||Wireless networks play a critical role in our modern lives. Since the time 802.11 protocols started to provide multiple rates for data transmission, rate adaptation has been a popular topic attracting a lot of attention, and much work has been done in this area. Several rate adaptation algorithms have been proposed to maximize the throughput and achieve a very satisfactory performance. Vehicular Networks are novel wireless networks specifically for inter-vehicle communications. In Vehicular Networks, there are many new characteristics and challenges and the existing rate adaptation algorithms are no longer applicable. However, the few available rate adaptation algorithms designed for Vehicular Networks have many issues. We are proposing a Hybrid Rate Adaptation algorithm (HRA) which is more applicable to Vehicular Networks. The key to this algorithm is to make use of both context information and signal strength information to estimate the current channel conditions more quickly and accurately. It dynamically switches the rate selection resources between the context information model and the SNR table according to the current situation. This approach solves many problems in vehicular networks, and provides high mobility, high density and high variation. We compare this scheme with two types of traditional rate adaptation algorithms and one vehicular network rate adaptation algorithm in simulation experiments. The results shows HRA performs better in most scenarios.