Driving in developing cities presents numerous challenges. Traffic congestion and traffic accidents are the most visible challenges which are caused by different underlying factors. Two chief factors are poorly planned and maintained roadway infrastructure and the decisions made by the drivers. Drivers are constantly forced to negotiate road hazards, like potholes, unlabeled speed bumps as well as moving obstacles, like pushcarts, motorcycles, and animals. Current Usage Based Insurance (UBI) models do not include the context which in many cities may be paramount to understanding driver behavior. This article presents the Context-based Driver Score (CDS) model as a unified model for scoring a driver based on a unique formulation of context that includes road quality. We demonstrate the CDS model on a real-world use case in Nairobi, Kenya, where waste-collection trucks were instrumented with smartphones in order to collect inertial and telematic data. We present an analysis of the CDS model and driver behaviors in contexts that include weather, time-of-day, and road quality. Our results show that the distribution of driving behaviors, like harsh braking and swerving, vary greatly based on the context and the definition of the CDS model. Ultimately, this work aims to extend the utility and scalability of UBI models in order to make them more suitable for deployment in developing cities.