Das Deutsche Zentrum Luft- und Raumfahrt (DLR) zeigt auf der IAA Mobility 2021 in München, wie Klimaschutz und Mobilität im Straßenverkehr vereinbar werden. Im Zentrum steht u.a. ein futuristischer Prototyp: das Fahrzeugkonzept U-Shift. Das U-Shift demonstriert urbane Mobilität und Logistik neu – und trennt die U-förmige Antriebseinheit von den auf die jeweilige Transportaufgabe zugeschnittenen Aufbauten. Für dieses Fahrzeug entwickeln wir das HMI für die Technische Aufsicht (Teleoperation).
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Our new journal article is online:
Kurtz, M., Oehl, M., & Sutter, C. (2021). “Just One Short Voice Message”—Comparing the Effects of Text- vs. Voice-Based Answering to Text Messages via Smartphone on Young Drivers’ Driving Performances. Safety, 7(3), 57. doi: 10.3390/safety7030057
Despite the well-known distracting effects, many drivers still engage in phone use, especially texting and especially among young drivers, with new emerging messaging modes. The present study aims to examine the effects of different answering modes on driving performance. Twenty-four students (12 females), aged between 19 and 25 years (M = 20.83, SD = 1.53), volunteered for the study. They accomplished the Lane Change Task (LCT) with baseline and dual-task runs in a driving simulator. In dual-task runs, participants answered text messages on a smartphone by voice or text message with varying task complexity. Driving performance was measured by lane deviation (LCT) and subjective measures (NASA-TLX). Across all trials, driving performance deteriorated during dual-task runs compared with the baseline runs, and subjective demand increased. Analysis of dual-task runs showed a benefit for voice-based answering to received text messages that leveled off in the complex task. All in all, the benefits of using voice-based answering in comparison with text-based answering were found regarding driving performance and subjective measures. Nevertheless, this benefit was mostly lost in the complex task, and both the driving performance and the demand measured in the baseline conditions could not be reached.
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Our new journal paper „Impact of External Human-Machine Interface Communication Strategies of Automated Vehicles on Pedestrians’ Crossing Decisions and Behaviors in an Urban Environment“ is online.
Abstract: The development of automated vehicles (AVs) and their integration into traffic are seen by many vehicle manufacturers and stakeholders such as cities or transportation companies as a revolution in mobility. In future urban traffic, it is more likely that AVs will operate not in separated traffic spaces but in so-called mixed traffic environments where different types of traffic participants interact. Therefore, AVs must be able to communicate with other traffic participants, e.g., pedestrians as vulnerable road users (VRUs), to solve ambiguous traffic situations. To achieve well-working communication and thereby safe interaction between AVs and other traffic participants, the latest research discusses external human–machine interfaces (eHMIs) as promising communication tools. Therefore, this study examines the potential positive and negative effects of AVs equipped with static (only displaying the current vehicle automation status (VAS)) and dynamic (communicating an AV’s perception and intention) eHMIs on the interaction with pedestrians by taking subjective and objective measurements into account. In a Virtual Reality (VR) simulator study, 62 participants were instructed to cross a street while interacting with non-automated (without eHMI) and automated vehicles (equipped with static eHMI or dynamic eHMI). The results reveal that a static eHMI had no effect on pedestrians’ crossing decisions and behaviors compared to a non-automated vehicle without any eHMI. However, participants benefit from the additional information of a dynamic eHMI by making earlier decisions to cross the street and higher certainties regarding their decisions when interacting with an AV with a dynamic eHMI compared to an AV with a static eHMI or a non-automated vehicle. Implications for a holistic evaluation of eHMIs as AV communication tools and their safe introduction into traffic are discussed based on the results.
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Our new paper on driving anger and the validation of the Driving Anger Scale for German drivers is online:
In 1994, Deffenbacher et al. published the Driving Anger Scale (DAS), a tool for assessing a driver’s propensity to experience anger in road traffic. Since then, much research has used this scale to measure the driving anger experienced in various countries around the world. This study examines the scale’s validity for German drivers. It also relates their experiences of anger while driving to their experiences and expressions of anger in general, as well as to certain demographic variables. In addition, it compares German drivers’ experiences of driving anger to those reported by drivers from other countries. We distributed a German version of the DAS and the State-Trait Anger Expression Inventory (STAXI) to a sample of 1136 German drivers. Results showed that a 22-items version of the DAS with six factors produced good fit indices for German drivers. Furthermore, data analysis revealed small to moderate significant relationships between German drivers’ driving anger experiences and their experiences and expressions of anger in general, underlining the idea that driving anger is a personality characteristic that is related to one’s general experience and expression of anger. Finally, German drivers‘ driving anger experiences differed from those of drivers from other countries in that German drivers reported less driving anger than drivers from Spain and New Zealand, comparable levels to those from Turkey, Malaysia, and the United States, and more driving anger than drivers from France, Australia, China, and the United Kingdom. In addition, discourteous driver actions and hostile gestures consistently triggered highest driving anger ratings whereas police presence was rated lowest. Given these results, we conclude that the DAS can be applied to German drivers in its modified version.
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Our new paper on reducing subjective uncertainty to increase the acceptance of automated and connected driving is online:
An important factor for the acceptance and thus the spread of automated and connected driving (ACD) is the degree of subjective uncertainty that users experience when interacting with automated vehicles. Subjective uncertainties always occur when people are not able to predict the further course of a situation or future events due to lack of experience or information. If such uncertainties occur during the use of automated vehicles, the development of trust and thus acceptance of this technology is impaired by the negative emotions accompanying subjective uncertainties. Within the AutoAkzept project (which full title translates to: Automation without uncertainty to increase the acceptance of automated and connected driving), solutions for user-focused automation have been developed that put vehicle occupants at the center of system development. User-focused systems take into account two basic human needs in human-machine interaction, the need to understand and the need to be understood. For this purpose, user-focused systems use different sensors to detect subjective uncertainties and their influencing factors in real time, integrate this information with context data and make adjustments that reduce subjective uncertainties. The systemic adaptations of user-focused systems follow a holistic approach that includes the levels of vehicle guidance, interior adaptation and information presentation as well as target guidance are included. By reducing or avoiding subjective uncertainties, the project developments contribute to a positive, comfortable user experience and help to increase the acceptance of ACD. This paper presents research results of AutoAkzept on the topics of user state and activity modelling as well as needs-based adaptation strategies, which represent key components for the implementation of user-focused automation.
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Our new paper on teleoperation for highly automated vehicles in public transport is online:
Paving the way to future mobility, teleoperation of vehicles promises a reachable solution to effectively use the benefits of automated driving as long as fully automated vehicles (SAE 5) are not entirely feasible. Safety and reliability are assured by a human operator who remotely observes the vehicle and takes over control in cases of disturbances that exceed the vehicle automation’s skills. In order to integrate the vehicle’s automation and human remote-operation, we developed a novel user-centered human-machine interface (HMI) for teleoperation. It is tailored to the remote-operation of a highly automated shuttle (SAE 4) by a public transport control center and based on a systematic analysis of scenarios, of which detailed requirements were derived. Subsequently, a paper-pencil prototype was generated and refined until a click-dummy emerged. This click-dummy was evaluated by twelve control center professionals. The experts were presented the prototype in regular mode and were then asked to solve three scenarios with disturbances in the system. Using structured interview and questionnaire methodology, the prototype was evaluated regarding its usability, situation awareness, acceptance, and perceived workload. Results support our HMI design for teleoperation of a highly automated shuttle, especially regarding usability, acceptance, and workload. Participant ratings and comments indicated particularly high satisfaction with the interaction design to resolve disturbances and the presentation of camera images. Participants’ feedbacks provide valuable information for a refined HMI design as well as for further research.
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Our new journal paper on motion sickness mitigation is online.
Abstract: Motion sickness (MS) is a syndrome associated with symptoms like nausea, dizziness, and other forms of physical discomfort. Automated vehicles (AVs) are potent at inducing MS because users are not adapted to this novel form of transportation, are provided with less information about the own vehicle’s trajectory, and are likely to engage in non-driving related tasks. Because individuals with an especially high MS susceptibility could be limited in their use of AVs, the demand for MS mitigation strategies is high. Passenger anticipation has been shown to have a modulating effect on symptoms, thus mitigating MS. To find an effective mitigation strategy, the prototype of a human–machine interface (HMI) that presents anticipatory ambient light cues for the AV’s next turn to the passenger was evaluated. In a realistic driving study with participants (N = 16) in an AV on a test track, an MS mitigation effect was evaluated based on the MS increase during the trial. An MS mitigation effect was found within a highly susceptible subsample through the presentation of anticipatory ambient light cues. The HMI prototype was proven to be effective regarding highly susceptible users. Future iterations could alleviate MS in field settings and improve the acceptance of AVs.
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Wir sind Teil der U-Shift-Projektfamilie im DLR für die Erforschung der Teleoperation hochautomatisierter Fahrzeuge. Das hochautomatisierte, fahrerlose, elektrische Fahrzeugkonzept U-Shift ermöglicht durch die Trennung von Fahrmodul und Transportkapsel eine neue Art der Modularität und damit auch eine neue Intermodalität, neue Produkte und Geschäftsmodelle. Das Fahrmodul kann in Kombination mit verschiedenen Kapseltypen sowohl zum Transport von Personen als auch von Gütern eingesetzt werden. Anwendungsbeispiele sind z.B. autonome, elektromobile Nachtbelieferung, autonome Intra-Logistik und barrierefreier Personentransport.
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Description:
Driver performance and behavior can be partially predicated based on one’s emotional state. Through ascertaining the emotional state of passengers and employing various mitigation strategies, empathic cars can show potential in improving user experience and driving performance. Challenges remain in the implementation of such strategies, as individual differences play a large role in mediating the effect of affective intervention. Therefore, we propose a workshop that aims to bring together researchers and practitioners interested in affective interfaces and in-vehicle technologies as a forum for the development of targeted emotion intervention methods. During the workshop, we will focus on a common set of use cases and generate approaches that can suit different user groups. By the end of this short workshop, researchers will determine ideal intervention methods for prospective user groups. This will be achieved through the method of insight combination to generate and discuss ideas. […]
Organizers:
Chihab Nadri, Virginia Tech
Jingyi Li, LMU Munich
Esther Bosch, German Aerospace Center (DLR)
Michael Oehl, German Aerospace Center (DLR)
Ignacio Alvarez, Intel Labs
Michael Braun, BMW Group Research
Myounghoon Jeon, Virginia Tech
Register here.
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German Aerospace Center (DLR)
Institute of Transportation Systems | HMI Group
Lilienthalplatz 7
38108 Braunschweig, Germany