A Comprehensive Literature Review of Traditional and Spatial Methods for Black Spot Identification in Road Crash Analysis

Abstract

The desire to greatly reduce traffic accidents, enhance road safety, and remove black spots from junctions has led to an increased interest in researching the various black spot (BS) identification systems. Conventional and spatial Black spot detection systems are created using a variety of concepts and methodologies; however, as each approach has a unique input and output based on zones, area, size, and other factors, it might not be suitable for every situation. The next step in this research is to conduct a comprehensive literature review of various Black spot detection approaches and the technology tools that support them. The goal is to identify, evaluate, and assess the acceptability, feasibility, accuracy, and appropriateness of various scenarios and parameters. Through accounting for several types of inadvertent correlation between the location of the accident and traffic information, the research discovered multiple methods for Black spot identification, each based on unique ideas and a range of methods and instruments. According to the study, each BS identification method has particular advantages and disadvantages. The principal objectives of this review are to assess the principal methods for evaluating traffic accidents, identify black spots, and explore possible distinctions between traditional and spatial traffic data analysis. To execute the statistical outcomes of occurrences that are examined, both the conventional method and GIS are used. This review paper provides an overview of three basic GIS approaches, explains a traditional method for identifying traffic incidents, and provides some often-used accident analysis tools for traffic safety.