Research On Bus Route Layout Of Regional Microcirculation Based On Large Data

Vigorously developing public transport is an important measure to alleviate the current situation of urban ground traffic congestion.In recent years,the idea of "wide road,dredging road network" has gradually been replaced by "narrow road,dense road network".Open up the city's broken roads,increase the density of road network,give full play to the functions of subtrunk roads and branches,so as to share the traffic volume of the main road.Perfect road grade provides preconditions for building hierarchical bus network system.Therefore,as a supplement to conventional bus routes and providing door-to-door service,microcirculation bus has more room for development.The microcirculation bus mainly achieves the two goals of connecting rail transit and satisfying passenger travel in the passenger area.The arrival of the era of big data provides more reliable data support for the formulation of microcirculation bus lines.In this paper,Oracle software is used to process Xi'an bus IC card,GPS data and taxi GPS data.On the one hand,the passenger flow at bus stations is obtained by conventional bus data,and the operation status of bus lines and spatial accessibility of conventional buses are analyzed.The distribution area of microcirculation buses is determined by combining the nature of land use.On the other hand,the taxi GPS data is used to accurately acquire the passenger flow at bus stations.OD clustering of passengers' travel in this region provides theoretical support for setting up waiting stations on microcirculation bus lines.The purpose of this paper is to make full use of the information obtained from the large data of buses and taxis,accurately lay out the microcirculation bus lines,solve the problem of "the last kilometer" of residents' travel,at the same time improve the bus coverage,reduce passenger travel time,and ultimately realize the efficient service of hierarchical public transport system.The main contents and innovations of this paper are as follows:Firstly,processing IC card and GPS data with Oracle software.Oracle data has the characteristics of large quantity,sharing and reliability.Oracle is used to process the IC card and GPS data of Xi'an,and Javascript API is used to get the longitude and latitude information of bus stations in the map.Through data preprocessing and identification of passenger boarding points,the passenger flow at bus stops can be obtained.Secondly,determining Potential Stations of Microcirculation Bus by Using Big Data.The taxi GPS data are studied,and the taxi departure and departure locations are obtained by density-based spatial clustering algorithm.Combined with the microcirculation bus route layout area obtained from the bus data,some starting and ending points in the area are selected as candidate stations for microcirculation bus,and the residents' travel OD matrix is obtained by Python programming.Finally,constructing a microcirculation bus route layout model.Firstly,the road network is constructed in the study area.Then,taking the minimum travel cost of residents as the main objective,the bus company uses the minimum operating cost to transport the maximum passenger volume as the secondary objective to construct a bilevel programming model.Finally,the genetic algorithm is used to solve the model.