The Optimized path for the public transportation of Incheon in South Korea

TL;DR

This paper presents a modified A* algorithm to optimize bus routes in Incheon, South Korea, improving real-time shortest path calculations based on passenger demand compared to traditional algorithms.

Contribution

The study introduces a modified A* algorithm tailored for real-time bus route optimization considering passenger demand in Incheon.

Findings

Modified A* outperforms Genetic and Dijkstra algorithms

Real-time shortest path computation for large datasets

Improved efficiency in public transportation routing

Abstract

Path-finding is one of the most popular subjects in the field of computer science. Pathfinding strategies determine a path from a given coordinate to another. The focus of this paper is on finding the optimal path for the bus transportation system based on passenger demand. This study is based on bus stations in Incheon, South Korea, and we show that our modified A* algorithm performs better than other basic pathfinding algorithms such as the Genetic and Dijkstra. Our proposed approach can find the shortest path in real-time even for large amounts of data(points).