People with more misconceptions about automated vehicles might be more positive toward them

Automated vehicle (AV) technology is likely to influence transportation, mobility, and society dramatically. The year 2020 was a horizon year for the AV, as manufacturers expected commercial AVs to be available to the general market. However, we experienced one cycle of hyperbole for these “self-driving” cars, which are still unavailable to consumers. Meanwhile, many persistent beliefs about this technology are factual or arguable misconceptions. However, the public attitude literature rarely examines public misconceptions of AVs. Thus, we explored the prevalence of three misconceptions: “AVs are already available in the market,” “AVs do not need to be driven manually at all,” and “Mature business models for AVs have been established.” We investigated these misconceptions’ correlations with several cognitive (i.e., benefit and risk perceptions), affective (i.e., positive and negative affect), and behavioral components (i.e., behavioral intention and willingness to pay) of attitudes and trust in AVs. Our online survey in China (N = 1,026) indicated that more than 70% of participants hold one or more of the three misconceptions, with one-third believing that AVs are already available in the market. Furthermore, participants believing one or more of the three misconceptions were more positive regarding specific attitudinal factors (e.g., those who believed that AVs are already available reported greater behavioral intention to use and willingness to pay for AVs than those who rejected this misbelief). This finding indicates that people who are more wrong about AVs might be more positive toward AVs. We need effective and accurate public communication to dispel public misconceptions about AVs and build rational expectations.     

Psychological consequences of motor vehicle accidents: A systematic review

People involved in motor vehicle accidents (MVA) are at increased risk for psychological problems. Although the existing literature states that MVAs cause substantial negative mental health effects, summarizing and comparing these effects to understand their consequences could be more explored. This systematic literature review provides an overview of the literature surrounding the psychological consequences of MVAs to summarize and quantify their effects on mental health. The studies published in an English-language journal in the last 20 years (2001–2021) that present psychological consequences of MVAs were included. Web of Science, Scopus, and PubMed databases were used for the literature search. The systematic literature search found 23 eligible studies. After identifying all relevant studies on the topic, we synthesized the applied psychological assessment methods and the psychological consequences of MVAs. Current gaps in the reviewed papers and what future research are needed are also discussed. Results indicated that negative psychological consequences following an MVA are substantial, with all studies pointing to negative consequences in at least one psychopathology. Trauma-related MVA injuries are associated with elevated psychological distress, and MVA-related psychological consequences could have long-term effects if left untreated.     

The dynamics of purchasing an electric vehicle – A prospective longitudinal study of the decision-making process

This paper presents the results of a longitudinal prospective study which followed 113 people interested in the purchase of an electric vehicle for a period of two months. Based on an adapted stage model of self-regulated behavioral change (Bamberg, 2013b), a short online questionnaire with a stage diagnostic and the measurement of central model constructs was administered to the participants every second day. The analysis shows that 85% of transitions between the stages occur along the paths of the stage model. Stage transitions are preceded by increases in goal intentions and implementation intentions during the week before the transition. Intentions are predicted by most of the expected model constructs, but the effects were different on the between-person and the within-person level. The average stage durations are between two and three weeks. Implications of the study for research on stage models and practice are discussed.     

How does glance behavior influence crash and injury risk? A ‘what-if’ counterfactual simulation using crashes and near-crashes from SHRP2

As naturalistic driving data become increasingly available, new analyses are revealing the significance of drivers’ glance behavior in traffic crashes. Due to the rarity of crashes, even in the largest naturalistic datasets, near-crashes are often included in the analyses and used as surrogates for crashes. However, to date we lack a method to assess the extent to which driver glance behavior influences crash and injury risk across both crashes and near-crashes. This paper presents a novel method for estimating crash and injury risk from off-road glance behavior for crashes and near-crashes alike; this method can also be used to evaluate the safety impact of secondary tasks (such as tuning the radio). We apply a ‘what-if’ (counterfactual) simulation to 37 lead-vehicle crashes and 186 lead-vehicle near-crashes from lead-vehicle scenarios identified in the SHRP2 naturalistic driving data. The simulation combines the kinematics of the two conflicting vehicles with a model of driver glance behavior to estimate two probabilities: (1) that each event becomes a crash, and (2) that each event causes a specific level of injury. The usefulness of the method is demonstrated by comparing the crash and injury risk of normal driving with the risks of driving while performing one of three secondary tasks: the Rockwell radio-tuning task and two hypothetical tasks. Alternative applications of the method and its metrics are also discussed. The method presented in this paper can guide the design of safer driver–vehicle interfaces by showing the best tradeoff between the percent of glances that are on-road, the distribution of off-road glances, and the total task time for different tasks.     

Unmanned Aircraft Systems Selection Practices: Current Research and Future Directions

This review examines evolving personnel selection practices for unmanned aircraft systems/remotely piloted aircraft (UAS/RPA) across the U.S. Air Force, U.S. Naval Services, and U.S. Army. Findings across services revealed several themes, including strengths (e.g., strong predictive validities, consistency in operator profiles), weaknesses (e.g., small number of predictive validation studies, small sample sizes), and gaps (e.g., need for further investigation of noncognitive predictors). Ongoing and proposed research, including development and implementation of new instruments and methodologies, are discussed, followed by suggestions to facilitate enhanced UAS/RPA selection practices across the services.     

One- and two-year prospective follow-up of cognitive behavior therapy or supportive psychotherapy

We followed up over 90% of 57 motor vehicle accident survivors, who completed a controlled comparison of cognitive behavioral therapy (CBT) to supportive psychotherapy (SUPPORT). One-year results showed a continued significant advantage on categorical diagnosis (PTSD or not) and structured interview measures (CAPS) for CBT over SUPPORT. Other measures generally showed the same results. At two years, we were able to follow-up only 75% of one-year completers. Although there continued to be arithmetic differences favoring CBT over SUPPORT, with these attenuated samples only differences on PTSD Checklist and Impact of Event Scale scores and in overall categorical diagnoses were significant. There was very modest improvement from end of treatment to the two-year follow-up.     

Factors of acceptability,acceptance and usage for non-rail autonomous public transport vehicles: A systematic literature review

Non-rail autonomous public transport vehicles have emerged over the last few years. Technical progress in automation has resulted in a growing number of autonomous shuttle pilot experiments. Although these systems are technologically feasible, determining the extent to which they correspond to users’ needs and expectations remains a major issue. In order to answer that question, we conducted a systematic review which synthesizes the literature regarding the acceptability and willingness to use this type of autonomous public transport. This literature review allowed us to identify 39 documents addressing 70 factors of acceptability, acceptance and usage of non-rail autonomous public transport vehicles. The most cited factors in the literature concern service characteristics (times, schedules, fares) and safety issues (road-safety, on-board security). Factors related to automation level, comfort and access to the vehicle feature appear to a lesser extent. Acceptance is also related to personal factors, such as socio-demographics, travel habits, and personality. This review could be of interest to designers and manufacturers of non-rail autonomous public transport vehicles, as well as policy makers, and assist with the successful implementation of autonomous public transport services which are better adapted and meet the needs of all potential users.     

Measuring driver-vehicle cooperation: Development and validation of the Human-Machine-Interaction-Interdependence Questionnaire (HMII)

The development of partially and highly autonomous vehicles that take over parts of the driving task will result in changes in e.g. the responsibilities, interface and system design, task allocation and communication between driver and automated vehicle. To support this change and the increasing space of cooperative possibilities between driver and vehicle, generally accepted design principles and preconditions for successful driver-vehicle cooperation (Directability, Mutual Predictability, Joint Goals and Mutual Task-Dependency) were defined. However, research lacks validated scales measuring the proposed basic principles of driver-vehicle cooperation. Furthermore, a theory is missing that links those basic principles with a theory that enables an understanding of the influence of drivers' perception of the autonomous vehicle and context on driver-vehicle cooperation. Therefore, this work links the basic theoretical principles of driver-vehicle cooperation with the social psychological Theory of Interdependence and their dimensions (Conflict, Power, Mutual Dependence, Information Certainty, Future Interdependence). Filling the gap of missing validated scales for the principles of driver-vehicle cooperation, this study provides the development and validation of the Human-Machine-Interaction-Interdependence (HMII) questionnaire.In two studies, the new HMII questionnaire to measure drivers' perception in driver-vehicle cooperation was developed. In the first study (n = 94), items for the perception of the situation were transferred from the original Theory of Interdependence to the driver-vehicle cooperation. A 7-dimension model was identified via Explorative Factor Analysis. In the second study (n = 314), the model and items were validated via confirmatory factor analysis. A seven-factor model (Power, Conflict, Mutual Dependence Information Certainty: System to Human, Information Certainty (two levels) Future Interdependence (two levels) with 33 items showed a good fit to the data, chi² = 841, p < .001, adjusted chi² = 1.77, SRMR = 0.071. In sum, this questionnaire can help designers evaluate the impact of their system designs on driver perceptions of the driver-vehicle cooperation.     

Visualizing the autonomous vehicle’s maneuvers – Does an ecological interface help to increase the hedonic quality and safety?

This paper examines whether ecological speed information describing ongoing driving maneuvers during automated driving enhances the hedonic quality and driving safety immediately after a driving takeover. Visualizing maneuvers and trajectories has already proven effective. However, planned acceleration and deceleration in an automated vehicle have not yet been investigated. Therefore, this paper assesses how an automated vehicle’s speed control information might be presented by an ecological interface. Besides a possible increase in the hedonic quality, this information might enhance safe behavior of the human driver when it comes to a takeover. To assess these two aspects, 43 drivers participated in a dynamic driving simulator study. Using a within-subject design, two scenarios were used to compare an ecological interface, dynamically visualizing speed changes, to a conventional pop-up interface, using pop-up icons to visualize speed changes. The experimental results indicate that ecological feedback and conventional pop-up feedback do not differ regarding the hedonic quality, which was reflected by the state anxiety, usefulness, and satisfaction with the overall human-machine interface (HMI). Nonetheless, the post-hoc questionnaire on situational awareness showed a significantly lower rating for the ecological interface which may be the result of a more automatic and subconscious processing of the information given. Analyzing the takeover performance, the initial takeover time was comparably low for both interfaces. However, concerning safety, the ecological interface significantly enhanced the lateral control after takeover, and the drivers looked at the vehicle mirrors significantly earlier. In conclusion, the results show that the information given by the ecological interface may help drivers cope with a sudden takeover in a faster and more controlled way. Future applications of these findings might serve to enhance the acceptance and safety of semi-autonomous vehicles by implementing ecological interfaces.     

A Recourse Stochastic Goal Programming Approach for the Multi‐objective Stochastic Vehicle Routing Problem

This paper addresses a multi‐objective stochastic vehicle routing problem where several conflicting objectives such as the travel time, the number of vehicles in use and the probability of an accident are simultaneously minimized. We suppose that demands and travel durations are of a stochastic nature. In order to build a certainty equivalent program to the multi‐objective stochastic vehicle routing problem, we propose a solution strategy based on a recourse approach, a chance‐constrained approach and a goal‐programming approach. The resulting certainty equivalent program is solved to optimality using CPLEX. Copyright © 2016 John Wiley & Sons, Ltd.