Connected vehicle technology can provide traffic signal controllers with abundant types of data resources, e.g., vehicle occupancy data, etc. The provided data can be used to improve the performance of signal control methods and enable conversion from vehicle-based controls to person-based controls, which focus on optimizing person-related objective values, such as minimising average person delay. However, so far research in relevant fields has not fully exploited potential paradigms and benefits of person-based controls. In respect of such, this study has provided a better understanding about the impacts of occupancy information collected from connected vehicles (CVs) on urban signal controls and potential benefits to person-related performance that those information can bring. The contributions of this study include: 1) development of a three-layered DP person-based signal control mechanism (PerSiCon-Junction) in a fully CV environment at an isolated junction with a signal phase transition exploration mechanism and car-following updating theories; 2) development of a person-based control mechanism (PerSiCon-Bus) with completely flexible signal plans to apply the PerSiCon-Junction to more complex vehicle mixtures of cars and buses in a generalized 8-phases options junction; 3) proposal of a coordinated paradigm PerSiCon-Network to better understand how PerSiCon-Bus with flexible phase combinations and stage sequences should be implemented in multiple junctions; 4) realistic case and scenarios studies that assess the performance of the proposed method against benchmarking models involving vehicle-based controls using CV data; and 5) proposal of a EUVO algorithm to estimate status of unequipped vehicles with occupancy so as to improve the behaviour of PerSiCon-Network under imperfect CV penetration rate environments.