摘要
随着城市化加速发展,交通拥堵已成为全球大城市面临的共同难题。高效、准确地分析与发现交通状态与影响因素的空间变化关系是优化道路交通要素配置的重要基础。提出了城市道路交通空间地理加权(road grid geographically weighted regression,RG-GWR)模型,首先以两种尺寸网格嵌套的九宫格计算区域路网承载力比率,识别出路网配置不均衡区域;然后结合实况交通态势,以地理加权回归模型计算单元网格的交通时空运行态势影响异质性参数及其回归关系,得到基于网格的邻近区域路网交通要素配置配比,实现以九宫格为单元的路网要素优化配置。以成都市核心区为例,构建了3种尺寸的空间网格,形成多级叠加的九宫格模型,计算提取了两种级别九宫格模型区域承载力参数,结果与高德实际路况匹配度分别达到62.5%与87.5%;RG-GWR模型在不同时段交通态势拟合度达到80%以上。结果表明,从空间角度分析道路交通均衡配置高效、可行,具有服务于智能化平台的广阔前景。
Objectives:With the rapid development of urbanization,traffic congestion has become a common problem faced by big cities all over the world.Scientific analysis of road network carrying capacity and traffic impact factors is a prerequisite for optimizing the spatial allocation of road traffic factors.How to give full play to the advantages of spatial information technology,efficiently and accurately analyze the balance of regional road network carrying capacity,and find the spatial change relationship between traffic state and influencing factors,is very important for alleviating urban traffic congestion.Methods:The road grid geographically weighted regression(RG-GWR) analysis method is proposed.The carrying capacity ratio of regional road network is calculated by the nine-grids model composed of two kinds of nested grids.By calculating the carrying capacity ratio of the central cell of the nine grids and analyzing the ratio according to the law of conservation of flow,the unbalanced area of road network configuration is identified.By analyzing the regression relationship between the grid cell traffic situation and the influencing factors,the traffic spacetime operation situation is obtained.Taking Chengdu city as an example,three grid models with different sizes are constructed.Results:The results match the actual road conditions of AMap by 62.5% and 87.5%,respectively.By further analyzing the traffic influencing factors,the fitting degree of RG-GWR model in traffic situation of different periods could be more than 80%.Conclusions:The grid model is an efficient and feasible method to analyze the road network carrying capacity and traffic impact factors from the perspective of space and has a broad prospect to serve the intelligent platform and intelligent transportation.
作者
姜栋
赵文吉
王艳慧
万碧玉
JIANG Dong;ZHAO Wenji;WANG Yanhui;WAN Biyu(College of Resources,Environment and Tourism,Capital Normal University,Beijing 100048,China;Chinese Society for Urban Studies,National Smart City Joint Laboratory,Beijing 100835,China)
出处
《武汉大学学报（信息科学版）》
EI
CAS
CSCD
北大核心
2023年第6期988-996,共9页
Geomatics and Information Science of Wuhan University
基金
国家重点研发计划(2021YFF0601600,2018YFB2101400,2018YFC0706000)
中欧政府间科技合作项目(776783)。
关键词
电子地图
GIS
路网承载力
网格
地理加权回归
electronic map
GIS
road network carrying capacity
grid
geographically weighted regression(GWR)
