| AN INTEGRATED NETWORK-CONSTRAINED SPATIAL ANALYSIS FOR CAR ACCIDENTS: A CASE STUDY OF TEHRAN CITY, IRAN |
| Paper ID : 1294-SMPR |
| Authors: |
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Mahmoud Reza Delavar *1, Seyed Ahmad Eslami nezhad2 1North Kargar Ave., After Jalal Al Ahmad Crossing, School of Surveying and Geospatial Eng., Campus 2, College of Engineering, The University of Tehran, Tehran, Iran 2Department of Surveying and Geospatial Eng., College of Engineering, University of Tehran, Tehran, Iran |
| Abstract: |
| Research on determination of spatial clusters in urban car accidents plays an important role in improving urban safety and development. The aim of this study is to detect and statistically prioritize the accident-prone segments of an urban road network by integration of network kernel density estimation (NKDE) method and network-constrained Getis-Ord Gi* statistics. The first step involves estimating the density of car accidents in the one dimensional space of the road network using the NKDE method. This method is used to study and visualize car accidents in the network space. Due to the topology changes in the nodes of the network, in this research the density of car accidents is calculated based on the Equal-split continuous and Equal-split discontinuous kernel functions. In the second step, the result of the NKDE method is integrated with network-constrained Getis-Ord Gi* statistics to measure and compare the accident-prone segments based on the statistical parameter. We also used The Network K-Function method to display the clustering of car accidents at different interval scales. These methods were tested using the data of damage car accidents in Tehran District 3 during 2013-2017. The results of the network-constrained Getis-Ord Gi* statistics for the two kernel functions were compared at 99% confidence level. It was confirmed that for damage car accidents, the integration of NKDE method (continuous kernel function) and network-constrained Getis-Ord Gi* statistics has identified more accident-prone segments compared to those of the integration of the NKDE method (discontinuous kernel function) and the network-constrained Getis-Ord Gi* statistics. |
| Keywords: |
| Network kernel density estimation, Getis-Ord Gi*, Network K-Function |
| Status : Conditional Accept (Oral Presentation) |
