How Accurate are Locations in Malaysian Accident Data? Development of a Rectification Procedure based on Nested Filtered Search Technique

GIS-Based Spatial Analysis Model for Assessing Impact and Cumulative Risk in Road Traffic Accidents via Analytic Hierarchy Process (AHP)—Case Study: Romania

“…There is currently a vast amount of literature focusing on the analysis of road accidents from several perspectives: location [4][5][6][7][8][9], weather conditions of occurrence [10], severity [11][12][13][14][15][16], traffic problem areas in terms of infrastructure [17][18][19][20], real time monitoring of incidents [21][22][23][24], and also on data analysis methods used in the study and prediction of road accidents [17,[25][26][27]. Thus, the majority of research relies on statistics that are produced, gathered, kept, and publicly released by government bodies or their authorized representatives responsible for managing, enforcing, or reporting road accident data [15,17,20,25,[28][29][30].…”

“…The diversity of study objectives and data highlight the difficulty for scholars in developing a unified analytical or predictive model. This has also been influenced by the methods of developing, calibrating, and adapting models to the socio-economic, cultural and development conditions of the areas in where they have been proposed and tested [5,32,[37][38][39]. The increasing availability of car crash data has enabled the development of a new research direction related to road accident prediction, in which machine learning analysis methods are used due to their ability to flexibly process and manage multi-dimensional data to determine crash severity [12,[40][41][42][43][44][45].…”