Artificial Intelligence for Autonomous Vehicles: The Future of Driverless Technology

With the advent of advanced technologies in AI, driverless vehicles have elevated curiosity among various sectors of society. The automotive industry is in a technological boom with autonomous vehicle concepts. Autonomous driving is one of the crucial application areas of Artificial Intelligence (AI). Autonomous vehicles are armed with sensors, radars, and cameras. This made driverless technology possible in many parts of the world. In short, our traditional vehicle driving may swing to driverless technology. Many researchers are trying to come out with novel AI algorithms that are capable of handling driverless technology. The current existing algorithms are not able to support and elevate the concept of autonomous vehicles. This addresses the necessity of novel methods and tools focused to design and develop frameworks for autonomous vehicles.

There is a great demand for energy-efficient solutions for managing the data collected with the help of sensors. These operations are exclusively focused on non-traditional programming approaches and depend on machine learning techniques, which are part of AI. There are multiple issues that AI needs to resolve for us to achieve a reliable and safe driverless technology.

The purpose of this book is to find effective solutions to make autonomous vehicles a reality, presenting their challenges and endeavors. The major contribution of this book is to provide a bundle of AI solutions for driverless technology that can offer a safe, clean, and more convenient riskless mode of transportation.

隨著人工智慧技術的進步，無人駕駛車輛引起了社會各界的好奇心。汽車行業正處於自主駕駛概念的技術繁榮時期。自主駕駛是人工智慧的重要應用領域之一。無人駕駛車輛配備了傳感器、雷達和攝像頭，這使得無人駕駛技術在世界各地成為可能。簡而言之，我們傳統的駕駛方式可能會轉向無人駕駛技術。許多研究人員正在努力提出新穎的人工智慧算法，以應對無人駕駛技術。目前現有的算法無法支持和提升自主駕駛車輛的概念。這就需要新的方法和工具，專注於設計和開發自主駕駛車輛的框架。

對於通過傳感器收集的數據，有一個對節能解決方案的巨大需求。這些操作專注於非傳統的編程方法，依賴於機器學習技術，這是人工智慧的一部分。人工智慧需要解決多個問題，以實現可靠和安全的無人駕駛技術。

本書的目的是找到有效的解決方案，使無人駕駛車輛成為現實，並介紹其挑戰和努力。本書的主要貢獻是提供一系列針對無人駕駛技術的人工智慧解決方案，可以提供一種安全、清潔和更便利的無風險交通方式。

Sathiyaraj Rajendran, PhD, is an assistant professor in the School of Engineering & Technology at the Chikka Muniyappa Reddy University, Bangalore. He completed his PhD at Anna University, Chennai. He has more than nine years of experience and has collaborated actively with researchers in several other disciplines of computer science, particularly traffic prediction systems and intelligent systems. Additionally, he has authored more than 25 publications and filed five patents.

Munish Sabharwal, PhD, is a professor and dean in the School of Computing Science & Engineering, Galgotias University, Greater Noida, India, as well as an adjunct professor in the department of Applied Mathematics and IT at Samarkand State University, Samarkand, Uzbekistan. He has contributed over 21 years in teaching, education management, research, and software development. Additionally, he has published more than 55 research papers in conferences and journals and three books.

Yu-Chen Hu, PhD, is a professor in the Department of Computer Science and Information Management, Providence University, Sha-Lu, Taiwan. He is a senior member of Institute of Electrical and Electronics Engineers. He is also a member of Computer Vision, Graphics, and Image Processing (CVGIP), the Chinese Cryptology and Information Security Association (CCISA), Computer Science and Information Management (CSIM), and the Phi Tau Phi Society of the Republic of China. His research interests include digital forensics, information hiding, image and signal processing, data compression, information security, and data engineering.

Rajesh Kumar Dhanaraj, PhD, is an associate professor in the School of Computing Science and Engineering at Galgotias University, Greater Noida, Uttar Pradesh, India. He has published over 35 articles in various journals and conference proceedings and contributed chapters to many books. In addition to his teaching role, he is also an Expert Advisory Panel Member of Texas Instruments Inc., USA.

Balamurugan Balusamy is a professor at Galgotias University, Greater Noida, Uttar Pradesh, India with over 14 years of experience. He has published close to 30 books on various technologies, as well as over 150 quality journal, conference, and book chapters combined, visiting over 15 countries for his technical discourse. He serves on the advisory committee for several startups and forums and does consultancy work for the industry on Industrial Internet of Things.

Sathiyaraj Rajendran博士是班加羅爾Chikka Muniyappa Reddy大學工程與技術學院的助理教授。他在安娜大學完成了博士學位。他擁有超過九年的經驗，並與計算機科學的其他領域的研究人員積極合作，尤其是交通預測系統和智能系統。此外，他還撰寫了25多篇論文並申請了五項專利。

Munish Sabharwal博士是印度Greater Noida的Galgotias大學計算科學與工程學院的教授和院長，也是Samarkand State大學應用數學和信息技術系的兼職教授。他在教學、教育管理、研究和軟件開發方面貢獻了超過21年。此外，他在會議和期刊上發表了55多篇研究論文和三本書。

Yu-Chen Hu博士是臺灣沙鹿的靜宜大學計算機科學與資訊管理系的教授。他是電機與電子工程師學會的高級會員，也是計算機視覺、圖形和圖像處理（CVGIP）、中國密碼學與信息安全協會（CCISA）、計算機科學與信息管理（CSIM）以及中華民國Phi Tau Phi學會的成員。他的研究興趣包括數字取證、信息隱藏、圖像和信號處理、數據壓縮、信息安全和數據工程。

Rajesh Kumar Dhanaraj博士是印度Uttar Pradesh Greater Noida的Galgotias大學計算科學與工程學院的副教授。他在各種期刊和會議論文中發表了35多篇文章，並為許多書籍撰寫了章節。除了教學工作外，他還是美國德州儀器公司的專家顧問委員會成員。

Balamurugan Balusamy是印度Uttar Pradesh Greater Noida的Galgotias大學的教授，擁有超過14年的經驗。他出版了近30本關於各種技術的書籍，並在質量優良的期刊、會議和書籍章節中發表了150多篇文章，並在15個國家進行了技術演講。他是幾家初創企業和論壇的顧問委員會成員，並為工業物聯網領域的行業提供諮詢服務。