IDEAS home Printed from https://ideas.repec.org/a/eee/transb/v126y2019icp256-279.html
   My bibliography  Save this article

Modelling car-following behaviour of connected vehicles with a focus on driver compliance

Author

Listed:
  • Sharma, Anshuman
  • Zheng, Zuduo
  • Bhaskar, Ashish
  • Haque, Md. Mazharul

Abstract

This paper incorporates the driver compliance behaviour into a connected vehicle driving strategy (CVDS) that can be integrated with traditional car-following (CF) models to better describe the connected vehicle CF behaviour. Driver compliance, a key human factor for the success of connected vehicles technology, is modelled using a celebrated theory of decision making under risk – the Prospect theory (PT). The reformulated value and weighting functions of PT are consistent with the driver compliance behaviour and also preserve the integral elements of PT. Furthermore, the connected vehicle trajectory data collected from a carefully designed advanced driving simulator experiment are utilised to calibrate CVDS integrated with Intelligent Driver Model (IDM), i.e., CVDS-IDM. The calibration results reveal that drivers in the connected environment drive safely and efficiently. Moreover, the CVDS-IDM can successfully model and predict the CF dynamics of connected vehicles and is more behaviourally and numerically sound than a traditional CF model.

Suggested Citation

  • Sharma, Anshuman & Zheng, Zuduo & Bhaskar, Ashish & Haque, Md. Mazharul, 2019. "Modelling car-following behaviour of connected vehicles with a focus on driver compliance," Transportation Research Part B: Methodological, Elsevier, vol. 126(C), pages 256-279.
    • Handle: RePEc:eee:transb:v:126:y:2019:i:c:p:256-279
    DOI: 10.1016/j.trb.2019.06.008
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0191261518306362
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.trb.2019.06.008?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier, 2013. "Prospect theory in the health domain: A quantitative assessment," Journal of Health Economics, Elsevier, vol. 32(6), pages 1057-1065.
    2. Arthur E. Attema & Werner B.F. Brouwer & Olivier l'Haridon, 2013. "A quantification of prospect theory in the health domain," Economics Working Paper Archive (University of Rennes & University of Caen) 201321, Center for Research in Economics and Management (CREM), University of Rennes, University of Caen and CNRS.
    3. Jia, Dongyao & Ngoduy, Dong, 2016. "Enhanced cooperative car-following traffic model with the combination of V2V and V2I communication," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 172-191.
    4. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    5. Nicholas Barberis & Ming Huang, 2008. "Stocks as Lotteries: The Implications of Probability Weighting for Security Prices," American Economic Review, American Economic Association, vol. 98(5), pages 2066-2100, December.
    6. Chen, Danjue & Laval, Jorge A. & Ahn, Soyoung & Zheng, Zuduo, 2012. "Microscopic traffic hysteresis in traffic oscillations: A behavioral perspective," Transportation Research Part B: Methodological, Elsevier, vol. 46(10), pages 1440-1453.
    7. Punzo, Vincenzo & Montanino, Marcello, 2016. "Speed or spacing? Cumulative variables, and convolution of model errors and time in traffic flow models validation and calibration," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 21-33.
    8. Zheng, Zuduo & Ahn, Soyoung & Chen, Danjue & Laval, Jorge, 2011. "Freeway traffic oscillations: Microscopic analysis of formations and propagations using Wavelet Transform," Transportation Research Part B: Methodological, Elsevier, vol. 45(9), pages 1378-1388.
    9. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521766555.
    10. Daniel Kahneman & Amos Tversky, 2013. "Prospect Theory: An Analysis of Decision Under Risk," World Scientific Book Chapters, in: Leonard C MacLean & William T Ziemba (ed.), HANDBOOK OF THE FUNDAMENTALS OF FINANCIAL DECISION MAKING Part I, chapter 6, pages 99-127, World Scientific Publishing Co. Pte. Ltd..
    11. Zheng, Zuduo & Ahn, Soyoung & Chen, Danjue & Laval, Jorge, 2011. "Applications of wavelet transform for analysis of freeway traffic: Bottlenecks, transient traffic, and traffic oscillations," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 372-384, February.
    12. Saifuzzaman, Mohammad & Zheng, Zuduo & Mazharul Haque, Md. & Washington, Simon, 2015. "Revisiting the Task–Capability Interface model for incorporating human factors into car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 1-19.
    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. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    15. Laval, Jorge A. & Toth, Christopher S. & Zhou, Yi, 2014. "A parsimonious model for the formation of oscillations in car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 70(C), pages 228-238.
    16. Sun, Jie & Zheng, Zuduo & Sun, Jian, 2018. "Stability analysis methods and their applicability to car-following models in conventional and connected environments," Transportation Research Part B: Methodological, Elsevier, vol. 109(C), pages 212-237.
    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. Hensher,David A. & Rose,John M. & Greene,William H., 2015. "Applied Choice Analysis," Cambridge Books, Cambridge University Press, number 9781107465923, September.
    19. Hamdar, Samer H. & Mahmassani, Hani S. & Treiber, Martin, 2015. "From behavioral psychology to acceleration modeling: Calibration, validation, and exploration of drivers’ cognitive and safety parameters in a risk-taking environment," Transportation Research Part B: Methodological, Elsevier, vol. 78(C), pages 32-53.
    20. Laval, Jorge A., 2011. "Hysteresis in traffic flow revisited: An improved measurement method," Transportation Research Part B: Methodological, Elsevier, vol. 45(2), pages 385-391, February.
    21. Chen, Danjue & Ahn, Soyoung & Laval, Jorge & Zheng, Zuduo, 2014. "On the periodicity of traffic oscillations and capacity drop: The role of driver characteristics," Transportation Research Part B: Methodological, Elsevier, vol. 59(C), pages 117-136.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Dong, Jiakuan & Gao, Zhijun & Luo, Dongyu & Wang, Jiangfeng & Chen, Lei, 2024. "Impact of beyond-line-of-sight connectivity on the capacity and stability of mixed traffic flow: An analytical and numerical investigation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 635(C).
    2. Mohammadian, Saeed & Zheng, Zuduo & Haque, Mazharul & Bhaskar, Ashish, 2023. "NET-RAT: Non-equilibrium traffic model based on risk allostasis theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    3. Calvert, Simeon C. & Schakel, Wouter J. & van Lint, J.W.C., 2020. "A generic multi-scale framework for microscopic traffic simulation part II – Anticipation Reliance as compensation mechanism for potential task overload," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 42-63.
    4. Luo, Ying & Chen, Yanyan & Lu, Kaiming & Chen, Liang & Zhang, Jian, 2024. "Modeling and analysis of heterogeneous traffic flow considering dynamic information flow topology and driving behavioral characteristics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 637(C).
    5. Li, Huamin & Jin, Shiyu, 2024. "Intelligent vehicle car-following model based on cyber physical system and its simulation under mixed traffic flow," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 634(C).
    6. Yin, Jiacheng & Li, Zongping & Cao, Peng & Li, Linheng & Ju, Yanni, 2023. "Car-following modeling based on Morse model with consideration of road slope in connected vehicles environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 622(C).
    7. Haque, Md. Mazharul & Oviedo-Trespalacios, Oscar & Sharma, Anshuman & Zheng, Zuduo, 2021. "Examining the driver-pedestrian interaction at pedestrian crossings in the connected environment: A Hazard-based duration modelling approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 150(C), pages 33-48.
    8. Wang, Lichao & Yang, Min & Li, Ye & Hou, Yiqi, 2022. "A model of lane-changing intention induced by deceleration frequency in an automatic driving environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 604(C).
    9. Ren, Wenhao & Zhao, Xiaohua & Li, Haijian & Fu, Qiang, 2024. "Traffic flow impact of mixed heterogeneous platoons on highways: an approach combining driving simulation and microscopic traffic simulation," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 643(C).
    10. Li, Zheng & Hensher, David A. & Zeng, Jingjing, 2022. "Travel choice behaviour under uncertainty in real-market settings: A source-dependent utility approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    11. Li, Xia & Xiao, Yuewen & Zhao, Xiaodong & Ma, Xinwei & Wang, Xintong, 2023. "Modeling mixed traffic flows of human-driving vehicles and connected and autonomous vehicles considering human drivers’ cognitive characteristics and driving behavior interaction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 609(C).
    12. Hua, Xuedong & Yu, Weijie & Wang, Wei & Zhao, De, 2023. "Impact of multi-class stochastic cyberattacks on vehicle dynamics and rear-end collision risks for heterogeneous traffic," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 626(C).
    13. Sun, Jie & Zheng, Zuduo & Sun, Jian, 2020. "The relationship between car following string instability and traffic oscillations in finite-sized platoons and its use in easing congestion via connected and automated vehicles with IDM based control," Transportation Research Part B: Methodological, Elsevier, vol. 142(C), pages 58-83.

    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. Saifuzzaman, Mohammad & Zheng, Zuduo & Haque, Md. Mazharul & Washington, Simon, 2017. "Understanding the mechanism of traffic hysteresis and traffic oscillations through the change in task difficulty level," Transportation Research Part B: Methodological, Elsevier, vol. 105(C), pages 523-538.
    2. 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.
    3. 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.
    4. Oh, Simon & Yeo, Hwasoo, 2015. "Impact of stop-and-go waves and lane changes on discharge rate in recovery flow," Transportation Research Part B: Methodological, Elsevier, vol. 77(C), pages 88-102.
    5. Mohammadian, Saeed & Zheng, Zuduo & Haque, Mazharul & Bhaskar, Ashish, 2023. "NET-RAT: Non-equilibrium traffic model based on risk allostasis theory," Transportation Research Part A: Policy and Practice, Elsevier, vol. 174(C).
    6. Yao, Handong & Li, Qianwen & Li, Xiaopeng, 2020. "A study of relationships in traffic oscillation features based on field experiments," Transportation Research Part A: Policy and Practice, Elsevier, vol. 141(C), pages 339-355.
    7. 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.
    8. Zheng, Shi-Teng & Jiang, Rui & Tian, Jun-Fang & Zhang, H.M. & Li, Zhen-Hua & Gao, Lan-Da & Jia, Bin, 2021. "Experimental study on properties of lightly congested flow," Transportation Research Part B: Methodological, Elsevier, vol. 149(C), pages 1-19.
    9. Saifuzzaman, Mohammad & Zheng, Zuduo & Mazharul Haque, Md. & Washington, Simon, 2015. "Revisiting the Task–Capability Interface model for incorporating human factors into car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 82(C), pages 1-19.
    10. Zheng, Zuduo & Su, Dongcai, 2016. "Traffic state estimation through compressed sensing and Markov random field," Transportation Research Part B: Methodological, Elsevier, vol. 91(C), pages 525-554.
    11. Mohammadian, Saeed & Zheng, Zuduo & Haque, Md. Mazharul & Bhaskar, Ashish, 2021. "Performance of continuum models for realworld traffic flows: Comprehensive benchmarking," Transportation Research Part B: Methodological, Elsevier, vol. 147(C), pages 132-167.
    12. Xu, Tu & Laval, Jorge, 2020. "Statistical inference for two-regime stochastic car-following models," Transportation Research Part B: Methodological, Elsevier, vol. 134(C), pages 210-228.
    13. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier & Pinto, Jose Luis, 2016. "An elicitation of utility for quality of life under prospect theory," Journal of Health Economics, Elsevier, vol. 48(C), pages 121-134.
    14. Arthur E. Attema & Marieke Krol & Job Exel & Werner B. F. Brouwer, 2018. "New findings from the time trade-off for income approach to elicit willingness to pay for a quality adjusted life year," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 19(2), pages 277-291, March.
    15. Alexander L. Brown & Taisuke Imai & Ferdinand M. Vieider & Colin F. Camerer, 2024. "Meta-analysis of Empirical Estimates of Loss Aversion," Journal of Economic Literature, American Economic Association, vol. 62(2), pages 485-516, June.
    16. Li, Baibing & Hensher, David A., 2017. "Risky weighting in discrete choice," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 1-21.
    17. Kpegli, Yao Thibaut & Corgnet, Brice & Zylbersztejn, Adam, 2023. "All at once! A comprehensive and tractable semi-parametric method to elicit prospect theory components," Journal of Mathematical Economics, Elsevier, vol. 104(C).
    18. Sharma, Anshuman & Zheng, Zuduo & Bhaskar, Ashish, 2019. "Is more always better? The impact of vehicular trajectory completeness on car-following model calibration and validation," Transportation Research Part B: Methodological, Elsevier, vol. 120(C), pages 49-75.
    19. Attema, Arthur E. & Brouwer, Werner B.F. & l’Haridon, Olivier & Pinto, Jose Luis, 2015. "Estimating sign-dependent societal preferences for quality of life," Journal of Health Economics, Elsevier, vol. 43(C), pages 229-243.
    20. Kairies-Schwarz, Nadja & Kokot, Johanna & Vomhof, Markus & Weßling, Jens, 2017. "Health insurance choice and risk preferences under cumulative prospect theory – an experiment," Journal of Economic Behavior & Organization, Elsevier, vol. 137(C), pages 374-397.

    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:eee:transb:v:126:y:2019:i:c:p:256-279. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description .

    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.