CMSV: a New Cloud Multi-Agents for Self-Driving Vehicles as a Services

Abstract

The development of autonomous vehicles has changed the way of transmitting goods to users, with the potential to improve road safety and efficiency. One of the effective issues of self-driving vehicles is path planning issue. In this paper, a new system is proposed for addressing the potential of using multi-agent systems (MAS) to address path planning problems in autonomous vehicles. The system is called Cloud Multi-Agents for Self-Driving Vehicles as A Services (CMSV). It is used to solve the dependent delivery problem, where the vehicle transmits the goods/deliveries, that are dependent on each other, to specific locations in ordering or with specific directions. The new system consists of three phases: (1) converting the problem into TSP sub problems according to deliveries dependency, (2) applying GDC to select the good solutions (3) applying multi-agent system to select the optimal solution. The proposed system is compared with systems that use a genetic algorithm, Ant Colony algorithm, Particle Swarm Optimization and The Harris hawk optimization (HHO) algorithm. From the findings, we find that the proposed system is more efficient than the other systems.