Emergence of longitudinal queue behavior based on topological interaction and asynchronous dynamics

Coordinated longitudinal queue behavior in biological groups, such as migratory bird flocks, remains underexplored in classical collective motion models that focus on metric-based interactions and synchronous dynamics. This study utilizes a modified self-propelled particle model incorporating topological interactions, gliding asynchrony, and limited view angle to investigate the mechanisms driving longitudinal queue formation. Simulations reveal that interacting with only two topological neighbors is critical for stable queue emergence, with an optimal view angle range of [200°, 270°] balancing frontward tracking and lateral collision avoidance. Gliding asynchrony enhances queue formation efficiency by reducing neighbor interaction frequency, leading to higher success rates and lower interaction complexity compared to synchronous or random update mechanisms. Topological interaction networks exhibit high connectivity and stability, fundamentally supporting queue maintenance, while metric-based or Voronoi interactions fail to produce linear order. The study highlights the interplay of limited sensory perception, low neighbor connectivity, and asynchronous dynamics in self-organized migration queues, providing a theoretical guidance for understanding animal collective behavior and guiding robotic swarm design.