These days, the problem of traffic and traffic congestion on crowded streets has become an integral part of life in metropolitan areas. Intelligent traffic control will be crucial as the number of continuous road users increases and the resources provided by the current infrastructure are limited. The purpose of this study is to model traffic flow and control Ramp measurement using fuzzy method, To achieve this goal, traffic Ramps at the entrances are used to regulate access to the main corridor of the highway or freeway, in order to maintain the flow close to the capacity of the highway. In this research, by presenting a new solution, modeling traffic flow and controlling Ramp measurement has been done by fuzzy intelligent method in MATLAB software environment. Data collection was performed using field method and on the highways of Isfahan. This algorithm tries to make the Ramp control system intelligent by maintaining simplicity and non-computational complexity. According to the information received from the vehicle, which are located at certain distances from each Ramp, the queue length, vehicle entry rate and demand level of each Ramp are measured, and then the controller determines the minimum time and phase of the Ramp according to this information. According to the obtained results, the average intensity of the factors of total queue length in the Ramp, stop time in the Ramp, stopping times and traffic congestion in the open loop mode is higher than the closed loop mode based on the fuzzy method algorithm.

Highways are one infrastructure facilities that play a vital role in transportation. There are several approaches for the highway management; such as Intelligent Transportation System (ITS), which control technologies to improve traffic flow quality in transportation networks. Different methods have been developed such as Ramp metering (RM), variable speed limits (VSL), route recommendation and variable message signs (VMS) are recognized as the most effective for relieving traffic congestion. This research paper discusses the optimal coordination of variable speed limits and Ramp metering in a highway traffic network. The control problem is to determine the optimal combination of control variables that result in the best network performance. Efficiency of this problem was evaluated based on the total time that a vehicle spent in the network. The applied co-ordination approach incorporates the macroscopic traffic flow model METANET and genetic algorithm. The proposed model was implemented on a highway network. The results showed that applying this model to the highway networks could prevent traffic breakdown and therefore, the satisfied traffic flow could be achieved.

This paper aims to evaluate and compare the effects of different methods of Ramp metering on the operational conditions of traffic flow at three levels: the network level (including the freeway and its connected Ramps), the entrance Ramp, and the upstream segment of the entrance. To achieve this aim, one of the most important urban freeways in the metropolis of Isfahan was selected. The traffic volume passing through this freeway and its connected Ramps were determined during peak hours (7 to 9 am), and the south band flows were simulated using microscopic analysis in AIMSUN software. After calibration and validation of the model, a specific on-Ramp (the entrance Ramp of Samadiyeh) was reviewed as the selected Ramp, by using the fixed-time plan and ALINEA algorithm at demand levels of 100%, 110% and 80%. The results indicate that for normal demand level (100% demand), Ramp metering does not have a significant effect on traffic flow. Further, Ramp metering significantly improved upstream traffic flow in the freeway at high demand levels (110% demand), indicating its usefulness at high demand levels. At this demand level, Ramp metering leads to traffic flow deviation. At low demand (80% demand), Ramp metering increased the delay time of both the freeway and the Ramp, indicating the ineffectiveness of Ramp metering at low demands.

This paper proposes an integrated system to control Ramps and ad-just variable speed limits. It includes three essential modules to predict the starting time of congestion and a fuzzy controller to determine the parameters and a model predictive control. An Apriori algorithm that is a powerful tool for frequent pattern mining is used in the , rst module. The proposed system is neither sensitive to the tra, c distribution nor computationally intensive. Two tra, c simulators of Aimsun and CTMSIM are applied to validate the results. Compared with the most recent algorithms, including Gated Recurrent Unit (GRU) and Long Short-Term Memory (LSTM), this system improves prediction accuracy up to 2. 63%. The results of Ramp metering and variable speed limit subsystems are also promising. The embedded controller shows 0. 6% and 4% overall and rush hour improvement in the total travel time.

One of the new traffic engineering tools is micro simulation. It can prevent some try and errors and help the road administrators save the resources. Although the micro simulation is a valuable tool for traffic behavior prediction, it can cause some problem in some cases. For example if the model is not well established and well calibrated, it can be misleading and produce some wrong outputs. On the other hand, regarding to the large number of inputs that a micro simulator needs to be calibrated, the calibration and verification is a high cost and expensive process. Therefore the most effective factors should be identified regarding to the outputs and the most effective factors should be calibrated first. In this paper, the Plackett Burman method is applied in order to find the most effective parameters in a micro simulation model of an urban highway. The simulated highway has on Ramps that are controlled by Ramp-metering and the speed in the main stream is dependent on the Ramp metering action. In the simulation model, the cycle length of the Ramp-metering is the most effective parameter on mean speed of the main stream. In addition to, the effectiveness for the other parameters has been achieved too.

jams and, as a result, long queues, increased travel time, increased chances of accidents, and environmental pollution. Several methods, such as Ramp metering control, variable speed limit, lane change control, tolls, etc., have been studied and investigated to control highways. One of the approaches to improve the performance of these controls is their simultaneous and coordinated integration and implementation. In this paper, we will investigate the effect of the combination of three concurrent controls of Ramp metering, variable speed limit, and highway tolls on the traffic conditions of the highway network. For this purpose, the reinforcement learning method has been used to manage the control values as variables. Traffic data is first predicted by predictive models based on neural networks and then given to the simulation of Sumo software. The controller model then selects the Ramp rate, speed limit, and toll values based on the simulation outputs and applies them to the network. The results of implementing the proposed model show the significant impact of the model in improving traffic parameters . The model reduced the average travel time by 11.5% compared to the condition without controls, which is more than the effect of implementing single controls or a double combination of the mentioned methods. In addition, in the event of an accident in the network, the proposed management can significantly improve the network conditions compared to the situation without control.

Due to the high speed of the air inside the combustion chamber of Scramjet engines, the proper mixing of fuel and air in the combustion chamber is one of the challenges and key issues in the design and analysis of such engines. To improve the mixing, various methods are used, including the implementation of a Ramp ahead of the injection port. In the present work, the effect of Ramp height on the area of double hydrogen jet cross-jet flow in supersonic airflow has been investigated numerically and the effect of Ramp height on parameters such as mixing efficiency, effective mixing area ratio and stagnation pressure losses has been investigated. Numerical simulations have been performed using the solution of the three-dimensional Reynolds-Averaged Navier-Stokes equations with the two-equation turbulence model k-ω,sst. Initially, the results of numerical solution were validated with the experimental data, which comparison of numerical solution results with experimental data shows their good agreement with each other. Then, the effect of the presence of a Ramp upstream of the injection port is numerically investigated for several Ramps with different heights.

Unaccounted-for-water is a misleading term long used by water industry. Unaccounted-for-water includes unmeasured volume of water that run out of access from supply to end consumer and consequently leads no revenue for supplier. Examples of water losses are: meter inaccuracies, illegal connection and unauthorized usage of water, abnormal meter reading, reservoir seepage and leakage, reservoir overflow, underground leakage, pipe breaks, unwanted problem in the water treatment process, malfunction of distribution system controls, water consumption of hydrant. In domestic water network system, Meter inaccuracies are one of the most important parts of Unaccounted-for-water. Through meter inaccuracies water consume by consumers but there is no payment. So many parameters could cause meter inaccuracies: erosion parts of meter, high water and environment temperature, suspended solid in inlet water, impure filter, low ended gears and unsuitable keep of meter in store. The solution for survey of meters in water system is meter testing. In this research a part of Varamin with 6000 subscription and 4500 healthy meters was chosen as pilot of studies. One percent of meters choose randomly and the results were statistic analyzed .The results generalization to the whole city and total Unaccounted-for-water was calculated. According to the results repair meter after 5 or 6 years is uneconomic and if after the test error of meter was found it should be changes with new one. In this region most of changing meter is repaired meter .before using meter the new meter and repaired meter should be test in the workshop and if has any problem should be back to the factory.87.5 percent of meter in the pilot area has no physical losses, 6.25 percent was in the standard limit and 6.25 percent gives more money to the supplier.