Bicycle queues at signalized intersections — A drone-based empirical analysis of headways, saturation flows, and time losses

Empirical evidence on macroscopic flow characteristics, capacities, and differences between different types of bicycles remains limited. In particular, long bicycle queues at signalized intersections—where cyclists incur the greatest time losses and consequently also leading to non-compliant behavior—remain insufficiently addressed. Therefore, this study investigates the traffic flow characteristics and time losses of bicycle queues at two signalized intersections in Munich, Germany. Utilizing aerial drone videos, trajectories were extracted from 154 queues during morning peak hours to analyze headways, saturation flows, time losses and non-compliant behavior. The results demonstrate that in extended waiting queues, headways for the last cyclists in the queue tend to increase, resulting in a reduction of saturation flow. Regarding vehicle types, cargo bikes exhibited significantly higher headways compared to standard bicycles. Correspondingly, time losses at intersections were significantly higher for both cargo bikes and bicycles with trailers. Despite these individual differences, fleet composition had a negligible impact on overall queue dissipation, which was primarily influenced by queue density. Finally, the significant correlation between waiting times and non-compliant behavior suggests that long delays are a main reason for such behavior. • Drone-based analysis of 154 bicycle queues during peak hours in Munich, Germany. • Long queues show increased headways beyond 18 m induced by a self-sorting effect. • Higher e-bike shares show a statistically significant but slight impact on discharge. • Cargo bikes experience higher headway and time losses but barely affect total discharge. • Non-compliant footpath usage correlates significantly with increased waiting times.