A state of art on pedestrian simulation model based on heuristic search algorithm

Abstract

A pedestrian algorithm has been used across many areas mostly in prediction such as software testing, artificial intelligence and autonomous vehicle predictions and is mostly used to consider the effect of on pedestrians’ future motion behaviors. This paper present narrative reviews different heuristic search algorithms for pedestrian prediction in the domains mentioned above. Additionally, this paper explores Heuristic Search Algorithms used in Pedestrian Simulation Models, and how can Heuristic Search Algorithms be Feasible in Spatial Layout Design Elements for Pedestrian Flow. Basic guidelines of conducting narrative review were followed. Articles outside the scope of the paper were excluded. A total 17 peer-reviewed articles from google scholar and research gate databases were identified in the search. 4 articles were included in the final review as they met the inclusion and exclusion criteria. Finally, this paper not only presents a comprehensive overview of heuristic search algorithms in pedestrian simulation models but also underscores the critical role of predictive algorithms in shaping the future of pedestrian dynamics. By identifying research gaps and proposing directions for more effective definition of interacting agents in pedestrian algorithms, this study sets the stage for transformative advancements in heuristic-based pedestrian prediction and spatial design elements.