Combining UAV and Vehicle Detection Technology for In-Depth Analysis of Conflict Risk at Cloverleaf Interchange Weaving Areas

The weaving area is a potential bottleneck that affects the efficiency and safety of freeways and urban expressways. As a typical hub interchange, the weaving section inside the cloverleaf interchange is generally short, and the probability of vehicle collision accidents is also higher. Therefore, this paper profoundly analyzed the conflict risk of the weaving areas of cloverleaf interchanges and its influencing factors. A methodological framework based on UAV videos was constructed to identify and track vehicles and extract high-precision trajectories. Based on trajectory data, an extended time-to-collision was proposed to identify traffic conflicts and evaluate collision risks. Subsequently, the spatial distributions of traffic conflicts were examined, and the risks under different operating conditions and traffic states were discussed. Finally, a regression model was established to quantify the impact of traffic variables on conflict risks. The results show that the proportion of lateral conflicts in the cloverleaf interchange weaving area is higher and more severe than that of longitudinal conflicts. The concentrated region of traffic conflicts is the merging area at the front of the weaving area, and it presents an exponential attenuation trend with the segments of the weaving area. The conflict risk under different operating conditions and traffic states varies significantly. The conflict risks from mainline-to-ramp vehicles are higher than those from ramp-to-mainline vehicles and mainline-to-mainline vehicles. Moreover, the more congested the traffic state is, the higher the potential collision risk in the weaving area. These results can help traffic participants develop reasonable risk control plans for weaving areas.