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Understanding the traffic arrival process and its patterns is of vital importance for delay and queue analysis at intersections. The installation of advance loop detectors to sense vehicle arrivals could be costly and biased. Utilizing sampled vehicle trajectory data to reconstruct the traffic arrival flow might suffer from small sample sizes. License plate recognition (LPR) data commonly available at intersections in cities in China are promising for overcoming such limitations. This study aims to estimate a lane-based traffic arrival pattern by using LPR data collected at downstream and upstream intersections. The proposed method develops a probability model with an assumption of a two-stage piecewise arrival process for upstream merge movements. Given observations of vehicle arrivals provided by matched cars and trucks in LPR data, the model estimates second-based mean arrival rates for each lane at the …