How do the recognizability and driving styles of automated vehicles affect human drivers’ gap acceptance at T- Intersections?

Future traffic will be composed of both human-driven vehicles (HDVs) and automated vehicles (AVs). To accurately predict the performance of mixed traffic, an important aspect is describing HDV behavior when interacting with AVs. A few exploratory studies show that HDVs change their behavior when interacting with AVs, being influenced by factors such as recognizability and driving style of AVs. Unsignalized priority intersections can significantly affect traffic flow efficiency and safety of the road network. To understand HDV behavior in mixed traffic at unsignalized priority T-intersections, a driving simulator experiment was set up in which 95 drivers took part in it. The route in the driving simulator included three T-intersections where the drivers had to give priority to traffic on the major road. The participants drove different scenarios which varied in whether the AVs were recognizable or not, and in their driving style (Aggressive or Defensive). The results showed that in mixed traffic having recognizable aggressive AVs, drivers accepted significantly larger gaps (and had larger critical gaps) when merging in front of AVs as compared to mixed traffic having either recognizable defensive AVs or recognizable mixed AVs (composed of both aggressive and defensive). This was not the case when merging in front of an HDV in the same scenarios. Drivers had significantly smaller critical gaps when driving in traffic having non-recognizable aggressive AVs compared to non-recognizable defensive AVs. The findings suggest that human drivers change their gap acceptance behavior in mixed traffic depending on the combined effect of recognizability and driving style of AVs, including accepting shorter gaps in front of non-recognizable aggressive AVs and changing their original driving behavior. This could have implications for traffic efficiency and safety at such priority intersections. Decision makers must carefully consider such behavioral adaptations before implementing any policy changes related to AVs and the infrastructure.     

Speed reductions and judgments of travel time loss: Biases and debiasing

Priority decisions concerning maintenance or reconstruction of roads are made with the aim of road improvements with as little traffic disturbance and time loss as possible. However, it cannot be avoided that speed will be reduced and travel time increased during the time of construction. The present study shows how intuitive judgments of travel time losses are biased in a way similar to the times saving bias (Svenson, 2008), but not perfectly corresponding to that bias. This means that when speed is decreased from a slow speed <50 km/h, the time loss is underestimated and when speed is decreased from a high speed >80 km/h it is overestimated. Also, drivers, politicians and policy makers who do not make exact calculations are likely victims of the time loss bias. The time loss bias was weakened but not eliminated by a debiasing instruction including mathematical computations of travel times. When driving speed restrictions are implemented, in particular on fast motorways, it is necessary to consider and counteract the time loss bias and inform the public. This can be done, for example, in communications about travel time facts, by information in driver training and by mounting temporary road signs informing about the average travel time prolongation due to a road work.     

Beyond “accident-proneness”: Using Five-Factor Model prototypes to predict driving behavior

Research on the association between personality traits and driving behavior as well as accident involvement has produced mixed results. In order to obtain empirical evidence for a consistent relation between personality and driving behavior, a prototype approach based on the Five-Factor Model (FFM) was applied. In two samples of drivers, cluster analyses of FFM scales revealed three prototypes that replicate previous ones. The prototypes, labeled Resilient, Overcontrolled, and Undercontrolled, were found to differ reliably in accident involvement and driving behavior, indicating differential accident liability. Undercontrollers are the most problematic drivers followed by Resilients, whereas Overcontrollers most consistently obey traffic rules and drive accordingly.     

Boredom: Practical consequences and a theory

Boredom is defined as a unique psychophysiological state possessing interrelated and inseparable emotional, motivational, perceptual and cognitive concomitants. Practical consequences of boredom are reviewed, including diminished performance efficiency, general life satisfaction and health. Finally, the outline of a theoretical model is presented.     

Does traffic congestion increase driver aggression?

In his recent article about aggressive driving, David Shinar proposed that the classical frustration-aggression hypothesis (Dollard, J., Doob, L., Miller, N., Mowrer, O. & Sears, R. (1939). Frustration and aggression. New Haven, CN: Yale University Press) provides a useful tool for understanding driver aggression (Shinar, D. (1998). Aggressive driving: the contribution of the drivers and situation. Transportation Research Part F, 1, 137–160). According to Shinar's (1998) application of the frustration–aggression hypothesis, driver aggression is caused by frustration because of traffic congestion and delays. In the present study, the relationships between exposure to congestion (rush-hour driving) and aggressive violations (DBQ) were investigated in Great Britain, Finland and the Netherlands. Partial correlations showed that the frequency of rush-hour driving did not correlate statistically significantly with driver aggression. Correlations between driving during rush-hour and aggression did not differ in magnitude from those between driving on country roads and aggressive violations. In addition, correlations between exposure to congestion and aggressive violations in countries with large number of vehicles per road kilometre (UK, Netherlands) were not higher than those in a sparsely populated country (Finland). These results from three countries suggest that congestion does not increase driver aggression as directly as suggested by Shinar (1998).     

Evaluating the impact of adaptive signal control technology on driver stress and behavior using real-world experimental data

While the operational and crash reduction benefits of adaptive signal control technology (ASCT) have long been investigated, the impact of this technology on driver behavior and stress is still uncertain. This study evaluated the impact of ASCT on driver behavior and stress in a real-world environment. Participants travelled through two arterial corridors, one equipped with ASCT and the other having traditional time-of-day coordinated signals. Driver stress was measured using a heart rate detector and a perceived stress scale while driver behavior was examined using vehicular trajectory data. Overall, driving behavior improved on the ASCT as compared to the non-ASCT corridor, as indicated by higher speeds and a fewer number of stops on the ASCT corridor relative to the non-ASCT corridor. Repeated measures ANOVA showed a statistically significant reduction in driver heart rate by −10 beats per minute over the ASCT corridor. A similar trend was observed for drivers’ perceived stress, analyzed by Wilcoxon sign ranked test. Driving behavior also showed significant improvement with ASCT presence, and speed was found to be negatively correlated with stress. Furthermore, the participants’ speed was controlled by the two systems i.e. ASCT and non-ASCT as expected. This study provides a significant proof of concept that ASCT can create positive improvements in driver stress and behavior that can be further investigated in the future.     

How accurate are memories of traffic accidents? Increased false memory levels among motorcyclists when confronted with accident-related word lists

Previous studies have found that false memories increase when people receive stimuli which is related to their knowledge base. In the current set of four experiments, we examined how accident experience affected false memory production among motorcyclists using different types of false memory word lists. Specifically, Experiments 1, 2, and 3 were conducted involving motorcyclists with and without accident experience, whereas Study 4 was conducted on non-motorcyclists without accident experience. In all experiments, participants were given associatively-related word lists known to foster false memory creation. Different types of word lists were used consisting of accident-related words, emotionally-negative words, and neutral words. Levels of false memory were measured using recall and recognition tests. We found consistent results in Experiments 1, 2, and 3 in which among motorcyclists, accident-related words produced higher levels of false memory than emotionally-negative and neutral words. This pattern was not observed in Experiment 4 where non-motorcyclists were involved. Our results shed light on the role of previous experience on false memory formation. One implication could be that the police should be careful with reports of motorcyclists' experiences about their accidents as motorcyclists may spontaneously come up with false, but related details concerning these experiences.     

What constitutes traffic event severity in terms of human danger perception?

This study focuses on the severity gradation of non-collision events. Earlier theoretical work has suggested that a proper severity measure for an event should reflect the risk of personal injury, which is often split into two components, including the risk of a collision and the potential consequences had the collision taken place. While a great number of severity measures have been suggested, most of them fail to address both components, thus resulting in counter-intuitive event gradations and inconclusive outcomes in validation studies. Conversely, it has been shown that human observers often show very good agreement when given a task to rank traffic situations by their severity or level of danger. The aim of this study is to investigate in depth how human judgements of the severity of traffic situations can be expressed by means of objective safety indicators. In this study, a set of video-recorded traffic situations, in which a cyclist passes straight through an intersection while a left or right-turning motor vehicle crosses the cyclist’s path, were analysed. Binary logistic regression was used to develop models assessing the most important traffic severity indicators associated with human feelings of danger. The results showed that the initial conditions of a traffic event, defined as a start of an evasive action, contain the most important information for explaining its severity. Moreover, variables related to both proximity and collision consequences are important and should be integrated into severity measures.     

Psychometric properties of driver self-image inventory for Chinese drivers and its associations with personality and driving style

This study aimed to adapt the Driver Self-image Inventory (DSII, Taubman-Ben-Ari, 2008) to Chinese drivers and examine its relationship with personality traits and driving style. Six hundred forty drivers aged 18–55 years agreed to participate in this study. Measurements included the DSII, a personality scale and a validated Chinese version of the Multidimensional Driving Style Inventory (MDSI). The results of exploratory factor analysis (n = 302) and confirmatory factor analysis (n = 305) yielded a three-factor scale with satisfactory reliability. Significant gender differences were found on the DSII factors, with male drivers scoring higher on the impulsive driver factor and lower on the cautious driver factor than female drivers. The validity of the DSII was supported by significant associations between the DSII factors and personality traits, driving style and number of traffic violations and accidents in the previous 12 months. Moreover, drivers with traffic accidents scored significantly lower on the cautious driver factor and higher on the impulsive driver factor than those without traffic accidents. These findings indicate that the reliability and validity of the Chinese version of the DSII are acceptable.     

Guiding drivers towards safer driving speed: Exploiting visual dominance in speed adaptation

Inappropriate speed is a main cause of accidents. Drivers are often unaware of potential risks due to inadequate speed. To prevent dangerous situations, we need to understand perceptual factors influencing human speed perception. Due to the prominent role of vision in driving, we examined the effect of visuo-spatial stimuli on speed based on the optic flow. While developing an adaptive infrastructure measure to reduce speed, we conducted two consecutive studies, a driving simulator study and a field test to investigate findings further. In both studies, we placed lights on two sides of a highway exit and either illuminated them statically or activated them in a way that they appeared to be moving towards the driver. We expected drivers to slow down more when seeing static light stimuli compared to a baseline without lights. We also expected drivers to decrease speed more in conditions with oncoming lights compared to a baseline, and to static lights, due to distorted speed perception. The first study in a static driving simulator revealed no difference between conditions. In the field test, both static lights and lights moving towards the driver led to a speed reduction compared to a baseline but did not differ from one another. Lights in general led to lower driving speed, potentially due to their warning character, but we found no difference between the light conditions, suggesting that the effect might not be based on the optic flow. Future research should investigate the relationship between driven and perceived speed more closely.