摘要
There is a growing concern in traffic accident rate in recent years. Using Mashhad city （Iran second populous city） traffic accident records as case study, this paper applied the combi- nation of geo-information technology and spatial-statistical analysis to bring out the influence of spatial factors in their formation. The aim of the study is to examine 4 clustering analyses to have a better understanding of traffic accidents patterns in complex urban network. In order to deploy the clustering technique in urban roads, 9331 point features for inner city traffic accidents during 12 months have been registered according to their x and y location in geographic information system （GIS）. The mentioned areas were analyzed by kernel density estimation （KDE） using ARCMAP and two other analyses using SANET 4th edition software so that the results of network analysis can be compared with traditional KDE method. In addi- tion, this research introduces five classifications for determining the eventfulness of the under study area based on standard deviation and to make priority in creating security in the area. The nearest neighbor and K-function output analysis consist of four curves and regarding the fact that for all fatal, injury and property damage only crashes, the observed value curve is above the 5% confidence interval. Accidents in the study region are more clustered than ex- pected by random chance. The importance of this study is to use GIS as a management system for accident analysis by combination of spatial-statistical methods.
There is a growing concern in traffic accident rate in recent years. Using Mashhad city （Iran second populous city） traffic accident records as case study, this paper applied the combi- nation of geo-information technology and spatial-statistical analysis to bring out the influence of spatial factors in their formation. The aim of the study is to examine 4 clustering analyses to have a better understanding of traffic accidents patterns in complex urban network. In order to deploy the clustering technique in urban roads, 9331 point features for inner city traffic accidents during 12 months have been registered according to their x and y location in geographic information system （GIS）. The mentioned areas were analyzed by kernel density estimation （KDE） using ARCMAP and two other analyses using SANET 4th edition software so that the results of network analysis can be compared with traditional KDE method. In addi- tion, this research introduces five classifications for determining the eventfulness of the under study area based on standard deviation and to make priority in creating security in the area. The nearest neighbor and K-function output analysis consist of four curves and regarding the fact that for all fatal, injury and property damage only crashes, the observed value curve is above the 5% confidence interval. Accidents in the study region are more clustered than ex- pected by random chance. The importance of this study is to use GIS as a management system for accident analysis by combination of spatial-statistical methods.
作者简介
Gholam Ali Shafabakhsh, PhD, is a professor in the Department of Civil Engineering at Semnan University. He is currently the head of the graduate faculty members of trans- portation and geotechnical engineering of Semnan University, and member of the tech- nical council of the underlying transport infrastructure and superstructure. He is also an editor and a member of the board of di- rectors of Iran pavement engineering. In addi- tion. he is member of the editorial board of the Journal of Rehabilitation in Civil Engineering.E-mail addresses： shafabakhsh@semnan.ac.irAfshin Famili is currently a doctoral student at Clemson University. He works under the supervision of Dr. Wayne Sarasua. His main research interests include spatial-temporal analysis on safety, travel behavior modeling, application of GIS in safety and statistical modeling of crash data. He is a student member of ITE.afshinf@clemson.eduMohammad Sadegh Bahadori is currently a doctoral student at University of Lisbon. He received a master＇s degree in civil engineer- ing in field of road and transportation from Semnan University and has 6 years of expe- rience and training in building construction, transportation, traffic engineering and envi- ronmental analyses projects. Sadegh is a lecturer in Ferdowsi University, Montazeri Technical College of Mashhad, Khavaran Institute of Higher Education （KHI） in Iran and an associate member of ASCE.sadegh.bahadori@tecnico.ulis-boa.pt
