  In dense and dynamic scenarios, planning a safe and comfortable trajectory is
full of challenges when traffic participants are driving at high speed. The
classic graph search and sampling methods first perform path planning and then
configure the corresponding speed, which lacks a strategy to deal with the
high-speed obstacles. Decoupling optimization methods perform motion planning
in the S-L and S-T domains respectively. These methods require a large free
configuration space to plan the lane change trajectory. In dense dynamic
scenes, it is easy to cause the failure of trajectory planning and be cut in by
others, causing slow driving speed and bring safety hazards. We analyze the
collision relationship in the spatio-temporal domain, and propose an
instantaneous analysis model which only analyzes the collision relationship at
the same time. In the model, the collision-free constraints in 3D
spatio-temporal domain is projected to the 2D space domain to remove redundant
constraints and reduce computational complexity. Experimental results show that
our method can plan a safe and comfortable lane-changing trajectory in dense
dynamic scenarios. At the same time, it improves traffic efficiency and
increases ride comfort.
