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.
| Original language | English |
|---|---|
| Title of host publication | New Trends on System Sciences and Engineering - Proceedings of ICSSE 2015 |
| Editors | Hamido Fujita, Shun-Feng Su |
| Publisher | IOS Press BV |
| Pages | 193-199 |
| Number of pages | 7 |
| ISBN (Electronic) | 9781614995210 |
| DOIs | |
| Publication status | Published - 2015 |
| Event | International Conference on System Science and Engineering, ICSSE 2015 - Morioka, Japan Duration: 2015 Jul 6 → 2015 Jul 8 |
Publication series
| Name | Frontiers in Artificial Intelligence and Applications |
|---|---|
| Volume | 276 |
| ISSN (Print) | 0922-6389 |
| ISSN (Electronic) | 1879-8314 |
Other
| Other | International Conference on System Science and Engineering, ICSSE 2015 |
|---|---|
| Country/Territory | Japan |
| City | Morioka |
| Period | 2015/07/06 → 2015/07/08 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Ant Colony Optimization
- Path planning
ASJC Scopus subject areas
- Artificial Intelligence
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