Analyzing Road Accident Patterns: Challenges and Insights from Heat Maps

Name Institutional Affiliations Date Measuring randomness and Concentration of Road Accidents What are the challenges to analyzing data for road traffic accidents? According to Prieto Curiel, González Ramírez, and Bishop (2018), there are three leading causes of road accidents with driver and environment proving avoidable in terms of impact and occurrence while bad luck claiming no way out. However, analyzing road accident traffic data proves a challenge as no proper strategy can confirm whether a specific area has an increased probability of accounting for an accident. As the authors argue, though road geometry, road obstacle, and traffic level have a defined impact on road accident distribution, the three tend to remain unchanged for an extended period. It is challenging to compare traffic accident data in different regions over different periods in some areas. Therefore, it is imperative to advocate for change in road geometry, obstacles, and traffic levels to allow for better analysis and comparison of traffic accident data for better recommendations to become defined on how certain accidents could remain avoided. What are the authors’ main points in their discussion of heat maps? The authors argue a heat map is a tool that helps in analyzing the frequency and location of road accidents among other spatially distr