B∗ Algorithm: Multiobjective Path Planning for Flexible Buses Traffic System

Abstract

Advances in vehicle intelligence have ushered in the rapid development of intelligent connected vehicles and the emergence of the Internet of Vehicles (IoV), greatly improving the passenger travel experience. However, as a new mode of transport, flexible public transportation presents challenges for operators in terms of reducing costs and improving passenger experiences through complex route planning. The present study introduces B^∗ as a heuristic multiobjective route planning algorithm that addresses these challenges. Using the trajectory extraction procedure (TEP) and route assignment procedure (RAP), B^∗ filters out inaccessible routes and plans efficient routes on the fly to save money and enhance the passenger experience. Experimental results show that B^∗ outperforms traditional methods in terms of shorter driving distances and reduced passenger waiting times, highlighting its potential to optimize bus utilization and improve travel experiences.