Artificial Intelligent Public Bus Arrivals for Smart Cities: A Survey

Abstract

This paper aims to explore the applications of smart bus systems and itgives an overview of the main terms related to public transportation systems in smart cities and introduces several relevant technologies. The study explores the application of machine learning and related technologies to enhance bus arrival predictions within smart city frameworks by reviewing 120 papers selected from IEEE Xplore, Google Scholar and arXiv. Key findings categorize research into four areas revealing a balanced distribution as depicted. The survey traces the evolution from early GPS-based methods to integrated data-driven approaches, highlighting improvements in prediction accuracy, urban efficiency, and passenger experience, while noting challenges. Statistical analysis of publication trends from 2002 to 2025, with a peak of 16 papers in 2017, underscores growing interest, offering a valuable reference for advancing intelligent transportation systems. By studying and analyzing the latest situations of smart bus arrivals, the paper summarizes the findings based on different applied technologies and presents several key points. Additional, this study discusses four main research topics related to smart bus arrivals and shows the potential value of smart bus arrival systems in smart cities. Through a systematic review of academic papers on smart bus arrivals, it provides a deeper understanding of the basic concepts and processes of these systems. It is expected that this review will serve as a useful reference for future research in the fields of smart buses and smart cities.