Modelling and Analysis of Oversaturated Intersections Using Jointly Hybrid Petri net and Hybrid Automata

Bouriachi, Fares; Kechida, Sihem

doi:10.1007/s13177-017-0144-4

Cited by 4 publications

(4 citation statements)

References 43 publications

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“…Lime and Roux (2006) proposed a method for constructing the state-class diagram of a bounded time PN as timed automata, which is referred to as state-class time automata. Bouriachi and Kechida (2018) proposed modeling of oversaturated intersections traffic to design a traffic control approach. This concept was based on the joint use of the two well-known hybrid representation tools: hybrid PN and HA.…”

Section: Automata Conceptsmentioning

confidence: 99%

Evaluation of predicted fault tolerance based on C5.0 decision tree algorithm in irrigation system of paddy fields

Rahi,

Ebrahimnejad,

Motameni

2023

IJICC

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PurposeTaking into consideration the current human need for agricultural produce such as rice that requires water for growth, the optimal consumption of this valuable liquid is important. Unfortunately, the traditional use of water by humans for agricultural purposes contradicts the concept of optimal consumption. Therefore, designing and implementing a mechanized irrigation system is of the highest importance. This system includes hardware equipment such as liquid altimeter sensors, valves and pumps which have a failure phenomenon as an integral part, causing faults in the system. Naturally, these faults occur at probable time intervals, and the probability function with exponential distribution is used to simulate this interval. Thus, before the implementation of such high-cost systems, its evaluation is essential during the design phase.Design/methodology/approachThe proposed approach included two main steps: offline and online. The offline phase included the simulation of the studied system (i.e. the irrigation system of paddy fields) and the acquisition of a data set for training machine learning algorithms such as decision trees to detect, locate (classification) and evaluate faults. In the online phase, C5.0 decision trees trained in the offline phase were used on a stream of data generated by the system.FindingsThe proposed approach is a comprehensive online component-oriented method, which is a combination of supervised machine learning methods to investigate system faults. Each of these methods is considered a component determined by the dimensions and complexity of the case study (to discover, classify and evaluate fault tolerance). These components are placed together in the form of a process framework so that the appropriate method for each component is obtained based on comparison with other machine learning methods. As a result, depending on the conditions under study, the most efficient method is selected in the components. Before the system implementation phase, its reliability is checked by evaluating the predicted faults (in the system design phase). Therefore, this approach avoids the construction of a high-risk system. Compared to existing methods, the proposed approach is more comprehensive and has greater flexibility.Research limitations/implicationsBy expanding the dimensions of the problem, the model verification space grows exponentially using automata.Originality/valueUnlike the existing methods that only examine one or two aspects of fault analysis such as fault detection, classification and fault-tolerance evaluation, this paper proposes a comprehensive process-oriented approach that investigates all three aspects of fault analysis concurrently.

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Section: Automata Conceptsmentioning

confidence: 99%

Evaluation of predicted fault tolerance based on C5.0 decision tree algorithm in irrigation system of paddy fields

Rahi,

Ebrahimnejad,

Motameni

2023

IJICC

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“…After training the data see Table 3. There is a constant improvement in traffic management for the Low-Traffic scenario, with around 39% improvement in total waiting time and 69% in average time per vehicle during one episode compared to traffic light straigie system [14][15][16], in another. On the other hand, we have the opposite with a deterioration in performance for the High-Traffic scenario.…”

Section: Low Gammamentioning

confidence: 99%

“…The same problem has been investigated in Ref. [16] for the past year, who used a Genetic Algorithm to improve the performance of traffic management in the Sofia intersection. The comparative study Between proposed control strategy (PCS) and STLS are shown in Table 5.…”

Section: Figure 13 Simulation Test Under Sumomentioning

confidence: 99%

Traffic Signal Control Model on Isolated Intersection Using Reinforcement Learning: A Case Study on Algiers City, Algeria

Bouriachi¹,

Zatla²,

Tolbi³

et al. 2021

RIA

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Traffic jams and congestion in our cities are a major problem because of the huge increase in the number of cars on the road. To remedy this problem, several control methods are proposed to prevent or reduce traffic congestion based on traffic lights. There are few works using reinforcement learning technique for traffic light control and recent studies have shown promising results. However, existing works have not yet tested the methods on the real-world traffic data and they only focus on studying the rewards without interpreting the policies. In this paper, we proposed a reinforcement learning algorithm to address the traffic signal control problem in real multi-phases isolated intersection. A case study based on Algiers city is conducted the simulation results from the different scenarios show that our proposed scheme reduces the total travel time of the vehicles compared to those obtained with traffic-adaptive control.

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“…In the above control models, it is assumed that the saturated flow rate and loss time of the imported lane group are fixed values, and the traffic flow is used as the input variable to optimize the signal cycle and green time, so as to achieve the minimum delay and saturation. However, through actual observation, it is found that due to the different channelization design of intersections and traffic conditions, the parameters such as saturated flow rate and loss time will change accordingly, which leads to the failure of optimization objective function and unreasonable timing scheme [9][10][11][12] . Therefore, this paper analyzes the characteristics of traffic flow release at high load intersection, puts forward the calculation model of traffic flow release rate and loss time, and further designs the signal timing optimization model of high load intersection, in order to provide guidance for signal timing design of oversaturated intersection [13][14][15][16] .…”

Section: Introductionmentioning

confidence: 99%

Intersection signal timing optimization method based on dynamic saturation flow rate

2021

jecet

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：In view of the unreasonable scheme design caused by the use of fixed parameters in the traditional timing model, this paper, on the basis of fully considering the intersection channelization and the relationship between supply and demand, first of all, finely analyzes the traffic flow release characteristics of high-load intersections, and determines the maximum release rate and duration of five stages. Then, the calculation model of total loss time of intersection is proposed, which is used as the optimization goal of signal timing at oversaturated intersection, and the optimization model of green light and signal cycle is constructed. Finally, the effectiveness of the model is verified by an example. The results show that the traffic efficiency of the intersection has been effectively improved.

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Modelling and Analysis of Oversaturated Intersections Using Jointly Hybrid Petri net and Hybrid Automata

Cited by 4 publications

References 43 publications

Evaluation of predicted fault tolerance based on C5.0 decision tree algorithm in irrigation system of paddy fields

Evaluation of predicted fault tolerance based on C5.0 decision tree algorithm in irrigation system of paddy fields

Traffic Signal Control Model on Isolated Intersection Using Reinforcement Learning: A Case Study on Algiers City, Algeria

Intersection signal timing optimization method based on dynamic saturation flow rate

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