{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,16]],"date-time":"2026-01-16T00:59:36Z","timestamp":1768525176335,"version":"3.49.0"},"reference-count":24,"publisher":"MDPI AG","issue":"22","license":[{"start":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/rs13224644","type":"journal-article","created":{"date-parts":[[2021,11,19]],"date-time":"2021-11-19T02:43:09Z","timestamp":1637289789000},"page":"4644","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Tide-Inspired Path Planning Algorithm for Autonomous Vehicles"],"prefix":"10.3390","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6110-9657","authenticated-orcid":false,"given":"Heba","family":"Kurdi","sequence":"first","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"},{"name":"Mechanical Engineering Department, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA"}]},{"given":"Shaden","family":"Almuhalhel","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3764-6169","authenticated-orcid":false,"given":"Hebah","family":"Elgibreen","sequence":"additional","affiliation":[{"name":"Mechanical Engineering Department, Massachusetts Institute of Technology (MIT), Cambridge, MA 02139, USA"},{"name":"Information Technology Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"},{"name":"Artificial Intelligence Center of Advanced Studies (Thakaa), King Saud University, Riyadh 11451, Saudi Arabia"}]},{"given":"Hajar","family":"Qahmash","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"}]},{"given":"Bayan","family":"Albatati","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"}]},{"given":"Lubna","family":"Al-Salem","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6410-0244","authenticated-orcid":false,"given":"Ghada","family":"Almoaiqel","sequence":"additional","affiliation":[{"name":"Computer Science Department, College of Computer and Information Sciences, King Saud University, Riyadh 11451, Saudi Arabia"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,18]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1016\/j.comcom.2019.10.014","article-title":"Path Planning Techniques for Unmanned Aerial Vehicles: A Review, Solutions, and Challenges","volume":"149","author":"Aggarwal","year":"2020","journal-title":"Comput. Commun."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"236","DOI":"10.1016\/j.asoc.2019.01.036","article-title":"Mobile Robot Path Planning Using Membrane Evolutionary Artificial Potential Field","volume":"77","author":"Montiel","year":"2019","journal-title":"Appl. Soft Comput."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"510","DOI":"10.1016\/j.procs.2018.07.064","article-title":"Optimal Path Planning of Mobile Robot Using Hybrid Cuckoo Search-Bat Algorithm","volume":"133","author":"Saraswathi","year":"2018","journal-title":"Procedia Comput. Sci."},{"key":"ref_4","unstructured":"Russell, S.J., and Norvig, P. (2016). Artificial Intelligence: A Modern Approach, Pearson Education Limited."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"8269698","DOI":"10.1155\/2018\/8269698","article-title":"An Overview of Nature-Inspired, Conventional, and Hybrid Methods of Autonomous Vehicle Path Planning","volume":"2018","author":"Ayawli","year":"2018","journal-title":"J. Adv. Transp."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Saicharan, B., Tiwari, R., and Roberts, N. (2016, January 4). Multi Objective Optimization Based Path Planning in Robotics Using Nature Inspired Algorithms: A Survey. Proceedings of the 2016 IEEE 1st International Conference on Power Electronics, Intelligent Control and Energy Systems, Delhi, India.","DOI":"10.1109\/ICPEICES.2016.7853442"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Smys, S., Bestak, R., and Rocha, \u00c1. (2019, January 29\u201330). Simple and Coverage Path Planning for Robots: A Survey. Proceedings of the Inventive Computation Technologies, Coimbatore, Tamil Nadu, India.","DOI":"10.1007\/978-3-030-33846-6"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1016\/j.robot.2016.08.001","article-title":"Heuristic Approaches in Robot Path Planning: A Survey","volume":"86","author":"Mac","year":"2016","journal-title":"Robot. Auton. Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"291","DOI":"10.1016\/S1474-0346(03)00018-1","article-title":"Path Planning in Construction Sites: Performance Evaluation of the Dijkstra, A\u2217, and GA Search Algorithms","volume":"16","author":"Soltani","year":"2002","journal-title":"Adv. Eng. Inform."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Lin, M., Yuan, K., Shi, C., and Wang, Y. (2017, January 28). Path Planning of Mobile Robot Based on Improved A\u2217 Algorithm. Proceedings of the 2017 29th Chinese Control And Decision Conference, Chongqing, China.","DOI":"10.1109\/CCDC.2017.7979125"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1238","DOI":"10.1109\/TSMC.2017.2662623","article-title":"Roberts A Rainbow Coverage Path Planning for a Patrolling Mobile Robot With Circular Sensing Range","volume":"48","author":"An","year":"2018","journal-title":"IEEE Trans. Syst. Man Cybern. Syst."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1820","DOI":"10.1109\/ACCESS.2017.2656999","article-title":"A Green Ant-Based Method for Path Planning of Unmanned Ground Vehicles","volume":"5","author":"Jabbarpour","year":"2017","journal-title":"IEEE Access"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"435","DOI":"10.1007\/s00500-016-2045-x","article-title":"A Novel Path Planning Algorithm Based on Plant Growth Mechanism","volume":"21","author":"Zhou","year":"2017","journal-title":"Soft Comput."},{"key":"ref_14","unstructured":"Semertzidou, C., Dourvas, N.I., Tsompanas, M.-A., Adamatzky, A., and Sirakoulis, G.C. (2021, January 25\u201327). Introducing Chemotaxis to a Mobile Robot. Proceedings of the IFIP International Conference on Artificial Intelligence Applications and Innovations, Crete, Greece."},{"key":"ref_15","first-page":"1","article-title":"Optimal Robot Path Planning Using Gravitational Search Algorithm","volume":"10","author":"Purcaru","year":"2013","journal-title":"Int. J. Artif. Intell."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1080\/0952813X.2014.971442","article-title":"Optimal Path Planning for a Mobile Robot Using Cuckoo Search Algorithm","volume":"28","author":"Mohanty","year":"2016","journal-title":"J. Exp. Theor. Artif. Intell."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"64","DOI":"10.20965\/jaciii.2021.p0064","article-title":"Path Planning Based on Improved Hybrid A* Algorithm","volume":"25","author":"Tang","year":"2021","journal-title":"J. Adv. Comput. Intell. Intell. Inform."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Elkazzaz, F.S., Abozied, M.A.H., and Hu, C. (2017, January 8\u201310). Hybrid RRT\/DE Algorithm for High Performance UCAV Path Planning. Proceedings of the 2017 VI International Conference on Network, Communication and Computing, Kunming, China.","DOI":"10.1145\/3171592.3171618"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Garro, B.A., Sossa, H., and Vazquez, A.R. (2006, January 13). Path Planning Optimization Using Bio-Inspirited Algorithms. Proceedings of the 2006 Fifth Mexican International Conference on Artificial Intelligence, Apizaco, Mexico.","DOI":"10.1109\/MICAI.2006.38"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"5829","DOI":"10.1007\/s00500-016-2161-7","article-title":"An Improved Ant Colony Algorithm for Robot Path Planning","volume":"21","author":"Liu","year":"2017","journal-title":"Soft Comput."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1108\/IJIUS-07-2018-0021","article-title":"Optimal Path Planning of Mobile Robot Using the Hybrid Cuckoo\u2013Bat Algorithm in Assorted Environment","volume":"7","author":"Gunji","year":"2019","journal-title":"Int. J. Intell. Unmanned Syst."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"113816","DOI":"10.1016\/j.eswa.2020.113816","article-title":"Self-Driving Cars: A Survey","volume":"165","author":"Badue","year":"2021","journal-title":"Expert Syst. Appl."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.asoc.2015.01.067","article-title":"Mobile Robot Path Planning Using Artificial Bee Colony and Evolutionary Programming","volume":"30","year":"2015","journal-title":"Appl. Soft Comput."},{"key":"ref_24","unstructured":"(2021, November 16). Center for Operational Oceanographic Products and Services (CO-OPS) Detailed Explanation of Differential Tide Producing Forces, Available online: https:\/\/tidesandcurrents.noaa.gov\/restles3.html#:~:text=The%20Effect%20of%20Centrifugal%20Force,from%20the%20center%20of%20revolution."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/22\/4644\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:32:07Z","timestamp":1760167927000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/22\/4644"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,18]]},"references-count":24,"journal-issue":{"issue":"22","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["rs13224644"],"URL":"https:\/\/doi.org\/10.3390\/rs13224644","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,18]]}}}