Safety at first sight? – Manual drivers’ experience and driving behavior at first contact with Level 3 vehicles in mixed traffic on the highway

Soon, manual drivers will interact with conditionally automated vehicles (CAVs; SAE Level 3) in a mixed traffic on highways. As of yet, it is largely unclear how manual drivers will perceive and react to this new type of vehicle. In a driving simulator study with N = 51 participants aged 20 to 71 years (22 female), we examined the experience and driving behavior of manual drivers at first contact with Level 3 vehicles in four realistic driving scenarios (highway entry, overtaking, merging, introduction of a speed limit) that Level 3 vehicles may handle alone once their operational domain extends beyond driving in congested traffic. We also investigated the effect of an external marking via a visual external human–machine interface (eHMI), with participants being randomly assigned to one of three experimental groups (none, correct, incorrect marking). Participants experienced each driving scenario four times, twice with a human-driven vehicle (HDV), and twice with a CAV. After each interaction, participants rated perceived driving mode of the target vehicle as well as perceived safety and comfort. Minimum time headways between participants and target vehicles served as an indicator of safety criticality in the interactions. Results showed manual driver can distinguish CAVs from HDVs based on behavioral differences. In all driving scenarios, participants rated interactions with CAVs at least as safe as interactions with HDVs. The driving data analysis showed that manual driver interactions with CAVs were largely uncritical. However, the CAVs’ strict rule-compliance led to short time headways of following manual drivers in some cases. The eHMI used in this study neither affected the subjective ratings of the manual drivers nor their driving behavior in mixed traffic. Thus, the results do not support the use of eHMIs on the highway, at least not for the eHMI design used in this study.     

External communication of automated vehicles in mixed traffic: Addressing the right human interaction partner in multi-agent simulation

The urban traffic system is most likely to change in the next years to a mixed traffic with human drivers, vulnerable road users, and automated vehicles. In the past, the development of external communication approaches for automated vehicles focused on scenarios where an automated vehicle communicates with either a pedestrian or a human driver. However, interactions with more than one traffic partner are more realistic. Therefore, a study with 42 participants was conducted with a multi-agent simulation in which an automated vehicle interacted simultaneously with two participants, a pedestrian and a driver of a manual vehicle. In this study, two main scenarios were investigated in order to evaluate the safety and efficiency of the interactions and to determine whether the human road users feel correctly addressed. In one scenario, the pedestrian had to cross the road in front of the automated and the manual vehicle, which were approaching from different sides. In the other, the manual vehicle had to drive through a bottleneck in front of the oncoming automated vehicle, while the pedestrian had to cross the road after both vehicles passed. The communication approach of the automated vehicle consisted of implicit signals using a speed profile and lateral offset within its lane, and explicit signals using an external human–machine interface. The results of the study show that no collisions were observed in terms of safety and no significant negative effects on efficiency were measured. However, in contrast to single agent interactions, a majority of participants felt wrongly addressed in situations where the automated vehicle signals the right-of-way to the other human road user. It can be concluded that the communication approach of the automated vehicle needs to be modified in order to address certain road users more clearly.     

Using physiological and behavioral measurements in a picture-based road hazard perception experiment to classify risky and safe drivers

Every year, a considerable number of people got injured or even lost their lives in road traffic accidents. To decrease the number of fatalities and injuries, researchers are seeking methods to identify and restrain drivers before the happening of actual traffic accidents, who possess dangerous driving behaviors and may cause road traffic accidents. Such methods are usually exploited to decide drivers’ fitness to drive—an indicator to describe whether they are fit for driving. The aim of this study is to measure drivers’ physiological and behavioral responses to road hazards and to extract features from measurements for further classification of risky and safe drivers. 42 drivers participated in a picture-based road hazard perception experiment, where electroencephalography (EEG), electrodermal activity (EDA), behavioral responses to road hazards, multidimensional driving style inventory (MDSI) questionnaire, and demographic information were recorded. Results indicated that 5 specific physiological features regarding to road hazard perception showed significant differences between risky and safe drivers. Subsequently, participants were classified into risky or safe drivers group by applying only the 5 features. 81.82% and 77.78% accuracy of classification were attained for risky and safe drivers, respectively. It was evidenced that using physiological and behavioral responses to evaluate drivers’ road hazard perception might be utilized as a tool to measure drivers’ fitness to drive. For further studies, improvements to future experiment design were discussed.     

Comparative assessment of the behaviour of drivers with Mild Cognitive Impairment or Alzheimer’s disease in different road and traffic conditions

The objective of this research was the analysis of the driving performance of drivers with Mild Cognitive Impairment (MCI) or Alzheimer’s disease (AD), in different road and traffic conditions, on the basis of a driving simulator experiment. In this experiment, healthy “control” drivers, patients with MCI, and patients with AD, drove at several scenarios at the simulator, after a thorough neurological and neuropsychological assessment. The scenarios include driving in rural and urban areas in low and high traffic volumes. The driving performance of healthy and impaired drivers was analysed and compared by means of Repeated Measures General Linear Modelling techniques. A sample of 75 participants was analysed, out of which 23 were MCI patients and 14 were AD patients. Various driving performance measures were examined, including longitudinal and lateral control measures. The results suggest that the two examined cerebral diseases do affect driving performance, and there were common driving patterns for both cerebral diseases, as well as particular characteristics of specific pathologies. More specifically, cognitively impaired drivers drive at lower speeds and with larger headway compared to healthy drivers. Moreover, they appear to have difficulties in positioning the vehicle on the lane. The group of patients had difficulties in all road and traffic environments, and especially when traffic volume was high. Most importantly, both cerebral diseases appear to significantly impair reaction times at incidents. The results of this research suggest that compensatory behaviours developed by impaired drivers are not adequate to counterbalance the direct effects of these cerebral diseases on driving skills. They also demonstrate that driving impairments increase as cognitive impairments become more severe (from MCI to AD).     

Interaction between pedestrians and automated vehicles: Exploring a motion-based approach for virtual reality experiments

External human machine interfaces (eHMI) might contribute to an enhanced traffic flow and road safety by providing relevant information to surrounding road users. To quantify the effect of eHMI on traffic flow, the majority of studies required participants to indicate their crossing decision in an explicit manner, such as pressing a button. While this approach proved to be efficient, the transfer to real-world behavior is unclear. Here, we propose a more realistic, motion-based approach allowing pedestrians to actually cross the road in front of a vehicle in a virtual reality environment. Participants (N = 51) encountered simulated automated vehicles (AVs) in two scenarios. We investigated the effect of different eHMIs on traffic flow and road safety. Pedestrians’́ body movements were obtained using a motion capturing system with six sensors. Our approach was validated using a two-step procedure. First, we assessed crossing behavior and subjective safety feeling while approaching AVs with and without eHMI. Second, we tested to which extent objective crossing behavior matched self-reported safety feeling. For this purpose, we evaluated if subjective safety feeling can be reliably predicted from actual crossing behavior using a functional data analysis. The proposed motion-based approach proved a valid investigation method for eHMI designs. The results indicated that eHMIs have a beneficial effect on traffic flow and road safety. Regarding traffic flow, participants crossed the road earlier and felt significantly safer when encountering an AV with an eHMI compared to no eHMI. In addition, in situations in which only some of the AVs were equipped with an eHMI, participants’ crossing behavior and safety feeling became more conservative for encounters without eHMI, indicating higher road safety. Further, subjective safety feeling was significantly predicted from actual crossing behavior. These findings highlight that eHMIs are beneficial for pedestrians’ crossing decision, both from an objective and subjective perspective.     

The impact of a dedicated lane for connected and automated vehicles on the behaviour of drivers of manual vehicles

Connected and automated vehicles (CAVs) are expected to enhance traffic efficiency by driving at shorter time headways, and traffic safety by shorter reaction times. However, one of the main concerns regarding their deployment is the mixed traffic situation, in which CAVs and manually driven vehicles (MVs) share the same road.This study investigates the behavioural adaptation of MV drivers in car-following and lane changing behaviour when they drive next to a dedicated lane (DL) for CAVs and compares that to a mixed traffic situation. The expectation is that in a mixed traffic situation, the behavioural adaptation of MV drivers is negligible due to lower exposure time and scarce platoons, while concentrating the CAVs on one dedicated lane may cause significant behavioural adaptation of MV drivers due to a higher exposure time and conspicuity of CAV platoons.Fifty-one participants were asked to drive an MV on a 3-lane motorway in three different traffic scenarios, in a fixed-base driving simulator: (1) Base, only MVs were present in traffic, (2) Mixed, platoons of 2–3 CAVs driving on any lane and mixed with MVs, (3) DL, platoons of 2–3 CAVs driving only on a DL. The DL was recognizable by road signs and a buffer demarcation which separated the DL from the other lanes. A moderate penetration rate of 43% was assumed for CAVs.During the drives, the car following headways and the accepted merging gaps by participants were collected and used for comparisons of driving behaviour in different scenarios.Based on the results, we conclude that there is no significant difference in the driving behaviour between Base and Mixed scenarios at tested penetration rate, confirming our research expectation. However, in DL scenario, MV drivers drove closer to their leaders specially when driving on the middle lane next to the platoons and accepted shorter gaps (up to 12.7% shorter at on-ramps) in lane changing manoeuvres. Dedicating a lane to CAVs increases the density of CAV platoons on one lane and consequently their conspicuity becomes higher. As a result, MV drivers are influenced by CAV platoons on a DL and imitate their behaviour.The literature suggests that dedicating a lane to CAVs improves the traffic efficiency by providing more possibilities for platooning. This study shows that implementing such a solution will affect the driving behaviour of human drivers. This should be taken into consideration when evaluating the impacts of dedicated lanes on traffic efficiency and traffic safety.     

Aging and driving in a complex world: Exploring age differences in attentional demand while driving

We investigated the relationship between attention and road complexity in a convenience sample of older drivers. The study sought to examine the impact of age-associated changes in attention in response to situations with an elevated risk of crash. Scenarios were manipulated in terms of handling and information processing complexity. Twenty-six older drivers and 30 mid-aged drivers completed a series of 20 simulated driving scenarios incorporating either rear-end or crossing path situations. For each scenario, the complexity of the driving environment was systematically manipulated in terms of vehicle handling and information processing elements. The attentional demands of half of the scenarios were assessed by means of a peripheral detection task (PDT) as well as through a subjective measure of overall difficulty. The results indicated that when information processing demands were increased, through the addition of traffic, and buildings, all participants exhibited greater workload regardless of age. While no main effects of age were observed, older drivers did exhibit significantly longer PDT responses in the low vehicle handling condition of the crossing path scenario. The results confirm the impact of environmental complexity on attention but suggest that the PDT may not be the most appropriate means of assessing attentional demands among older drivers, particularly when the driving complexity is elevated.     

Similarities between self-reported road safety behavior of teenage drivers and their perceptions concerning road safety behavior of their parents

The study investigated 401 19-year-olds, who were licensed car drivers in Lithuania. The focus of the survey was on the self-reported road safety behaviors of teenage drivers and their perceptions of their parents’ road safety behaviors, in order to assess behavioral similarities between teenagers and their parents. The survey also investigated whether parents and teenagers discuss issues of driving safely, and whether there is an association between these conversations and driving restrictions.According to teenagers’ reporting, road safety behavior of teenage drivers and their parents often is similar: most of them break the speed limit, drive when feeling fatigued, use a cell phone when driving, and do not fasten the seat belt as a passenger in the back seat. The study indicated that there is a positive moderate correlation between road safety behaviors of teenagers and their parents, as reported by the teenagers. A majority of teenagers report that they discuss road safety factors, driving safely and driving behavior with their parents. Based on teenager reports, the parents, who discuss road safety issues with their children, are more likely to apply restrictions on teenagers’ driving.     

After you?! – Use of external human-machine interfaces in road bottleneck scenarios

In the near future, automated vehicles (AVs) will enter the urban transport system. This fact will lead to mixed traffic consisting of AVs, human car drivers and vulnerable road users. Since the AV’s passenger no longer has to monitor the driving scene, conventional communication does not exist anymore, which is essential for traffic efficiency and safety. In research, there are plenty of studies focusing on how AVs could communicate with pedestrians. One approach is to use external human-machine interfaces (eHMIs) on the AV’s surface. In contrast to the studies dealing with AV-pedestrian communication, this paper focuses on communication strategies of AVs with drivers of regular vehicles in different road bottleneck scenarios. The eHMI development and design is building on previously defined requirements and on fundamentals of human visual perception. After designing several eHMI drafts, we conducted a user survey with 29 participants resulting in the final eHMI concept. The evaluation of the evolved eHMI was conducted in a driving simulator experiment with 43 participants investigating the AV-human driver interaction at road bottlenecks. The participants were assigned either to the experimental group being faced with the eHMI or to the baseline group without explicit communication. The results show significantly shorter passing times and fewer crashes among the human drivers in the group with the eHMI. Additionally, the paper researches the aftereffects of an automation failure, where the AV first yields the right of way and then changes its strategy and insisted on priority. Experiencing the automation failure is reflected in increased passing times, reduced acceptance ratings and a lower perceived usefulness. In conclusion, especially in unregulated bottleneck scenarios flawless communication via eHMIs increases traffic efficiency and safety.     

Further evidence of associations of type a personality scores and driving-related attitudes and behaviors

The present study examined the effects of Type A personality on specific self-reported driving attitudes and behaviors when operating a motor vehicle. 102 undergraduate students completed the student version of the Jenkins Activity Survey (Form T) and several questionnaires asking participants about their driving history, driving attitudes, and driving behaviors. When the full range of Type A scores were examined, Type A personality was significantly related to more traffic accidents, greater frequency of breaking traffic laws, higher impatience when driving, more displays of aggression on the road, and engaging in more risky driving behaviors (rs<.17). When extreme Type A and Type B scores were compared, Type A drivers reported being involved in significantly more motor vehicle accidents and reported displaying more aggression on the road. Further research should examine actual behavioral data using more diverse samples to validate the results.     

Anger-congruent behaviour transfers across driving situations

Anger and aggression on the road may sometimes appear unprovoked and unrelated to current driving circumstances. It is unclear whether such anger and aggression arises because of events prior to those circumstances in which anger is experienced and aggression is exhibited. In this study, time pressure and enforced following of a slowly moving vehicle were used to increase drivers’ anger in order to assess whether affect and behaviour during a subsequent, non-provocative, drive would change accordingly. Ninety-six drivers drove twice in a simulated urban environment. During the first drive, oncoming traffic and a slowly moving lead vehicle required that half of the drivers travelled far slower than they would choose. During the second drive, drivers again followed slower vehicles and were required to respond to traffic events not encountered in the manipulation drive. Mood (Profile of Mood States) was assessed before and after each drive, and anger evaluations, arousal (heart rate) and behaviour (speed, lane position and collisions) were measured during drives. Anger increased and both mood and driving behaviour deteriorated in drivers exposed to slower lead vehicles, compared with control group drivers. These behavioural differences of speed and lane positioning carried over into the subsequent drive even to driving situations unlike those where provocation had previously occurred. Drivers who had previously been impeded later approached hazards with less caution, and attempted more dangerous overtaking manoeuvres. It is concluded that sometimes dangerous driving may result from anger provoked by circumstances other than those in which the behaviour is exhibited.     

Perceptual training to increase drivers’ ability to spot motorcycles at T-junctions

Motorcyclists too often collide with other road users who pull out of side roads in front of them. These other road users typically report making all the necessary visual checks, despite failing to see the approaching motorcycle. These Look But Fail To See errors appear to be attenuated in road users who themselves have motorcycling experience, suggesting that motorcycle exposure may lower thresholds for spotting these vulnerable road users through natural perceptual learning. This raises the possibility that perceptual training could improve car drivers’ abilities to spot motorcycles. Two experiments are reported. The first experiment demonstrated that a T-junction task, requiring participants to detect an approaching vehicle in briefly displayed images, was sensitive to participants’ motorcycle experience, with dual drivers (who both ride motorcycles and drive cars) performing better than average car drivers. Following this, a second experiment split the car drivers into 2 groups. One group undertook a Pelmanism task requiring participants to match pairs of motorcycles, while the control group had to match pairs of fruit. When the two groups were re-tested on the T-junction task, the group who had undergone perceptual training for motorcycles via the Pelmanism task, were better able to identify approaching motorcycles, but not approaching cars. The results suggest that gamification of perceptual training for motorcycle detection provides a novel opportunity to improve driver safety.     

Approaching intersections: Gaze behavior of drivers depending on traffic,intersection type,driving maneuver,and secondary task involvement

Urban intersections are hotspots for crashes because they provide a location for several traffic streams and types of road users to cross. A main cause of crashes is the misinformation of drivers as they fail to sense relevant visual information. We aimed to analyze the gaze behavior of car drivers in a variety of intersection scenarios, bringing together the partial findings of previous research, and examine the interdependencies of the contributing factors to provide a database for driver modeling. In a driving simulator study with 59 participants, we varied intersection scenarios regarding drivers’ right of way (yield sign, green traffic light), intersection type (T junction, X intersection), surrounding traffic (none, irrelevant, relevant), and intended driving maneuver (left turn, right turn, going straight). A total of 25 intersection scenarios were presented in a within-subjects design to a control group and a group with a cognitive load task (counting back in numbers of two). Fixations were coded regarding defined areas of interest in the field of view and separated according to three segments of the intersection approach: 75–50 m, 50–25 m, and 25–0 m before entering the intersection. The results show that the effect of surrounding traffic, secondary task engagement, and the intended driving maneuver changed dramatically depending on the right of way of the driver. Surrounding traffic primarily affected gaze behavior in scenarios of ceding the right of way close to the intersection entry. The cognitive load task increased fixations on the road center especially in situations where the driver had the right of way, but less in situations of ceding the right of way. Interactions with the type of intersection were only apparent for different driving maneuvers. This study provides a detailed and comprehensive picture of drivers’ attentional processes when approaching intersections which is relevant for understanding and modeling of driver behavior in urban traffic.     

Predicting pedestrians’ intention to cross the road in front of automated vehicles in risky situations

Due to the absence of a human driver, the introduction of fully automated vehicles (FAVs) may bring new safety challenges to the traffic system, especially when FAVs interact with vulnerable road users such as pedestrians. To ensure safer interactions between pedestrians and FAVs, this questionnaire-based study aims to understand Australian pedestrians’ intention to engage in risky road-crossing behaviors when they interact with FAVs vs. human-driven vehicles (HDVs). A 2 × 2 between-subject design was utilized, in which two risky road-crossing scenarios were designed and took into account the vehicle type (FAV vs. HDV) and vehicle speed (30 km/h vs. 50 km/h). A total of 493 participants (aged 18–77) were randomly assigned to one of the four experimental conditions and completed an online questionnaire based on the extended Theory of Planned Behavior (TPB). This questionnaire measured pedestrians’ intentions to cross the road in the assigned scenarios as well as the motivational factors behind these intentions in terms of attitude, subjective norm, perceived behavioral control, perceived risk and trust in the vehicle. The results show that pedestrians had significantly higher intentions to cross the road in front of approaching FAVs than HDVs. Participants also reported a lower risk perception of crossing in front of FAVs and greater trust in this type of vehicle. Attitude, subjective norm, and perceived behavioral control were significant predictors of intentions to engage in risky road-crossing behavior. Findings of this study provide important implications for the development and implementation of FAVs in the future road transport system.     

From anticipation to behavioral intention: Insights into human processing of multiple retrieval cues in road traffic

Anticipation in road traffic enables safer and more comfortable driving. Anticipatory driving is achieved through effective retrieval of prior driving-relevant knowledge using mental models and appropriate cues. Knowing when and which retrieval cues have a critical impact on the anticipation process and how information compatibility affects anticipation can be the basis for supporting people in anticipating and appropriate behavior in road traffic.For generating in-depth insights into the processing of retrieval cues, a video-based experimental study was conducted combining specific compatible and incompatible retrieval cues in urban driving scenarios. From a driver's perspective, participants were asked to anticipate in a two-step approach (measuring low and high certainty anticipation) whether a vehicle ahead would enter their lane or turn onto another street due to a lane blockage ahead. Further, they choose their preferred behavioral intention (accelerate, decelerate or maintain speed). In general, drivers strived for coherent situation representation, and in this process, multiple retrieval cues influenced anticipation in different ways. Participants were more likely to be consistent in their anticipation response. That is, they tend to follow their first intention (equivalent low and high certainty anticipation for either lane change or turn) even in the presence of incompatible stimuli. Inconsistent compared to consistent anticipation responses, however, led to reduced subjective confidence, and in part to increased criticality. Not only anticipation but also intended behavior was influenced by retrieval cues. In accordance, the anticipation of others' behaviors can be considered a predictor of specific intended behavior in road traffic.     

Other road users’ adaptations to increase safety in response to older drivers’ behaviour

Changes in physical and cognitive abilities not only challenge the driving ability of older adults, in some situations age-related changes in driving behaviour require other road users to adapt their behaviour to maintain a safe traffic situation. In this study, we aimed to map age-related differences in driving behaviour and assess the impact on other road users. A group younger and a group older adults drove four different routes containing challenging situations (e.g., merging into motorway traffic) in a driving simulator while measures of driving behaviour were collected. Other road users’ deceleration responses to the driver’s behaviour were also collected as a measure of behavioural adaptation. Our results showed similar driving performance between young and older drivers when task complexity was low, but reduced performance in older drivers when tasks requirements increased. Lower driving speed and longer waiting times that were observed in older drivers can be interpreted as compensatory behaviour aimed at creating more time to lower task requirements. Crucially, in a non-time critical situation this compensatory behaviour was found to be successful, however in a time-critical situation (merging onto a motorway) this strategy had negative side effects because other road users had to decelerate in order to keep a safe distance. Our results show the importance of anticipation and adaptation by other road users for the success of older driver’s strategies and traffic safety.     

Factors underlying bus-related crashes in Hanoi,Vietnam

Road traffic crashes accounted for almost 13% of the total mortality recorded at the public health facilities in Vietnam in 2010. This qualitative study investigated factors related to bus-related crashes in Hanoi, Vietnam using focus group discussions and in-depth interviews among 75 participants who are bus drivers, motorcycle users, bus passengers, bus company managers, traffic policemen and local authorities. The results suggested that bus drivers were not the sole contributor to road traffic crashes with other vehicles. The rapid population growth due to rural to urban migration and the poor transport system appeared to be important contributing factors. In addition, “village culture” was likely to influence both the traffic behaviors of road users and the practices of law enforcement officers. Moreover, drink-driving behaviors appeared to be an important contributor to bus-related crashes. Supervision and penalty policies of bus companies also appeared to influence the driving performance of bus drivers. For a long-term solution to reduce bus-related crashes, it is vital to improve the transport infrastructure and the state management capacity regarding road safety as well as to assist the positive transition of citizens migrating from rural areas to their new urban lifestyle.     

Does driving experience in video games count? Hazard anticipation and visual exploration of male gamers as function of driving experience

Risk perception and distribution of visual attention while driving are crucial elements for accident prevention and new-driver improvement. This study investigates how racing videogames could shape the visual exploration of virtual and real road in male pre-drivers. The visual performance of players of racing video games with and without driver’s license was tested in virtual vs. real scenarios. Attention to specific elements of different types of road interactions was monitored using an eye-tracking system. Results showed that habitual use of racing video games was not found to foster a positive effect on users’ distribution of visual attention, supporting visual patterns typical of novice drivers. Gamers without driving experience replicated the same patterns in a real road scenario, ignoring road signs and potential areas of interactions with other drivers, while experienced drivers gamers explored video games roads like real roads. The fact that the gamers’ driving performance was not comparable to drivers in the virtual scenario suggests that there are other variables in the gameplay that create a less complex traffic scene, still the visual complexity of different real road interactions is kept in video game interactions, opening new perspectives towards gamers’ visual exploration of the road.     

The impact of courteous and discourteous drivers on physiological stress

Prior studies into road safety have concentrated largely on studying unsafe forms of driving behaviour such as aggressive, stressed, and risky driving. Little attention has been given to ‘positive’ driving behaviour, such as how pro-social driving may help to promote cooperation with other road users and decrease incidences of aggressive and stressful driving. This study aimed to compare the impact of courteous and discourteous driving on the immediate physical health of other drivers (blood pressure, heart rate, and markers of stress) whilst controlling for other recognized factors responsible for driver stress such as road infrastructure (e.g. roadworks, traffic lights, freeways) and driving maneuvers (e.g. merging, tail-gaiting, navigating roundabouts). Using actors in a deception study, a naturalistic driving scenario was created in a lab-based simulation. All participants (n = 10; 39 ± 14.5 years) drove the same route in a simulator and engaged with the same driving behaviours and other virtual road users on two separate occasions separated by 7 days. The difference between conditions was whether the participant interacted with other drivers who displayed: a) courteous or b) discourteous behaviours. Blood pressure, heart rate variability and salivary hormone concentrations (cortisol and alpha amylase) were measured before and immediately after each simulated drive. After interacting with the discourteous drivers, participants experienced significantly higher mean arterial blood pressure, systolic and diastolic pressure, central systolic and diastolic pressure, and heart rate, and lower heart rate variability (indicative of acute stress) compared to interacting with the courteous drivers. Conversely, these markers of stress were reduced after interacting with the courteous drivers. The results support courtesy on the road to provide short-term benefits for the recipient of the action, while also increasing road safety more generally.     

Anger-congruent behaviour transfers across driving situations

Anger and aggression on the road may sometimes appear unprovoked and unrelated to current driving circumstances. It is unclear whether such anger and aggression arises because of events prior to those circumstances in which anger is experienced and aggression is exhibited. In this study, time pressure and enforced following of a slowly moving vehicle were used to increase drivers' anger in order to assess whether affect and behaviour during a subsequent, non-provocative, drive would change accordingly. Ninety-six drivers drove twice in a simulated urban environment. During the first drive, oncoming traffic and a slowly moving lead vehicle required that half of the drivers travelled far slower than they would choose. During the second drive, drivers again followed slower vehicles and were required to respond to traffic events not encountered in the manipulation drive. Mood (Profile of Mood States) was assessed before and after each drive, and anger evaluations, arousal (heart rate) and behaviour (speed, lane position and collisions) were measured during drives. Anger increased and both mood and driving behaviour deteriorated in drivers exposed to slower lead vehicles, compared with control group drivers. These behavioural differences of speed and lane positioning carried over into the subsequent drive even to driving situations unlike those where provocation had previously occurred. Drivers who had previously been impeded later approached hazards with less caution, and attempted more dangerous overtaking manoeuvres. It is concluded that sometimes dangerous driving may result from anger provoked by circumstances other than those in which the behaviour is exhibited.