
Determining Spatial Patterns of Road Accidents at Expressway by Applying Getis-Ord Gi* Spatial Statistic
Author(s) -
Norhafizah Manap,
Muhamad Nazri Borhan,
Muhamad Razuhanafi,
Mat Yazid,
Mohd Khairul,
Azman Hambali,
Asyraf Rohan
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.c1004.1183s319
Subject(s) - hotspot (geology) , geography , statistic , cartography , statistics , transport engineering , computer science , mathematics , engineering , geophysics , geology
This paper was using Getis–Ord (Gi*) spatial statistics to identify hot spots on the controlled-access expressway. The application of the method was demonstrated through a case study by using the reported road accident cases in North-South Expressway (NSE). The method successfully identified the clusters of accidents from more than 47,359 accident records from 2016 to 2019. 25 hotspot locations were identified at this study area represents 26.81% of reported cases with the lengthiest hotspot is 31.2 km and the shortest is 300m. The largest and the second largest means of z score of hotspots were identified near to well-known high populated and busy city Kuala Lumpur with scores of 6.17243 and 6.074437. The largest z score means the more intense clustering at the location will be and statistically significance to reject the null hypothesis. This study also found that the accident hotspots tend to occur at the location where the continuous traffic flow is disturbed. There are 16 hotspot locations were identified which is equivalent to 64% from the total hotspots that occur at the location where were the existing of interchange, exit ramp, slip road, rest area or lay by spotted at the area. The interference of traffic flows including diverge and merge activities will affect the speed consistency and which if often, leads to sideswipe and rear accidents. By using GIS, the location of hotspots can be analyzed meticulously at the location. It can help in determining effective countermeasures based on the analysis of the causal factors