With the advent of Internet of Vehicles (IoV), coupled with enormous number of devices performing computational and storage tasks between the cloud and users, Vehicular Fog Computing (VFC) can be an answer to the surging challenges in today’s Intelligent Transportation Systems (ITS). However, the decentralized and heterogeneous nature of VFC infrastructures makes Vehicular Fog Network Planning (VFNP) problem complex and challenging. To deal with this problem, we propose an Integer Linear Programming (ILP) model that determines the optimal location, the capacity and the number of Fog Computing Nodes (FCN) towards minimizing the overall network delay and energy consumption. By running an example problem on default settings of GAMS CPLEX solver, we demonstrate the working of VFNP model and the associated constraints. We also analyzed the delay and energy variation for different problem sizes. The results show that, as the input size increases the overall delay increases linearly, the energy consumption follows parabolic path and the solution time shows a non-deterministic polynomial (NP) behavior.