Conducting a study to investigate eco-driving strategies with battery electric vehicles - a multiple method approach

被引:13
|
作者
Guenther, Madlen [1 ]
Rauh, Nadine [1 ]
Krems, Josef F. [1 ]
机构
[1] Tech Univ Chemnitz, Cognit & Engn Psychol, Wilhelm Raabe Str 43, D-09120 Chemnitz, Germany
关键词
user behaviour; motivation; field study; eletric vehicle; multiple data source;
D O I
10.1016/j.trpro.2017.05.431
中图分类号
U [交通运输];
学科分类号
08 ; 0823 ;
摘要
The objective of our study was to present a multiple method design to examine users' eco-driving behaviour while driving a battery electric vehicle in a critical range situation. We adapted an existing research design and used a combination of users' self-reported data (questionnaires and interviews) and driving data (data logger). A sample of 53 participants drove a standardized route on which they experienced a critical range situation (marginal remaining range). We showed that this research design is also suitable for motivating eco-driving strategies and examining ecodriving behaviour. (C) 2017 The Authors. Published by Elsevier B.V.
引用
收藏
页码:2247 / 2261
页数:15
相关论文
共 50 条
  • [31] Real-Time Optimal Eco-Driving for Hybrid-Electric Vehicles
    Zhu, Jiamin
    Ngo, Caroline
    Sciarretta, Antonio
    [J]. IFAC PAPERSONLINE, 2019, 52 (05): : 562 - 567
  • [32] Evaluation of the driving performance and user acceptance of a predictive eco-driving assistance system for electric vehicles
    Chada, Sai Krishna
    Goerges, Daniel
    Ebert, Achim
    Teutsch, Roman
    Subramanya, Shreevatsa Puttige
    [J]. TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2023, 153
  • [33] Model-Based Reinforcement Learning for Eco-Driving Control of Electric Vehicles
    Lee, Heeyun
    Kim, Namwook
    Cha, Suk Won
    [J]. IEEE ACCESS, 2020, 8 : 202886 - 202896
  • [34] Design and experimental validation of eco-driving system for connected and automated electric vehicles
    Luo, Xi
    Cheng, Yifan
    Hong, Jinlong
    Dong, Shiying
    Na, Xiaoxiang
    Gao, Bingzhao
    Chen, Hong
    [J]. Control Engineering Practice, 2025, 154
  • [35] Eco-Driving Assistance System for Electric Vehicles based on Speed Profile Optimization
    Lin, Xiaohai
    Goerges, Daniel
    Liu, Steven
    [J]. 2014 IEEE CONFERENCE ON CONTROL APPLICATIONS (CCA), 2014, : 629 - 634
  • [36] Distributed Eco-Driving Control of a Platoon of Electric Vehicles Through Riccati Recursion
    Lacombe, Remi
    Gros, Sebastien
    Murgovski, Nikolce
    Kulcsar, Balazs
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2023, 24 (03) : 3048 - 3063
  • [37] Traffic Information-Based Hierarchical Control Strategies for Eco-Driving of Plug-In Hybrid Electric Vehicles
    Li, Yapeng
    Yang, Yalian
    Lin, Xianke
    Hu, Xiaosong
    [J]. IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY, 2024, 73 (03) : 3206 - 3217
  • [38] Eco-Driving at Signalized Intersections: A Multiple Signal Optimization Approach
    Yang, Hao
    Almutairi, Fawaz
    Rakha, Hesham
    [J]. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, 2021, 22 (05) : 2943 - 2955
  • [39] Carbon savings, fun, and money: The effectiveness of multiple motives for eco-driving and green charging with electric vehicles in Germany
    Kramer, Jule
    Riza, Laura
    Petzoldt, Tibor
    [J]. ENERGY RESEARCH & SOCIAL SCIENCE, 2023, 99
  • [40] A Real-Time Optimal Eco-driving Approach for Autonomous Vehicles Crossing Multiple Signalized Intersections
    Meng, Xiangyu
    Cassandras, Christos G.
    [J]. 2019 AMERICAN CONTROL CONFERENCE (ACC), 2019, : 3593 - 3598