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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]

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]

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]

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]

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]

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]

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]

Highlights: [•] Understanding simulator capability and comparing options is important. [•] For that reason a driving simulator classification method arises. [•] In this research study, a classification method for driving simulators is aimed. [•] In the proposed method, the driving simulator general characteristics were considered. [•] The criteria were adapted from helicopter flight simulation training device standards. [Copyright &y& Elsevier]

Simulators offer an alternative medium to investigate issues with driving and to conduct vehicle control and situation awareness tests. To ensure transferability of research findings, drivers' behaviour and reactions within vehicle simulators should be comparable to those observed on real roads. However, various questions relating to simulator validity have been raised, often focused on physical dimensions of fidelity (does the simulator look and feel like the real-world?), rather than psycho-physiological properties (does it replicate the relevant emotional and cognitive factors?). To address whether drivers in simulators behave and emotionally express themselves in response to perceived hazards as would be expected in the real-world, 24 drivers - 12 in a low fidelity and 12 in medium-fidelity simulator - drove on a rural road and encountered an emergency braking event (a vehicle pulling out from a parked position) towards the end of the drive. Drivers' subjective responses were measured through an Emotion Questionnaire, nonverbal expressions (facial, vocal, gestures and postural movements) of emotion response and physiological measures of Heart-Rate (HR), Respiration-Rate (RR) and Breathing-Wave Amplitude (BWA). Drivers' subjective responses to the emotion items showed higher ratings on the negative emotions of anger, fear, disgust, sadness and surprise during the emergency braking event (the hazard phase) compared to the non-hazard phase. Similar results were shown for drivers' HR, RR and BWA measures. Furthermore, drivers exhibited realistic reactions and emotional gestures e.g. withdrawal of the head back towards the vehicle head restraint, and tensing of arms as if bracing for an impact. Facial expressions revealed a continuity of negative and adaptive emotional expressions. Results also showed comparability across measures taken from both simulators and the literature for equivalent on-road situations. [ABSTRACT FROM AUTHOR]

Abstract: Background: Cannabis and alcohol are the most popular drugs amongst recreational users, and most prevalent in injured and deceased drivers. Clarification of the interactive effects of these drugs upon driving behaviour is critical for reducing drug-related road deaths. Objectives: The current study had two objectives, to examine the effects of cannabis and alcohol on driving performance, and identify if any differences between the effects of cannabis and alcohol on driving performance exist between regular cannabis users and non-regular cannabis users. Methods: The project involved 80 participants (49 male, 31 female) who were abstinent recreational users of alcohol and marijuana. They participated in six experimental sessions that involved the consumption of cannabis cigarettes containing no THC, 1.8% THC or 3% THC together with the consumption of alcohol to obtain either 0% BAC, 0.03% BAC or 0.05% BAC. The six sessions were double-blind, counter-balanced, placebo-controlled and medically supervised. Forty participants were allocated to the cannabis with low alcohol (0.03% BAC) group, and 40 participants were allocated to the cannabis with high alcohol (0.05% BAC) group. Driving simulator performance was assessed at 20min post-drug administration and blood samples were taken before and after driving. Results: Driving simulator performance was more impaired in the THC and alcohol combined conditions. Consistent with past research, the level of THC detected in blood is higher when THC is consumed with alcohol, than when cannabis is consumed alone, and regular cannabis users returned higher levels of THC in plasma than non-regular users. Generally, regular cannabis users displayed more driving errors than non-regular cannabis users. [Copyright &y& Elsevier]

Visualization of highway traffic environments in virtual reality plays a key role on fidelity of simulation and validity of driving behaviors in driving simulator studies. This paper describes a procedure to replicate a signalized intersection with many complex features into a driving simulator's 3-D databases through building a graphical visual database, constructing a road motion database, and creating simulated traffic. The validity of the visualization was assessed via the comparison of the drivers' speeds in the simulator and the speed data at the real intersection. It was found that both speed data follow normal distributions and have equal means for each intersection approach; however, that the speeds measured in the driving simulator have a larger variability than those measured in the field. The users' subjective evaluation results indicated that 92% subjects could recognize the simulated intersection in the driving simulator experiment. Therefore, the strategy of geo-specific environment modeling would be useful for studying driving behaviors in virtual environments. [ABSTRACT FROM AUTHOR]

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 μ V 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". [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. [ABSTRACT FROM AUTHOR]