Evaluating spatiotemporal speed metrics for traffic state estimation on complex urban roads

Conducting city-wide tests of intelligent transport systems (ITS) is a costly endeavor that requires extensive funding and planning. Combined traffic simulations can be utilized to alleviate initial costs, and allow easy parameterization to deduce real-world requirements. In this paper, we aim to contribute to two frontiers in the domain of traffic state estimation (TSE) within an urban environment. First, we introduce speed estimation and different sensor technologies, reiterating the foundations of traffic dynamics. Second, we present a simulation-based assessment utilizing the open-source co-simulation framework Eclipse MOSAIC, alongside a newly developed TSE application suite, executed on top of the BeST Berlin traffic scenario. This evaluation highlights the estimation capabilities of different sensor technologies and speed estimates in an urban scenario, addressing their effectiveness in various city areas.