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In the near future vehicles will be equipped with embedded communication capabilities in order to perform context-sensitive tasks such as traffic flow control and incident avoidance. In large scale vehicular networks it is of vital importance that the information exchanged between the vehicles meets a certain level of quality so that they can make informed automated decisions. In this paper we define Quality of Context (QoC) and Peer Reputation (PR) for nodes in vehicular networks and propose ways to apply them for efficient communication. Thus, we provide a two-fold solution in which on the one hand we focus on the quality of the information and on the other hand we aim at determining the reputation of the nodes involved in the communication. This helps to eliminate the use of erroneous, ambiguous and imprecise information provided by unknown entities. Our simulated experiments show that our mechanism significantly reduces network traffic usage, eases out the decision making process and guarantees a minimum level of quality.