Design and optimization of dynamic customized bus system based on particle swarm algorithm

The study explores dynamic customized public transportation, which is emerging as a promising solution to address traffic congestion and meet varied travel demands. The purpose is to enhance the efficiency and flexibility of bus services through a passenger-centered, data-driven approach. This paper takes dynamic customized bus as the research object. First, the service process is divided into three stages: passenger reservation, route design, information feedback and ticket purchase. Its design concept focuses on demand analysis and prediction, dynamic line planning, intelligent scheduling system, passenger service platform, vehicle configuration and operation, safety and reliability guarantee and other aspects, and is committed to providing flexible and efficient services that meet personalized needs. The dynamic customized bus variable route as the research object is divided according to the functions of special airport line, tourist direct line, campus line, and the dynamic route is generated and optimized by particle group algorithm to provide the optimal route for passengers. The system supports booking two months in advance, covering popular scenic spots, and can push the best departure time and bus arrival time for passengers three hours before travel, so as to enhance the convenience and flexibility of customized buses.