@article{ref1,
title="Speed profile estimation using license plate recognition data",
journal="Transportation research part C: emerging technologies",
year="2017",
author="Mo, Baichuan and Li, Ruimin and Zhan, Xianyuan",
volume="82",
number="",
pages="358-378",
abstract="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 information from a field experiment conducted in Langfang City in China. <br><br>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.<p /> <p>Language: en</p>",
language="en",
issn="0968-090X",
doi="10.1016/j.trc.2017.07.006",
url="http://dx.doi.org/10.1016/j.trc.2017.07.006"
}