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Main Authors: Wu, Hao, Yao, Jiarong, Kang, Peize, Tan, Chaopeng, Cai, Yang, Zhou, Junjie, Chung, Edward, Tang, Keshuang
Format: Preprint
Published: 2025
Subjects:
Online Access:https://arxiv.org/abs/2502.19435
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author Wu, Hao
Yao, Jiarong
Kang, Peize
Tan, Chaopeng
Cai, Yang
Zhou, Junjie
Chung, Edward
Tang, Keshuang
author_facet Wu, Hao
Yao, Jiarong
Kang, Peize
Tan, Chaopeng
Cai, Yang
Zhou, Junjie
Chung, Edward
Tang, Keshuang
contents Arrival flow profiles enable precise assessment of urban arterial dynamics, aiding signal control optimization. License Plate Recognition (LPR) data, with its comprehensive coverage and event-based detection, is promising for reconstructing arrival flow profiles. This paper introduces an arrival flow profile estimation and prediction method for urban arterials using LPR data. Unlike conventional methods that assume traffic homogeneity and overlook detailed traffic wave features and signal timing impacts, our approach employs a time partition algorithm and platoon dispersion model to calculate arrival flow, considering traffic variations and driving behaviors using only boundary data. Shockwave theory quantifies the piecewise function between arrival flow and profile. We derive the relationship between arrival flow profiles and traffic dissipation at downstream intersections, enabling recursive calculations for all intersections. This approach allows prediction of arrival flow profiles under any signal timing schemes. Validation through simulation and empirical cases demonstrates promising performance and robustness under various conditions.
format Preprint
id arxiv_https___arxiv_org_abs_2502_19435
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Arrival flow profile estimation and predication for urban arterials using license plate recognition data
Wu, Hao
Yao, Jiarong
Kang, Peize
Tan, Chaopeng
Cai, Yang
Zhou, Junjie
Chung, Edward
Tang, Keshuang
Physics and Society
Arrival flow profiles enable precise assessment of urban arterial dynamics, aiding signal control optimization. License Plate Recognition (LPR) data, with its comprehensive coverage and event-based detection, is promising for reconstructing arrival flow profiles. This paper introduces an arrival flow profile estimation and prediction method for urban arterials using LPR data. Unlike conventional methods that assume traffic homogeneity and overlook detailed traffic wave features and signal timing impacts, our approach employs a time partition algorithm and platoon dispersion model to calculate arrival flow, considering traffic variations and driving behaviors using only boundary data. Shockwave theory quantifies the piecewise function between arrival flow and profile. We derive the relationship between arrival flow profiles and traffic dissipation at downstream intersections, enabling recursive calculations for all intersections. This approach allows prediction of arrival flow profiles under any signal timing schemes. Validation through simulation and empirical cases demonstrates promising performance and robustness under various conditions.
title Arrival flow profile estimation and predication for urban arterials using license plate recognition data
topic Physics and Society
url https://arxiv.org/abs/2502.19435