Coupled map car-following model and its delayed-feedback control.

Area of Science:

• Traffic flow dynamics
• Nonlinear systems analysis
• Control theory

Background:

• Traffic congestion is a significant issue in transportation systems.
• Existing car-following models often struggle to accurately predict and prevent traffic jams.
• Understanding vehicle dynamics in single-lane traffic is crucial for traffic management.

Purpose of the Study:

• To propose a novel coupled map car-following traffic model.
• To analyze the conditions leading to traffic jam formation and propagation.
• To develop a control strategy for mitigating traffic congestion.

Main Methods:

• Development of a piecewise linear optimal velocity car-following model.
• Mathematical derivation of conditions for the absence of traffic jams.
• Application of a dynamic decentralized delayed-feedback control strategy.

Main Results:

• The model demonstrates the emergence of traffic jams under varying lead-vehicle speeds.
• A specific condition was derived under which traffic jams are guaranteed to never occur.
• The proposed control strategy effectively suppresses traffic jam formation.

Conclusions:

• The coupled map car-following model provides insights into traffic jam dynamics.
• The derived condition offers a theoretical basis for jam prevention.
• Decentralized delayed-feedback control is a viable method for enhancing traffic flow stability.