The conditioned anticipation of people (CAP) model of driving in urban spaces

Despite significant gains in overall collision rates, pedestrian and bicycle safety in complete street environments remains an on-going challenge. However, urban areas with the most risk exposure for pedestrians continue to maintain lower incident rates than their suburban counterparts (“Dangerous by Design” 2021). Under most driving circumstances, the over-rehearsed nature of driving leads to a psychological state similar to self-hypnosis, where attention is subconsciously maintained on the driving task while metacognitive awareness is minimized or eliminated. This state continues until some type of conflict, uncertainty, and/or novel stimulus is presented. The primary difference in driver attention in urban environments is postulated to result from the Conditioned Anticipation of People (CAP). Based on the human neurological predisposition to recognize and fixate on human faces and figures, we hypothesize that in areas where drivers have been conditioned to expect human presence, low-level metacognition is preemptively re-engaged to address their presence, resulting in higher attentional resource expenditure and increased distraction management. Such conditioning may be generated by contextual features common to pedestrian-friendly environments but, necessarily, must be reinforced over time by the Actual Presence of People (APP). CAP driver engagement is limited by the perceptual abilities of the driver such that at higher speeds or within wider corridors, the presence of pedestrians is more difficult to perceive. This results in a non-CAP attention pattern, exhibiting minimal metacognitive activity, high levels of automaticity, and reduced attention. This model was generated based on the observation that vulnerable user presence and the roadway contextual features that support the driver's ability to see vulnerable users were related to attention data measured during the SHRP2 Naturalistic Driving Study. Visually discernable features that were associated with vulnerable user presence had relationships with attention and large effect sizes (η² > 0.5). Contextual features that had relationships with vulnerable user presence, but minimal visual impact or interfered with the driver’s ability to see vulnerable users had no relationship to driver attention. This behavioral pattern provides supportive evidence for the proposed model.     

Analyzing driver's response to the yellow onset at signalized intersections

Intersections are critical points within the highway system at which the risk of crashes increases. This study seeks to better understand drivers’ behavior at an intersection by examining the relationship between their observed driving behavior, psychological attributes and decision to proceed through an intersection. A driving simulator and self-report questionnaire were used to understand driver decision-making at the onset of the yellow phase across several signalized intersections. The simulator measured driving outcomes such as speed, braking, and throttle as drivers cross through four increasingly difficult intersections. The questionnaires measured demographics, psychological traits including mindfulness and impulsiveness along with self-reported driving behaviors. A total of 102 participants completed the questionnaire as well as the driving simulator experiment. Hierarchical clustering served to classify drivers into four groups on the basis of their observed driving in the simulator: the safest drivers, safe drivers, speed demons, and aggressive drivers. These driving styles moderated the relationship between the drivers’ psychological traits and their decision to stop or proceed at each intersection. Results showed that mindfulness was highly related to the safest drivers’ decision to stop at the first intersection, while impulsiveness and anxiety were related to the speed demons’ decision to stop at the third intersection. These findings lay a strong foundation for developing progressive educational campaigns incorporating driver psychology in their methodology. Findings also provide support for research linking driving performance and psychological traits with implications for intersection design.     

Manual drivers’ experience and driving behavior in repeated interactions with automated Level 3 vehicles in mixed traffic on the highway

In the near future, conditionally automated vehicles (CAVs; SAE Level 3) will travel alongside manual drivers (≤ SAE level 2) in mixed traffic on the highway. It is yet unclear how manual drivers will react to these vehicles beyond first contact when they interact repeatedly with multiple CAVs on longer highway sections or even during entire highway trips. In a driving simulator study, we investigated the subjective experience and behavioral reactions of N = 51 manual drivers aged 22 to 74 years (M = 41.5 years, SD = 18.1, 22 female) to driving in mixed traffic in repeated interactions with first-generation Level 3 vehicles on four highway sections (each 35 km long), each of which included three typical speed limits (80 km/h, 100 km/h, 130 km/h) on German highways. Moreover, the highway sections differed regarding the penetration rate of CAVs in mixed traffic (within-subjects factor; 0%, 25%, 50%, 75%). The drivers were assigned to one of three experimental groups, in which the CAVs differed regarding their external marking, (1) status eHMI, (2) no eHMI, and (3) a control group without information about the mixed traffic. After each highway section, drivers rated perceived safety, comfort, and perceived efficiency. Drivers were also asked to estimate the penetration rate of CAVs on the previous highway section. In addition, we analyzed drivers’ average speed and their minimum time headways to lead vehicles for each speed zone (80 km/h, 100 km/h, 130 km/h) as well as the percentage of safety critical interactions with lead vehicles (< 1 s time headway). Results showed that manual drivers experienced driving in mixed traffic, on average, as more uncomfortable, less safe and less efficient than driving in manual traffic, but not as dangerous. A status eHMI helps manual drivers identify CAVs in mixed traffic, but the eHMI had no effect on manual drivers’ subjective ratings or driving behavior. Starting at a level of 25% Level 3 vehicles in mixed traffic, participants' average speed decreased significantly. At the same time, the percentage of safety critical interactions with lead vehicles increased with an increasing penetration rate of CAVs. Accordingly, additional measures may be necessary in order to at least keep the existing safety level of driving on the highway.     

A scoping review of predictors of driving under the influence of cannabis (DUIC) in young drivers

BackgroundRecreational and medical legalization of cannabis or marijuana use in countries and states continues to increase. Young adults aged 16–24 years have the highest prevalence rates of cannabis use. Young driver cannabis use is an incompletely understood traffic safety issue.ObjectivesThe purposes of this scoping review were to characterize the predictors of driving under the influence of cannabis (DUIC) among healthy young drivers and to identify research gaps.Inclusion criteriaA self-reported measure of DUIC and a correlation (r, odds ratio, risk ratio) to demographic or behavioral variables such as age, gender and frequency of use was required for inclusionSources of evidenceAPA PsycInfo, SPORTDiscus, Academic Search Complete, Google Scholar, MEDLINE Complete, Scopus, Embase, ERIC, TRID and POPLINE databases were searched using an a priori protocol.MethodsThe PRISMA-ScR methods and checklist were used to conduct the scoping review. After the removal of duplicates, abstract screening (N = 999), and full-text review (N = 173), 19 primary studies met inclusion criteria. Predictors were coded and mapped into four primary thematic categories: social, individual, driving and substance use.ResultsOf the included studies, a total of 52,197 respondents were surveyed in-person or online and 51.8 percent were males. The predominant predictors of DUIC included being a male, high school senior, with lower grades, having a younger ‘age of first cannabis use’, a higher frequency of consumption, a reduced perception of danger, repeatedly binge drinking, a history of driving under the influence of alcohol and living with fewer parents.Research gapsIdentified research gaps include methods used to study young drivers, cannabis edibles, chronic user tolerance, driver adaptation, passengers of drivers who consumed cannabis, combined use with other legal and illicit drugs, and combined smartphone and cannabis use.ConclusionThe results of this scoping review can be used to develop and target general and specific predictors of DUIC in novice, teen and young drivers. Additional research designs will be required to gain a more complete evidence-based understanding of the effects of cannabis on young drivers.     

Drinking,drug use and road rage in Turkish drivers

Alcohol or drug use and road rage behaviors in drivers are threats to traffic safety. The purpose of this research is to examine the relationship between alcohol or drug use and aggression in Turkish drivers, and to evaluate the mediating role of driving anger in this relationship. 270 amateur and professional Turkish drivers (170 male, 100 female) have filled up Driving Anger Scale (DAS), Driver Aggression Indicators Scale (DAIS), Alcohol Use Disorders Identification Test (AUDIT) and the Questionnaire Form. 15.9% of the participants scored 8 and higher on the AUDIT scale (alcohol problem). The most prevalent substance is cannabis, used at least once in a lifetime (20%). The results of mediated regression analysis indicates that driving anger has an increasing mediating role in the relationship between alcohol use and driver aggression. Due to limitations in the data, we could not reveal the relationship between substance use and driver aggression. These findings have led us to think that drinking use may contribute to being a perpetrator and/or a victim of the road rage. Taking precautions against drinking driving and road rage and going over the current implementations is important in order to create a safer traffic environment. Scientific researches carried out in this field must aim to provide the desired efficiency on prevention and intervention programs that reduce the prevalance of such dangerous acts.     

Exploring behavioral validity of driving simulator under time pressure driving conditions of professional drivers

Driving simulators have become an important tool in human factors research, given that they are appropriately validated. Therefore, this study aims to explore the behavioral (absolute and relative) validity of a fixed-base driving simulator by analyzing different driving behavior measures such as speed, longitudinal acceleration, lateral acceleration, and brake pedal force. Thirty professional drivers participated in the experiment and the data was collected in real and simulated worlds under No Time Pressure (NTP) and Time Pressure (TP) driving conditions. Initially, comparative analyses were conducted on different driving behavior measures using Wilcoxon-signed rank test to examine absolute validity of the driving simulator. Finally, Generalized Linear Mixed (GLM) models were developed for computing the effective distance between real and simulated worlds by quantifying the parameters and for establishing relative validity. In general, the continuous profiles of driving behavior measures followed similar trends in real and simulated worlds and comparative analyses indicated relative validity of the driving simulator. The GLM models showed significant interaction effect of driving environments (real-world and simulated world) and driving conditions (NTP and TP) where high driving speed, high brake pedal force, and low lateral acceleration were observed in simulated world under TP driving condition than real-world under TP driving condition. Overall, the statistical analyses showed qualitative correspondence (relative validity) of the driving behavior measures in between real and simulated worlds. The findings from the current study showed expediency of the driving simulator and its effectiveness in conducting research on human factors and driver safety.     

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.     

Social exclusion affects aggressive driving behaviour: The mediating effect of prosocial tendencies and driving anger

Social exclusion—being rejected or ignored by individuals or groups—is a common and adverse experience in social life. As a social activity, driving behaviour can be influenced by many factors. Whether social exclusion is one of these factors is an open question. Therefore, the aim of this study is to explore the impact of the social exclusion experience on individuals and their driving behaviours and the mediating effect of prosocial tendencies and driving anger. A total of 240 (104 males and 136 females) participants from China completed a questionnaire including the Ostracism Experiences Scale (OES), the prosocial tendencies measure (PTM), the Driving Anger Scale (DAS) and the Driver Behaviour Questionnaire (DBQ). The hierarchical multiple regression analysis and pathway analysis results showed that social exclusion experience and driving anger positively predicted aberrant driving behaviours (including aggressive violations, ordinary violations, lapses and errors), while prosocial tendencies had a negative impact on aberrant driving behaviour. Moreover, prosocial tendencies and driving anger mediated the relationship between social exclusion and driver behaviour, accounting for 11.18% and 46.71% of the total effect, respectively. The chain-mediated effect of prosocial tendencies and driving anger was also significant, accounting for 5.26% of the total effect of social exclusion on driver behaviour. This study examines the mechanisms underlying social exclusion experiences that positively predict individuals' unsafe driving behaviours, thereby filling a gap in social exclusion research and suggesting new avenues of exploration into the personal and social influences that affect driving behaviours.     

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.     

Safety implications of co-locating road signs: A driving simulator investigation

BackgroundAs road complexity increases the requirement for number of road signs also increases, although the amount of road side space does not. One practical strategy to address this is to present multiple road signs on the same gantry (sign co-location). However, there is very little research on the safety implications of this practice.Method36 participants (mean age = 42.25 years, SD = 13.99, 18 females) completed three driving simulator scenarios, each scenario had a different sign co-location condition: no co-location, dual co-location and triple co-location. Each scenario presented similar information using direction signs, variable message signs and variable speed limit signs, under. Each drive included standard motorway driving (100 km/h speed zone) in free flow traffic and one emergency event where a lead vehicle suddenly braked. The scenario order was counterbalanced and the emergency event vehicle varied.ResultsOverall, there was no impact of co-locating signs on general driving performance. No significant difference was observed between conditions for reaction time and minimum headway in response to the emergency event. Participants were able to correctly choose their destination whether the signs were co-located or not.DiscussionFor the particular configuration of signs tested there is no evidence that co-location negatively impacts driving performance. However, there may be some implications for travel speed and the manner in which the emergency event is responded to. Future work should confirm the findings on real roads. These findings provided support for sign co-location as a practical and safe option for displaying multiple road signs in a confined area.