ABSTRACT

Improve taxi service efficiency, enhance passenger satisfaction, reduce traffic congestion and environmental impact, and increase operational cost-effectiveness. The system leverages scientific data analysis and optimization algorithms to achieve efficient taxi dispatching and service quality enhancement through intelligent route planning and pick-up point optimization.Firstly, by integrating historical taxi GPS trajectory data,traffic flow data, and road network data, a comprehensive data processing platform is constructed. This platform utilizes big data technologies and machine learning algorithms to deeply mine and analyze taxi operating trajectories and passenger demand. Through an improved DBSCAN clustering algorithm and BP neural network prediction model, the system can accurately identify and predict high-demand areas for taxis, thereby optimizing the setting of pick-up points and route planning.Secondly, the system provides rich decision support functions, including real-time monitoring and dynamic adjustment. Administrators can view the operational status of taxis, the distribution of passenger demand, and traffic conditions in real- time through the system interface, making timely dispatch decisions.The system also features automatic optimization. Additionally, the system focuses on enhancing passenger satisfaction. By reducing passenger wait times and travel times and optimizing the convenience and rationality of pick-up points, the system can significantly improve the passenger travel experience. The system also offers rich user interaction features, allowing passengers to check taxi locations, booking status, and submit feedback through a mobile application.Environmentally, the system effectively reduces vehicle carbon emissions and fuel consumption by optimizing taxi operating routes and reducing idle driving, positively impacting urban environmental protection. The intelligent dispatching function of the system can also alleviate traffic congestion by reducing ineffective taxi driving on the roads, improving urban traffic efficiency..Experimental results show that the decision support system for managing taxi pick-up and drop-off points significantly improves taxi service efficiency and passenger satisfaction while effectively reducing traffic congestion and environmental pollution, demonstrating broad application prospects and promotion value.

Keywords: taxi management system, pick up point, decision support
https://doi.org/ 10.57180/zlaq6630