19,643 research outputs found

    Amused, accepted, and used? Attitudes and emotions towards automated vehicles, their relationships, and predictive value for usage intention

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    Automated vehicles (AVs) have left the laboratories and can be experienced in several projects, e.g. at the premises of a clinic in Germany. With this transition, research on AV attitudes no longer needs to rely on questionnaires with hypothetical scenarios and simulations. Previous research – limited by the unavailability of AVs – has provided ambivalent results regarding age and gender differences in attitudes towards AVs. We present research results about the role of age and gender in connection with attitudes such as acceptance, perceived safety, and trust, as well as intention to use. We additionally demonstrate relationships between those constructs and emotions such as amusement, fear, and surprise. Data were collected from participants (n = 125) after having experienced an AV ride with level 4 automation on two campuses of a clinic in Berlin, Germany. Results reveal strong correlations between all attitudes (0.55 ≀ r ≀ 0.71; p < 0.01) and show acceptance and perceived safety to be solid predictors of intention to use AVs. We also found age to be a significant predictor for usage intention even when other attitudes are considered (ÎČ = −0.22; p < 0.01). MANOVA results point to gender differences in all constructs, but with limited confidence (5.40 ≀ F ≀ 18.34; p ≀ 0.02). However, we reject our hypothesis that young men are highly accepting, trusting, and intending to use AVs compared to other combinations of age and gender. We recommend using a mix of attitude, emotion, and behavioural (intention) measures in future research on AVs together with more transparency regarding construct definitions and study materials

    Examining the effects of emotional valence and arousal on takeover performance in conditionally automated driving

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    In conditionally automated driving, drivers have difficulty in takeover transitions as they become increasingly decoupled from the operational level of driving. Factors influencing takeover performance, such as takeover lead time and the engagement of non-driving-related tasks, have been studied in the past. However, despite the important role emotions play in human-machine interaction and in manual driving, little is known about how emotions influence drivers’ takeover performance. This study, therefore, examined the effects of emotional valence and arousal on drivers’ takeover timeliness and quality in conditionally automated driving. We conducted a driving simulation experiment with 32 participants. Movie clips were played for emotion induction. Participants with different levels of emotional valence and arousal were required to take over control from automated driving, and their takeover time and quality were analyzed. Results indicate that positive valence led to better takeover quality in the form of a smaller maximum resulting acceleration and a smaller maximum resulting jerk. However, high arousal did not yield an advantage in takeover time. This study contributes to the literature by demonstrating how emotional valence and arousal affect takeover performance. The benefits of positive emotions carry over from manual driving to conditionally automated driving while the benefits of arousal do not

    What impressions do users have after a ride in an automated shuttle? An interview study

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    In the future, automated shuttles may provide on-demand transport and serve as feeders to public transport systems. However, automated shuttles will only become widely used if they are accepted by the public. This paper presents results of an interview study with 30 users of an automated shuttle on the EUREF (EuropĂ€isches Energieforum) campus in Berlin-Schöneberg to obtain in-depth understanding of the acceptance of automated shuttles as feeders to public transport systems. From the interviews, we identified 340 quotes, which were classified into six categories: (1) expectations about the capabilities of the automated shuttle (10% of quotes), (2) evaluation of the shuttle performance (10%), (3) service quality (34%), (4) risk and benefit perception (15%), (5) travel purpose (25%), and (6) trust (6%). The quotes indicated that respondents had idealized expectations about the technological capabilities of the automated shuttle, which may have been fostered by the media. Respondents were positive about the idea of using automated shuttles as feeders to public transport systems but did not believe that the shuttle will allow them to engage in cognitively demanding activities such as working. Furthermore, 20% of respondents indicated to prefer supervision of shuttles via an external control room or steward on board over unsupervised automation. In conclusion, even though the current automated shuttle did not live up to the respondents’ expectations, respondents still perceived automated shuttles as a viable option for feeders to public transport systems.Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.Transport and PlanningHuman-Robot InteractionIntelligent VehiclesTransport and Plannin

    Measuring, analysing and explaining the value of travel time savings for autonomous driving

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    Autonomes Fahren (AF) wird potenziell die PrĂ€ferenzen fĂŒr die im Auto verbrachte Zeit stark beeinflussen und dementsprechend den Wert der Reisezeit, der ein SchlĂŒsselelement von Kosten-Nutzen-Analysen im Verkehr ist. Die Untersuchung dieses Aspekts des AF ist daher entscheidend fĂŒr die Analyse potenzieller Auswirkungen der Technik auf die zukĂŒnftige Verkehrsnachfrage. Trotz der steigenden Anzahl an Studien zu diesem Thema, gibt es noch erhebliche ForschungslĂŒcken. Der Fokus der Dissertation ist die potenziellen Änderungen des Reisezeitwerts, die durch das AF entstehen, zu messen sowie ihre Determinanten zu analysieren. Es wurden sowohl qualitative AnsĂ€tze als auch quantitative Methoden verwendet. Dabei wurden zwei Konzepte von AF betrachtet: privates und geteiltes autnomes Fahrzeug. Die Ergebnisse der Analysen zeigen einen niedrigeren Wert der Reisezeitersparnis beim AF im Vergleich zum manuellen Fahren, allerdings nur auf Pendelwegen. Das private Fahrzeug wird als eine attraktivere Option als ein geteiltes Fahrzeug wahrgenommen, jedoch unterscheiden sich die NutzerprĂ€ferenzen fĂŒr geteilte Fahrzeug stark zwischen den durchgefĂŒhrten Studien. Individuelle Charakteristiken, wie Erfahrung mit Fahrassistenzsystemen, beeinflussen stark die Wahrnehmung der Zeit im AF; andere sozio-demographischen Faktoren, wie Alter und Geschlecht haben vor allem einen indirekten Effekt auf den Reisezeitwert indem sie Einstellungen potenzieller Nutzer beeinflussen. Die Verbesserung des Fahrterlebnisses durch das AF und das Vertrauen in die Technik sind wichtige Determinanten der Reisezeitwahrnehmung. FahrvergnĂŒgen und andere wahrgenommene Vorteile vom manuellen Fahren gleichen in einem gewissen Ausmaß den Nutzen vom AF aus. Es wurden Reisezeitwerte fĂŒr unterschiedliche potenzielle Nutzersegmente berechnet. Abschließend wurden politische Implikationen, Empfehlungen fĂŒr die Entwicklung von AF sowie Empfehlungen fĂŒr kĂŒnftige Studien und potenziellen Forschungsgebiete abgeleitet.Autonomous driving will potentially strongly affect preferences for time spent in a vehicle and, consequently, the value of travel time savings (VTTS). As VTTS is a key element of cost-benefit analysis for transport, these interrelations are crucial for analysing the potential impact of the technology on future travel demand. Despite the increasing number of studies dedicated to this topic there are still many unanswered questions. The focus of the thesis is to measure potential changes in the VTTS resulting from the introduction of autonomous driving and analyse their determinants. Qualitative approaches and quantitative methods were used. Two concepts of AVs were considered: a privately-owned AV (PAV) and a shared AV (SAV). The analysis results suggest lower VTTS for autonomous driving compared to manual driving, but only on commuting trips. A PAV is perceived as a more attractive option than an SAV, but user preferences for SAVs vary between the conducted studies. Individual characteristics, such as experience with advanced driver assistance systems, strongly affect the perception of time in an AV; other socio-demographic factors, such as age and gender, affect mode choices and the VTTS mainly indirectly by influencing the attitudes of potential users. The improvement in travel experiences due to autonomous driving and trust in the technology are important determinants of the perception of travel time. Enjoyment of driving and other perceived benefits of manual driving partially counterbalance the utility of riding autonomously. VTTS for different potential user segments were calculated. In conclusion, several policy implications, development recommendations for AVs as well as recommendations for future studies and potential research avenues are derived from the findings

    Clustering Human Trust Dynamics for Customized Real-time Prediction

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    Trust calibration is necessary to ensure appropriate user acceptance in advanced automation technologies. A significant challenge to achieve trust calibration is to quantitatively estimate human trust in real-time. Although multiple trust models exist, these models have limited predictive performance partly due to individual differences in trust dynamics. A personalized model for each person can address this issue, but it requires a significant amount of data for each user. We present a methodology to develop customized model by clustering humans based on their trust dynamics. The clustering-based method addresses the individual differences in trust dynamics while requiring significantly less data than personalized model. We show that our clustering-based customized models not only outperform the general model based on entire population, but also outperform simple demographic factor-based customized models. Specifically, we propose that two models based on ``confident'' and ``skeptical'' group of participants, respectively, can represent the trust behavior of the population. The ``confident'' participants, as compared to the ``skeptical'' participants, have higher initial trust levels, lose trust slower when they encounter low reliability operations, and have higher trust levels during trust-repair after the low reliability operations. In summary, clustering-based customized models improve trust prediction performance for further trust calibration considerations.Comment: To be published in 2021 IEEE 24rd International Conference on Intelligent Transportation Systems (ITSC

    Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

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    The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications

    Analysis of Human and Agent Characteristics on Human-Agent Team Performance and Trust

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    The human-agent team represents a new construct in how the United States Department of Defense is orchestrating mission planning and mission accomplishment. In order for mission planning and accomplishment to be successful, several requirements must be met: a firm understanding of human trust in automated agents, how human and automated agent characteristics influence human-agent team performance, and how humans behave. This thesis applies a combination of modeling techniques and human experimentation to understand the concepts aforementioned. The modeling techniques used include static modeling in SysML activity diagrams and dynamic modeling of both human and agent behavior in IMPRINT. Additionally, this research consisted of human experimentation in a dynamic, event-driven, teaming environment known as Space Navigator. Both the modeling and the experimenting depict that the agent\u27s reliability has a significant effect upon the human-agent team performance. Additionally, this research found that the age, gender, and education level of the human user has a relationship with the perceived trust the user has in the agent. Finally, it was found that patterns of compliant human behavior, archetypes, can be created to classify human users

    Acceptability and Acceptance of Connected Automated Vehicles:A Literature Review and Focus Groups

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    A lot of resources and manpower are being allocated to develop Connected Automated Vehicles (CAV). CAV are Automated Vehicles (AV) with vehicle connectivity abilities to further increase road safety and user convenience. For a successful implementation of CAV, the psychological factors that predict its acceptance have to be researched. The present paper provides a literature review of the individual differences and perceived characteristics that could influence CAV's acceptance. Additionally, we report the results of several focus groups that were held in 4 European countries to highlight additional factors not reported in the literature yet
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