{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T15:53:20Z","timestamp":1776354800040,"version":"3.51.2"},"reference-count":25,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2023,3,2]],"date-time":"2023-03-02T00:00:00Z","timestamp":1677715200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Princess Nourah bint Abdulrahman University Researchers Supporting Project","award":["PNURSP2023R359"],"award-info":[{"award-number":["PNURSP2023R359"]}]},{"name":"Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia","award":["PNURSP2023R359"],"award-info":[{"award-number":["PNURSP2023R359"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This paper considers the main challenges for all components engaged in the driving task suggested by the automation of road vehicles or autonomous cars. Numerous autonomous vehicle developers often invest an important amount of time and effort in fine-tuning and measuring the route tracking to obtain reliable tracking performance over a wide range of autonomous vehicle speed and road curvature diversities. However, a number of automated vehicles were not considered for fault-tolerant trajectory tracking methods. Motivated by this, the current research study of the Differential Lyapunov Stochastic and Decision Defect Tree Learning (DLS-DFTL) method is proposed to handle fault detection and course tracking for autonomous vehicle problems. Initially, Differential Lyapunov Stochastic Optimal Control (SOC) with customizable Z-matrices is to precisely design the path tracking for a particular target vehicle while successfully managing the noise and fault issues that arise from the localization and path planning. With the autonomous vehicle\u2019s low ceilings, a recommendation trajectory generation model is created to support such a safety justification. Then, to detect an unexpected deviation caused by a fault, a fault detection technique known as Decision Fault Tree Learning (DFTL) is built. The DLS-DFTL method can be used to find and locate problems in expansive, intricate communication networks. We conducted various tests and showed the applicability of DFTL. By offering some analysis of the experimental outcomes, the suggested method produces significant accuracy. In addition to a thorough study that compares the results to state-of-the-art techniques, simulation was also used to quantify the rate and time of defect detection. The experimental result shows that the proposed DLS-DFTL enhances the fault detection rate (38%), reduces the loss rate (14%), and has a faster fault detection time (24%) than the state of art methods.<\/jats:p>","DOI":"10.3390\/e25030443","type":"journal-article","created":{"date-parts":[[2023,3,3]],"date-time":"2023-03-03T02:03:08Z","timestamp":1677808988000},"page":"443","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["Decision Fault Tree Learning and Differential Lyapunov Optimal Control for Path Tracking"],"prefix":"10.3390","volume":"25","author":[{"given":"S. Subash Chandra","family":"Bose","sequence":"first","affiliation":[{"name":"Department of Computer Science, Islamiah College (Autonomous), Vaniyambadi 635751, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Badria Sulaiman","family":"Alfurhood","sequence":"additional","affiliation":[{"name":"Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh 11671, Saudi Arabia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2514-4812","authenticated-orcid":false,"given":"Gururaj H","family":"L","sequence":"additional","affiliation":[{"name":"Department of Information Technology, Manipal Institute of Technology Bengaluru, Manipal Academy of Higher Education, Manipal 576104, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2833-7196","authenticated-orcid":false,"given":"Francesco","family":"Flammini","sequence":"additional","affiliation":[{"name":"IDSIA USI-SUPSI, University of Applied Sciences and Arts of Southern Switzerland, 6928 Manno, Switzerland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajesh","family":"Natarajan","sequence":"additional","affiliation":[{"name":"Information Technology Department, University of Technology and Applied Sciences-Shinas, Al-Aqr, Shinas 324, Oman"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheela Shankarappa","family":"Jaya","sequence":"additional","affiliation":[{"name":"Department of Electronics and Communication, SIT Siddaganga Institute of Technology, Tumkur 572103, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Raouf, I., Khan, A., Khalid, S., Sohail, M., Azad, M.M., and Kim, H.S. 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