TIIS (한국인터넷정보학회)
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| 한글제목(Korean Title) |
A New Traffic Congestion Detection and Quantification Method Based on Comprehensive Fuzzy Assessment in VANET |
| 영문제목(English Title) |
A New Traffic Congestion Detection and Quantification Method Based on Comprehensive Fuzzy Assessment in VANET |
| 저자(Author) |
Lanlan Rui
Yao Zhang
Haoqiu Huang
Xuesong Qiu
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| 원문수록처(Citation) |
VOL 12 NO. 01 PP. 0041 ~ 0060 (2018. 01) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
Recently, road traffic congestion is becoming a serious urban phenomenon, leading to massive adverse impacts on the ecology and economy. Therefore, solving this problem has drawn public attention throughout the world. One new promising solution is to take full advantage of vehicular ad hoc networks (VANETs). In this study, we propose a new traffic congestion detection and quantification method based on vehicle clustering and fuzzy assessment in VANET environment. To enhance real-time performance, this method collects traffic information by vehicle clustering. The average speed, road density, and average stop delay are selected as the characteristic parameters for traffic state identification. We use a comprehensive fuzzy assessment based on the three indicators to determine the road congestion condition. Simulation results show that the proposed method can precisely reflect the road condition and is more accurate and stable compared to existing algorithms.
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| 키워드(Keyword) |
VANET
vehicle clustering
comprehensive fuzzy assessment
traffic congestion detection
traffic state estimation
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| 파일첨부 |
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