Yoon, S., Yoon, S.E., Lee, U., et al. (2015) Recursive Path Planning Using Reduced States for Car-Like Vehicles on Grid Maps. IEEE Transactions on Intelligent Transportation Systems, 16, 2797-2813.
https://doi.org/10.1109/TITS.2015.2422991

has been cited by the following article:

• TITLE: Intelligent Vehicle Global Path Planning Based on Improved Particle Swarm Optimization

  AUTHORS:

  KEYWORDS: Intelligent Transportation System, Path Planning, Particle Swarm Optimization, Nonlinear Inertia Weight

  JOURNAL NAME: Open Access Library Journal, Vol.5 No.4, April 27, 2018

  ABSTRACT: 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.