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相关概念视频

Collisions in Multiple Dimensions: Problem Solving01:06

Collisions in Multiple Dimensions: Problem Solving

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In multiple dimensions, the conservation of momentum applies in each direction independently. Hence, to solve collisions in multiple dimensions, we should write down the momentum conservation in each direction separately. To help understand collisions in multiple dimensions, consider an example.
A small car of mass 1,200 kg traveling east at 60 km/h collides at an intersection with a truck of mass 3,000 kg traveling due north at 40 km/h. The two vehicles are locked together. What is the...
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Design Example: Alignment of a Road Line Using GIS01:17

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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...
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Elastic Collisions: Case Study01:15

Elastic Collisions: Case Study

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Elastic collision of a system demands conservation of both momentum and kinetic energy. To solve problems involving one-dimensional elastic collisions between two objects, the equations for conservation of momentum and conservation of internal kinetic energy can be used. For the two objects, the sum of momentum before the collision equals the total momentum after the collision. An elastic collision conserves internal kinetic energy, and so the sum of kinetic energies before the collision equals...
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Collisions in Multiple Dimensions: Introduction01:05

Collisions in Multiple Dimensions: Introduction

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It is far more common for collisions to occur in two dimensions; that is, the initial velocity vectors are neither parallel nor antiparallel to each other. Let's see what complications arise from this. The first idea is that momentum is a vector. Like all vectors, it can be expressed as a sum of perpendicular components (usually, though not always, an x-component and a y-component, and a z-component if necessary). Thus, when the statement of conservation of momentum is written for a...
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Vertical Curve: Problem Solving01:23

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Vertical curves provide the transition between two roadway grades, ensuring safety, comfort, and functionality. Calculating elevations at specific stations along the curve involves several systematic steps based on the curve's geometry and provided design parameters.The vertical curve is defined by its length, grades, Point of Vertical Intersection (P.V.I.) location, and P.V.I. elevation. The stations of the Point of Vertical Curvature (P.V.C.), where the curve begins, and the Point of Vertical...
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Horizontal Curve: Problem Solving01:03

Horizontal Curve: Problem Solving

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A horizontal curve is characterized by its radius, intersection angle, and stationing of key points. In this case, the radius is 400 meters, and the angle of intersection is 30 degrees, with the station of the point of curvature (P.C.) at 0 + 150 meters. The goal is to determine the station values at the point of intersection (P.I.), point of tangency (P.T.), and midpoint of the curve, as well as the length of the long chord.The process begins with calculating the tangent distance (T) and the...
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V-FCW:使用V2X网络进行曲线道路冲突的基于矢量向前碰撞预警算法.

Xiangpeng Cai1, Bowen Lv2, Hanchen Yao3

  • 1College of Transportation and Navigation, Quanzhou Normal University, Donghai Street 398, Quanzhou 362046, Fujian, China.

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|November 21, 2024
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概括

一个新的基于矢量向前碰撞预警 (V-FCW) 算法通过在曲的道路上准确检测车辆来提高交通安全. 这种先进的驾驶辅助系统 (ADAS) 减少了错误警告,增强了智能驾驶系统.

关键词:
蜂式车辆到一切 (C-V2X)有曲线的道路冲突.前方碰撞预警系统

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科学领域:

  • 智能运输系统 智能运输系统
  • 汽车工程 汽车工程
  • 计算机科学 计算机科学

背景情况:

  • 先进的驾驶辅助系统 (ADAS),特别是前置碰撞预警 (FCW) 算法,对于预防交通事故至关重要.
  • 现有的FCW算法在曲线道路上难以准确确定车辆距离,导致持续的交通冲突.
  • 对于能够处理复杂的道路几何形状的增强算法的需求对于改善道路安全至关重要.

研究的目的:

  • 提出和评估一种新的基于矢量向前碰撞预警 (V-FCW) 算法,该算法旨在克服非传统路段当前FCW系统的局限性.
  • 提高主机车辆 (HV) 和远程车辆 (RV) 之间的距离和相对角度估计在直线和曲线道路上的准确性.
  • 为促进车辆与道路之间的合作,在Cellular Vehicle-to-Everything (C-V2X) 支持的智能驾驶环境中做出贡献.

主要方法:

  • V-FCW算法利用向量关系通过车辆到车辆 (V2V) 通信来估计HV和RV的姿势 (位置,速度,方向角).
  • 车道定位是使用车辆到基础设施 (V2I) 通信进行的,支持基于路边单位 (RSU) 的本地地图.
  • 该算法在Simcenter Prescan模拟平台和蜂式车辆到一切 (C-V2X) 通信平台上实施和测试,包括硬件在循环中的实验.

主要成果:

  • 模拟结果证实了V-FCW算法的能力,能够准确地识别和警告在直线和曲的道路段上危险的车辆.
  • 硬件在循环中的实验证明了算法的有效性,可以在各种道路条件下准确预测四个不同的警告级别.
  • V-FCW算法显著减少了错误警告,提高了防撞系统的可靠性.

结论:

  • 拟议的V-FCW算法有效地解决了在曲线道路上准确估计车辆距离的挑战,这是当前ADAS的一个关键局限性.
  • 在C-V2X框架内集成V2V和V2I通信,使V-FCW系统的性能稳定.
  • 这项研究代表了车辆与道路合作的重大进步,为更安全,更智能的自动驾驶铺平了道路.