As global carbon reduction efforts intensify, the rapid proliferation of electric vehicles (EVs) is accelerating the profound integration of traffic and power networks. However, the carbon-intensive nature of upstream power generation and the persistent emission challenges posed by conventional gasoline vehicles (GVs) remain fundamental bottlenecks restricting the overall decarbonization efficacy of the coupled network. To address these challenges, this paper de-velops an energy-carbon integrated pricing methodology and a synergistic low-carbon scheduling model tailored for coupled traffic-power networks (CTPN). Specifically, by leveraging carbon emission flow theory, the carbon footprints inherent in the power network are traced to the traffic side, enabling the formulation of spatiotemporally differentiated nodal carbon prices for EV charging. For GVs, a direct carbon pricing is implemented according to their emission models. Meanwhile, a power system model is constructed based on the alternating current optimal power flow equations, and an integrated ener-gy-carbon price regulation system is established at the cross-network level to achieve coordinated low-carbon scheduling of the CTPN. Furthermore, an efficient iterative solution algorithm is designed to resolve the complex syn-ergistic scheduling optimization problem. A case study demonstrates that the proposed mechanism accurately identifies carbon emission responsibilities and facilitates the scientific allocation of carbon-related costs among diverse stakeholders. Compared with conventional scheduling paradigms, the proposed scheme significantly enhances the decarbonization potential of the coupled network while effectively balancing operational economy. This research pro-vides essential theoretical insights and technical support for the low-carbon evolution of the modern urban energy internet.