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相关概念视频

Design Example: Alignment of a Road Line Using GIS01:17

Design Example: Alignment of a Road Line Using GIS

47
The alignment of a road line using Geographic Information Systems (GIS) is a critical process in civil engineering, combining advanced technology with practical decision-making. This methodology begins with the collection of geospatial data, including information on land cover, geomorphology, drainage patterns, slope, and contour details. Such data is typically acquired through satellite imagery and GIS tools, offering a comprehensive understanding of the terrain.Once the data is gathered, it...
47
PD Controller: Design01:26

PD Controller: Design

218
In automotive engineering, car suspension systems often employ Proportional Derivative (PD) controllers to enhance performance. PD controllers are utilized to adjust the damping force in response to road conditions. A controller, acting as an amplifier with a constant gain, demonstrates proportional control, with output directly mirroring input.
Designing a continuous-data controller requires selecting and linking components like adders and integrators, which are fundamental in Proportional,...
218
Load-frequency control01:28

Load-frequency control

150
Load-frequency control (LFC) is vital for maintaining power system stability, ensuring that frequency and power flows remain within acceptable limits during load changes. Turbine-governor control eliminates rotor accelerations and decelerations following load changes. However, a steady-state frequency error persists when the change in the turbine-governor reference setting is zero. In an interconnected power system, each area agrees to export or import a scheduled amount of power through...
150
Root-Locus Method01:19

Root-Locus Method

145
A cruise control system in a car is designed to maintain a specified speed automatically by adjusting the gas pedal. The system continuously measures the vehicle's speed and makes fine adjustments to the pedal to achieve this goal. The root locus method is particularly useful for understanding how the cruise control system's behavior changes under varying conditions, such as when the car goes uphill, downhill, or faces strong wind resistance.
This system can be represented by a block...
145
Time-Domain Interpretation of PD Control01:07

Time-Domain Interpretation of PD Control

92
Proportional-Derivative (PD) control is a widely used control method in various engineering systems to enhance stability and performance. In a system with only proportional control, common issues include high maximum overshoot and oscillation, observed in both the error signal and its rate of change. This behavior can be divided into three distinct phases: initial overshoot, subsequent undershoot, and gradual stabilization.
Consider the example of control of motor torque. Initially, a positive...
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Manipulation and Analysis01:21

Manipulation and Analysis

23
GIS manipulation and analysis functions are vital for decision-making and planning. These activities range from data retrieval tasks, such as selecting information based on specific criteria, to advanced analytical techniques that address complex spatial problems.One critical GIS analysis method is overlaying, which combines multiple data layers to examine impacts. For example, overlaying a river-dammed lake boundary with road networks can identify affected infrastructure. Another common...
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相关实验视频

Updated: Jun 22, 2025

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
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一个动态的交通信号控制算法,以缓解大都市地区的交通拥堵.

Bharathi Ramesh Kumar1, Narayanan Kumaran1, Jayavelu Udaya Prakash2

  • 1Department of Mathematics, Vel Tech Rangarajan Dr. Sagunthala R&D Institute of Science and Technology, Chennai 600062, Tamil Nadu, India.

Sensors (Basel, Switzerland)
|June 27, 2024
PubMed
概括

这项研究引入了一种新的CNN模型,用于交通信号控制,增强车辆流动. 深度Q学习方法比传统方法更有效地优化了交通信号定时.

关键词:
卷积神经网络 (CNN) 是一种神经网络.多排队系统多排队系统.实时的交通场景.信号的分配信号的分配.交通流量流速的流量流速.

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科学领域:

  • 人工智能的人工智能
  • 运输工程 运输工程
  • 计算机科学 计算机科学

背景情况:

  • 交通拥堵是城市地区的一个重要问题,导致旅行时间和排放量增加.
  • 当前的交通信号控制系统往往难以动态地适应不断变化的交通条件.
  • 交通信号定时的优化对于改善城市流动性和减少环境影响至关重要.

研究的目的:

  • 为信号分布控制算法 (SDCA) 提出一种新的卷积神经网络 (CNN) 模型.
  • 在每个交叉阶段最大限度地提高动态车辆交通信号流量.
  • 通过使用深度Q学习来增强交通信号时间优化.

主要方法:

  • 开发一个与信号分布控制算法 (SDCA) 集成的CNN模型.
  • 解构多向队列系统 (MDQS) 架构以确定最佳路由策略.
  • 使用深度Q学习方法与四元代理来增强决策.

主要成果:

  • 拟议的算法成功地确定了交通场景的最佳奖励值和新状态.
  • 结合深度Q学习的CNN-SDCA模型,在优化交通信号定时方面表现出卓越的性能.
  • 开发的方法明显优于传统的交通信号控制方法.

结论:

  • 基于CNN的SDCA模型为动态交通信号优化提供了有效的解决方案.
  • 深度Q学习提高了交通信号控制系统的适应性和效率.
  • 这项研究有助于通过智能信号管理改善城市交通流量并减少拥堵.