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The paper presents a proposed methodology for designing and planning research on driver behavior at pedestrian crossings using whole-vehicle simulators. It was assumed that dedicated research should be conducted in specific problem contexts. The problems identified were the identification of hazards and the risk of accidents involving vulnerable road users. The purpose of this identification is to determine the determinants of safety at pedestrian crossings, which should constitute guidance when designing new solutions for safety support systems at pedestrian crossings. A number of hazard factors were identified; divided into categories, including types of crossings, location, and surroundings; behavior of vulnerable road users; and attention (focus) distractors, both inside and outside the vehicle. A method for defining and selecting research scenarios and selecting a group of research participants was proposed. Additionally, it was proposed to conduct repeatable test scenarios for different driving speeds and different weather conditions. With respect to the publications on this topic, this work focuses on the process of designing and planning dedicated simulation studies, which may provide a source of guidance and good practices for other researchers. This is an example of how interdisciplinary research involving human factors, traffic organization, and ITS systems can be planned and implemented. [ABSTRACT FROM AUTHOR]

There is a wide range of different driving simulator systems, which vary greatly in terms of cost as well as system characteristics. Higher fidelity simulators are often assumed to produce more valid results. While there are many studies that have compared simulator driving to real-world driving, to date there has been no large study comparing different simulator systems to each other and to real-world driving. Aiming at closing this gap, the present research offers an extensive comparison of six different driving simulators with the results of a previous real-world study. In terms of absolute validity, most of the simulators provided good results for distance to a vehicle in front and standard deviation of the lateral position, whereas the results for driving speed were inconsistent. Simulator fidelity appears to positively affect distance perception, although differences between higher fidelity simulators were generally small, and no real-world comparison data were available here. With respect to simulator sickness, a clear advantage of using a high fidelity simulator was found, while the effect size depended on the use case. In summary, the results suggest that different simulators are suitable for different use cases to different degrees, and the differences between simulators are not always related to higher simulator fidelity. The presented study can serve as a basis for understanding simulator requirements associated with different use cases. • Comparative validation study with N = 267 subjects. • Six driving simulators and five scenarios, including real-world comparison data. • Less simulator sickness in high-fidelity driving simulators. • No clear relationship of simulator fidelity and valid driving behavior. [ABSTRACT FROM AUTHOR]

Abstract Background Patients are recommended not to drive for at least the first 24 h after endoscopy with propofol sedation. However, the evidence underlying these recommendations is scarce. We hypothesized that after endoscopic procedures performed under propofol sedation, the subject’s driving ability was restored in less than 24 h. Methods We prospectively enrolled thirty patients between 20 and 70 years possessing a legitimate driver’s license scheduled for endoscopy at our hospital. The sample chosen was a convenience sample. Gastroscopy or colonoscopy was performed with propofol sedation. Before and after endoscopy, the investigator drove the subjects to the laboratory to assess their driving skills using a driving simulation system, which employs 3 driving scenarios designed by professional transportation researchers. The blood propofol concentration was estimated before endoscopy, and 2 and 4 h after endoscopy. The primary outcome was the time required for subjects to recover their driving ability after propofol sedation. The secondary outcome was the blood propofol concentration before and after endoscopic procedures under propofol anesthesia. Results Thirty volunteers participated in the study and 18 of them completed all the interventions. In the low-risk S-curve scene, the mean acceleration, lane deviation, and number of deviations from the path at baseline (0.016 cm/s2, 42.50 cm, and 0.83, respectively) were significantly less than that at post-2 h (0.029 cm/s2, P = 0.001; 53.80 cm, P = 0.014; 2.06, P = 0.022). In the moderate-(overtaking) and high-risk (emergency collision avoidance) scenes, the tested parameters at baseline and post-2 h were statistically comparable. In the low-, moderate-, and high-risk scenes the tested parameters at baseline and post-4 h were statistically comparable. The total range of propofol was 120-280 mg.The mean blood concentration of propofol at post-2 h was 0.81 ± 0.40 µg/mL, and at post-4 h was below the limit of detection. Conclusion After endoscopy performed under propofol sedation, subjects’ driving abilities were completely restored at 4 h when tested on a simulator.

The paper presents a proposed methodology for designing and planning research on driver behavior at pedestrian crossings using whole-vehicle simulators. It was assumed that dedicated research should be conducted in specific problem contexts. The problems identified were the identification of hazards and the risk of accidents involving vulnerable road users. The purpose of this identification is to determine the determinants of safety at pedestrian crossings, which should constitute guidance when designing new solutions for safety support systems at pedestrian crossings. A number of hazard factors were identified; divided into categories, including types of crossings, location, and surroundings; behavior of vulnerable road users; and attention (focus) distractors, both inside and outside the vehicle. A method for defining and selecting research scenarios and selecting a group of research participants was proposed. Additionally, it was proposed to conduct repeatable test scenarios for different driving speeds and different weather conditions. With respect to the publications on this topic, this work focuses on the process of designing and planning dedicated simulation studies, which may provide a source of guidance and good practices for other researchers. This is an example of how interdisciplinary research involving human factors, traffic organization, and ITS systems can be planned and implemented.

Drivers know that smartphones distract. Trying to limit distraction, drivers can use handsfree devices, where they onlybriefly glance at the smartphone. However, the cognitive cost of switching tasks from driving to communicating back todriving adds an underappreciated, potentially long period to the total distraction time. This project measured the effectsof handsfree smartphones on driving behaviors by engaging ninety-seven 21- to 78-year-old individuals whoselfidentified as active drivers and smartphone users in a simulated driving scenario that included smartphonedistractions. Peripheral-cue and car-following tasks were used to assess driving behavior, along with synchronized eyetracking. This research found that simulated driving performance drops to dangerous levels after smartphone distractionfor all ages and for both voice and texting. The participants swerved for 15.1 seconds after a voice distraction and for alonger 20.6 seconds after a text distraction. Participants from the 71+ age group missed seeing about 50% of peripheralcues within 4 seconds of the distraction. Coherence with the lead car during following task dropped from 0.54 to 0.045during distraction, and seven participants rear-ended the lead car.

Drivers know that smartphones distract. Trying to limit distraction, drivers can use handsfree devices, where they onlybriefly glance at the smartphone. However, the cognitive cost of switching tasks from driving to communicating back todriving adds an underappreciated, potentially long period to the total distraction time. This project measured the effectsof handsfree smartphones on driving behaviors by engaging ninety-seven 21- to 78-year-old individuals whoselfidentified as active drivers and smartphone users in a simulated driving scenario that included smartphonedistractions. Peripheral-cue and car-following tasks were used to assess driving behavior, along with synchronized eyetracking. This research found that simulated driving performance drops to dangerous levels after smartphone distractionfor all ages and for both voice and texting. The participants swerved for 15.1 seconds after a voice distraction and for alonger 20.6 seconds after a text distraction. Participants from the 71+ age group missed seeing about 50% of peripheralcues within 4 seconds of the distraction. Coherence with the lead car during following task dropped from 0.54 to 0.045during distraction, and seven participants rear-ended the lead car.

Background: Patients are recommended not to drive for at least the first 24 h after endoscopy with propofol sedation. However, the evidence underlying these recommendations is scarce. We hypothesized that after endoscopic procedures performed under propofol sedation, the subject's driving ability was restored in less than 24 h. Methods: We prospectively enrolled thirty patients between 20 and 70 years possessing a legitimate driver's license scheduled for endoscopy at our hospital. The sample chosen was a convenience sample. Gastroscopy or colonoscopy was performed with propofol sedation. Before and after endoscopy, the investigator drove the subjects to the laboratory to assess their driving skills using a driving simulation system, which employs 3 driving scenarios designed by professional transportation researchers. The blood propofol concentration was estimated before endoscopy, and 2 and 4 h after endoscopy. The primary outcome was the time required for subjects to recover their driving ability after propofol sedation. The secondary outcome was the blood propofol concentration before and after endoscopic procedures under propofol anesthesia. Results: Thirty volunteers participated in the study and 18 of them completed all the interventions. In the low-risk S-curve scene, the mean acceleration, lane deviation, and number of deviations from the path at baseline (0.016 cm/s2, 42.50 cm, and 0.83, respectively) were significantly less than that at post-2 h (0.029 cm/s2, P = 0.001; 53.80 cm, P = 0.014; 2.06, P = 0.022). In the moderate-(overtaking) and high-risk (emergency collision avoidance) scenes, the tested parameters at baseline and post-2 h were statistically comparable. In the low-, moderate-, and high-risk scenes the tested parameters at baseline and post-4 h were statistically comparable. The total range of propofol was 120-280 mg.The mean blood concentration of propofol at post-2 h was 0.81 ± 0.40 µg/mL, and at post-4 h was below the limit of detection. Conclusion: After endoscopy performed under propofol sedation, subjects' driving abilities were completely restored at 4 h when tested on a simulator. [ABSTRACT FROM AUTHOR]

Although driving simulators could be commonly assumed as very useful technological resources for both novel and experienced drivers' instruction under risk control settings, the evidence addressing their actual effectiveness seems substantially limited. Therefore, this study aimed to analyze the existing original literature on driving simulators as a tool for driver training/instruction, considering study features, their quality, and the established degree of effectiveness of simulators for these purposes. Methods: This study covered a final number of 17 empirical studies, filtered and analyzed in the light of the PRISMA methodology for systematic reviews of the literature. Results: Among a considerably reduced set of original research studies assessing the effectiveness of driving simulators for training purposes, most sources assessing the issue provided reasonably good insights into their value for improving human-based road safety under risk control settings. On the other hand, there are common limitations which stand out, such as the use of very limited research samples, infrequent follow-up of the training outcomes, and reduced information about the limitations targeted during the simulator-based training processes. Conclusions: Despite the key shortcomings highlighted here, studies have commonly provided empirical support on the training value of simulators, as well as endorsed the need for further evaluations of their effectiveness. The data provided by the studies included in this systematic review and those to be carried out in the coming years might provide data of interest for the development and performance improvement of specific training programs using simulators for driver instruction. [ABSTRACT FROM AUTHOR]

The mobility of people with motor disabilities combined with sensory or cognitive disabilities, sometimes leads to safety issues that make independent travel impossible. In this context, teams based in Rennes in the west of France have been working together for several years to design two devices: - an power wheelchair simulator to promote learning to drive in an immersive virtual environment - a driving assistance module that can be added to an power wheelchair to pass and avoid obstacles. This transdisciplinary work was made possible by the geographical and human proximity of the scientific, technical and clinical teams in order to best meet the needs of the end users who were integrated into this co-design approach. This article describes the evolution of this work and future prospects. [ABSTRACT FROM AUTHOR]

Although driving simulators could be commonly assumed as very useful technological resources for both novel and experienced drivers’ instruction under risk control settings, the evidence addressing their actual effectiveness seems substantially limited. Therefore, this study aimed to analyze the existing original literature on driving simulators as a tool for driver training/instruction, considering study features, their quality, and the established degree of effectiveness of simulators for these purposes. Methods: This study covered a final number of 17 empirical studies, filtered and analyzed in the light of the PRISMA methodology for systematic reviews of the literature. Results: Among a considerably reduced set of original research studies assessing the effectiveness of driving simulators for training purposes, most sources assessing the issue provided reasonably good insights into their value for improving human-based road safety under risk control settings. On the other hand, there are common limitations which stand out, such as the use of very limited research samples, infrequent follow-up of the training outcomes, and reduced information about the limitations targeted during the simulator-based training processes. Conclusions: Despite the key shortcomings highlighted here, studies have commonly provided empirical support on the training value of simulators, as well as endorsed the need for further evaluations of their effectiveness. The data provided by the studies included in this systematic review and those to be carried out in the coming years might provide data of interest for the development and performance improvement of specific training programs using simulators for driver instruction.

This article evaluates the driver's reaction times in a driving simulator environment. The research focused mainly on young drivers under the age of 26, who cause many accidents. Each participating driver provided basic information later used for mathematical-statistical analysis. The main advantage of driving simulators is limitless usage. It is possible to simulate situations that would be unacceptable in real road traffic. Therefore, this study is also able to examine drunk driving. The main goal of the article is to evaluate if gender, practice, or alcohol significantly affected the reaction time of 30 drivers. We also focused on drinking before driving for a smaller number of the drivers; ten of them performed driving under the influence of alcohol. For these mathematical-statistical purposes, we used a one-sample t-test, a paired-samples t-test, an independent-sample t-test, and a correlation analysis together with the assessment of its statistical significance. [ABSTRACT FROM AUTHOR]

Objective: The aim of this study is to investigate how anticipatory driving is influenced by distraction. Background: The anticipation of future events in traffic can allow potential gains in recognition and response times. Anticipatory actions (i.e., control actions in preparation for potential traffic changes) have been found to be more prevalent among experienced drivers in simulator studies when driving was the sole task. Despite the prevalence of visual-manual distractions and their negative effects on road safety, their influence on anticipatory driving has not yet been investigated beyond hazard anticipation. Methods: A simulator experiment was conducted with 16 experienced and 16 novice drivers. Half of the participants were provided with a self-paced visual-manual secondary task presented on a dashboard display. Results: More anticipatory actions were observed among experienced drivers; experienced drivers also exhibited more efficient visual scanning behaviors as indicated by higher glance rates toward and percent times looking at cues that facilitate the anticipation of upcoming events. Regardless of experience, those with the secondary task displayed reduced anticipatory actions and paid less attention toward anticipatory cues. However, experienced drivers had lower odds of exhibiting long glances toward the secondary task compared to novices. Further, the inclusion of glance duration on anticipatory cues increased the accuracy of a model predicting anticipatory actions based on on-road glance durations. Conclusion: The results provide additional evidence to existing literature supporting the role of driving experience and distraction engagement in anticipatory driving. Application: These findings can guide the design of in-vehicle systems and guide training programs to support anticipatory driving. [ABSTRACT FROM AUTHOR]

Background: Driving cessation is difficult for persons living with cognitive decline (PLWCD) and their caregivers (CG). Physicians are often required to notify authorities of driving risks, and typically base decisions on paper-based cognitive assessments and on-road tests. This study examines experiences surrounding cessation and CG’s views regarding simulators in the process. Methods: Semi-structured virtual interviews were conducted with CGs of PLWCD from an academic memory clinic. Experiences around cessation were explored first, followed by discussions regarding the simulator. Framework analysis was applied to transcribed interviews. Results: Six females and two males, three children and five spouses participated. PLWCD viewed driving cessation negatively, often had difficulty understanding why, and believed cessation was temporary. CGs experienced relief and/or shock. Cessation negatively impacted the relationships between the PLWCD and both the physician and CG. Isolation, coping challenges and loss of independence were experienced by the PLWCD. The lives of caregivers were adversely affected, especially regarding driving burden and worsening mental health. CGs were generally supportive of simulators. Positives included: measurement of driving skills, method of testing, and providing an understanding regarding the driving suspension. Potential drawbacks included difficulty using the machine, testing anxiety and stress induced by a crash. Caregivers were concerned about: PLWCD’s disappointment of failure, requesting to retest, and reluctance to accept the decision. Conclusion: PLWCD and caregivers had negative experiences related to the driving cessation. Generally, caregivers viewed implementing driving simulators positively, in a context of a practice session and support for PLWCD’s potential reactions to the decision.

Development of a method for calculating the optimal mode of conducting a train in terms of energy saving meet the safety requirements and schedules. The method of calculation must solve the assigned tasks without significant time spent on the calculation. To implement this method of calculation was used a simplified model of the train as a controlled system. The existing mathematical and algorithmic methods for solving isoperimetric problems of finding the optimal solution in the presence of restrictions on resources were the information base for methodology development. Scientific works of domestic and foreign scientists, professional periodicals, materials of scientific and practical conferences, methodical and normative materials, currently in force on Ukrainian Railways. The results of these studies were used to create simulators on the basis of computer technology for the training of locomotive drivers. The scientific novelty of the proposed calculation method consists in applying the simplified calculations of the status of the train as a controlled system, without the use of differential equations of motion that allows to significantly increase the speed of the calculations. This, in turn, will solve the problems of finding optimal control in real time, taking into account changing conditions during the movement of the train. The practical significance of the obtained results is the use of such a calculation method that does not require significant time for its implementation and can be used as a subsystem of the on-board train control system capable of per-forming calculations taking into account changes in the current train situation.

This article evaluates the driver’s reaction times in a driving simulator environment. The research focused mainly on young drivers under the age of 26, who cause many accidents. Each participating driver provided basic information later used for mathematical-statistical analysis. The main advantage of driving simulators is limitless usage. It is possible to simulate situations that would be unacceptable in real road traffic. Therefore, this study is also able to examine drunk driving. The main goal of the article is to evaluate if gender, practice, or alcohol significantly affected the reaction time of 30 drivers. We also focused on drinking before driving for a smaller number of the drivers; ten of them performed driving under the influence of alcohol. For these mathematical-statistical purposes, we used a one-sample t-test, a paired-samples t-test, an independent-sample t-test, and a correlation analysis together with the assessment of its statistical significance.

In this paper, we designed from scratch, realized, and characterized a six-channel EEG wearable headband for the measurement of stress-related brain activity during driving. The headband transmits data over WiFi to a laptop, and the rechargeable battery life is 10 h of continuous transmission. The characterization manifested a measurement error of 6 μV in reading EEG channels, and the bandwidth was in the range [0.8, 44] Hz, while the resolution was 50 nV exploiting the oversampling technique. Thanks to the full metrological characterization presented in this paper, we provide important information regarding the accuracy of the sensor because, in the literature, commercial EEG sensors are used even if their accuracy is not provided in the manuals. We set up an experiment using the driving simulator available in our laboratory at the University of Udine; the experiment involved ten volunteers who had to drive in three scenarios: manual, autonomous vehicle with a “gentle” approach, and autonomous vehicle with an “aggressive” approach. The aim of the experiment was to assess how autonomous driving algorithms impact EEG brain activity. To our knowledge, this is the first study to compare different autonomous driving algorithms in terms of drivers’ acceptability by means of EEG signals. The obtained results demonstrated that the estimated power of beta waves (related to stress) is higher in the manual with respect to autonomous driving algorithms, either “gentle” or “aggressive”.

Highlights • Lateral specific force scaling has a time-varying effect during curve driving simulation. • The lateral specific force can be scaled down further during the curve onset than during the remainder of the curve. • The lateral specific force can be scaled down by 30% during a curve's sustained part. • The lateral specific force can be scaled up by at least 30% during a curve's sustained part. Abstract In motion simulation, motion input scaling is often applied to deal with the limited motion envelopes of motion simulators. In this research, the time-varying effects of scaling the lateral specific force up or down during passive curve driving in a car driving simulation are investigated through a simulator experiment. It is concluded that lateral specific force scaling has a time-varying effect on the perceived fidelity of a curve-driving simulation. In particular, motion scaling during a curve entry is found to be less detrimental than motion scaling during a curve's sustained part and during the curve exit. [ABSTRACT FROM AUTHOR]

Driving is an integral aspect of many modern societies, and motor vehicle safety is an important public health issue. With advances in sensor technology, more and more driving data are being collected by researchers, insurers, and automobile companies, which has increased the need and opportunities for statisticians to be involved in driving research. This report discusses several practical and statistical challenges in driver-level studies, including the process of defining meaningful driving metrics, issues related to "Big Data" aspects of driving research, and the principle of reproducible research. [ABSTRACT FROM AUTHOR]

This paper describes the design of a two channels electrodermal activity (EDA) sensor and two channels electrocardiogram (ECG) sensor. The EDA sensors acquire data on the hands and transmit them to the ECG sensor with wireless WiFi communication for increased wearability. The sensors system acquires two EDA channels to improve the removal of motion artifacts that take place if EDA is measured on individuals who need to move their hands in their activities. The ECG channels are acquired on the chest and the ECG sensor is responsible for aligning the two ECG traces with the received packets from EDA sensors; the ECG sensor sends via WiFi the aligned packets to a laptop for real time plot and data storage. The metrological characterization showed high-level performances in terms of linearity and jitter; the delays introduced by the wireless transmission from EDA to ECG sensor have been proved to be negligible for the present application.

Highlights • Driving simulators are search tools which allow the study of driver behavior in various driving scenarios, quickly, safely and economically. • This work comprised the experiment in the simulator to measure the perception of signaling within the virtual environment. Abstract Road accidents are a major societal issue for every country. The purpose of this paper is to assess and to analyze how drivers perceive traffic signals within a simulated environment direction, supported the use of an eye tracking system. Driving simulators are search tools which allow the study of driver behavior in various driving scenarios, quickly, safely and economically. This manuscript comprised the experiment in the driver simulator to measure the perception of signaling within the virtual environment in Brazil. In the experiment, 21 drivers went on a stretch of 10 km of a federal highway with 31 traffic signals, to measure the distance perception, number of fixations and the observation time signaling, as well as the variation in velocity after perception. The perception signaling within the virtual environment was similar to that reported in the literature for roads studies: on average the drivers perceived three signals, the observation time was 360 ms, the distance perception was 100 m and only the perception of velocity limits was relevant in driver behavior. [ABSTRACT FROM AUTHOR]

Abstract: Previous electroencephalography studies on anger suggest that greater left than right frontal cortical activity is associated with approach motivation of anger. Our previous study showed that greater left‐superior frontal activation of electroencephalography was associated with subjective anger during a traffic jam simulation that forced participants to maintain a slower speed than expected in elderly adults, but not in young adults. We subsequently observed similar left‐superior frontal brain activity using near‐infrared spectroscopy (NIRS) in elderly adults in the same driving situation. Using NIRS, the present study demonstrated that the elderly, but not young adults, exhibited left‐superior brain activity in the front‐dorsolateral area when they were forced to stop four times at a red traffic light in a driving simulator. Driving through the same intersections with green lights did not elicit brain activation in either age group. After four red lights, but not after four green lights, a yellow light induced left‐superior brain activity in elderly adults. This asymmetric brain activity is associated with Trail Making Test score, which reflects executive functioning. These results are discussed with regard to the inhibitory potential of aged adults. [ABSTRACT FROM AUTHOR]

In this paper, a sonification algorithm for developing the off-road models for driving simulators, is proposed. The aim of this algorithm is to overcome difficulties of heuristics identification which are best suited to a particular off-road profile built by measurements. The sonification algorithm is based on the stochastic polynomial chaos analysis suitable in solving equations with random input data. The fluctuations are generated by incomplete measurements leading to inhomogeneities of the cross-sectional curves of off-roads before and after deformation, the unstable contact between the tire and the road and the unreal distribution of contact and friction forces in the unknown contact domains. The approach is exercised on two particular problems and results compare favorably to existing analytical and numerical solutions. The sonification technique represents a useful multiscale analysis able to build a low-cost virtual reality environment with increased degrees of realism for driving simulators and higher user flexibility. [ABSTRACT FROM AUTHOR]

Modern cars are more and more frequently equipped not only with the driver assisting systems, but also with multimedia devices allowing to track the information, use the Internet or send and receive e-mails. This type of activity can cause dangerous situations by inducing various forms of distraction to the driver. In order to identify the effects caused by performing additional tasks while driving, two types of secondary tasks were proposed. The following article presents the results of a pilot study that uses two additional tasks to induce the driver with cognitive load not related to driving. At the same time, in the course of the experiment, both the driving performance and the quality of performing additional tasks were observed. The article describes selected results of the conducted study. [ABSTRACT FROM AUTHOR]

The use of dynamical driving simulators is nowadays common in many different application fields, such as driver training, vehicle development, and medical studies. Platforms with different mechanical structures have been designed, depending on the particular application and the corresponding targeted market. The effectiveness of such devices is related to their capabilities of well reproducing the driving sensations, and hence, it is crucial that the motion control strategies generate both realistic and feasible inputs to the platform, to ensure that it is kept within its limited operation space. Such strategies are called motion cueing algorithms (MCAs). In this brief, we describe an MCA based on nonlinear model predictive control (MPC) techniques, for a nine-degree of freedom simulator based on a hexapod mounted on a flat base moved by a tripod, exhibiting highly nonlinear behavior. The algorithm has been evaluated in a simulation environment. Simulation results show that the full exploitation of the working area is achieved, while managing at best all the limitations given by the particular structure and preserving the easiness and intuitiveness of tuning, which is typical of linear MPC-based approaches. [ABSTRACT FROM AUTHOR]

This article first develops an integrated traffic-driving-networking simulator (ITDNS) intended for the design and evaluation of cyber transportation systems (CTS) and connected vehicle (CV) applications. The ITDNS allows a human driver to control a subject vehicle, in a virtual environment, that is capable of communicating with other vehicles and the infrastructure with CTS messages. The challenges associated with the integration of the three simulators, and how those challenges were overcome, are discussed. As an application example, an eco-signal system, which recommends the approach speed for vehicles approaching the intersection so as to minimize fuel consumption and emissions, was implemented in the ITDNS. Test drivers were then asked to virtually drive through a signalized corridor twice, one time with the eco-signal system in place and another without the system. Thanks to the human-in-the-loop component of ITDNS, the research was able to evaluate the likely benefits of the eco-signal system, while accounting for the response of human drivers to the recommended speed profiles. Moreover, the study compared the energy consumption and emission production rates of human-controlled vehicles’ approach trajectories to the rates associated with “idealistic” trajectories that may be attainable via vehicle automation. With respect to ITDNS, the study demonstrates the unique advantages of the simulator and the broad range of applications it can address. Regarding the eco-signal application example, preliminary results demonstrate the potential of the concept to result in tangible reductions of around 9% for energy consumption, 18% for carbon monoxide, and 25% for nitrogen oxides emissions. Moreover, the application eliminated hard accelerations and decelerations maneuvers, and thus may have an additional positive safety impact. [ABSTRACT FROM AUTHOR]

Automotive manufacturers and suppliers develop new vehicle systems, such as Advanced Driver Assistance Systems (ADAS), to increase traffic safety and driving comfort. ADAS are technologies that provide drivers with essential information or take over demanding driving tasks. More complex and intelligent vehicle systems are being developed toward fully autonomous and cooperative driving. Apart from the technical development challenges, training of drivers with these complex vehicle systems represents an important concern for automotive manufacturers. This paper highlights the new evolving requirements concerning the training of drivers with future complex vehicle systems. In accordance with these requirements, a new training concept is introduced, and a prototype of a training platform is implemented for utilization in future driving schools. The developed training platform has a scalable and modular architecture so that more than one driving simulator can be networked to a common driving instructor unit. The participating driving simulators provide fully immersive visualization to the drivers by utilizing head-mounted displays instead of conventional display screens and projectors. The driving instructor unit consists of a computer with a developed software tool for training session control, monitoring, and evaluation. Moreover, the driving instructor can use a head-mounted display to participate interactively within the same virtual environment of any selected driver. A simulation model of an autonomous driving system was implemented and integrated in the participating driving simulators. Using this simulation model, training sessions were conducted with the help of a group of test drivers and professional driving instructors to prove the validity of the developed concept and show the usability of the implemented training platform.

We examined the crash avoidance behaviors of older and middle-aged drivers in reaction to six simulated challenging road events using two different driving simulator platforms. Thirty-five healthy adults aged 21–36 years old ( M = 28.9 ± 3.96) and 35 healthy adults aged 65–83 years old ( M = 72.1 ± 4.34) were tested using a mid-level simulator, and 27 adults aged 21–38 years old ( M = 28.6 ± 6.63) and 27 healthy adults aged 65–83 years old ( M = 72.7 ± 5.39) were tested on a low-cost desktop simulator. Participants completed a set of six challenging events varying in terms of the maneuvers required, avoiding space given, directional avoidance cues, and time pressure. Results indicated that older drivers showed higher crash risk when events required multiple synchronized reactions. In situations that required simultaneous use of steering and braking, older adults tended to crash significantly more frequently. As for middle-aged drivers, their crashes were attributable to faster driving speed. The same age-related driving patterns were observed across simulator platforms. Our findings support the hypothesis that older adults tend to react serially while engaging in cognitively challenging road maneuvers. [ABSTRACT FROM AUTHOR]

In driving simulation, a scenario includes definitions of the road environment, the traffic situation, simulated vehicles’ interactions with the participant’s vehicle and measurements that need to be collected. The scenarios need to be designed in such a way that the research questions to be studied can be answered, which commonly imply exposing the participant for a couple of predefined specific situations that has to be both realistic and repeatable. This article presents an integrated algorithm based on Dynamic Actor Preparation and Automated Action Planning to control autonomous simulated vehicles in the simulation in order to generate predefined situations. This algorithm is thus able to plan driving actions for autonomous vehicles based on specific tasks with relevant contextual information as well as handling longitudinal transportation of simulated vehicles based on the contextual information in an automated manner. The conducted experiment shows that the algorithm is able to guarantee repeatability under autonomous traffic flow. The presented algorithm can benefit not only the driving simulation community, but also relevant areas, such as autonomous vehicle and in-vehicle device design by providing them with an algorithm for target pursue and driving task accomplishment, which can be used to design a human-vehicle cooperation system in the coming era of autonomous driving. [ABSTRACT FROM AUTHOR]