Effects of a driver assistance system with foresighted deceleration control on the driving performance of elderly and younger drivers

It is imperative to enhance the safety of elderly individuals on the roads to ensure the quality of their daily life. Near-miss incidents or accidents at blind intersections often result from a conflict between the behaviors of the driver and of other road users (pedestrians and cyclists). The failure to search for potential conflict in the context of blind intersections is a concern pertaining to road safety. The proposed assistance system performs a proactive braking intervention to achieve a referenced velocity in uncertain situations, such as one in which an unobserved pedestrian might initiate a road crossing. The proactive braking intervention attempts to manage the potential risk of crashing with respect to covert hazards. Because an automated system may impair a human’s ability to perceive and respond to hazardous situations while driving, this study was designed to examine the effects of proactive braking intervention and visual support cues on elderly and younger drivers’ ability to respond to information about potentially hazardous situations. We conducted a public-road driving experiment involving 108 elderly and younger drivers from two non-overlapping age groups. It was observed that the vehicle slowdown realized through the proactive braking intervention enabled the drivers to perform safety confirmation near blind spots and caused them to be more sensitive to and wary of potential hazards. This approach could be effective not only for elderly drivers, but also for young or inexperienced ones.     

Should older people be considered a homogeneous group when interacting with level 3 automated vehicles?

Exploring the future mobility of older people is imperative for maintaining wellbeing and quality of life in an ageing society. The forthcoming level 3 automated vehicle may potentially benefit older people. In a level 3 automated vehicle, the driver can be completely disengaged from driving while, under some circumstances, being expected to take over the control occasionally. Existing research into older people and level 3 automated vehicles considers older people to be a homogeneous group, but it is not clear if different sub-groups of old people have different performance and perceptions when interacting with automated vehicles. To fill this research gap, a driving simulator investigation was conducted. We adopted a between-subjects experimental design with subgroup of old age as the independent variable. The differences in performance, behaviour, and perception towards level 3 automated vehicles between the younger old group (60–69 years old) and older old group (70 years old and over) was investigated. 15 subjects from the younger old group (mean age = 64.87 years, SD = 3.46 years) and 24 from the older old group (mean age = 75.13 years, SD = 3.35 years) participated in the study. The findings indicate that older people should not be regarded as a homogeneous group when interacting with automated vehicle. Compared to the younger old people, the older old people took over the control of the vehicle more slowly, and their takeover was less stable and more critical. However, both groups exhibited positive perceptions towards level 3 automation, and the of older old people’s perceptions were significantly more positive. This study demonstrated the importance of recognising older people as a heterogeneous group in terms of their performance, capabilities, needs and requirements when interacting with automated vehicles. This may have implications in the design of such systems and also understanding the market for autonomous mobility.     

Evaluation of a dynamic blocking concept to mitigate driver distraction: Three simulator studies

In recent years, the number and complexity of in-vehicle infotainment systems has been steadily increasing. While these systems certainly improve the driving experience, they also increase the risk for driver distraction. International standards and guidelines provide methods of measuring this distraction along with test criteria that help automakers decide whether an interface task is too distracting to be used while driving. Any specific function failing this test should therefore be locked out for use by the driver. This study implemented and tested a dynamic approach to this blocking by algorithmically reacting to driver inputs and the pace of the interaction in order to prevent drivers from having prolonged or too intense sequences of in-vehicle interactions not directly related to driving. Three simulated driving experiments in Germany and the United States were conducted to evaluate this dynamic function blocking concept and also cater for differences in the status quo of either no blocking or static blocking. The experiments consisted of a car following scenario with various secondary interface tasks and always included a baseline condition where no blocking occurred as well as an implementation of the dynamic function blocking. While Experiments 1 and 3 were aimed at collecting and analyzing gaze and driving data from more than 20 participants, Experiment 2 focused on the user experience evaluation of different visual feedback implementations from 13 participants. The user experience as rated by these participants increased throughout the course of all three studies and helped further improve both the concept and feedback design. In the experiments the total glance time towards the road was significantly higher in the dynamic function blocking condition compared to the baseline, already accounting for the increase in total task time inherent to the dynamic condition. Participants developed two strategies of interacting with the dynamic function blocking. They either operated at their normal baseline speed and incurred task blockings or operated slower to avoid the blockings. In the latter strategy, participants chunked their interactions into smaller steps with the present data suggesting that they used the pauses in between chunks to look back onto the road ahead. Theoretical and practical implications of this first evaluation of a dynamic function blocking concept are discussed.     

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.     

The quiet passenger: Cognitions,avoidance, and onset among people with driving anxiety

BackgroundAnxiety over driving can have consequences for road safety and individual well-being. This area is under-researched in Australia, despite international research suggesting that most drivers experience some level of anxiety over driving.ObjectivesThis study aimed to contribute to the understanding of driving anxiety by 1) confirming the factor structure of two questionnaires designed to understand the concerns (Driving Cognitions Questionnaire: DCQ) and avoidance behaviours (Driving and Riding Avoidance Scale: DRAS); 2) providing evidence of anxiety manifestations in Australian drivers, and 3) understanding whether these differ according to the initial onset of this anxiety.MethodsA total of 1,600 people (77% females; age ranging from 18 to 89 [M = 27.92; ± 13.49], 75% licenced, 20% learning, 5% unlicenced) in Australia who identified as having “some” level of anxiety over driving, completed an online questionnaire regarding their anxiety.ResultsConfirmatory Factor Analyses showed the two-factor structure of the DRAS (general and traffic avoidance; and weather and riding avoidance) and the two-factor structure of the DCQ (crash-related concerns and social and panic related concerns) best fit the data. The most common anxiety onsets were crash involvement (14%), knowing someone who had been in a crash (9%) and due to criticism from others (9%). While no differences emerged between these groups on avoidance behaviour nor on crash concerns, social and panic concerns were higher for the criticism onset group.ConclusionsThe results demonstrate difference sources of anxiety and provide evidence of the importance of interactions with passengers in determining how a driver feels about the driving task.Practical implicationsAvenues for the reduction or avoidance of anxiety are proposed. These include better awareness and education for drivers regarding the importance of positive interactions and/or well as better journey management to avoid triggers of anxiety.     

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.