We present the framework design and modeling for an integrated vehicular and human-centric urban sensing system. The goal is to understand the impact of vehicles and human activities on the surrounding environment. This is achieved through a seamless integration of the human aspect into vehicular and urban sensing going beyond the traditional human-in-the-loop sampling methodologies. We describe the framework design of this system which allows humans to make decisions or take actions and gather feedback to understand the effect of those actions. Based on this framework, a prototype BusSense system has been developed based on the university campus shuttle buses. We describe the system architecture and implementation. We present tools for modeling the system based on Hidden Markov Models (HMM). These models are used for detecting events and identifying patterns in the data. We also present modeling results and analysis using the experimental data.