Gasoline conservation: a procedure for measuring and reducing the driving of college students

The study sought to motivate college students to reduce the number of miles they drove each day and thus save gasoline. Students in two psychology classes were divided by class into two groups. The experimental group was offered various combinations of prizes such as cash, a tour of a mental-health facility, car servicing, and a university parking sticker for reducing driving. The value of the prize received was scaled in terms of per cent reduction in driving. The contrast group received no inducements. The condition in which the experimental group's mileage reduction was reinforced was counterbalanced by two baseline conditions. Several special recording procedures were used to reduce and detect the possibility of subjects altering their odometers, the source of the driving data. Experimental subjects reduced their average daily mileage by 20% relative to the initial baseline; the contrast group did not change. During the one-month reinforcement condition, the 12 experimental subjects saved some 170 gallons (worth $102) of gasoline.     

Long-term benefits of prompts to use safety belts among drivers exiting senior communities

Senior drivers are vulnerable to automobile crashes and subsequent injury and death. Safety belts reduce health risks associated with auto crashes. Therefore, it is important to encourage senior drivers to wear safety belts while driving. Using a repeated baseline design (AAB), we previously reported that motivating signs boosted safety belt usage by drivers exiting senior communities from baseline (72% and 68% usage), to postinstallation of signs (94%), to 6 months follow-up (80%). The current study was a 4-year follow-up in which six senior communities, with seat belt signs, were compared to six matched control senior communities with no signs. Safety belt usage was stable, across 4 years, at approximately 80% for both male and female drivers and front seat passengers for the six communities with signs, and was approximately 55% for control sites. These finding suggest that the simple and low-cost intervention of erecting signs to prompt safety belt use has persistent benefits that affect driver and passenger behavior alike.     

THE FAILURE OF FEEDBACK ON ALCOHOL IMPAIRMENT TO REDUCE IMPAIRED DRIVING

We examined the effects of rules to govern drinking, individual feedback on blood alcohol concentration (BAC), and public posting of group data on impaired driving on the incidence of impaired driving. Level of impairment was determined from breath samples taken from tavern patrons. Following baseline, an intervention package consisting of (a) cards to guide patrons in pacing their drinking to stay under the legal limit, (b) individual feedback on BAC, and (c) posted group feedback on the percentage of patrons driving while impaired the preceding week was introduced in two taverns. Results indicated that the intervention package did not reduce the percentage of impaired drivers departing either tavern. The addition of a brief intensive police enforcement program directed at impaired driving produced a short-term reduction in impaired driving.     

The influence of just-world beliefs on driving anger and aggressive driving intentions

Decades of research demonstrate that the extent to which one believes the world is just can have important interpersonal consequences. Unfortunately, most of the commonly studied consequences are negative in nature. Guided by previous research demonstrating the buffering effect of just‐world beliefs and anger, the present research explores how belief in a just world (BJW) may mitigate anger in the domain of driving anger and examines the limiting conditions of this effect. Study 1 demonstrated the expected negative relation between common measures of BJW and anger expression in a driving context. Study 2 found that the buffering effects of just‐world beliefs and driver aggression were greater when BJW was violated (vs. not). Study 3 replicated the effects on aggression and anger and established a mediational role of anger on the buffering effects of just‐world beliefs on thoughts and driver aggression. Aggr. Behav. 38:389‐402, 2012. © 2012 Wiley Periodicals, Inc.     

Kano model of autonomous driving user acceptance according to driver characteristics: A survey study

The development of advanced technology has revolutionized human life. In this regard, autonomous driving, a core technology currently being developed, is changing rapidly. In addition to improving technology, the acceptance of technology users must be secured. Most relevant studies conducted hitherto have involved evaluation using acceptance elements defined based on the technology acceptance model and the unified theory of acceptance and use of technology. In this study, 21 elements associated with the acceptance of autonomous driving are defined. The Kano model is used to classify the acceptance elements into five attributes and to propose guidelines for improving acceptance. Driver characteristics are classified based on four human factors, which are used to investigate differences in acceptance between groups. A Google survey and fieldwork were completed by 187 participants. Contrary to previous studies, no significant gender differences are observed in the current study. In terms of age, many obstacles are encountered in securing autonomous driving acceptance from the elderly driver group. Additionally, a more conservative tendency is indicated by people with more driving experience. The results of this study reveal important points for identifying elements that hinder future sustainability and commercialization of autonomous driving, thereby facilitating its further technological development.     

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.     

Comparing eye-tracking metrics of mental workload caused by NDRTs in semi-autonomous driving

The objective of this study was to verify the effectiveness of eye-tacking metrics in indicating driver’s mental workload in semi-autonomous driving when the driver is engaged in different non-driving related tasks (NDRTs). A driving simulator was developed for three scenarios (high-, medium-, and low-mental workload presented by SAE (Society of Automotive Engineers) Levels 0, 1, and 2) and three uni-modality secondary tasks. Thirty-six individuals participated in the driving simulation experiment. NASA-TLX (Task Load Index), secondary task performance, and eye-tracking metrics were used as indicators of mental workload. The subjective rating using the NASA-TLX showed a main effect of autonomous level on mental workload in both visual and auditory tasks. Correlation-matrix calculation and principal-component extraction indicated that pupil diameter change, number of saccades, saccade duration, fixation duration, and 3D gaze entropy were effective indicators of a driver’s mental workload in the visual and auditory multi-tasking situations of semi-autonomous driving. The accuracy of predicting the mental-workload level using the K-Nearest Neighbor (KNN) classifier was 88.9% with bootstrapped data. These results can be used to develop an adaptive multi-modal interface that issues efficient and safe takeover requests.     

Examining U.S. drivers’ characteristics in relation to how frequently they engage in speeding on freeways

Speeding and speed-related crashes have consistently represented over 25% of all traffic fatalities over the past two decades. The severity of these speed-related incidents not only impact the drivers but all road users. Thus, characterizing drivers who speed, understanding their motivations, and identifying the types of risky driving behaviors associated with speeding play a critical role in developing, implementing, and sustaining effective countermeasures. Using a survey administered to a U.S. nationally representative sample (N = 2,930 licensed drivers aged 16 or older), this study develops a partial proportional odds model to examine differences in characteristics between types of speeders – frequent, occasional, and non-speeders – and explores characteristics and risk driving behaviors that are most associated with speeding behavior. Additionally, motivations for speeding are examined for drivers who frequently speed compared with those who occasionally speed. Results show speeders tended to engage in other unsafe driving behaviors, such as distracted, aggressive, unbelted, and alcohol-impaired driving. Among demographic and socio-economic variables examined in this study, drivers’ age was the greatest associated determinant. The association with engagement in red-light running, however, outweighed that with drivers’ age. Interestingly, the interaction between educational attainment and engagement in aggressive driving was also predictive of speeding behavior. For motivations for speeding, frequent speeders were more likely to report enjoying driving fast and disagreeing with speed limits compared with occasional speeders. The findings of this study are useful towards identifying the various characteristics and behaviors of drivers who engage in speeding, which can provide future insights into where effective countermeasures and prevention efforts should be focused.     

The effect of the dominance of an in-vehicle agent’s voice on driver situation awareness,emotion regulation,and trust: A simulated lab study of manual and automated driving

As in-vehicle voice agents increase in popularity, related research is extending to how voice messages can affect the driver’s cognitive and emotional states. Accordingly, we investigated how in-vehicle agent (IVA) voice dominance and driving automation can affect the driver’s situation awareness (SA), emotion regulation (ER), and trust. To this end, a lab-based experiment was conducted with a medium-fidelity driving simulator using actor-recorded voice agents. Twenty-two female and nineteen male driver-licensed participants were recruited to drive simulated vehicles with voice agents and evaluated. The results demonstrated that compared with the dominant voice, the agent with a submissive voice significantly increased ER in both manual and automated driving. Furthermore, the submissive voice significantly increased trust in automated driving compared with the dominant agent. Cross and synergistic interaction effects exist between voice dominance and driving automation in SA and ER, respectively. This study revealed that both the content of the messages of the IVAs and their voice characteristics are essential for modulating the driver’s SA, ER, and trust in driving. It is expected that larger-scale future studies with simulation or on a real road would increase the validity of this study.     

How the initial level of trust in automated driving impacts drivers’ behaviour and early trust construction

Trust in Automation is known to influence human-automation interaction and user behaviour. In the Automated Driving (AD) context, studies showed the impact of drivers’ Trust in Automated Driving (TiAD), and linked it with, e.g., difference in environment monitoring or driver’s behaviour. This study investigated the influence of driver’s initial level of TiAD on driver’s behaviour and early trust construction during Highly Automated Driving (HAD). Forty drivers participated in a driving simulator study. Based on a trust questionnaire, participants were divided in two groups according to their initial level of TiAD: high (Trustful) vs. low (Distrustful). Declared level of trust, gaze behaviour and Non-Driving-Related Activities (NDRA) engagement were compared between the two groups over time. Results showed that Trustful drivers engaged more in NDRA and spent less time monitoring the road compared to Distrustful drivers. However, an increase in trust was observed in both groups. These results suggest that initial level of TiAD impact drivers’ behaviour and further trust evolution.