Analysis of lane-change conflict between cars and trucks at merging section using UAV video data
This addresses safety issues for drivers and traffic management agencies at crash-prone merging areas, but it is incremental as it applies existing methods to new vehicle type data.
The study analyzed traffic conflicts between different vehicle types at freeway merging sections using UAV video data, finding that car-car conflicts had the smallest time-to-collision while truck-truck conflicts had the largest, with frequent conflicts at on-ramps and acceleration lanes.
The freeway on-ramp merging section is often identified as a crash-prone spot due to the high frequency of traffic conflicts. Very few traffic conflict analysis studies comprehensively consider different vehicle types at freeway merging section. Thus, the main objective of this study is to analyse conflicts between different vehicle types at freeway merging section. Field data are collected by Unmanned Aerial Vehicle (UAV) at merging areas in Shanghai, China. Vehicle extraction method is utilized to obtain vehicle trajectories. Time-to-collision (TTC) is utilized as the surrogate safety measure. TTC of car-car conflicts are the smallest while TTC of truck-truck conflicts are the largest. Traffic conflicts frequently occur at on-ramp and acceleration lane. Results show the spatial distribution of lane-change conflicts is significantly different between different vehicle types, suggesting that vehicle drivers should maintain safe distance especially car drivers. Besides, in order to decrease lane-change conflict at merging area, traffic management agencies are suggested to change dotted lie to solid lane at the beginning of acceleration lane.