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Spatial Inference of Traffic Transition Using Micro–Macro Traffic Variables
2015
IEEE transactions on intelligent transportation systems (Print)
This paper proposes an online traffic inference algorithm for road segments in which local traffic information cannot be directly observed. Using macro-micro traffic variables as inputs, the algorithm consists of three main operations. First, it uses interarrival time (time headway) statistics from upstream and downstream locations to spatially infer traffic transitions at an unsupervised piece of segment. Second, it estimates lane-level flow and occupancy at the same unsupervised target site.
doi:10.1109/tits.2014.2345742
fatcat:7e623axx7ndn5p2jjmfxuo5xvy