Distributional Heterogeneity of Longitudinal Driving‐Behavior Parameters Across Vehicle‐Interaction Modes in Real‐World Mixed Traffic: Evidence From UAV Aerial Trajectory Data

The increasing deployment of connected and automated vehicles (CAVs) challenges the behavioral‐homogeneity assumption of classical traffic‐flow theory, yet direct empirical evidence on how microscopic longitudinal driving behavior varies across vehicle‐interaction modes in real‐world mixed traffic remains limited. Existing simulation and driving‐simulator studies rely on idealized CAV control assumptions, while trajectory‐based studies frequently adopt inverse calibration of predefined car‐following models, introducing model‐structure assumptions, parameter non‐identifiability, and equifinality. Using same‐source unmanned aerial vehicle (UAV) trajectory data from an urban open‐road test segment, this study develops a regime‐based empirical framework to identify and quantify four driving‐behavior parameters: minimum time headway ( T _min ) in the steady car‐following regime, minimum standstill net gap ( s _min ) in the full‐stop regime, maximum deceleration ( d _max ) in the closing‐in car‐following regime, and maximum acceleration ( a _max ) in the free‐flow acceleration regime. For each parameter, regime‐specific trajectory episodes are identified, values are extracted using within‐regime quantile‐based statistics, and threshold sensitivity is described by comparing sample retention and parameter medians across 196 discrete candidate combinations. Empirical distributions are profiled in terms of central location, dispersion, skewness, kurtosis, and tail behavior; cross‐mode differences are quantified using the first‐order Wasserstein distance and Cliff’s δ . In the observed mixed‐traffic setting, behavioral heterogeneity manifests not only through mean‐level shifts but also through systematic distributional reshaping. Relative to the HDV–HDV reference group, CAV–HDV interactions exhibit a substantial upward shift and stronger concentration in T _min , whereas HDV–CAV interactions show larger and more dispersed s _min . For d _max , both heterogeneous interaction modes attenuate the high‐intensity braking tail, with HDV–CAV showing a more pronounced downward shift. In the free‐flow acceleration regime, CAVs exhibit slightly higher and more concentrated a _max values than HDVs. These findings provide same‐source empirical evidence for microscopic longitudinal driving‐behavior heterogeneity and offer parameter‐level references for interaction‐mode‐specific simulation, tail modeling, capacity analysis, and disturbance‐propagation studies.