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VANETs (Vehicular Ad Hoc Networks) aim to provide safety and comfort services for drivers on roads and highways. Among these services, there are computation-intensive tasks in real-time applications that need to be executed as quickly as possible. Using VCC (Vehicular Cloud Computing) paradigm, where vehicles offer their underutilized computing resources as a service and with the goal of reducing the execution time of tasks, this paper investigates how the computation offloading technique can be leveraged to speed up the execution of tasks under different conditions and in varied scenarios. We present an offloading decision algorithm and several simulations results that show we can achieve better processing times than to execute locally and better success rates than random algorithm.