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In this paper we propose a traffic information system based on the distribution of knowledge provided by the cars themselves. Prior work in this area attempted to realize this distribution via vehicular ad-hoc networks, i. e., by direct communication between cars. Such an approach faces serious problems due to capacity constraints, high data dissemination latencies, and limited initial deployment of the required technology. In this paper, we present a solution that is not based on ad-hoc networking, but is still fully decentralized. It establishes a peer-to-peer overlay over the Internet, using cellular Internet access. We present a structure for the overlay, a prototype implementation in a simulation environment, and results that underline the feasibility of such a system in a city scenario. We also provide an estimate of expected user benefits when our system is used for dynamic route guidance.

Simulation of cellular network communication is complex and typically requires a high degree of knowledge about the underlying network and its parameters. At the same time simulating cellular networks is important for the automotive industry in order to be able to test the feasibility of applications that use car-to-x-communication before performing costly field tests. In this paper we propose a trace-based simulation model derived from real-world measurements. It does not require any information about the network besides information that can be readily measured by a regular user, it is much faster than regular simulation, and it has been validated by comparing simulation results to real world measurements.

The transmission of vehicular trajectory information is one basic building block of car-to-car communication. Frequently, this information is transmitted as raw data, i. e., as a sequence of location measurements. In this paper we argue that, due to the laws of physics and the requirement to follow a road, vehicular mobility has very specific characteristics. Hence, vehicular trajectory information can be compressed very efficiently using domain-specific lossy compression schemes. We discuss and compare three promising approaches that can be used to this end: linear approximation, cubic splines, and clothoids.