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Vehicular Fog Computing (VFC) makes computing power available much closer to the vehicles and end-user thereby, reducing latency. The latency is of critical importance for ensuring safety and quality of service (QoS) in today’s Intelligent Transportation System (ITS). However, achieving low latency, while meeting the workload demand from vehicular nodes in VFC is challenging due to dynamic changes in resource availability and demand. In this research work, an investigation is conducted on characteristics of optimal Vehicular Fog Node (VFN), and a multi-variable constrained non-linear multi-objective optimization (MOO) model-based technique is proposed, for minimizing latency in vehicular fog network. Then proposed MOO technique is evaluated for optimum latency under varying parameters like radio bandwidth, the number of vehicles, request arrival rate, and workload sizes. Statistical validation of …