Tunnel Traffic Evolution during Capacity Drop Based on High-Resolution Vehicle Trajectory Data

Capacity drop is the critical phenomenon that triggers traffic congestion, while evolution very complex during a capacity drop. This study applied empirical vehicle trajectory data to explore characteristics at tunnel bottleneck section. We first construct analysis model using image processing technology extract high-precision trajectories. then analyze of process area. The results show dynamic from free flow congested where operation distinct. shows difference between and non-congested flow. driving drivers in two states are also different. influence lane-changing behavior on estimated. In state, disturbance caused by can be quickly eliminated. With increase numbers area, frequent accumulates disturbance. When reaches certain degree, congestion will occur, vehicle’s speed sharply, resulting