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January 10, 2024Open Access

A novel lattice model considering traffic flow gradient estimation information on curved road in CPS environment

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Authors

YKYirong KangGuizhou Institute of TechnologyCTChuan TianChinese Academy of Sciences

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Overview

Simulation study demonstrates reduced congestion from traffic flow gradient estimation on curved roads, indicating that driver anticipation in cyber-physical networks stabilizes traffic.

Key Points

  • Investigate how driver anticipation of traffic flow gradients influences traffic stability and congestion on curved roads within a cyber-physical systems environment.
  • Formulated an improved curved-road lattice hydrodynamic model incorporating mechanical road curvature properties and a flow gradient parameter representing driver anticipation.
  • Derived traffic stability criteria using linear stability theory and extracted density wave solutions across stable, unstable, and metastable regions via the perturbation reduction method.
  • Conducted numerical simulations to evaluate the spatiotemporal evolution of traffic congestion under varying road radians and gradient information conditions.
  • Traffic gradient estimation information significantly enhanced control stability and suppressed traffic congestion on curved road segments.
  • Macroscopic traffic flow stability along curved roads improved as road radian increased under identical initial vehicle density conditions.

Cite This Study

Kang et al. (2024) studied this question.

synapsesocial.com/papers/6aa28d69c1342f4f607f63dehttps://doi.org/10.21203/rs.3.rs-3837387/v1
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