Telematics Data

Telematics data, encompassing vehicle location and driving behavior information, is increasingly used to predict driving risk and insurance claims. Current research focuses on leveraging this data, often augmented with contextual information like road type, to build predictive models, employing machine learning algorithms such as XGBoost, and exploring the use of synthetic datasets to address privacy and data scarcity concerns. These advancements offer significant potential for improving road safety through proactive risk identification and more accurate insurance pricing, while also creating new avenues for urban planning and transportation research.