Rapid advances in connected and automated vehicles (CAVs) are reshaping travel behaviours, road capacity characteristics and urban mobility systems. Classical urban traffic planning theories are developed for human-driven traffic flows and cannot fully capture the operational features of CAVs. This paper explores the theoretical implications of CAVs for urban traffic planning. It first reviews core assumptions embedded within classical traffic planning theories from traffic flow, travel demand modelling and network equilibrium perspectives. Next, the study identifies key transformations introduced by CAV technology, including improved flow stability, coordinated vehicle scheduling, altered travel demand patterns and revised parking requirements. This work further analyses theoretical challenges raised by mixed traffic environments and cooperative vehicle operations, and proposes potential extensions to existing planning paradigms. The results provide theoretical support for revising urban traffic layout, road resource allocation and mobility governance under CAV deployment.