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Tide-Inspired Path Planning Algorithm for Autonomous Vehicles
| Content Provider | MDPI |
|---|---|
| Author | Kurdi, Heba Almuhalhel, Shaden Elgibreen, Hebah Qahmash, Hajar Albatati, Bayan Al-Salem, Lubna Almoaiqel, Ghada |
| Copyright Year | 2021 |
| Description | With the extensive developments in autonomous vehicles (AV) and the increase of interest in artificial intelligence (AI), path planning is becoming a focal area of research. However, path planning is an NP-hard problem and its execution time and complexity are major concerns when searching for optimal solutions. Thus, the optimal trade-off between the shortest path and computing resources must be found. This paper introduces a path planning algorithm, tide path planning (TPP), which is inspired by the natural tide phenomenon. The idea of the gravitational attraction between the Earth and the Moon is adopted to avoid searching blocked routes and to find a shortest path. Benchmarking the performance of the proposed algorithm against rival path planning algorithms, such as A*, breadth-first search (BFS), Dijkstra, and genetic algorithms (GA), revealed that the proposed TPP algorithm sì³®ded in finding a shortest path while visiting the least number of cells and showed the fastest execution time under different settings of environment size and obstacle ratios. |
| Starting Page | 4644 |
| e-ISSN | 20724292 |
| DOI | 10.3390/rs13224644 |
| Journal | Remote Sensing |
| Issue Number | 22 |
| Volume Number | 13 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-11-18 |
| Access Restriction | Open |
| Subject Keyword | Remote Sensing Transportation Science and Technology Path Planning Nature-inspired Algorithms Autonomous Vehicles Transportation |
| Content Type | Text |
| Resource Type | Article |
