research-article

In-vehicle Human Machine Interface: An Approach to Enhance Eco-Driving Behaviors

Authors:

Pietro Di Lena,

Paola Salomoni,

Giovanni DelnevoAuthors Info & Claims

SmartObject '17: Proceedings of the 2017 ACM Workshop on Interacting with Smart Objects

Pages 7 - 12

https://doi.org/10.1145/3038450.3038455

Published: 13 March 2017 Publication History

Abstract

In the context of behavioral change for a more sustainability mobility, we designed and implemented an in-vehicle human machine interface for electric vehicles, on the basis of an approach we propose that exploits gamification and machine learning techniques. Our main goal is to equip the driver with instant and accurate eco\-driving strategies, obtaining an optimization of the energy consumption. More specifically, we have developed a prototype that collects data related to the driver's braking style and makes use of a machine learning model to forward-predict the resulting energy gain. It then accordingly fosters custom eco-driving behaviour by means of gamified interactions provided on an infotainment dashboard on the car. We have conducted some tests and this paper presents the preliminary and promising results we obtained.

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Cited By

Gödker MMoll VFranke T(2024)Energy Consumption Displays in Electric Vehicles: Differential Effects on Estimating Consumption and Experienced Energy Dynamics AwarenessHuman Factors: The Journal of the Human Factors and Ergonomics Society10.1177/00187208231222154Online publication date: 9-Jan-2024
https://doi.org/10.1177/00187208231222154
Stampf AColley MKnuth ATasci CRukzio E(2024)Examining Psychological Conflict-Handling Strategies for Highly Automated Vehicles to Resolve Legal User-Vehicle ConflictsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785118:3(1-25)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678511
Wallius EKöse D(2024)Fictional or Real? a review of how gamification types effect eco-driving on the roadTransportation Research Part F: Traffic Psychology and Behaviour10.1016/j.trf.2024.08.036107(288-300)Online publication date: Nov-2024
https://doi.org/10.1016/j.trf.2024.08.036
Show More Cited By

Index Terms

In-vehicle Human Machine Interface: An Approach to Enhance Eco-Driving Behaviors
1. Human-centered computing
  1. Interaction design
    1. Interaction design process and methods
      1. Interface design prototyping
      2. User centered design

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cover image ACM Conferences

SmartObject '17: Proceedings of the 2017 ACM Workshop on Interacting with Smart Objects

March 2017

44 pages

ISBN:9781450349024

DOI:10.1145/3038450

General Chairs:
Dirk Schnelle-Walka
Harman International, Germany
,
Florian Müller
TU Darmstadt, Germany

Copyright © 2017 ACM.

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Publication History

Published: 13 March 2017

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IUI'17

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IUI'17: 22nd International Conference on Intelligent User Interfaces

March 13, 2017

Limassol, Cyprus

Acceptance Rates

SmartObject '17 Paper Acceptance Rate 3 of 3 submissions, 100%;

Overall Acceptance Rate 3 of 3 submissions, 100%

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IUI '25

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30th International Conference on Intelligent User Interfaces

March 24 - 27, 2025

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Cited By

Gödker MMoll VFranke T(2024)Energy Consumption Displays in Electric Vehicles: Differential Effects on Estimating Consumption and Experienced Energy Dynamics AwarenessHuman Factors: The Journal of the Human Factors and Ergonomics Society10.1177/00187208231222154Online publication date: 9-Jan-2024
https://doi.org/10.1177/00187208231222154
Stampf AColley MKnuth ATasci CRukzio E(2024)Examining Psychological Conflict-Handling Strategies for Highly Automated Vehicles to Resolve Legal User-Vehicle ConflictsProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/36785118:3(1-25)Online publication date: 9-Sep-2024
https://dl.acm.org/doi/10.1145/3678511
Wallius EKöse D(2024)Fictional or Real? a review of how gamification types effect eco-driving on the roadTransportation Research Part F: Traffic Psychology and Behaviour10.1016/j.trf.2024.08.036107(288-300)Online publication date: Nov-2024
https://doi.org/10.1016/j.trf.2024.08.036
ÇÖPGEVEN NÖZKAYA HAYDIN S(2023)Açık ve uzaktan öğrenmede yapay zeka destekli oyunlaştırmaArtificial intelligence based gamification in open and distance learningAçıköğretim Uygulamaları ve Araştırmaları Dergisi10.51948/auad.12037009:1(386-407)Online publication date: 31-Jan-2023
https://doi.org/10.51948/auad.1203700
Modi TGochhait S(2023)Impact of Artificial Intelligence on Gamification: Current Applications2023 International Conference on Innovative Data Communication Technologies and Application (ICIDCA)10.1109/ICIDCA56705.2023.10099771(287-290)Online publication date: 14-Mar-2023
https://doi.org/10.1109/ICIDCA56705.2023.10099771
Presta RDe Simone FTancredi CChiesa S(2023)Nudging the Safe Zone: Design and Assessment of HMI Strategies Based on Intelligent Driver State Monitoring SystemsHCI in Mobility, Transport, and Automotive Systems10.1007/978-3-031-35678-0_10(166-185)Online publication date: 9-Jul-2023
https://doi.org/10.1007/978-3-031-35678-0_10
Stampf AColley MRukzio E(2022)Towards Implicit Interaction in Highly Automated Vehicles - A Systematic Literature ReviewProceedings of the ACM on Human-Computer Interaction10.1145/35467266:MHCI(1-21)Online publication date: 20-Sep-2022
https://dl.acm.org/doi/10.1145/3546726
Jansen PColley MRukzio E(2022)A Design Space for Human Sensor and Actuator Focused In-Vehicle Interaction Based on a Systematic Literature ReviewProceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies10.1145/35346176:2(1-51)Online publication date: 7-Jul-2022
https://dl.acm.org/doi/10.1145/3534617
Curiel-Ramirez LRamirez-Mendoza RBustamante-Bello MMorales-Menendez RLopez-Aguilar ALugo-Galeana CGarcia-Chavez A(2020)Interactive urban route evaluation system for smart electromobilityInternational Journal on Interactive Design and Manufacturing (IJIDeM)10.1007/s12008-020-00708-2Online publication date: 11-Sep-2020
https://doi.org/10.1007/s12008-020-00708-2
Khakpour AColomo-Palacios R(2020)Convergence of Gamification and Machine Learning: A Systematic Literature ReviewTechnology, Knowledge and Learning10.1007/s10758-020-09456-426:3(597-636)Online publication date: 12-Jul-2020
https://doi.org/10.1007/s10758-020-09456-4
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