The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
pandangan teks lengkap
100
Teknologi maklumat dan komunikasi telah meningkatkan kualiti sistem pengangkutan pintar (ITS). Dengan menganggarkan daripada data kenderaan terapung selular (CFVD) adalah lebih menjimatkan kos, dan lebih mudah diperoleh daripada cara tradisional. Kajian ini mencadangkan kaedah berasaskan kuar sel (CP) untuk menganalisis isyarat rangkaian selular (cth, ketibaan panggilan, serahan dan kemas kini lokasi), dan model regresi dilatih untuk anggaran kelajuan kenderaan. Dalam eksperimen, kajian ini membandingkan maklumat trafik praktikal pengesan kenderaan (VD) dengan anggaran maklumat trafik mengikut kaedah yang dicadangkan. Keputusan eksperimen menunjukkan ketepatan anggaran kelajuan kenderaan dengan kaedah berasaskan CP ialah 97.63%. Oleh itu, kaedah berasaskan CP boleh digunakan untuk menganggar kelajuan kenderaan daripada CFVD untuk ITS.
Chi-Hua CHEN
Fuzhou University
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Salinan
Chi-Hua CHEN, "A Cell Probe-Based Method for Vehicle Speed Estimation" in IEICE TRANSACTIONS on Fundamentals,
vol. E103-A, no. 1, pp. 265-267, January 2020, doi: 10.1587/transfun.2019TSL0001.
Abstract: Information and communication technologies have improved the quality of intelligent transportation systems (ITS). By estimating from cellular floating vehicle data (CFVD) is more cost-effective, and easier to acquire than traditional ways. This study proposes a cell probe (CP)-based method to analyse the cellular network signals (e.g., call arrival, handoff, and location update), and regression models are trained for vehicle speed estimation. In experiments, this study compares the practical traffic information of vehicle detector (VD) with the estimated traffic information by the proposed methods. The experiment results show that the accuracy of vehicle speed estimation by CP-based method is 97.63%. Therefore, the CP-based method can be used to estimate vehicle speed from CFVD for ITS.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/transfun.2019TSL0001/_p
Salinan
@ARTICLE{e103-a_1_265,
author={Chi-Hua CHEN, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={A Cell Probe-Based Method for Vehicle Speed Estimation},
year={2020},
volume={E103-A},
number={1},
pages={265-267},
abstract={Information and communication technologies have improved the quality of intelligent transportation systems (ITS). By estimating from cellular floating vehicle data (CFVD) is more cost-effective, and easier to acquire than traditional ways. This study proposes a cell probe (CP)-based method to analyse the cellular network signals (e.g., call arrival, handoff, and location update), and regression models are trained for vehicle speed estimation. In experiments, this study compares the practical traffic information of vehicle detector (VD) with the estimated traffic information by the proposed methods. The experiment results show that the accuracy of vehicle speed estimation by CP-based method is 97.63%. Therefore, the CP-based method can be used to estimate vehicle speed from CFVD for ITS.},
keywords={},
doi={10.1587/transfun.2019TSL0001},
ISSN={1745-1337},
month={January},}
Salinan
TY - JOUR
TI - A Cell Probe-Based Method for Vehicle Speed Estimation
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 265
EP - 267
AU - Chi-Hua CHEN
PY - 2020
DO - 10.1587/transfun.2019TSL0001
JO - IEICE TRANSACTIONS on Fundamentals
SN - 1745-1337
VL - E103-A
IS - 1
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - January 2020
AB - Information and communication technologies have improved the quality of intelligent transportation systems (ITS). By estimating from cellular floating vehicle data (CFVD) is more cost-effective, and easier to acquire than traditional ways. This study proposes a cell probe (CP)-based method to analyse the cellular network signals (e.g., call arrival, handoff, and location update), and regression models are trained for vehicle speed estimation. In experiments, this study compares the practical traffic information of vehicle detector (VD) with the estimated traffic information by the proposed methods. The experiment results show that the accuracy of vehicle speed estimation by CP-based method is 97.63%. Therefore, the CP-based method can be used to estimate vehicle speed from CFVD for ITS.
ER -