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Introduction : In Brazil, driver aggressiveness in road traffic is a critical issue and could be an important contributing factor to the high number of traffic accidents . Because no instruments are available in Portuguese to register driving aggressiveness or driving anger in Brazil, we adapted English instruments into the Brazilian context. The aims of this study were to provide a Brazilian adaptation of the Driving Anger Expression Inventory (DAX) and to try to validate it by testing its psychometric properties and investigating its relationships with risky driving behaviors (DBQ), road accidents, driving sensation seeking, and hostility. Method: The Brazilian adaptations of the DAX, DBQ, the Driving Sensation Seeking Scale (DSSS) and the hostility Scale were administered to a sample of 512 undergraduate students (with a mean age of 23.7 years, 52.1% men). Results : Confirmatory factor analysis of the Brazilian DAX (DAX-BR) items yielded a four-factor solution with 43 items, which obtained the best goodness-of-fit to the data. Cronbach’s alpha for the DAX-BR factors ranged from 0.69 to 0.88. Other results on validity were a positive correlation (range 0.39–0.59) between the factors of the DAX-BR, DSSS, and DBQ. Conclusion : DAX-BR as the same structure as the original and is a reliable instrument for use with young drivers. Other studies should be conducted to further validate the DAX-BR in different types of populations such as older and more experienced drivers, professional drivers, and traffic regulation offenders whose driver's license has been taken away. Practical applications: This Brazilian version can be recommended for the assessment of driving anger expression in Brazil among young drivers in view of helping them driver more safely, and in particular to reduce traffic violations.

Night driving is challenging for driving simulations. At night, the constraints on Computer Graphics performance are unusually strong, as many relevant details have low contrasts and low luminance values, while the overall contrast is very high, due to light sources from road lighting and vehicle headlamps. Some level of realism is needed in terms of contrast rendering, because contrast impacts visibility and motion perception, which in turn impact the driving behavior. This is usually achieved in Computer Graphics with Tone Mapping Operators (TMOs), in order to display the computed images on a standard, Low Dynamic Range (LDR) display device. We explore in this paper the drawbacks of these operators for nighttime driving simulations, focusing on motion cues, and discuss the potential benefit of the emerging technology of High Dynamic Range (HDR) display devices. We have focused on a night-time road environment with an incoming motorcycle. Two experiments have been conducted, with 33 participants. Time-to-Collision (TTC) was considered as a proxy for motion perception. TTC estimations were collected on a HDR display and compared to degraded visual environments. The first experiment shows that the visibility of the motorcycle’s outline is the main visual cue for the TTC estimation in nighttime conditions (but this doesn’t happen with cars). It suggests that the main drawbacks of TMOs with respect to TTC estimation involves the mapping of low contrasts, which either enhances or impairs the motorcycle visibility. The second experiment explores this hypothesis and shows that enhancing the visibility of the motorcycle leads to biases in the TTC estimation, whereas removing it does not impact the TTC estimation — at the cost of other realism problems. These results suggest that motion cues at night are more realistic with a HDR Display, and that such display devices may be useful in situations where a realistic perception of hardly visible contrasts is needed.

Driving with a cataract can be dangerous, especially at night when road lighting and automotive lighting produce glare. Disability glare alters visual performance, while discomfort glare contributes to restricted mobility, with drivers avoiding driving at night. The present study was focused on the visual effects of an early cataract, and aimed at comparing three driving performance indexes at night, under glare conditions, with and without a simulated cataract. Two indexes directly referred to road safety, while a measure could be related to behavioral adaptation. Using a driving simulator, twenty-six participants were asked to drive in simulated night-time conditions, under controlled photometric conditions where the adaptation luminance and the glare level were consistent with a two-lane rural road at night with oncoming traffic. The visual effects of a bilateral cataract were simulated using goggles which were in the range of an early cataract in terms of light scattering, light transmission, visual acuity and contrast sensitivity loss. Participants were asked to avoid virtual pedestrians on the road, both with and without a simulated cataract. Three performance indexes were considered: the rate of pedestrian crashes, the distance to the pedestrian when the participant avoided the crash, and the mean speed, which allowed to control for a possible behavioral adaptation to the reduced visual performance. For a better understanding of the visual functions responsible for the degraded driving behavior, contrast sensitivity and time-to-collision performance were also measured in glare conditions. While simulated cataract resulted in slightly slower speeds, poorer driving performance was observed with the goggles than without, with more pedestrians being hit and shorter stopping distances. Time-to-collision estimates at 90 km/h were found to be predictive of stopping distances with a simulated cataract, while contrast sensitivity in glare conditions at 13 cycles per degree was found to be associated with the occurrence of a crash with cataract. The decrease in speed with a simulated cataract was real but ineffective in terms of driving safety, which suggests that the behavioral adaptation to the degraded visual performance was insufficient. The precise impact of a cataract on driving abilities remains to be further studied, to provide scientific knowledge to help practitioners determine the moment when the individuals should forego driving.

The purpose of this study was to identify the influence of situation complexity and driving experience on subjective workload and driving performance, and the less costly and the most effective strategies faced with a hazard pedestrian crossing. Four groups of young drivers (15 traditionally trained novices, 12 early-trained novices, 15 with three years of experience and 15 with a minimum of five years of experience) were randomly assigned to three situations (simple, moderately complex and very complex) including unexpected pedestrian crossings, in a driving simulator. The subjective workload was collected by the NASA-TLX questionnaire after each situation. The main results confirmed that the situation complexity and the lack of experience increased the subjective workload. Moreover, the subjective workload, the avoidance strategies and the reaction times influenced the number of collisions depending on situation complexity and driving experience. These results must be taken into account to target the prevention actions.

Recent improvements of communication technologies leads to several innovations in road vehicles energy consumption. As an example, several ecodriving applications already appeared on all smartphone application markets. Using embedded smartphone signals, such applications provide real time feedback to drivers according to their performances. However most of these applications does not take into account upcoming events such as curves, slopes or crossings to advise the driver on the best actions to undertake to lower energy consumption. Furthermore, they do not analyze data coming from vehicle sensors. In this paper, we present an android application, developed within the FP7 European project ecoDriver, which provides several innovative properties: advice according to upcoming events, a real time evaluation of the driving behavior, the analysis of past actions, an interface with OBD2 connector and some more. This paper further develops the complete architecture and links between each innovative function. Future works will concentrate on integrating image processing in this application in order to detect the possible presence of a front vehicle.

Except for Quebec, all Canadian provinces have introduced administrative laws to lower the permitted blood alcohol concentration (BAC) to .05% or .04% for driving-or having the care of-a motor vehicle. Using linear mixed effects models for longitudinal data, this study evaluates the effect of administrative BAC laws on fatal alcohol related crashes and law enforcement patterns in Canada from 1987 to 2010. Results reveal a significant decrease of 3.7% (95% C.I.: 0.9-6.5%) in fatally injured drivers with a BAC level equal or greater than .05% following the introduction of these laws. Reductions were also observed for fatally injured drivers with BAC levels greater that .08% and .15%. The introduction of administrative BAC laws led neither to significant changes in the rate of driving while impaired (DWI) incidents reported by police officers nor in the probability of being charged for DWI under the Criminal Code.

If previous research studied acceptability of partially or highly automated driving, few of them focused on fully automated driving (FAD), including the ability to master longitudinal control, lateral control and maneuvers. The present study analyzes a priori acceptability, attitudes, personality traits and intention to use a fully automated vehicle. 421 French drivers (153 males, M = 40.2 years, age range 19-73) answered an online questionnaire. 68.1% Of the sample a priori accepted FAD. Predictors of intention to use a fully automated car (R2 =.671) were mainly attitudes, contextual acceptability and interest in impaired driving (i.e. the two components of FAD acceptability), followed by driving related sensation seeking, finally gender. FAD preferred use cases were on highways, in traffic congestion and for automatic parking. Furthermore, some drivers reported interest in impaired driving misuses, despite awareness of their responsibility for both the vehicle and the driving. These results are discussed regarding previous knowledge about acceptability of advanced driving assistance systems and consequences for the use of fully automated cars.

While driving the activation of particular schemata induces an attentional focus where road users and road elements can be expected. Moreover, negative emotions can interfere with the information processing and the management of attentional resources leading to inattention. We compared two negative emotions according to the arousal dimension (exciting versus calming) rather than according to the hedonic value. Three mood states (anger, sadness and neutral) have been induced to reveal their effects on the localization of road elements. We used a modified version of the jumble scenes paradigm to provide evidence for the existence of driving-related schemata which appeared to be guiding visual search. The results reported here revealed that the three groups take more or less advantage of the use of their visual schemata to localize road elements. Sadness increased the localization error rate. Participants induced in anger, were slower to locate road elements than participants induced in sadness and in neutral mood. These results are congruent with the fact that drivers exposed to anger-could be slower to detect atypical hazards. Future studies should go deeper in the understanding of how emotional states regulate attentional capacities.

After memory impairment, one of the most common troubles of early Alzheimer's disease (AD) is the impairment of executive functioning. However, it can have major consequences on daily life, notably on the driving activity. The present study focused on one important executive function involved in driving: mental flexibility; and considered how this impairment can affect driving. Ten patients with early AD were matched with 29 healthy older drivers. All participants were given an evaluation of mental flexibility through neuropsychological tests and an experimental test developed on a static driving simulator. The experiment was divided in two conditions; one without mental flexibility and another condition with a mental flexibility demand. AD patients showed impairments in the neuropsychological tests evaluating mental flexibility. These deficits are linked to the deficits they showed in the driving simulator flexibility tests. This study contributes to the understanding of mental flexibility mechanisms and on their role in driving activity. It also confirms that the driving simulator is a suitable tool to explore cognitive disorders and driving ability.