Bayesian network evaluation of road network resilience in the Guangdong-Hong Kong-Macao Greater Bay Area city cluster
With the further increase of the urbanization rate in China,the resilience of urban road networks has attracted increasing attention.In this paper,a resilience evaluation model for the urban road network is developed based on the Bayesian network model.Then,taking the city cluster in the mainland of the Guangdong-Hong Kong-Macao Greater Bay Area as an example,the road network resilience of nine cities in the mainland part of the Guangdong-Hong Kong-Macao Greater Bay Area during the period 2000-2019 is evaluated.According to the resilience function,the functional layer is constructed based on the four indicators as resilience,stability,reconfigurability,and recovery,the nine factors as stability,variability,maintainability,reliability,serviceability,safety,robustness,repairability,and adaptability are selected to establish the performance layer,and the nine factors as passenger volume,number of buses,road area rate,number of cabs,number of traffic fatalities,public transportation investment,number of buses per 10 000 people,number of road transportation employees,and road area per capita are selected to build the factor layer.The results show that Shenzhen's road network resilience index is the highest at 60％,while Zhongshan's is the lowest at 43％.The road network resilience of Guangzhou,Shenzhen,Zhuhai,and Dongguan has been growing steadily during the period 2000-2019,while that of Foshan,Huizhou,Zhongshan,Jiangmen,and Zhaoqing fluctuates slightly.The urban road network resilience does not always increase with the GDP growth but is also related to per capita GDP.The sensitivity analysis for the elements of function layer,performance layer and factor layer in the Bayesian network model shows that the road network reconfigurability,road network reliability,and number of traffic fatalities are the most influential factors on road network resilience in their respective layers,and strengthening the links between the central city and other cities can improve the resilience of urban road networks.The research results of this paper can provide some technical references for the improvement and resilience growth of the transportation network function in the Guangdong-Hong Kong-Macao Greater Bay Area city cluster.
safety systematologyresilience evaluationBayesian networksensitivity analysisGuangdong-Hong Kong-Macao Greater Bay AreaGeographic Information Systems(GIS)
NETL
NSTL
万方数据
维普
