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Path Planning Algorithm for Vehicles Based on Time-dependent Optimization Criterion

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4 Author(s)
Qing Li ; Ryerson Univ., Toronto ; Sijiang Xie ; Xinhai Tong ; Guangjun Liu

A specialized genetic algorithm is proposed in this paper for path planning of vehicles based on time-dependent optimization criterion. A variable signal encoding scheme is adopted to represent the path and a particular fitness function is investigated for time-dependent shortest path planning. Domain heuristic knowledge based crossover, mutation and deletion operators are also specifically designed to fit the vehicle path planning problem. Furthermore, a new fuzzy logic control algorithm is integrated to self-adaptively adjust the probabilities of crossover and mutation in the proposed genetic algorithm. Simulation for both off-line and on-line path planning under five different environments are carried out, and the comparative studies with Dijkstra and A* algorithm are presented. The simulation results show that the proposed genetic algorithm exhibits better performances such as rapid search speed and high search quality.

Published in:

Control and Automation, 2007. ICCA 2007. IEEE International Conference on

Date of Conference:

May 30 2007-June 1 2007

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