IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i14p6481-d1702258.html
   My bibliography  Save this article

A Sustainable Approach to Modeling Human-Centric and Energy-Efficient Vehicle Acceleration Profiles in Non-Car-Following Scenarios

Author

Listed:
  • Wei Deng

    (School of Big Data Statistics, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yi Luo

    (School of Management, Guizhou University of Commerce, Guiyang 550014, China)

  • Shaopeng Yang

    (School of Management, Guizhou University of Commerce, Guiyang 550014, China)

  • Yini Ren

    (Department of Rail Transit Engineering, Guizhou Communications Polytechnic University, Guiyang 551400, China)

  • Dongyi Hu

    (School of Big Data Statistics, Guizhou University of Finance and Economics, Guiyang 550025, China)

  • Yong Shi

    (School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China)

Abstract

Previous studies have described vehicle acceleration profiles in non-car-following scenarios; however, the underlying mechanisms governing these profiles remain incompletely understood. This study aims to enhance the understanding of these mechanisms by proposing an improved model based on an optimal control problem with two bounded conditions (OCP2B), segmenting vehicle acceleration curves into three distinct phases. Specifically, the proposed model imposes constraints on acceleration through maximum jerk and maximum acceleration functions, thereby capturing essential dynamics previously unexplained by conventional models. Our key contributions include establishing a comprehensive analytical framework for accurately describing vehicle acceleration profiles and elucidating critical characteristics overlooked in the prior literature. Our findings demonstrate that incorporating human-centric considerations, such as driving comfort, significantly enhances the model’s practical applicability. Moreover, the proposed approach provides crucial insights for designing autonomous vehicle (CAV) trajectories consistent with human driving behaviors and effectively predicts the movements of human-driven vehicles (HVs), thus facilitating smoother interactions and potentially reducing conflicts between CAVs and HVs.

Suggested Citation

  • Wei Deng & Yi Luo & Shaopeng Yang & Yini Ren & Dongyi Hu & Yong Shi, 2025. "A Sustainable Approach to Modeling Human-Centric and Energy-Efficient Vehicle Acceleration Profiles in Non-Car-Following Scenarios," Sustainability, MDPI, vol. 17(14), pages 1-20, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:14:p:6481-:d:1702258
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/14/6481/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/14/6481/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gipps, P.G., 1981. "A behavioural car-following model for computer simulation," Transportation Research Part B: Methodological, Elsevier, vol. 15(2), pages 105-111, April.
    2. Jin, Wen-Long, 2017. "Kinematic wave models of lane-drop bottlenecks," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 507-522.
    3. Jin, Wen-Long & Laval, Jorge, 2018. "Bounded acceleration traffic flow models: A unified approach," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 1-18.
    4. Zhang, Jian & Tang, Tie-Qiao & Yan, Yadan & Qu, Xiaobo, 2021. "Eco-driving control for connected and automated electric vehicles at signalized intersections with wireless charging," Applied Energy, Elsevier, vol. 282(PA).
    5. Pier Giuseppe Anselma, 2021. "Optimization-Driven Powertrain-Oriented Adaptive Cruise Control to Improve Energy Saving and Passenger Comfort," Energies, MDPI, vol. 14(10), pages 1-28, May.
    6. Fiori, Chiara & Ahn, Kyoungho & Rakha, Hesham A., 2016. "Power-based electric vehicle energy consumption model: Model development and validation," Applied Energy, Elsevier, vol. 168(C), pages 257-268.
    7. R. Akcelik & D. C. Biggs, 1987. "Acceleration Profile Models for Vehicles in Road Traffic," Transportation Science, INFORMS, vol. 21(1), pages 36-54, February.
    8. Newell, G. F., 2002. "A simplified car-following theory: a lower order model," Transportation Research Part B: Methodological, Elsevier, vol. 36(3), pages 195-205, March.
    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. Martínez, Irene & Jin, Wen-Long, 2020. "Optimal location problem for variable speed limit application areas," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 221-246.
    2. Jin, Wen-Long & Laval, Jorge, 2018. "Bounded acceleration traffic flow models: A unified approach," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 1-18.
    3. Zhao, Jing & Knoop, Victor L. & Wang, Meng, 2020. "Two-dimensional vehicular movement modelling at intersections based on optimal control," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 1-22.
    4. Seo, Toru & Kawasaki, Yutaka & Kusakabe, Takahiko & Asakura, Yasuo, 2019. "Fundamental diagram estimation by using trajectories of probe vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 122(C), pages 40-56.
    5. Guo, Qiangqiang & Ban, Xuegang (Jeff), 2023. "A multi-scale control framework for urban traffic control with connected and automated vehicles," Transportation Research Part B: Methodological, Elsevier, vol. 175(C).
    6. He, Zhengbing & Zheng, Liang & Guan, Wei, 2015. "A simple nonparametric car-following model driven by field data," Transportation Research Part B: Methodological, Elsevier, vol. 80(C), pages 185-201.
    7. Simin Hesami & Majid Vafaeipour & Cedric De Cauwer & Evy Rombaut & Lieselot Vanhaverbeke & Thierry Coosemans, 2023. "Dynamic Pro-Active Eco-Driving Control Framework for Energy-Efficient Autonomous Electric Mobility," Energies, MDPI, vol. 16(18), pages 1-19, September.
    8. Kai Nagel & Peter Wagner & Richard Woesler, 2003. "Still Flowing: Approaches to Traffic Flow and Traffic Jam Modeling," Operations Research, INFORMS, vol. 51(5), pages 681-710, October.
    9. Bliemer, Michiel C.J. & Loder, Allister & Zheng, Zuduo, 2024. "A novel mobility consumption theory for road user charging," Transportation Research Part B: Methodological, Elsevier, vol. 189(C).
    10. Tordeux, Antoine & Lassarre, Sylvain & Roussignol, Michel, 2010. "An adaptive time gap car-following model," Transportation Research Part B: Methodological, Elsevier, vol. 44(8-9), pages 1115-1131, September.
    11. Xiao, Guosheng & Yao, Zhihong & Zhang, Shimiao & Jiang, Yangsheng, 2024. "Cooperative eco-driving for mixed platoons at signalized intersections with wireless charging lanes," Energy, Elsevier, vol. 313(C).
    12. Tian, Junfang & Li, Guangyu & Treiber, Martin & Jiang, Rui & Jia, Ning & Ma, Shoufeng, 2016. "Cellular automaton model simulating spatiotemporal patterns, phase transitions and concave growth pattern of oscillations in traffic flow," Transportation Research Part B: Methodological, Elsevier, vol. 93(PA), pages 560-575.
    13. Tian, Junfang & Treiber, Martin & Ma, Shoufeng & Jia, Bin & Zhang, Wenyi, 2015. "Microscopic driving theory with oscillatory congested states: Model and empirical verification," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 138-157.
    14. Ponnu, Balaji & Coifman, Benjamin, 2015. "Speed-spacing dependency on relative speed from the adjacent lane: New insights for car following models," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 74-90.
    15. Chen, Jie & Hu, Maobin & Shi, Congling, 2023. "Development of eco-routing guidance for connected electric vehicles in urban traffic systems," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 618(C).
    16. Tian, Junfang & Zhu, Chenqiang & Chen, Danjue & Jiang, Rui & Wang, Guanying & Gao, Ziyou, 2021. "Car following behavioral stochasticity analysis and modeling: Perspective from wave travel time," Transportation Research Part B: Methodological, Elsevier, vol. 143(C), pages 160-176.
    17. Zheng, Zuduo, 2014. "Recent developments and research needs in modeling lane changing," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 16-32.
    18. Yeo, Hwasoo, 2008. "Asymmetric Microscopic Driving Behavior Theory," University of California Transportation Center, Working Papers qt1tn1m968, University of California Transportation Center.
    19. Wang, Pangwei & Wang, Xindi & Ye, Rongsheng & Sun, Yuanzhe & Liu, Cheng & Zhang, Juan, 2024. "Eco-driving-based mixed vehicular platoon control model for successive signalized intersections," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 639(C).
    20. Wagner, Peter, 2012. "Analyzing fluctuations in car-following," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1384-1392.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:gam:jsusta:v:17:y:2025:i:14:p:6481-:d:1702258. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.