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基于GIS的通勤班车线路优化研究 被引量:3

A Study of Optimization of Shuttle Bus Route Based on GIS
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摘要 通勤班车是企业员工上下班的重要交通方式。通过Python大数据挖掘技术分析手机信令数据,确定合肥某单位A的员工居住地分布。以20公里半径为研究范围,通过地理信息系统GIS划分208个交通小区,计算各交通小区客流需求规模。建立通勤班车线路优化模型,设立优化目标和约束条件,以先点后线的方式,规划3条通勤班车路线。通过GIS缓冲区分析,计算线路评价指标。结果显示,优化后路线覆盖率由17.8%提升为32.2%,说明模型能适应通勤线路的优化设计。 Shuttle bus is an important way for people to go to work.Through Python big data mining technology,the mobile signaling data is analyzed,and the employee’s residence distribution of enterprise A in Hefei is determined.With a radius of 20 kilometers as the study scope,208 traffic zones are divided by GIS,and the passenger flow demand of each traffic zone is calculated.The optimization model of shuttle routes is established,the optimization objectives and constraints are set up,and three shuttle routes are planned in the way of point first and then route.Through buffer analysis,the evaluation index of the route is calculated.The results show that the coverage of the optimized route is increased from 17.8%to 32.2%,which shows that the model can adapt to the optimal design of shuttle routes.
作者 肖赟 段园煜 王志辉 张成哲 Xiao Yun;Duan Yuanyu;Wang Zhihui;Zhang Chengzhe(School of Urban Construction and Transportation,Hefei University,Hefei,Anhui 230601,China)
出处 《黑龙江工业学院学报(综合版)》 2020年第6期76-82,共7页 Journal of Heilongjiang University of Technology(Comprehensive Edition)
基金 合肥学院人才基金项目(编号:18—19RC02) 安徽省交通运输厅委托研究项目(编号:2019FACN1613)。
关键词 通勤班车 GIS 手机信令数据 线路优化 shuttle bus GIS mobile signaling data route optimization
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