Are Truck Drivers Ready to Save Fuel? The Objective and Subjective Effectiveness of an Ecological Driver Assistance System

Henzler, Michael; Boller, Alisa; Buchholz, Michael; Dietmeyer, Klaus

doi:10.1109/itsc.2015.325

Cited by 7 publications

(8 citation statements)

References 23 publications

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“…Besides, whole-body kinesthetic output was investigated by Gaspar et al [114] who conveyed forward collision warnings via brake pulses. We also found approaches for haptic pedals that, e.g., provided force feedback to guide drivers toward applying ideal throttle [73] or a pressure point such that the pedal is pressed no further than the recommended angle for ecological driving [141].…”

Section: Output Modalitiesmentioning

confidence: 99%

“…Regarding output, we found that out of the 12 anchored locations, only rear and floor were not utilized for visual output. Besides, output was mainly provided using auditory modalities via speakers in the front (e.g., [286]), and via kinesthetic modalities at the center stack (e.g., [139]), steering wheel (e.g., [154]), seat (e.g., [123]), or floor [141]. Similarly, tactile output was provided at the center stack (e.g., [376]), steering wheel (e.g., [329]), or seat (e.g., [114]).…”

Section: Interaction Locationsmentioning

confidence: 99%

“…Regarding multimodal output, we found that most publications include visual modalities, mainly because their approaches required a display to visualize a task or an UI. Accordingly, display was combined with various output modalities, e.g., with auditory (speech [359], sound [269], music [16]), kinesthetic (haptic pedal [141], seat movement [289]), or tactile (vibration [369], ultrasound [117], cutaneous push [337]). Other visual output modalities used were LED and HUD.…”

Section: Multimodal Interactionmentioning

confidence: 99%

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A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

Jansen

Colley

Rukzio

2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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Automotive user interfaces constantly change due to increasing automation, novel features, additional applications, and user demands. While in-vehicle interaction can utilize numerous promising modalities, no existing overview includes an extensive set of human sensors and actuators and interaction locations throughout the vehicle interior. We conducted a systematic literature review of 327 publications leading to a design space for in-vehicle interaction that outlines existing and lack of work regarding input and output modalities, locations, and multimodal interaction. To investigate user acceptance of possible modalities and locations inferred from existing work and gaps unveiled in our design space, we conducted an online study (N=48). The study revealed users' general acceptance of novel modalities (e.g., brain or thermal activity) and interaction with locations other than the front (e.g., seat or table). Our work helps practitioners evaluate key design decisions, exploit trends, and explore new areas in the domain of in-vehicle interaction.

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Section: Output Modalitiesmentioning

confidence: 99%

Section: Interaction Locationsmentioning

confidence: 99%

Section: Multimodal Interactionmentioning

confidence: 99%

See 1 more Smart Citation

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

Jansen

Colley

Rukzio

2022

Proc. ACM Interact. Mob. Wearable Ubiquitous Technol.

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“…Performance expectancy and social influence were found to have significant effects on behavioural intentions, but the explanatory power of the model for intentions to use this system was only 20% when independent variables (PE, EE, and SI) were included in the modelling. Henzler, Boller [25] used UTAUT to investigate driver acceptance of a driver assistance system which provides eco-driving recommendations. The results showed that performance expectancy and effort expectancy may both have a direct effect on behavioural intentions.…”

Section: Statement Of the Problemmentioning

confidence: 99%

Attention Pedestrians Ahead: Evaluating User Acceptance and Perceptions of a Cooperative Intelligent Transportation System-Warning System for Pedestrians

Zhang

Blythe

et al. 2022

Sustainability

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Warning system for pedestrians (WSP), one of cooperative intelligent transport system (C-ITS) applications, is designed to increase safety for pedestrians but also for drivers and other road users. The evaluation of end-user acceptance and perceptions of this technology is crucial before deploying it in transportation systems. Five WSP human–machine interfaces (HMIs) were designed and simulated using a driver’s first-view video footage of driving through a pedestrian crossing in Newcastle upon Tyne. The five WSP designs were evaluated with 24 younger end users (35 years old and younger). This study first evaluated the usefulness of the unified theory of acceptance and use of technology (UTAUT) in modelling end-user acceptance in terms of behavioural intentions to use WSP. The results suggest that the UTAUT can be applied to investigate the end-user acceptance of WSP, with performance expectancy and effort expectancy influencing the behavioural intentions to use WSP. Furthermore, we investigated end-user attitudes towards various WSP human–machine interface (HMI) designs. Participants showed more positive attitudes towards visual-only interfaces than towards audio-only and multi-modal (combinations of visual and audio) interfaces. Above all, the findings of this research increase our understanding of public acceptance and perceptions of this C-ITS application.

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“…Reward-based interventions were proven to be effective in various areas of risk prevention [ 45 ]. However, some researchers argue that drivers should become aware of the benefits offered by ADAS and use them daily without receiving incentives [ 46 ].…”

Section: Introductionmentioning

confidence: 99%

Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

Voinea

Postelnicu

Duguleană

et al. 2020

IJERPH

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Technological advances are changing every aspect of our lives, from the way we work, to how we learn and communicate. Advanced driver assistance systems (ADAS) have seen an increased interest due to the potential of ensuring a safer environment for all road users. This study investigates the use of a smartphone-based ADAS in terms of driving performance and driver acceptance, with the aim of improving road safety. The mobile application uses both cameras of a smartphone to monitor the traffic scene and the driver’s head orientation, and offers an intuitive user interface that can display information in a standard mode or in augmented reality (AR). A real traffic experiment consisting of two driving conditions (a baseline scenario and an ADAS scenario), was conducted in Brasov, Romania. Objective and subjective data were recorded from twenty-four participants with a valid driver’s license. Results showed that the use of the ADAS influences the driving performance, as most of them adopted an increased time headway and lower mean speeds. The technology acceptance model (TAM) questionnaire was used to assess the users’ acceptance of the proposed driver assistance system. The results showed significant interrelations between acceptance factors, while the hierarchical regression analysis indicates that the variance of behavioral intention (BI) can be predicted by attitude toward behavior.

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Are Truck Drivers Ready to Save Fuel? The Objective and Subjective Effectiveness of an Ecological Driver Assistance System

Cited by 7 publications

References 23 publications

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature Review

Attention Pedestrians Ahead: Evaluating User Acceptance and Perceptions of a Cooperative Intelligent Transportation System-Warning System for Pedestrians

Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System

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