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Modelling decisions of control transitions and target speed regulations in full-range Adaptive Cruise Control based on Risk Allostasis Theory

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  • Varotto, Silvia F.
  • Farah, Haneen
  • Toledo, Tomer
  • van Arem, Bart
  • Hoogendoorn, Serge P.

Abstract

Adaptive Cruise Control (ACC) and automated vehicles can contribute to reduce traffic congestion and accidents. Recently, an on-road study has shown that drivers may prefer to deactivate full-range ACC when closing in on a slower leader and to overrule it by pressing the gas pedal a few seconds after the activation of the system. Notwithstanding the influence of these control transitions on driver behaviour, a theoretical framework explaining driver decisions to transfer control and to regulate the target speed in full-range ACC is currently missing.

Suggested Citation

  • Varotto, Silvia F. & Farah, Haneen & Toledo, Tomer & van Arem, Bart & Hoogendoorn, Serge P., 2018. "Modelling decisions of control transitions and target speed regulations in full-range Adaptive Cruise Control based on Risk Allostasis Theory," Transportation Research Part B: Methodological, Elsevier, vol. 117(PA), pages 318-341.
    • Handle: RePEc:eee:transb:v:117:y:2018:i:pa:p:318-341
    DOI: 10.1016/j.trb.2018.09.007
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    1. Greene, William H. & Gillman, Max & Harris, Mark N. & Spencer, Christopher, 2013. "The Tempered Ordered Probit (TOP) Model with an Application to Monetary Policy," CEI Working Paper Series 2013-04, Center for Economic Institutions, Institute of Economic Research, Hitotsubashi University.
    2. William H. Greene & David A. Hensher, 2010. "Ordered Choices and Heterogeneity in Attribute Processing," Journal of Transport Economics and Policy, University of Bath, vol. 44(3), pages 331-364, September.
    3. Vij, Akshay & Walker, Joan L., 2016. "How, when and why integrated choice and latent variable models are latently useful," Transportation Research Part B: Methodological, Elsevier, vol. 90(C), pages 192-217.
    4. 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.
    5. Hess, Stephane & Train, Kenneth E. & Polak, John W., 2006. "On the use of a Modified Latin Hypercube Sampling (MLHS) method in the estimation of a Mixed Logit Model for vehicle choice," Transportation Research Part B: Methodological, Elsevier, vol. 40(2), pages 147-163, February.
    6. Dubin, Jeffrey A & McFadden, Daniel L, 1984. "An Econometric Analysis of Residential Electric Appliance Holdings and Consumption," Econometrica, Econometric Society, vol. 52(2), pages 345-362, March.
    7. Rajagopal, 2014. "The Human Factors," Palgrave Macmillan Books, in: Architecting Enterprise, chapter 9, pages 225-249, Palgrave Macmillan.
    8. Koutsopoulos, Haris N. & Farah, Haneen, 2012. "Latent class model for car following behavior," Transportation Research Part B: Methodological, Elsevier, vol. 46(5), pages 563-578.
    9. 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.
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    2. Yongji Ma & Jinliang Xu & Chao Gao & Minghao Mu & Guangxun E & Chenwei Gu, 2022. "Review of Research on Road Traffic Operation Risk Prevention and Control," IJERPH, MDPI, vol. 19(19), pages 1-26, September.

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