Reviews on Traffic Flow Models for Autonomous Driving: The Artificial Intelligence and Cellular Automata Based Models

<div class="section abstract"><div class="htmlview paragraph">Cellular Automata (CA) has emerged as a powerful computational model that has been widely applied in the field of traffic flow simulation, effectively capturing the complex dynamic behaviors of traffic systems and variable environmental conditions. With the rapid advancements in autonomous driving technology, traditional CA traffic flow simulation models for human-driving condition are updating, especially adapting to the Artificial Intelligence (AI) integrated driving behavior of autonomous vehicle (AV). This paper conducts an analysis on the existing explorations of CA-based traffic flow modelling for AVs. First, this paper utilizes the knowledge graph analysis tool “VOSviewer” to visually represent the relations among the state of art studies. The keyword clustering helps to reveal current research hotspots and developmental trajectories. Subsequently, the paper classifies how CA models are improved to adapt the AVs, from the view of the car-following, lane-changing, AV platoon, and AV dedicated lane. Furthermore, this paper unravels how AI technologies can be integrated with CA models to enhance the accuracy and practicality of mixed traffic flow models. Finally, the paper summarizes the reviews as well as the research trends, including current research difficulties, challenges, and potential development directions, offering valuable references and insights for researchers and engineers in related fields.</div></div>