Traffic congestion causes driver frustration and costs billions of dollars annually in lost time and fuel consumption. This paper presents five traffic re-routing strategies designed to be incorporated in a cost-effective and easily deployable vehicular traffic guidance system that reduces travel time. The proposed strategies proactively compute individuallytailored re-routing guidance to be pushed to vehicles when signs of congestion are observed on their route. The five proposed strategies are Dynamic Shortest Path (DSP), A shortest path with repulsion (AR ), Random k-Shortest Paths (RkSP), Entropy Balanced k-Shortest Paths (EBkSP), and Flow Balanced k-Shortest Paths (FBkSP). Extensive simulation results show the proposed strategies are capable of reducing the travel time as much as a state-of-the-art Dynamic Traffic Assignment (DTA) algorithm, while avoiding the issues that make DTA impractical such as lack of scalability and robustness, and high computation time. Furthermore, the variety of proposed strategies allows tuning the system to different levels of trade-off between rerouting effectiveness and computational efficiency. Also, the proposed traffic guidance system can significantly improve the traffic even if many drivers ignore the guidance or if the system adoption rate is relatively low.