Vehicle‐Composition Dependent Insights Into Wide Moving Jam Propagation Using Aerial Traffic Observations

ABSTRACT Aerial observations with cameras or drones are a valuable technology for observing traffic over time and space. One drone flight allows the observation of approx. 600 m and 20 min of traffic, while camera observations cover longer time periods and larger freeway segments when positioned consecutively. The study uses extracted individual vehicle trajectories with a sampling rate of 0.1 s to analyse the propagation of wide moving jams. A major objective is the analysis of the downstream front propagation: the study investigates vehicle composition dependent wide moving jam propagation parameters based on heavily congested segments on the freeway A8 in Germany and the I‐24 in the US. A key finding is that the downstream front velocity depends on the vehicle composition present within the wide moving jam itself, not on the overall lane‐level traffic appearance. Kerner's Three‐Phase traffic theory sets the theoretical framework identifying three distinct phases: (i) free flow traffic, (ii) synchronized flow traffic and (iii) wide moving jams. All vehicle trajectories are processed with an adapted traffic state transition model with parameters refined with a sensitivity analysis. On the A8 in Germany, the results reveal the mean downstream front velocity of a wide moving jam for passenger cars propagates at approximately to while truck‐only lanes show a tendency toward considerably faster downstream velocities of approximately to . Wide moving jams with mixed traffic appearance show intermediate downstream front velocities. Despite a lack of lane regulation for trucks to use the further right lanes in the US, several wide moving jams with car‐only appearance and mixed traffic appearance are observed. While the I‐24 dataset shows less variability in downstream front velocities, downstream front velocities around are observed for car‐only wide moving jams. Additionally, increasing truck ratios enable faster downstream front velocities around for mixed traffic appearance. The study observes mean time delays in vehicle acceleration at a downstream front differing based on the vehicle type, from passenger cars with 1.5–2.0 s to trucks with 2.5–3.0 s. High data resolution enables detailed congestion analysis demonstrating the necessity of traffic regulations and traffic information services as part of the future developments.