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논문 기본 정보

자료유형
학술저널
저자정보
Xin Jin (Ajou University) Myunghwan Eom (Doosan Corporation Mottrol) Dongkyoung Chwa (Ajou University)
저널정보
대한전기학회 Journal of Electrical Engineering & Technology Journal of Electrical Engineering & Technology Vol.12 No.5
발행연도
2017.9
수록면
2,031 - 2,042 (12page)

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초록· 키워드

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In this paper, a novel traffic flow control method based-on ramp metering and speed regulation using an adaptive sliding mode control (ASMC) method along with a deadzoned parameter adaptation law is proposed at a stochastic macroscopic level traffic environment, where the influence of the density and speed disturbances is accounted for in the traffic dynamic equations. The goal of this paper is to design a local traffic flow controller using both ramp metering and speed regulation based on ASMC, in order to achieve the desired density and speed for the maintenance of the maximum mainline throughput against disturbances in practice. The proposed method is advantageous in that it can improve the traffic flow performance compared to the traditional methods using only ramp metering, even in the presence of ramp storage limitation and disturbances. Moreover, a prior knowledge of disturbance magnitude is not required in the process of designing the controller unlike the conventional sliding mode controller. A stability analysis is presented to show that the traffic system under the proposed traffic flow control method is guaranteed to be uniformly bounded and its ultimate bound can be adjusted to be sufficiently small in terms of deadzone. The validity of the proposed method is demonstrated under different traffic situations (i.e., different initial traffic status), in the sense that the proposed control method is capable of stabilizing traffic flow better than the previously well-known Asservissement Lineaire d"Entree Autoroutiere (ALINEA) strategy and also feedback linearization control (FLC) method.

목차

Abstract
1. Introduction
2. Stochastic Macroscopic Traffic Flow Model
3. Adaptive Sliding Mode Traffic Flow Control
4. Simulation Results
5. Conclusion
References

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UCI(KEPA) : I410-ECN-0101-2018-560-001201429