Dynamic stability analysis of mixed-composition platoons with spatially weighted cooperative control

Area of Science:

• Intelligent Transportation Systems
• Vehicle Dynamics and Control
• Traffic Flow Theory

Background:

• Mixed traffic environments comprise human-driven vehicles (HDVs) and automated vehicles (AVs), including Connected and Automated Vehicles (CAVs).
• Platoon stability and safety are critical in mixed traffic, yet the influence of CAV spatial distribution remains unquantified.
• Existing models often lack the flexibility to represent diverse vehicle compositions and the impact of CAV positioning.

Purpose of the Study:

• To develop a generalized stability modeling framework for heterogeneous platoons (HDVs, AVs, CAVs).
• To quantify the role of CAV spatial distribution on platoon stability and safety.
• To provide practical guidelines for optimizing CAV deployment in mixed traffic.

Main Methods:

• Introduction of a spatial weighting coefficient (γ) to model longitudinal CAV positioning.
• Linear stability analysis to assess theoretical stability boundaries.
• Time-domain simulations to investigate dynamic responses under varying conditions.

Main Results:

• Front- and center-loaded CAV configurations effectively suppress velocity perturbations and enhance string stability.
• Rear-loaded CAV configurations demonstrate a tendency towards early instability.
• An optimal spatial weighting coefficient (γ) range of 0.3-0.5 minimizes oscillation amplitude.

Conclusions:

• CAV spatial distribution is a decisive factor in mixed platoon stability and safety.
• Optimized CAV deployment, particularly front- or center-loading, is crucial for robust intelligent transportation systems.
• The developed framework and identified optimal γ range offer practical guidance for cooperative control strategies.