Research on Multi-Objective Urban Pedestrian Path Optimization Model: Integrating Time Efficiency and Greenery

Currently, traditional pedestrian navigation path planning focuses solely on minimizing time or distance, neglecting pedestrians’ needs for environmental comfort and travel experience. This project integrates time efficiency, path length, and greening index to propose an innovative path planning approach: a multi-objective weighted path planning model. This model abstracts urban road nodes and paths into a weighted graph G = (V, E), under a weighted function. This study integrates time efficiency (segment length and walking speed), waiting time cost (traffic light waiting time), and environmental comfort (greening index based on an inverse distance decay model C_e) into the weights. This study designs three path planning strategies: “highest efficiency”, “comfortable walk”, and “balanced recommendation”. The optimal walking path is solved using Dijkstra’s shortest path algorithm. The results show that the model can effectively balance time efficiency and comfort, providing decision support for urban residents to achieve more comfortable, safe, and green walking paths.