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Related Concept Videos

Bus Impedance Matrix01:24

Bus Impedance Matrix

187
Calculating subtransient fault currents for three-phase faults in an N-bus power system involves using the positive-sequence network. When a three-phase short circuit occurs at a specific bus, the analysis uses the superposition method to evaluate two separate circuits.
In the first circuit, all machine voltage sources are short-circuited, leaving only the prefault voltage source at the fault location. The positive-sequence bus impedance matrix can be determined by solving the nodal equations,...
187
Multi-input and Multi-variable systems01:22

Multi-input and Multi-variable systems

178
Cruise control systems in cars are designed as multi-input systems to maintain a driver's desired speed while compensating for external disturbances such as changes in terrain. The block diagram for a cruise control system typically includes two main inputs: the desired speed set by the driver and any external disturbances, such as the incline of the road. By adjusting the engine throttle, the system maintains the vehicle's speed as close to the desired value as possible.
In the absence...
178
Multimachine Stability01:25

Multimachine Stability

240
Multimachine stability analysis is crucial for understanding the dynamics and stability of power systems with multiple synchronous machines. The objective is to solve the swing equations for a network of M machines connected to an N-bus power system.
In analyzing the system, the nodal equations represent the relationship between bus voltages, machine voltages, and machine currents. The nodal equation is given by:
240
Reynolds Transport Theorem01:24

Reynolds Transport Theorem

1.4K
The Reynolds transport theorem provides a framework to relate the time rate of change of an extensive property within a system to that in a control volume, which is crucial for analyzing fluid dynamics. Extensive properties, such as mass, velocity, acceleration, temperature, and momentum, can be expressed in terms of the mass of a fluid portion. These properties are called extensive because they depend on the system's size, while intensive properties are their corresponding values per unit...
1.4K
Fast Decoupled and DC Powerflow01:24

Fast Decoupled and DC Powerflow

312
The fast decoupled power flow method addresses contingencies in power system operations, such as generator outages or transmission line failures. This method provides quick power flow solutions, essential for real-time system adjustments. Fast decoupled power flow algorithms simplify the Jacobian matrix by neglecting certain elements, leading to two sets of decoupled equations:
312
Transformers with Off-Nominal Turns Ratios01:25

Transformers with Off-Nominal Turns Ratios

222
In scenarios involving parallel transformers with disparate ratings, developing per-unit models requires accommodating off-nominal turns ratios. This situation arises when the selected base voltages are not proportional to the transformer’s voltage ratings. Consider a transformer where the rated voltages are related by the term a. If the chosen voltage bases satisfy a relationship involving term b, term c is defined as the ratio of these bases. This ratio is then substituted into the...
222

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Multi-Agent Adaptive Traffic Signal Control Based on Q-Learning and Speed Transition Matrices.

Sensors (Basel, Switzerland)·2025
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Motorway Bottleneck Probability Estimation in Connected Vehicles Environment Using Speed Transition Matrices.

Leo Tišljarić1, Filip Vrbanić1, Edouard Ivanjko1

  • 1Faculty of Transport and Traffic Sciences, University of Zagreb, 10000 Zagreb, Croatia.

Sensors (Basel, Switzerland)
|April 12, 2022
PubMed
Summary

This study introduces a new method for detecting traffic bottlenecks on motorways using Connected Vehicles (CVs) as mobile sensors. The model achieved 92% accuracy in identifying traffic jams, paving the way for smarter traffic management.

Keywords:
bottleneck detectionbottleneck probabilityconnected vehiclesfuzzy-based bottleneck probabilitymotorway bottleneckspeed transition matrixtraffic simulation

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Area of Science:

  • Intelligent Transport Systems
  • Traffic Engineering
  • Machine Learning

Background:

  • Urban development increases transport demand, leading to traffic congestion on motorways.
  • Intelligent Transport Systems (ITS) and Connected Vehicles (CVs) offer solutions for traffic management.
  • CVs act as mobile sensors, generating data for advanced traffic analysis.

Purpose of the Study:

  • To develop a novel method for detecting traffic bottlenecks on motorways.
  • To estimate bottleneck probability using data from Connected Vehicles.
  • To improve traffic flow and reduce congestion through efficient bottleneck resolution.

Main Methods:

  • A speed transition matrix-based model was developed for bottleneck probability estimation.
  • Vehicle speeds at segment transition points were used to create traffic patterns represented by transition matrices.
  • The 'center of mass' feature from traffic patterns was input into a fuzzy-based system for bottleneck detection.

Main Results:

  • The proposed method demonstrated comparable bottleneck detection across four simulated scenarios: collision sites, short/long recurring bottlenecks, and moving bottlenecks.
  • The model achieved a high accuracy of 92% on the validation dataset.
  • The method shows promise for real-world implementation in motorway environments with high CV penetration.

Conclusions:

  • The speed transition matrix model effectively estimates traffic bottleneck probability.
  • Connected Vehicles provide valuable data for advanced traffic monitoring and control.
  • The findings support the integration of machine learning-based control systems for traffic management using CV data.