@inproceedings{27770d57af4b49fcb6cac8c19d79280f,
title = "Realization of an Energy-Based Ant Colony Optimization Algorithm for Path Planning",
abstract = "In this paper, we propose an energy-based ant colony optimization algorithm for path planning. Because the shortest path does not guarantee the optimal energy-conserving way, this paper utilizes the ant colony optimization algorithm to acquire the optimal energy-conserving path. For battery-powered electric vehicles, the energy consumption depends on the road condition. Therefore, according to the road condition, the update law with energy pheromone is obtained. Finally, computer simulations and real road experiments of the battery-powered electric vehicle were conducted to verify the efficiency of the proposed method.",
keywords = "Ant Colony Optimization, Path planning",
author = "Lee, {Kuan Tung} and Huang, {Shih Hua} and Sun, {Shih Hsun} and Leu, {Yih Guang}",
note = "Publisher Copyright: {\textcopyright} 2015 The authors and IOS Press. All rights reserved.; International Conference on System Science and Engineering, ICSSE 2015 ; Conference date: 06-07-2015 Through 08-07-2015",
year = "2015",
doi = "10.3233/978-1-61499-522-7-193",
language = "English",
series = "Frontiers in Artificial Intelligence and Applications",
publisher = "IOS Press BV",
pages = "193--199",
editor = "Hamido Fujita and Shun-Feng Su",
booktitle = "New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015",
}
