  A traffic system is a random and complex large system, which is difficult to
conduct repeated modelling and control research in a real traffic environment.
With the development of automatic driving technology, the requirements for
testing and evaluating the development of automatic driving technology are
getting higher and higher, so the application of computer technology for
traffic simulation has become a very effective technical means. Based on the
micro-traffic flow modelling, this paper adopts the vehicle motion model based
on cellular automata and the theory of bicycle intelligence to build the
simulation environment of autonomous vehicle flow. The architecture of
autonomous vehicles is generally divided into a perception system, decision
system and control system. The perception system is generally divided into many
subsystems, responsible for autonomous vehicle positioning, obstacle
recognition, traffic signal detection and recognition and other tasks. Decision
systems are typically divided into many subsystems that are responsible for
tasks such as path planning, path planning, behavior selection, motion
planning, and control. The control system is the basis of the selfdriving car,
and each control system of the vehicle needs to be connected with the
decision-making system through the bus, and can accurately control the
acceleration degree, braking degree, steering amplitude, lighting control and
other driving actions according to the bus instructions issued by the
decision-making system, so as to achieve the autonomous driving of the vehicle.
