Big data analytics examines millions, if not billions of records, to unmask hidden patterns, provide actionable insights and interpretable results for various domains. One area that has great potential to leverage the value of big data and analytics is the critical analysis of traffic accidents. Investigation results help in providing an in-depth understanding of the risks and provide measures to potentially prevent these risk factors hence enhancing the well-being of individuals who may experience such accidents. This study explains existing models and proposes a data science methodology in a field where probabilistic modeling makes much sense for faster, better decision-making. The main objective of this data analytics study is to identify the high-risk factors with their apparent significance to influence the probability of injury severity on automobile crashes using a geographically representative car crash dataset. To obtain reliable, accurate, and intuitive results, a multi-step probabilistic inference model based on Bayesian Belief Network— highly-acclaimed machine learning methodology—is proposed. The underlying inference model provides researchers with a causally accurate way to explore the domain (with the subject matter expert inputs) while disengaging issues related to statistical correlations and causal effects. In this study, we also used the data to create a web-based probabilistic inference simulator, a Bayesian inference decision support tool, which will be a publicly available/accessible tool, to help decision-makers better understand and to conduct what-if analysis on variable interdependencies.

大数据分析检查数百万（如果不是数十亿）记录，以揭开隐藏的模式，为各个领域提供可操作的见解和可解释的结果。一个具有利用大数据和分析价值的巨大潜力的领域是交通事故的关键分析。调查结果有助于深入了解风险，并提供可能预防这些风险因素的措施，从而提高可能遇到此类事故的个人的福祉。这项研究解释了现有模型，并在概率建模对于更快、更好的决策非常有意义的领域中提出了一种数据科学方法。本数据分析研究的主要目标是使用具有地理代表性的车祸数据集来识别高​​风险因素，这些因素对影响车祸伤害严重程度的概率具有明显的意义。为了获得可靠、准确和直观的结果，提出了一种基于贝叶斯信念网络的多步概率推理模型——广受好评的机器学习方法。底层推理模型为研究人员提供了一种因果准确的方式来探索该领域（使用主题专家输入），同时解决与统计相关性和因果效应相关的问题。在这项研究中，我们还使用这些数据创建了一个基于网络的概率推理模拟器，一个贝叶斯推理决策支持工具，它将是一个公开可用/可访问的工具，