GIS-Based Spatial Analysis of Accident Hotspots: A Nigerian Case Study

被引:13
|
作者
Afolayan, Abayomi [1 ]
Easa, Said M. [2 ]
Abiola, Oladapo S. [1 ]
Alayaki, Funmilayo M. [1 ]
Folorunso, Olusegun [3 ]
机构
[1] Fed Univ Agr, Dept Civil Engn, PMB 2240, Abeokuta 2240, Nigeria
[2] Toronto Metropolitan Univ, Depatrment Civil Engn, Toronto, ON M5B 2K3, Canada
[3] Fed Univ Agr, Dept Comp Sci, PMB 2240, Abeokuta 2240, Nigeria
关键词
accidents; geographic information system; highway; hotspots; identification; KERNEL DENSITY-ESTIMATION; HAZARDOUS ROAD LOCATIONS; TRAFFIC ACCIDENTS; IDENTIFICATION; NETWORK; HIGHWAY; SPOTS;
D O I
10.3390/infrastructures7080103
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
This study identified high-risk locations (hotspots) using geographic information systems (GIS) and spatial analysis. Five years of accident data (2013-2017) for the Lokoja-Abuja-Kaduna highway in Nigeria were used. The accident concentration analysis was conducted using the mean center analysis and Kernel density estimation method. These locations were further verified using Moran's I statistics (spatial autocorrelation) to determine their clustering with statistical significance. Fishnet polygon and network spatial weight matrix approaches of the Getis-Ord Gi* statistic were used in the hotspot analysis. Hotspots exist for 2013, 2014, and 2017 with a significance level between 95-99%. However, hotspots for 2015 and 2016 have a low significance level and the pattern is random. The spatial autocorrelation analysis of the overall accident locations and the Moran's I statistic showed that the distribution of the accidents on the study route is random. Thus, preventive measures for hotspot locations should be based on a yearly hotspot analysis. The average daily traffic values of 31,270 and 16,303 were obtained for the northbound and southbound directions of the Abaji-Abuja section. The results show that hotspot locations with high confidence levels are at points where there are geometric features.
引用
收藏
页数:23
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