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Speed profile estimation using license plate recognition data
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DOI：10.1016/j.trc.2017.07.006.png)
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摘要
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Vehicle speed profile is a fundamental data support for calculating vehicular emission using the micro-emission model. However, achieving accuracy and breadth for the speed profile estimation is difficult. This study proposes a new vehicle speed profile estimation model using license plate recognition (LPR) data. This model allows speed profile estimation of every individual vehicle between two consecutive intersections. A systematic LPR data-mending method is developed to infer the information of unmatched vehicles. Using the complete arrival and departure information as boundary conditions, a customized car-following model combined with dummy-overtaking hypothesis and boundary constraints is then applied to estimate the speed profile of vehicles. The proposed model is validated using ground truth speed inforniation from a field experiment conducted in Langfang City in China. Results show that the model can fully capture the pattern of ground truth speed profile. A complementary model validation using the Next Generation Simulation dataset and a model application for calculating emissions are also conducted. The numerical results indicate the effectiveness of the proposed model in estimating vehicle speed profile and emissions. (C) 2017 Elsevier Ltd. All rights reserved.
Keyword:
Speed profile estimation
License plate recognition
Emission estimation
Car-following model
License plate number matching procedure
Minimum cost bipartite matching
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