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The Energy Interface Challenge. Towards Designing Effective Energy Efficiency Interfaces for Electric Vehicles

Published: 21 September 2019 Publication History

Abstract

The design of effective energy interfaces for electric vehicles needs an integrated perspective on the technical and psychological factors that together establish real-world vehicle energy efficiency. The objective of the present research was to provide a transdisciplinary synthesis of key factors for the design of energy interfaces for battery electric vehicles (BEVs) that effectively support drivers in their eco-driving efforts. While previous research tends to concentrate on the (visual) representation of common energy efficiency measures, we focus on the design of action-integrated metrics and indicators for vehicle energy efficiency that account for the perceptual capacities and bounded rationality of drivers. Based on this rationale, we propose energy interface examples for the most basic driving maneuvers (acceleration, constant driving, deceleration) and discuss challenges and opportunities of these design solutions.

References

[1]
David A. Abbink, Mark Mulder, and Erwin R. Boer. 2012. Haptic shared control: smoothly shifting control authority? Cognition, Technology & Work 14, 1: 19--28. https://doi.org/10.1007/s10111-011-0192-5
[2]
Cindie Andrieu and Guillaume Saint Pierre. 2012. Using statistical models to characterize eco-driving style with an aggregated indicator. In 2012 IEEE Intelligent Vehicles Symposium, 63--68. https://doi.org/10.1109/IVS.2012.6232197
[3]
Cecilia Aragon, Clayton Hutto, Andy Echenique, Brittany Fiore-Gartland, Yun Huang, Jinyoung Kim, Gina Neff, Wanli Xing, and Joseph Bayer. 2016. Developing a Research Agenda for Human-Centered Data Science. In Proceedings of the 19th ACM Conference on Computer Supported Cooperative Work and Social Computing Companion - CSCW '16 Companion, 529--535. https://doi.org/10.1145/2818052.2855518
[4]
Matthias G. Arend and Thomas Franke. 2017. The Role of Interaction Patterns with Hybrid Electric Vehicle Eco-Features for Drivers' Eco-Driving Performance. Human Factors: The Journal of the Human Factors and Ergonomics Society 59, 2: 314--327. https://doi.org/10.1177/0018720816670819
[5]
Matthias G. Arend and Thomas Franke. 2018. How can Automotive User Interfaces Represent Kinetic Energy as a Resource? In Proceedings of the 10th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '18, 204--209. https://doi.org/10.1145/3239092.3265967
[6]
Matthias G. Arend, Thomas Franke, and Neville A. Stanton. 2019. Know-how or know-why? The role of hybrid electric vehicle drivers' acquisition of eco-driving knowledge for eco-driving success. Applied Ergonomics 75: 221--229. https://doi.org/10.1016/J.APERGO.2018.10.009
[7]
Nicholas Barberis, Ming Huang, and Richard H. Thaler. 2006. Individual Preferences, Monetary Gambles, and Stock Market Participation: A Case for Narrow Framing. American Economic Review 96, 4: 1069--1090. https://doi.org/10.1257/aer.96.4.1069
[8]
Peter J. Brockwell and Richard A. Davis. 2016. Introduction to Time Series and Forecasting. Springer International Publishing, Cham. https://doi.org/10.1007/978-3-319-29854-2
[9]
André Dahlinger, Felix Wortmann, Benjamin Ryder, and Bernhard Gahr. 2018. The Impact of Abstract vs. Concrete Feedback Design on Behavior Insights from a Large Eco-Driving Field Experiment. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18, 1--11. https://doi.org/10.1145/3173574.3173953
[10]
Steven J. Davis, Ken Caldeira, and H Damon Matthews. 2010. Future CO2 emissions and climate change from existing energy infrastructure. Science 329, 5997: 1330--3. https://doi.org/10.1126/science.1188566
[11]
Edward L. Deci and Richard M. Ryan. 2010. Intrinsic Motivation. In The Corsini Encyclopedia of Psychology. John Wiley & Sons, Inc., Hoboken, NJ, USA, 1--2. https://doi.org/10.1002/9780470479216.corpsy0467
[12]
Edward L. Deci and Richard M Ryan. 2002. Overview of self-determination theory: An organismic dialectical perspective. In Handbook of self-determination research. Springer US, Boston, MA, USA, 113--148. https://doi.org/https://doi.org/10.1007/978-1-4899-2271-7_5
[13]
Wissam Dib, Alexandre Chasse, Philippe Moulin, Antonio Sciarretta, and Gilles Corde. 2014. Optimal energy management for an electric vehicle in eco-driving applications. Control Engineering Practice 29: 299--307. https://doi.org/10.1016/J.CONENGPRAC.2014.01.005
[14]
Ebru Dogan, Linda Steg, and Patricia Delhomme. 2011. The influence of multiple goals on driving behavior: The case of safety, time saving, and fuel saving. Accident Analysis & Prevention 43, 5: 1635--1643. https://doi.org/10.1016/J.AAP.2011.03.002
[15]
Nicholas Epley, Adam Waytz, and John T. Cacioppo. 2007. On seeing human: a three-factor theory of anthropomorphism. Psychological Review 114, 4: 864. https://doi.org/https://doi.org/10.1037/0033295x.114.4.864
[16]
Gregor Erbach and European Parliamentary Research Service. 2015. Briefing: Understanding energy efficiency. Retrieved from http://www.europarl.europa.eu/RegData/etudes/BRIE/2015/568361/EPRS_BRI%282015%29568361_EN.pdf
[17]
Umer Farooq and Jonathan Grundin. 2016. Human-Computer Integration. Interactions 23: 27--32. https://doi.org/https://doi.org/10.1145/3001896
[18]
Thomas Franke, Matthias Georg Arend, Rich C. McIlroy, and Neville A. Stanton. 2016. Ecodriving in hybrid electric vehicles -- Exploring challenges for user-energy interaction. Applied Ergonomics 55: 33--45. https://doi.org/10.1016/J.APERGO.2016.01.007
[19]
Ray Fuller. 2005. Towards a general theory of driver behaviour. Accident Analysis & Prevention 37, 3: 461--472. https://doi.org/10.1016/J.AAP.2004.11.003
[20]
James J. Gibson. 1977. The theory of affordances. Lawrence Erlbaum Associates, Hillsdale, NJ, USA, 2. https://doi.org/https://doi.org/10.2307/j.ctt1xp3nmm.20
[21]
E. Bruce Goldstein. 2009. Encyclopedia of perception. Sage, Thousand Oaks, CA, USA. https://doi.org/https://doi.org/10.4135/9781412972000
[22]
Lino Guzzella and Antonio Sciarretta. 2012. Vehicle Propulsion Systems. Springer. https://doi.org/10.1007/978-3-642-35913-2
[23]
Jihun Han, Ardalan Vahidi, and Antonio Sciarretta. 2019. Fundamentals of energy efficient driving for combustion engine and electric vehicles: An optimal control perspective. Automatica 103: 558--572. https://doi.org/10.1016/J.AUTOMATICA.2019.02.031
[24]
Thomas Hermann, Andy Hunt, and John G. Neuhoff. 2011. The sonification handbook. Logos Verlag Berlin, Germany.
[25]
A. Hamish Jamson, Daryl L. Hibberd, and Natasha Merat. 2015. Interface design considerations for an in-vehicle eco-driving assistance system. Transportation Research Part C: Emerging Technologies 58: 642--656. https://doi.org/10.1016/J.TRC.2014.12.008
[26]
Samantha L. Jamson, Daryl L. Hibberd, and A. Hamish Jamson. 2015. Drivers' ability to learn eco-driving skills; effects on fuel efficient and safe driving behaviour. Transportation Research Part C: Emerging Technologies 58: 657--668. https://doi.org/10.1016/J.TRC.2015.02.004
[27]
Daniel Kahneman. 2003. A perspective on judgment and choice: Mapping bounded rationality. American Psychologist 58, 9: 697--720. https://doi.org/10.1037/0003-066X.58.9.697
[28]
Daniel Kahneman. 2003. Maps of Bounded Rationality: Psychology for Behavioral Economics. American Economic Review 93, 5: 1449--1475. https://doi.org/10.1257/000282803322655392
[29]
Daniel Kahneman, Jack L. Knetsch, and Richard H Thaler. 1991. Anomalies: The Endowment Effect, Loss Aversion, and Status Quo Bias. Journal of Economic Perspectives 5, 1: 193--206. https://doi.org/10.1257/jep.5.1.193
[30]
Daniel Kahneman and Amos Tversky. 2013. Choices, Values, and Frames. In American Psychologist. 269--278. https://doi.org/10.1142/9789814417358_0016
[31]
Daniel Kahneman and Amos Tversky. 2013. Prospect Theory: An Analysis of Decision Under Risk. 99--127. https://doi.org/10.1142/9789814417358_0006
[32]
Katja Kircher, Carina Fors, and Christer Ahlstrom. 2014. Continuous versus intermittent presentation of visual eco-driving advice. Transportation Research Part F: Traffic Psychology and Behaviour 24: 27--38. https://doi.org/10.1016/J.TRF.2014.02.007
[33]
Marc Landau, Sebastian Loehmann, and Moritz Koerber. 2014. Energy Flow: A Multimodal "Ready" Indication for Electric Vehicles. In Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications -AutomotiveUI '14, 1--6. https://doi.org/10.1145/2667239.2667301
[34]
Richard P. Larrick and Jack B. Soll. 2008. The MPG illusion. Science 320, 5883: 1593--1594. https://doi.org/10.1126/science.1154983.
[35]
Ben Lewis-Evans, Dick de Waard, and Karel A Brookhuis. 2013. Contemporary models of behavioural adaptation. In Behavioural adaptation and road safety: Theory, evidence and action. CRC Press Boca Raton, FL, 35--59. https://doi.org/10.1201/b14931-7
[36]
Nira Liberman, Yaacov Trope, and Elena Stephan. 2007. Psychological distance. In Social psychology: Handbook of basic principles (2nd ed.), Arie W. Kruglanski and Edward Tory Higgins (eds.). Guilford Publications, New York, NY, USA, 353--383. https://doi.org/https://doi.org/10.1037/e633942013-052
[37]
Xiaohai Lin, Daniel Gorges, and Steven Liu. 2014. Eco-driving assistance system for electric vehicles based on speed profile optimization. In 2014 IEEE Conference on Control Applications (CCA), 629--634. https://doi.org/10.1109/CCA.2014.6981410
[38]
Sebastian Loehmann, Marc Landau, Moritz Koerber, and Andreas Butz. 2014. Heartbeat: Experience the pulse of an electric vehicle. In Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications -AutomotiveUI '14, 1--10. https://doi.org/10.1145/2667317.2667331
[39]
Anna Korina Loumidi, Steffi Mittag, William Brian Lathrop, and Frank Althoff. 2011. Eco-driving incentives in the North American market. In Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '11, 185. https://doi.org/10.1145/2381416.2381446
[40]
Anders Lundström and Cristian Bogdan. 2014. Having a Lead Foot? Exploring how to Visualize Energy Consumption and Driving in Electric Cars. In Proceedings of the 6th International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '14, 1--4. https://doi.org/10.1145/2667239.2667303
[41]
Rich C. McIlroy, Neville A. Stanton, and Louise Godwin. 2017. Good vibrations: Using a haptic accelerator pedal to encourage eco-driving. Transportation Research Part F: Traffic Psychology and Behaviour 46: 34--46. https://doi.org/10.1016/J.TRF.2017.01.002
[42]
Ronald W. McLeod and Helen E. Ross. 1983. Optic-Flow and Cognitive Factors in Time-to-Collision Estimates. Perception 12, 4: 417--423. https://doi.org/10.1068/p120417
[43]
Felicitas Mensing, Eric Bideaux, Rochdi Trigui, and Helene Tattegrain. 2013. Trajectory optimization for eco-driving taking into account traffic constraints. Transportation Research Part D: Transport and Environment 18: 55--61. https://doi.org/10.1016/J.TRD.2012.10.003
[44]
John A. Michon. 1985. A Critical View of Driver Behavior Models: What Do We Know, What Should We Do? In Human Behavior and Traffic Safety. Springer US, Boston, MA, 485--524. https://doi.org/10.1007/978-1-4613-2173-6_19
[45]
Maria L. Montoya Freire, Dominic Potts, Niraj Ramesh Dayama, Antti Oulasvirta, and Mario Di Francesco. 2019. Foraging-based optimization of pervasive displays. Pervasive and Mobile Computing 55: 45--58. https://doi.org/10.1016/J.PMCJ.2019.02.008
[46]
Jeremy Neubauer and Eric Wood. 2014. Thru-life impacts of driver aggression, climate, cabin thermal management, and battery thermal management on battery electric vehicle utility. Journal of Power Sources 259: 262--275. https://doi.org/10.1016/J.JPOWSOUR.2014.02.083
[47]
Giovanni De Nunzio, Carlos Canudas de Wit, Philippe Moulin, and Domenico Di Domenico. 2016. Eco-driving in urban traffic networks using traffic signals information. International Journal of Robust and Nonlinear Control 26, 6: 1307--1324. https://doi.org/10.1002/rnc.3469
[48]
Engin Ozatay, Umit Ozguner, and Dimitar Filev. 2017. Velocity profile optimization of on road vehicles: Pontryagin's Maximum Principle based approach. Control Engineering Practice 61: 244--254. https://doi.org/10.1016/J.CONENGPRAC.2016.09.006
[49]
Sanna M. Pampel, Samantha L. Jamson, Daryl L. Hibberd, and Yvonne Barnard. 2015. How I reduce fuel consumption: An experimental study on mental models of eco-driving. Transportation Research Part C: Emerging Technologies 58: 669--680. https://doi.org/10.1016/J.TRC.2015.02.005
[50]
Sanna M. Pampel, Samantha L. Jamson, Daryl L. Hibberd, and Yvonne Barnard. 2018. Old habits die hard? The fragility of eco-driving mental models and why green driving behaviour is difficult to sustain. Transportation Research Part F: Traffic Psychology and Behaviour 57: 139--150. https://doi.org/10.1016/J.TRF.2018.01.005
[51]
Nicolas Petit and Antonio Sciarretta. 2011. Optimal drive of electric vehicles using an inversion-based trajectory generation approach. IFAC Proceedings Volumes 44, 1: 14519--14526. https://doi.org/10.3182/20110828-6-IT-1002.01986
[52]
Claudia Pieke, Waldemar Stark, Felix Pfister, and Christian Schyr. 2017. DLG powermix on the dynamometer. ATZoffhighway worldwide 10, 2: 26--31. https://doi.org/10.1007/s41321-017-0018-3
[53]
SAE. 2014. Taxonomy and definitions for terms related to on-road motor vehicle automated driving systems. SAE International J3016, 1--12. https://doi.org/https://doi.org/10.4271/j3016_201401
[54]
Jeffrey S. Saltz and Jeffrey M. Stanton. 2017. An introduction to data science. SAGE Publications, Thousand Oaks, CA, USA.
[55]
Dario D. Salvucci and Rob Gray. 2004. A Two-Point Visual Control Model of Steering. Perception 33, 10: 1233--1248. https://doi.org/10.1068/p5343
[56]
T. M. Schouten, J. W. Bolderdijk, and L. Steg. 2014. Framing car fuel efficiency: linearity heuristic for fuel consumption and fuel-efficiency ratings. Energy Efficiency 7, 5: 891--901. https://doi.org/10.1007/s12053-014-9260-z
[57]
Doreen Schwarze, Matthias G. Arend, and Thomas Franke. 2019. The Effect of Displaying Kinetic Energy on Hybrid Electric Vehicle Drivers' Evaluation of Regenerative Braking. In Advances in Intelligent Systems and Computing. Springer, Cham, 727--736. https://doi.org/10.1007/978-3-319-96068-5_78
[58]
A. Sciarretta, L. Serrao, P.C. Dewangan, P. Tona, E.N.D. Bergshoeff, C. Bordons, L. Charmpa, Ph. Elbert, L. Eriksson, T. Hofman, M. Hubacher, P. Isenegger, F. Lacandia, A. Laveau, H. Li, D. Marcos, T. Nüesch, S. Onori, P. Pisu, J. Rios, E. Silvas, M. Sivertsson, L. Tribioli, A.-J. van der Hoeven, and M. Wu. 2014. A control benchmark on the energy management of a plug-in hybrid electric vehicle. Control Engineering Practice 29: 287--298. https://doi.org/10.1016/J.CONENGPRAC.2013.11.020
[59]
Antonio Sciarretta, Giovanni De Nunzio, and L. L. Ojeda. 2015. Optimal Ecodriving Control: Energy-Efficient Driving of Road Vehicles as an Optimal Control Problem. IEEE Control Systems 35, 5: 71--90. https://doi.org/10.1109/MCS.2015.2449688
[60]
Michael Sivak and Brandon Schoettle. 2012. Eco-driving: Strategic, tactical, and operational decisions of the driver that influence vehicle fuel economy. Transport Policy 22: 96--99. https://doi.org/10.1016/J.TRANPOL.2012.05.010
[61]
Maria Staubach, Norbert Schebitz, Nicola Fricke, Caroline Schießl, Martin Brockmann, and Detlef Kuck. 2014. Information modalities and timing of ecological driving support advices. IET Intelligent Transport Systems 8, 6: 534--542. https://doi.org/https://doi.org/10.1049/iet-its.2013.0021
[62]
Helena Strömberg, Pontus Andersson, Susanne Almgren, Johan Ericsson, MariAnne Karlsson, and Arne Nåbo. 2011. Driver interfaces for electric vehicles. In Proceedings of the 3rd International Conference on Automotive User Interfaces and Interactive Vehicular Applications - AutomotiveUI '11, 177. https://doi.org/10.1145/2381416.2381445
[63]
Heikki Summala. 2007. Towards Understanding Motivational and Emotional Factors in Driver Behaviour: Comfort Through Satisficing. In Modelling Driver Behaviour in Automotive Environments. Springer London, London, 189--207. https://doi.org/10.1007/978-1-84628-618-6_11
[64]
Pang-Ning Tan, Michael Steinbach, Vipin Kumar, and Anuj Karpatne. 2019. Introduction to Data Mining, Global Edition. Pearson Education Limited, Harlow, UK.
[65]
Richard H. Thaler. 1999. Mental accounting matters. Journal of Behavioral Decision Making 12, 3: 183--206. https://doi.org/10.1002/(SICI)1099-0771(199909)12:3<183::AID-BDM318>3.0.CO;2-F
[66]
Richard H. Thaler. 2000. From Homo Economicus to Homo Sapiens. Journal of Economic Perspectives 14, 1: 133--141. https://doi.org/10.1257/jep.14.1.133
[67]
Andreas Weißmann, Daniel Görges, and Xiaohai Lin. 2018. Energy-optimal adaptive cruise control combining model predictive control and dynamic programming. Control Engineering Practice 72: 125--137. https://doi.org/10.1016/J.CONENGPRAC.2017.12.001
[68]
Christopher D. Wickens, Justin G. Hollands, Simon Banbury, and Raja Parasuraman. 2015. Engineering psychology & human performance. Psychology Press, Upper Saddle River, NJ, USA. https://doi.org/https://doi.org/10.4324/9781315665177
[69]
Eugene Wu, Lilong Jiang, Larry Xu, and Arnab Nandi. 2016. Graphical Perception in Animated Bar Charts. Retrieved July 1, 2019 from http://arxiv.org/abs/1604.00080

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    AutomotiveUI '19: Proceedings of the 11th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
    September 2019
    402 pages
    ISBN:9781450368841
    DOI:10.1145/3342197
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    1. eco-driving
    2. electric vehicles
    3. energy efficiency
    4. energy interfaces

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