Traffic State Estimation with Mobile Phones Based on the “3R” Philosophy

Quang TRAN MINH; Eiji KAMIOKA

doi:10.1587/transcom.E94.B.3447

Traffic State Estimation with Mobile Phones Based on the “3R” Philosophy

Quang TRAN MINH, Eiji KAMIOKA

Full Text Views

0

Share
Cite this

Summary :

This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called “3R” philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The “3R” philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions.

Publication: IEICE TRANSACTIONS on Communications Vol.E94-B No.12 pp.3447-3458

Publication Date: 2011/12/01

Publicized

Online ISSN: 1745-1345

DOI: 10.1587/transcom.E94.B.3447

Type of Manuscript: PAPER

Category: Network

Cite this

Copy

Quang TRAN MINH, Eiji KAMIOKA, "Traffic State Estimation with Mobile Phones Based on the “3R” Philosophy" in IEICE TRANSACTIONS on Communications, vol. E94-B, no. 12, pp. 3447-3458, December 2011, doi: 10.1587/transcom.E94.B.3447.
Abstract: This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called “3R” philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The “3R” philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions.
URL: https://globals.ieice.org/en_transactions/communications/10.1587/transcom.E94.B.3447/_p

Copy

@ARTICLE{e94-b_12_3447,
author={Quang TRAN MINH, Eiji KAMIOKA, },
journal={IEICE TRANSACTIONS on Communications},
title={Traffic State Estimation with Mobile Phones Based on the “3R” Philosophy},
year={2011},
volume={E94-B},
number={12},
pages={3447-3458},
abstract={This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called “3R” philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The “3R” philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions.},
keywords={},
doi={10.1587/transcom.E94.B.3447},
ISSN={1745-1345},
month={December},}

Copy

TY - JOUR
TI - Traffic State Estimation with Mobile Phones Based on the “3R” Philosophy
T2 - IEICE TRANSACTIONS on Communications
SP - 3447
EP - 3458
AU - Quang TRAN MINH
AU - Eiji KAMIOKA
PY - 2011
DO - 10.1587/transcom.E94.B.3447
JO - IEICE TRANSACTIONS on Communications
SN - 1745-1345
VL - E94-B
IS - 12
JA - IEICE TRANSACTIONS on Communications
Y1 - December 2011
AB - This paper proposes a novel approach to traffic state estimation using mobile phones. In this work, a real-time traffic data collection policy based on the so-called “3R” philosophy, a unique vehicle classification method, and a reasonable traffic state quantification model are proposed. The “3R” philosophy, in which the Right data are collected by the Right mobile devices at the Right time, helps to improve not only the effectiveness but also the scalability of the traffic state estimation model. The vehicle classification method using the simple data collected by mobile phones makes the traffic state estimation more accurate. The traffic state quantification model integrates both the mean speed capacity and the density of a traffic flow to improve the comprehensibility of the traffic condition. The experimental results reveal the effectiveness as well as the robustness of the proposed solutions.
ER -