基于模型预测控制(mpc)的车辆换道,车辆轨迹跟踪,换道轨迹为五次多项式,matlab与carsim联防控制

ugdMoXOYfeZIP基于模型预测控制的车辆换.zip  2.41MB

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ZIP 基于模型预测控制的车辆换.zip 大约有15个文件
  1. 1.jpg 105.42KB
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  3. 3.jpg 920.12KB
  4. 4.jpg 908.02KB
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  8. 基于模型预测控制的车辆换道与轨迹跟踪一直是.txt 1.93KB
  9. 基于模型预测控制的车辆换道与轨迹跟踪技术分.txt 1.92KB
  10. 基于模型预测控制的车辆换道和车辆轨迹跟踪一直.txt 1.81KB
  11. 基于模型预测控制的车辆换道是一种先进的控制方法它.doc 1.71KB
  12. 基于模型预测控制的车辆换道车辆轨迹跟踪.html 5KB
  13. 基于模型预测控制的车辆换道车辆轨迹跟踪.txt 138B
  14. 基于模型预测控制的车辆换道轨迹跟踪技术分析一引.txt 2.02KB
  15. 基于模型预测控制的车辆换道轨迹跟踪技术分析一引言.txt 2.02KB

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基于模型预测控制(mpc)的车辆换道,车辆轨迹跟踪,换道轨迹为五次多项式,matlab与carsim联防控制

<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89761344/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89761344/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">基于模型预测控制<span class="ff2">(<span class="ff3">MPC</span>)</span>的车辆换道<span class="ff2">,</span>是一种先进的控制方法<span class="ff2">,</span>它通过预测车辆未来的行驶轨迹<span class="ff2">,</span></div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">以及对当前环境的感知<span class="ff2">,</span>实现车辆的安全<span class="ff4">、</span>稳定地换道行驶<span class="ff4">。</span>本文将以<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>算法为核心<span class="ff2">,</span>结合五次多</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">项式生成换道轨迹<span class="ff2">,</span>并介绍与<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>与<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>的联合仿真实现<span class="ff4">。</span></div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">在车辆的自动驾驶技术中<span class="ff2">,</span>换道行为是一项关键的功能之一<span class="ff4">。</span>对于自动驾驶车辆而言<span class="ff2">,</span>能够准确地进</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">行换道行驶是确保道路交通安全的重要任务<span class="ff4">。</span>而<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>作为一种先进的控制方法<span class="ff2">,</span>已经被广泛应用于车</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">辆的轨迹跟踪<span class="ff4">、</span>转向控制等方面<span class="ff4">。</span></div><div class="t m0 x1 h2 y7 ff3 fs0 fc0 sc0 ls0 ws0">MPC<span class="_ _1"> </span><span class="ff1">算法的核心思想是通过对车辆和环境的建模<span class="ff2">,</span>根据预测的车辆轨迹来生成最优控制策略<span class="ff4">。</span>在车辆</span></div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">换道中<span class="ff2">,<span class="ff3">MPC<span class="_ _1"> </span></span></span>算法可以通过对车辆的动力学模型进行数学建模<span class="ff2">,</span>并根据当前车辆状态和环境感知信息</div><div class="t m0 x1 h2 y9 ff2 fs0 fc0 sc0 ls0 ws0">,<span class="ff1">预测车辆未来的行驶轨迹<span class="ff4">。</span>通过优化控制策略</span>,<span class="ff1">使车辆能够按照预定的换道轨迹安全<span class="ff4">、</span>稳定地进行</span></div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">换道行驶<span class="ff4">。</span></div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">为了生成符合要求的换道轨迹<span class="ff2">,</span>本文采用了五次多项式来描述车辆换道的路径<span class="ff4">。</span>五次多项式具有较高</div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">的灵活性和逼近能力<span class="ff2">,</span>能够精确地描述车辆的换道轨迹<span class="ff4">。</span>通过合理选择换道轨迹的起始点<span class="ff4">、</span>朝向角以</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">及路径曲率等参数<span class="ff2">,</span>可以生成符合实际道路情况的换道路径<span class="ff4">。</span></div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">为了验证基于<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>算法的换道控制策略的性能<span class="ff2">,</span>本文采用了<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>与<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>的联合仿真实现<span class="ff4">。</span></div><div class="t m0 x1 h2 yf ff3 fs0 fc0 sc0 ls0 ws0">Matlab<span class="_ _1"> </span><span class="ff1">作为一种强大的数学建模与仿真工具<span class="ff2">,</span>可以方便地对<span class="_ _0"> </span></span>MPC<span class="_ _1"> </span><span class="ff1">算法进行实现和验证<span class="ff4">。</span>而<span class="_ _0"> </span></span>Carsim</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">则提供了真实车辆动力学模型的仿真环境<span class="ff2">,</span>可以对车辆的换道行为进行真实场景的模拟<span class="ff4">。</span></div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">通过<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>与<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>的联合仿真<span class="ff2">,</span>我们可以有效地评估<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>算法在车辆换道控制中的性能<span class="ff4">。</span>通</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">过对不同换道场景下的仿真实验<span class="ff2">,</span>可以验证<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>算法的鲁棒性和控制效果<span class="ff4">。</span>同时<span class="ff2">,</span>由于<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>算法的</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">灵活性<span class="ff2">,</span>可以通过调整控制参数来适应不同的换道需求<span class="ff2">,</span>实现个性化的换道行驶<span class="ff4">。</span></div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">综上所述<span class="ff2">,</span>基于模型预测控制的车辆换道是一种先进的控制方法<span class="ff2">,</span>可以实现车辆的安全<span class="ff4">、</span>稳定地换道</div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">行驶<span class="ff4">。</span>通过采用五次多项式来描述换道轨迹<span class="ff2">,</span>并结合<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>与<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>的联合仿真实现<span class="ff2">,</span>可以有效</div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">地验证<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>算法的性能<span class="ff4">。</span>未来<span class="ff2">,</span>随着自动驾驶技术的不断发展<span class="ff2">,</span>基于<span class="_ _0"> </span><span class="ff3">MPC<span class="_ _1"> </span></span>的车辆换道控制将发挥越</div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">来越重要的作用<span class="ff2">,</span>为道路交通安全和出行效率提供强有力的支持<span class="ff4">。</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>
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