IDEAS home Printed from https://ideas.repec.org/p/cdl/itsdav/qt9k86f889.html
   My bibliography  Save this paper

Goal Setting, Framing, and Anchoring Responses to Ecodriving Feedback

Author

Listed:
  • Stillwater, Tai
  • Kurani, Kenneth S.

Abstract

Ecodriving, defined here as the adoption of energy efficient driving styles and practices (primarily moderating acceleration, top speed, increased coasting, and improved maintenance practices), has long been recognized as a potential source of reductions in transportation energy use. Estimates of energy savings attributed to ecodriving range widely, from less than 5% to as high as 20% depending on the driving and experimental context. To explore the effects on ecodriving of interaction between drivers and in-vehicle energy feedback, a customized, interactive energy feedback interface was deployed in a field test with real-world drivers. This paper presents the results of interviews with 46 Plug-in Hybrid Electric Vehicle (PHEV) drivers who were given the ecodriving feedback interface for a multi-week trial including an interface off (baseline) and on (treatment) condition. This paper relies specifically on self-reports of driver motivations and behaviors to better understand what types of information motivated new ecodriving behavior; a future paper will investigate quantitative fuel consumption effects. Driver interviews at the conclusion of the study revealed that the introduction of feedback led three fourths of drivers to change driving styles to maximize on-road efficiency, at least in the short term. In addition, this study finds that the context of the feedback information, provided by a built-in goal or other contextualizing information such as a comparison value, is important for both comprehension and motivation. Personalization of the information allowed different drivers to access pertinent information, increasing the motivational value of the information. Instantaneous performance feedback such as real-time energy economy or power is used primarily for experimentation and learning of new ecodriving behaviors, whereas average performance feedback is used primarily for goal-setting and goal achievement. In addition, the direct comparison of personalized driver goals and average performance created a game-like experience that encouraged high achievement. Finally, the driver interviews revealed that feedback frames driving as a time to act in an efficient manner.

Suggested Citation

  • Stillwater, Tai & Kurani, Kenneth S., 2012. "Goal Setting, Framing, and Anchoring Responses to Ecodriving Feedback," Institute of Transportation Studies, Working Paper Series qt9k86f889, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt9k86f889
    as

    Download full text from publisher

    File URL: https://www.escholarship.org/uc/item/9k86f889.pdf;origin=repeccitec
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Barkenbus, Jack N., 2010. "Eco-driving: An overlooked climate change initiative," Energy Policy, Elsevier, vol. 38(2), pages 762-769, February.
    2. Boriboonsomsin, Kanok & Vu, Alexander & Barth, Matthew, 2010. "Eco-Driving: Pilot Evaluation of Driving Behavior Changes Among U.S. Drivers," University of California Transportation Center, Working Papers qt9z18z7xq, University of California Transportation Center.
    3. Stillwater, Tai, 2011. "Comprehending Consumption: The Behavioral Basis and Implementation of Driver Feedback for Reducing Vehicle Energy Use," Institute of Transportation Studies, Working Paper Series qt2ns9p8h7, Institute of Transportation Studies, UC Davis.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Stillwater, Tai & Kurani, Kenneth S., 2012. "Preliminary Results from a Field Experiment of Three Fuel Economy Feedback Designs," Institute of Transportation Studies, Working Paper Series qt11r5b3cs, Institute of Transportation Studies, UC Davis.
    2. Hsu, Chia-Yu & Yang, Chin-Sheng & Yu, Liang-Chih & Lin, Chi-Fang & Yao, Hsiu-Hsen & Chen, Duan-Yu & Robert Lai, K. & Chang, Pei-Chann, 2015. "Development of a cloud-based service framework for energy conservation in a sustainable intelligent transportation system," International Journal of Production Economics, Elsevier, vol. 164(C), pages 454-461.
    3. Carlos-Alberto Domínguez-Báez & Ricardo Mendoza-González & Huizilopoztli Luna-García & Mario Alberto Rodríguez-Díaz & Francisco Javier Luna-Rosas & Julio César Martínez-Romo & José M. Celaya-Padilla &, 2021. "A Methodological Process for the Design of Frameworks Oriented to Infotainment User Interfaces," Sustainability, MDPI, vol. 13(11), pages 1-14, May.
    4. Sanguinetti, Angela, 2018. "Onboard Feedback to Promote Eco-Driving: Average Impact and Important Features," Institute of Transportation Studies, Working Paper Series qt99m5j3q7, Institute of Transportation Studies, UC Davis.
    5. Barla, Philippe & Gilbert-Gonthier, Mathieu & Lopez Castro, Marco Antonio & Miranda-Moreno, Luis, 2017. "Eco-driving training and fuel consumption: Impact, heterogeneity and sustainability," Energy Economics, Elsevier, vol. 62(C), pages 187-194.
    6. Toledo, Galit & Shiftan, Yoram, 2016. "Can feedback from in-vehicle data recorders improve driver behavior and reduce fuel consumption?," Transportation Research Part A: Policy and Practice, Elsevier, vol. 94(C), pages 194-204.
    7. Sanguinetti, Angela & Queen, Ella & Yee, Christopher & Akanesuvan, Kantapon, 2020. "Average impact and important features of onboard eco-driving feedback: A meta-analysis," Institute of Transportation Studies, Working Paper Series qt9hm406d5, Institute of Transportation Studies, UC Davis.
    8. Ahmed, Sumayyah & Sanguinetti, Angela, 2015. "OBDEnergy: Making Metrics Meaningful in Eco-driving Feedback," Institute of Transportation Studies, Working Paper Series qt0x73t2jw, Institute of Transportation Studies, UC Davis.
    9. Pietro Stabile & Federico Ballo & Giorgio Previati & Giampiero Mastinu & Massimiliano Gobbi, 2023. "Eco-Driving Strategy Implementation for Ultra-Efficient Lightweight Electric Vehicles in Realistic Driving Scenarios," Energies, MDPI, vol. 16(3), pages 1-19, January.
    10. Nan, Sirui & Tu, Ran & Li, Tiezhu & Sun, Jian & Chen, Haibo, 2022. "From driving behavior to energy consumption: A novel method to predict the energy consumption of electric bus," Energy, Elsevier, vol. 261(PA).
    11. Yuan, Weichang & Frey, H. Christopher, 2020. "Potential for metro rail energy savings and emissions reduction via eco-driving," Applied Energy, Elsevier, vol. 268(C).
    12. Alejandro G. Tuero & Laura Pozueco & Roberto García & Gabriel Díaz & Xabiel G. Pañeda & David Melendi & Abel Rionda & David Martínez, 2017. "Economic Impact of the Use of Inertia in an Urban Bus Company," Energies, MDPI, vol. 10(7), pages 1-17, July.
    13. Chandra, Shailesh & Naik, R. Thirumaleswara & Venkatesh, Manoj & Mudgal, Abhisek, 2021. "Accessibility evaluations of the proposed road user charge (RUC) program in California," Transport Policy, Elsevier, vol. 113(C), pages 12-26.
    14. Xie, Shaobo & Lang, Kun & Qi, Shanwei, 2020. "Aerodynamic-aware coordinated control of following speed and power distribution for hybrid electric trucks," Energy, Elsevier, vol. 209(C).
    15. Nikoleta Mikušová & Gabriel Fedorko & Vieroslav Molnár & Martina Hlatká & Rudolf Kampf & Veronika Sirková, 2021. "Possibility of a Solution of the Sustainability of Transport and Mobility with the Application of Discrete Computer Simulation—A Case Study," Sustainability, MDPI, vol. 13(17), pages 1-24, September.
    16. Strömberg, Helena & Karlsson, I.C. MariAnne & Rexfelt, Oskar, 2015. "Eco-driving: Drivers’ understanding of the concept and implications for future interventions," Transport Policy, Elsevier, vol. 39(C), pages 48-54.
    17. Juliet Namukasa & Sheila Namagembe & Faridah Nakayima, 2020. "Fuel Efficiency Vehicle Adoption and Carbon Emissions in a Country Context," International Journal of Global Sustainability, Macrothink Institute, vol. 4(1), pages 1-21, December.
    18. Montag, Josef, 2015. "The simple economics of motor vehicle pollution: A case for fuel tax," Energy Policy, Elsevier, vol. 85(C), pages 138-149.
    19. Aurélien Saussay, 2019. "Dynamic heterogeneity: rational habits and the heterogeneity of household responses to gasoline prices," Post-Print hal-03632598, HAL.
    20. Carvalho, Irene & Baier, Thomas & Simoes, Ricardo & Silva, Arlindo, 2012. "Reducing fuel consumption through modular vehicle architectures," Applied Energy, Elsevier, vol. 93(C), pages 556-563.

    More about this item

    Keywords

    Engineering;

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cdl:itsdav:qt9k86f889. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Lisa Schiff (email available below). General contact details of provider: https://edirc.repec.org/data/itucdus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.