from the center of the road as the lateral deviation of the vehicle. The drivers' mental workload was recorded after the simulated driving test, using the verbal online subjective opinion scale. Results: The elderly drivers had the highest mean reaction time, 963.8 ms, and there was no significant difference between the mean reaction time for youth and middle-aged drivers (858.3 ms vs. 860 ms). Elderly drivers showed high lateral deviation, 0.69 m, and mental workload, 6.19, whereas youth drivers had the lowest lateral deviation (0.55 m) and mental workload (3.60). MANOVA revealed a significant effect of age (Pillai's trace, V = 0.55, P < 0.001). Univariate ANOVA showed that age significantly affected the lateral deviation (P < 0.001) and mental workload (P < 0.001), but reaction time wa not age dependent (P = 0.101). Poisson regression revealed no significant effect for age on the number of collisions (P = 0.357). Conclusion: Based on the variables under study, driving performance of the elderly group was poor as compared to that of the middle-aged and young ones. Old drivers were subjected to greater mental workload when responding to the stimulus of the driving environment.

The aim of this study was to compare and evaluate the production of exhaust emissions from a vehicle with a petrol engine with the Euro 4 emission standard and powered by petrol and LPG (liquefied petroleum gas). The paper presents new possibilities for monitoring exhaust emissions using an exhaust gas analyzer. At the same time, it points out the topicality and significance of the issue in the monitored area. It examines the impact of a change in fuel on emissions. This change is monitored in various areas of vehicle operation. Measurements were performed during real operation, which means that the results are fully usable and applicable in practice. The driving simulation as well as the test conditions correspond to the RDE (Real Driving Emissions) test standard. A commercially available car was first selected to perform the tests, which was first measured in the original configuration (petrol drive). Based on real-time RDE driving tests, it is possible to determine the number of exhaust emissions. Subsequently, the same measurements were performed with the same vehicle, but the vehicle’s propulsion was changed to LPG. The vehicle was equipped with an additional system that allowed the vehicle to be powered by LPG. The results from the individual driving tests allowed the determination of the exhaust emissions. Emissions of CO (carbon monoxide), CO2 (carbon dioxide), HC (hydrocarbons), and NOx (nitrogen oxides) were monitored as a matter of priority. Through the driving tests, it was found that the gasoline combustion produced higher CO (1.926 g/km) and CO2 (217.693 g/km) emissions compared to the combustion of liquefied gas, where the concentration of the CO emissions was 1.892 g/km and that of the CO2 emissions was 213.966 g/km. In contrast, the HC (0.00397 g/km) and NOx (0.03107 g/km) emissions were lower when petrol was burned. During LPG combustion, the HC emissions reached 0.00430 g/km, and the NOx emissions reached 0.05134 g/km. At the end of the research, the authors compared the emissions determined by real driving (in g/km) with the emission values produced by the emission standard EURO 4 and the certificate of conformity (COC). Practical measurements showed that the vehicle produced excessive amounts of CO when burning gasoline. This production is 0.926 g/km higher and 0.892 g/km higher when burning LPG compared to the limit set by the Euro 4 Emission Standard. The difference is even greater than the limit value stated in the COC document. For other substances, the monitored values are in the norm and are even far below the permitted value

Current research on eco-driving has focused on solving an optimal control problem (OCP) to generate a speed profile to be tracked by drivers. The optimization variables are often chosen as low level control actions such as engine torque and gear positions, which leads to complex mixed-integer problems. In this brief, we propose an eco-driving assistance system (EDAS) to improve current EDAS in two aspects. First, an adviser with simplified dynamical model is designed using model predictive control (MPC) to provide not only a speed profile but also real-time high level driving mode advice such as cruising and coasting. Second, drivers' reaction delay to follow the driving mode advice is explicitly compensated, which mitigates the effect of such delay on fuel savings. The time delay is converted to a spatial parameter in the MPC to provide driving advice in advance. To demonstrate the efficiency and effectiveness of the proposed EDAS, a numerical study and a simulation using measured data from a real-life driving test is conducted. Comparisons are made between the proposed EDAS and an eco-driving controller considering both high and low level control inputs without driver's reaction delay.