Research On Route Planning Method Based On Multiple Transportation Modes

In recent years,the modern urban transportation system is becoming increasingly diversified,large-scale and complicated.The use of modern information technology and the full integration of various modes of transportation to give full play to their comprehensive effectiveness has become a new way to alleviate the increasing traffic pressure in modern cities.Therefore,research on the rational travel planning of multimodal transportation is increasingly urgent.Based on the multiple transportation modes in modern cities and for the residents' personalized travel needs,this thesis studies the residents' travel route planning methods for mixed transportation modes.The main contents of this research are as follows:(1)The analysis of multiple transportation modes in modern cities.The multimodal transportation system is formed by multiple interconnected and independent transportation modes in modern cities.Playing different roles in the system,they closely cooperate and coordinate with specific functions and characteristics.Through a comprehensive analysis of the existing literature,this thesis describes and summarizes the composition,network characteristics,and operating characteristics of various typical transportation modes such as buses,subways,and taxis.(2)The modern urban multimodal transportation network model is constructed based on the analysis of the characteristics of each transportation mode.Aiming at the increasingly diversified personal travel preferences of residents,a “generalized shortest path” route planning model with the length of time,cost and number of transfers as evaluation criteria is constructed.This model proposes to mix taxi mode with other existing public transport modes,and considers the operation schedule of the bus system,so that it can better meet the more personalized travel needs of citizens.(3)Considering the large scale and complexity of the multimodal transportation route planning mode for citizens,the artificial bee colony algorithm with strong balance ability of global search and local search is adopted to solve the multi-objective “shortest path” problem.An improved adaptive artificial bee colony algorithm with adaptive mutation and source retention strategy is proposed.Comparing with the results obtained by the other algorithms,the experiments verify the effectiveness of the proposed improved artificial bee colony algorithm.