The trucking industry, a vital part of the economic structure, faces numerous challenges such as greenhouse gas emissions, labor-related issues, fluctuating fuel costs, and safety concerns. These challenges intensify as the industry expands to meet growing demand. The advent of artificial intelligence has led to the development of autonomous trucks, which are seen as a promising solution to these ongoing issues. This study is the first comprehensive review of literature on autonomous trucks, organized by theme and research method. Studies are initially categorized based on the timeline of the issues investigated, divided into two main subcategories: foundational aspects of autonomous truck implementation and practical implementation and economic analysis of autonomous trucks. Research on the foundational aspects of autonomous trucks is further divided into four categories: (1) Acceptance surveys, (2) Identification of barriers, (3) Core technologies for autonomous trucks implementation, and (4) Predictions of adoption rates. Research on practical and economical aspects of autonomous trucks falls into three subcategories: (1) Infrastructure, (2) Systemic performance optimization, and (3) Cost estimation. To enhance the accuracy of this review, a more detailed classification was conducted on two specific subcategories: core technologies for autonomous truck implementation and systemic performance optimization. Additionally, the studies were also categorized based on their research methods and assumptions, which include accurate descriptions of autonomous technology, data collection methods, assumptions about the study environment, the fuel type of autonomous trucks, and approach to analysis: simultaneous or separate. This comprehensive review of the literature offers a roadmap for researchers, aiding them in identifying unique and novel research topics, thereby propelling the advancement of autonomous trucks as a viable solution to numerous challenges in the trucking industry.
