CA MODELLING AND IMPROVED ALGORITHM: SAFE AND EFFICIENT DECISION MAKING FOR AUTONOMOUS DRIVING SYSTEM

Abstract

This study proposes a multi-model combinatorial congestion mitigation approach to solve the traffic problem of autonomous cars. The proposed model framework consists of three parts: a road modelling module based on meta cellular automata, a traffic flow speed prediction module consisting of an optimised long and short-term memory algorithm using a sparrow search algorithm, and a following distance prediction module that determines the optimal safe following distance using an adaptive cruise control algorithm. In simulation, this intelligent traffic model for autonomous cars can be applied to various complex traffic scenarios to improve traffic efficiency while reducing the collision risk of autonomous cars.