Open AccessRoute Optimization for Autonomous Container Truck Based on Rolling Window
Author(s) -
Qi Huang,
Zheng Guilin
Publication year - 2016
Publication title -
international journal of advanced robotic systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.394
H-Index - 46
eISSN - 1729-8814
pISSN - 1729-8806
DOI - 10.5772/64116
Subject(s) - container (type theory) , truck , ant colony optimization algorithms , computer science , path (computing) , motion planning , process (computing) , port (circuit theory) , key (lock) , window (computing) , grid , real time computing , simulation , automotive engineering , engineering , robot , computer network , algorithm , artificial intelligence , electrical engineering , mechanical engineering , geometry , computer security , mathematics , operating system
Route optimization for autonomous container truck is one of the key problems to realize the automatic container port. An environment model for container truck is built by grid method. Considering the complex and unknown construction environment of the container port, an improved ant colony optimization (IACO) algorithm based on rolling window is proposed to achieve path planning for container truck. In the simulations, it is obvious that the IACO will not only achieve a safe collision avoidance path, the length of which is shorter than the truck’s traditional route no matter how complex the environment is, but also show good analytical and disposing ability of dead ends in the path planning process. Compared with conventional ant colony optimization (ACO), the running time of IACO is shorter. The results of the simulation experiments demonstrate that the IACO is a good method which is applicable to route optimization for autonomous container truck
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