AI & ML
Maneuver Coordination Using V2I to Improve Traffic Efficiency at Intersections
arXiv cs.NI0 views
arXiv:2610.13394v1 Announce Type: new Abstract: Traffic efficiency and air pollutants are major issues in urban transport systems, as they are critical points for traffic flows and people living in urban areas, respectively. In response to this challenge, connected and autonomous vehicles (CAVs) have garnered increasing attention, with the potential to address the above challenges through cooperative maneuvering and real-time communication. In this paper, we consider an intersection served by a multi-access edge computing (MEC) where CAVs communicate with a controller to pass the intersection without the need of signals and without stopping unless in presence of heavy congestion. For this purpose, we propose a first-in-first-scheduled (FIFS) algorithm, and we specify the communication protocol for its practical implementation. The solution is validated through simulations with varying traffic densities, showing that it provides significant gains in travel time and emissions compared to both uncontrolled intersections, with or without traffic lights, and a benchmark solution derived from the literature.
Source:https://arxiv.org/abs/2610.13394PreviousConfiguration Migration Planning through Decoupled Modeling and SearchingNextOn the Alignment Between Spectral Efficiency and Positioning Accuracy in Multi-LEO Clusters
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