Sequence Calculation and Automatic Discrimination of Vehicle Merging Conflicts in Freeway Merging Areas

Abstract

The freeway is a continuous flow facility that improves the accessibility and operational efficiency of the road network. However; freeway merging areas are accident-prone areas. In order to investigate the reasons for the high occurrence of accidents in merging areas, this paper considers the dynamic nature of traffic conflicts, constructs a sequence model of merging conflicts with Time Difference to Collision (TDTC) as the index, and implements automatic identification of merging conflicts based on the LightGBM algorithm. A UAV was used to collect vehicle trajectory data at the Guanghe Freeway in Guangzhou to verify the accuracy of automatic identification, with an accuracy rate of 91%. The results show that the most important feature of severe conflicts is the choice of the merging position. In addition, the most important feature of general conflicts is the standard deviation of speed before merging. Lastly, the most important feature of minor conflicts is the longitudinal speed difference between the ramp and mainline vehicles.