Probabilistic Fuzzy Logic Signal and Ramp Metering at a Diamond Interchange

Pham, VC; Wang, Xu; Alam, Fakhrul; Fang, F. Clara

doi:10.1061/(asce)te.1943-5436.0000735

Cited by 3 publications

(1 citation statement)

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“…But in fuzzy control method, the fuzzy rules and membership functions are always set by empirical values. The robustness of system is not good enough [14], [15]. Liang et al [16] designed a traffic density controller based on LWR (Lighthill-Whitham-Richards) model and RBF neural network, which could keep the freeway traffic at a setting traffic density.…”

Section: Introductionmentioning

confidence: 99%

A Ramp Metering Method Based on Congestion Status in the Urban Freeway

Liu

Cao

et al. 2020

IEEE Access

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In ramp metering methods, the ALINEA algorithm is a very effective way and has been applied widely. But the critical occupancy in ALINEA algorithm is often difficult to obtain and not particularly accurate. It will greatly affect the performance of ALINEA algorithm. In this paper, an improved ALINEA algorithm, named CS-ALINEA, is proposed. In this method, the traffic flow is used to replace the occupancy as the control parameter and the control rate can be selected according to the congestion status reclassified adaptively. In the existing ramp control methods, to guarantee the traffic efficiency of mainstream, the impact of ramp overflow on ground road traffic is often ignored. In order to resolve this issue, the segmented control method is adopted in this paper. When the ramp queuing length exceeds the critical queue length, the signal timing scheme is adjusted by selecting the control rate to avoid the ramp overflow. The SUMO simulation platform is used to simulate the ramp control and test the CS-ALINEA algorithm. The experimental results show that the proposed method can optimize the ramp queuing length and reduce waiting time of vehicles while the efficiency of urban freeway can be guaranteed.

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Section: Introductionmentioning

confidence: 99%

A Ramp Metering Method Based on Congestion Status in the Urban Freeway

Liu

Cao

et al. 2020

IEEE Access

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An operational indicator for network mobility using fuzzy logic

Rashidy

Grant-Muller

2015

Expert Systems with Applications

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This paper proposes a fuzzy logic model for assessing the mobility of road transport networks from a network perspective. Two mobility attributes are introduced to account for the physical connectivity and road transport network level of service. The relative importance of the two mobility attributes has been established through the fuzzy inference reasoning procedure that was implemented to estimate a single mobility indicator. The advantage of quantifying two mobility attributes is that it improves the ability of the mobility indicator developed to assess the level of mobility under different types of disruptive events.A case study of real traffic data from seven British cities shows a strong correlation between the proposed mobility indicator and the Geo distance per minute, demonstrating the applicability of the proposed fuzzy logic model. The second case study of a synthetic road transport network for Delft city illustrates the ability of the proposed network mobility indicator to reflect variation in the demand side (i.e. departure rate) and supply side (i.e. network capcity and link closure). Overall, the proposed mobility indicator offers a new tool for decision makers in understanding the dynamic nature of mobility under various disruptive events.

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