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Taking advantage of the proliferation of wireless communication devices, we could well develop advanced transportation information systems based on inter-vehicle communication (IVC), in which drivers can have faster response to incidents and are able to communicate critical information in wake of disasters. Whether such IVC systems are feasible or not is highly related to the performance of multihop connectivity. Existing analytical studies of multihop connectivity, however, usually assume Poisson distribution of communication nodes or uniform distribution of vehicles on a road, and simulation-based studies are not suitable for real-time applications with computationally costly traffic simulators. In this paper, we present an analytical model for multihop connectivity of IVC in a traffic stream, in which positions of vehicles are all known through observations, traffic simulators, or traffic theories. After introducing most-forwarded-within-range communication chains and node- and hope-related events, we derive a recursive model of node and hop probabilities and further define a number of performance measures of multihop connectivity. We then apply the model to study multihop connectivity of IVC in both uniform and non-uniform traffic and obtain results consistent with those in literature. The new analytical model is efficient without repeating traffic simulations while capable of capturing the impact of arbitrary distribution patterns of vehicles. Thus it is suitable for evaluating connectivity of IVC for different traffic congestion patterns and extended for studies of other situations.