Direct or indirect sensor enabled eco-driving feedback: Which preference do corporate car drivers have?

Staake, Thorsten; Fleisch, Elgar

doi:10.1109/iot.2012.6402302

Cited by 5 publications

(7 citation statements)

References 28 publications

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“…For example, Darby [2] described the utility of accumulated household energy consumption feedback for assessing long-term patterns and trends for large energy loads and the impact over time of equipment investments or other changes; whereas instantaneous data can reveal impacts of behavior with respect to smaller end-uses. In the context of eco-driving feedback, studies have shown instantaneous feedback (e.g., momentary fuel efficiency) is used primarily for experimentation and learning new behaviors, whereas accumulated feedback (e.g., average fuel-efficiency) is used primarily for goal-setting and assessing overall performance [39,40]. As mentioned later with regard to feedback standards, it is also useful to provide information at multiple time scales for comparison [25].…”

Section: Data Granularitymentioning

confidence: 99%

Information, timing, and display: A design-behavior framework for improving the effectiveness of eco-feedback

Sanguinetti

Dombrovski

Sikand

2018

Energy Research & Social Science

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Eco-feedback is information about resource (energy, water, food) consumption provided back to consumer(s) with the goal of promoting more sustainable behavior. Effective eco-feedback relies upon an understanding of key eco-feedback design dimensions and how they relate to behavior change. This paper develops a conceptual framework that includes a typology of eco-feedback design dimensions and maps those dimensions on to the behavioral mechanisms of attention, learning, and motivation. To develop this framework, we synthesized, clarified, and expanded on previous discussions of eco-feedback design dimensions across multiple academic disciplines. Our analysis yielded three types of behaviorally-relevant eco-feedback design dimensions: information, timing, and display. Information dimensions include granularity, metrics, valence, and contextual information. Timing dimensions include latency, strategic timing, and frequency and duration. Display dimensions include medium, modality, style, location, audience, and response requirement. Each of these dimensions has implications for eco-feedback salience, precision, or meaning, qualities that correspond to the behavioral mechanisms of attention, motivation, and learning, respectively.

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Section: Data Granularitymentioning

confidence: 99%

Information, timing, and display: A design-behavior framework for improving the effectiveness of eco-feedback

Sanguinetti

Dombrovski

Sikand

2018

Energy Research & Social Science

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“…However, research has rarely considered mobile-only solutions for EDFIS. We have found only two corresponding contributions [5,19]. Indeed, mobile EDFIS can make an essential contribution to the avoidance of CO 2 emissions, especially in emerging trends such as car sharing [20].…”

Section: Introductionmentioning

confidence: 77%

“…Based on additional available information, drivers can adapt to their behavior. As different studies show, it is possible to reduce fuel consumption through feedback systems by between 1 and 7% on average (e.g., [5,6]).…”

Section: Introductionmentioning

confidence: 99%

Sustainable behavior in motion: designing mobile eco-driving feedback information systems

2022

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Emissions from road traffic contribute to climate change. One approach to reducing the carbon footprint is providing eco-driving feedback so that drivers adapt their driving style. Research about the impact of eco-feedback on energy consumption is the basis for designing a mobile eco-driving feedback information system that supports drivers in reducing fuel consumption. This work develops design knowledge from existing knowledge. Subsequently, we implement a prototypical instantiation based on the derived knowledge. Insights from a field study suggest that our design artifact allows most drivers to decrease fuel consumption by 4% on average. The paper’s theoretical contribution is a set of design principles and an architecture of the proposed mobile eco-driving feedback information system. One recommendation is to provide normative feedback that compares drivers with each other. This feedback appears to encourage drivers to decrease their fuel consumption additionally. The design knowledge may support researchers and practitioners in implementing efficient eco-driving feedback information systems.

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“…Y. K. Joo and J.-E. R. Lee investigated the use of an in-vehicle voice agent to promote eco-driving [37]. Another study used an eco-driving smartphone application called DriveGain in a driving simulator, concluding that using such a support tool reduced fuel consumption by 16% [38].…”

Section: Introductionmentioning

confidence: 99%

Developing and Testing an Eco-Cooperative Adaptive Cruise Control System for Buses

Samira

Mansoureh

2020

International Conference on Transportation and Development 2020

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Studies over the past decade have shown that eco-driving systems which provide speed advisories to drivers/vehicles using data received via vehicle-to-infrastructure and vehicle-to-vehicle communications can help improve traffic mobility and reduce vehicle energy and emission levels. This study extends the Eco-Cooperative Adaptive Cruise Control (Eco-CACC) system previously developed for light duty vehicles to heavy duty vehicles (diesel and hybrid electric buses). First, the energy consumption models for diesel and hybrid buses are discussed and the field data collected by Blacksburg Transit are used to calibrate bus models. Thereafter, the bus Eco-CACC system is developed by incorporating the vehicle dynamic model and energy consumption model for buses. The developed Eco-CACC system has manual and automated modes to control buses. The manual Eco-CACC mode was tested by participants using driving simulators at Morgan State University under various scenarios that included different types of information. In addition, the automated bus Eco-CACC system was tested using the INTEGRATION microscopic simulation software to quantify the system-wide impacts of the proposed system under various traffic demand and vehicle types. The test results demonstrated that the proposed system could improve transit operations by reducing delay and helping transit agencies save on energy costs, resulting in an improved transit level of service, increased ridership, and improved traffic mobility.

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Direct or indirect sensor enabled eco-driving feedback: Which preference do corporate car drivers have?

Cited by 5 publications

References 28 publications

Information, timing, and display: A design-behavior framework for improving the effectiveness of eco-feedback

Information, timing, and display: A design-behavior framework for improving the effectiveness of eco-feedback

Sustainable behavior in motion: designing mobile eco-driving feedback information systems

Developing and Testing an Eco-Cooperative Adaptive Cruise Control System for Buses

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