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Traffic jerk effect in connected and autonomous vehicles under cyberattacks

Author

Listed:
  • Qiao, Yanfeng
  • Yao, Ronghan
  • Xue, Yu
  • Pan, Baofeng
  • Zhang, Wensong

Abstract

This paper proposes an extended car-following model to investigate the impacts of the traffic jerk effect on connected and autonomous vehicles (CAVs) under cyberattacks. Linear and nonlinear stability analyses are conducted to derive the neutral stability boundary and reveal the nonlinear characters. Numerical simulations under both circular and open road conditions are further performed to validate the theoretical findings. Results demonstrate that wider communication ranges enhance the stability of traffic flow; however, the improvement becomes negligible once a certain threshold is exceeded. Moreover, CAV stability is highly sensitive to cyberattacks, with falsified headway information causing severe oscillations. Importantly, incorporating the traffic jerk effect dampens traffic oscillatory behavior, accelerates recovery to steady states, and enhances the resilience of CAVs platoon against external perturbations.

Suggested Citation

  • Qiao, Yanfeng & Yao, Ronghan & Xue, Yu & Pan, Baofeng & Zhang, Wensong, 2026. "Traffic jerk effect in connected and autonomous vehicles under cyberattacks," Chaos, Solitons & Fractals, Elsevier, vol. 205(C).
    • Handle: RePEc:eee:chsofr:v:205:y:2026:i:c:s0960077925018533
    DOI: 10.1016/j.chaos.2025.117839
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