  With the rapid development of autonomous driving, the attention of academia
has increasingly focused on the development of anti-collision systems in
emergency scenarios, which have a crucial impact on driving safety. While
numerous anti-collision strategies have emerged in recent years, most of them
only consider steering or braking. The dynamic and complex nature of the
driving environment presents a challenge to developing robust collision
avoidance algorithms in emergency scenarios. To address the complex, dynamic
obstacle scene and improve lateral maneuverability, this paper establishes a
multi-level decision-making obstacle avoidance framework that employs the safe
distance model and integrates emergency steering and emergency braking to
complete the obstacle avoidance process. This approach helps avoid the
high-risk situation of vehicle instability that can result from the separation
of steering and braking actions. In the emergency steering algorithm, we define
the collision hazard moment and propose a multi-constraint dynamic collision
avoidance planning method that considers the driving area. Simulation results
demonstrate that the decision-making collision avoidance logic can be applied
to dynamic collision avoidance scenarios in complex traffic situations,
effectively completing the obstacle avoidance task in emergency scenarios and
improving the safety of autonomous driving.
