Research Review of"Door-to-Door"Intercity Travel Path Planning for Passengers
With the accelerated advancement of urban agglomeration integration,intercity travel demand is increasingly growing.To enhance the quality of passenger travel services and promote green travel,this study comprehensively reviewed Chinese and international research achievements over the past decade on"door-to-door"travel path planning.It systematically analyzed the modeling of path planning problems for single-mode and multimodal travel and summarized the characteristics and applicable scenarios of path search algorithms such as the shortest path algorithm,A* algorithm,and Dijkstra algorithm.In terms of travel path recommendations,methods based on various data types(e.g.,survey data and historical travel trajectory data)were reviewed,with detailed discussions on the application progress of artificial intelligence algorithms,particularly deep learning and reinforcement learning technologies,in feature extraction and recommendation model construction.Future research should focus on the intelligent integration and optimization of multimodal transportation,the construction of more refined travel service systems,and the realization of"end-to-end"path planning systems,so as to promote intelligent transportation development and optimize green travel.
Travel Path PlanningPath SearchPath RecommendationPersonalizationMobility as a Service
国家科技期刊平台
NSTL
万方数据
