Analysis of driving behavior in weak lane disciplined traffic at the merging and diverging sections using unmanned aerial vehicle data

The complexity of vehicular interactions at the merging and diverging sections is more severe due to the multiple decisions the driver has to make in a short time. The present study investigates and quantifies the driving behavior at the toll plaza's merging and diverging sections. High-quality trajectory data for more than 7500 vehicle trajectories was derived from traffic video footage recorded by two Unmanned Aerial Vehicles (UAVs) operating concurrently upstream and downstream of the toll plaza. The data was extracted at 5 Hz, generating more than 5 million data points for the study. This approach facilitated a comprehensive and simultaneous capture of traffic dynamics. Various macroscopic and microscopic traffic parameters, like lateral and longitudinal speeds, following time, perception time, longitudinal standstill distance, and lateral clearance in the upstream and downstream sections, have been determined under weak lane disciplined traffic conditions. The mean speed in the merging section is 33.13 % lower than in the diverging section. Additionally, the average lateral speed in the merging section is 1.65 km/h, in contrast to 2.08 km/h in the diverging section, reflecting a 26 % increase. The lane changing and merging is prominent only up to 120 m to 140 m from the toll plaza in the merging section, and for diverging, 100 m to 200 m towards the toll plaza. The average following time in the diverging section is 5.7 s; for the merging section, it is 6.94 s, which is 13.86 % higher. The average perception time for the diverging section is 15.32 s; for the merging section, it is 13.13 s, which is 14.29 % lower. It has been observed that lateral clearance has a concave relationship with the speed in the merging section, whereas a convex relationship is in the diverging section due to the geometrical changes. The results presented in the study are expected to imitate heterogeneous traffic conditions observed in the field more realistically and will accelerate the understanding of behavioral aspects in complex interactive environments like that at merging and diverging sections of toll plazas.