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Tide-Inspired Path Planning Algorithm for Autonomous Vehicles
Name
remotesensing-13-04644.pdf
Size
3.36 MB
Format
Adobe PDF
Checksum (MD5)
ea9de807ba59933bdbf0c3206744a50e
Author(s)
Kurdi, Heba
Almuhalhel, Shaden
Elgibreen, Hebah
Qahmash, Hajar
Albatati, Bayan
Al-Salem, Lubna
Almoaiqel, Ghada
Date Issued
November 18, 2021
Publisher
Multidisciplinary Digital Publishing Institute
Citation
Remote Sensing 13 (22): 4644 (2021)
Version
Final published version
Abstract
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 succeeded 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.
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Creative Commons Attribution
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.3390/rs13224644
