Intelligent Transportation System (ITS) is able to reduce traffic jams and the
incidence of accidents, and it is the current research hotspot. Intelligent
vehicle is the key element of ITS, and path planning is one of the key technologies
of intelligent vehicle. Particle Swarm Optimization (PSO) is a swarm-based
intelligence algorithm. Using PSO for path planning can achieve good results.
In order to improve PSO to get a better path planning result, a nonlinear
inertia weight is proposed. The improved PSO and traditional PSO are compared
in a global complex environment and the simulation results show that the
improved PSO has a shorter path and better real-time performance.
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