自动驾驶控制-斯坦利（stanely）算法路径跟踪仿真matlab和carsim联合仿真搭建的无人驾驶斯坦利控制器仿真验证，可以实现双移线，圆形，以及其他自定义的路径跟踪 跟踪效果如图，几乎没有误
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自动驾驶控制-斯坦利（stanely）算法路径跟踪仿真matlab和carsim联合仿真搭建的无人驾驶斯坦利控制器仿真验证，可以实现双移线，圆形，以及其他自定义的路径跟踪。跟踪效果如图，几乎没有误差，跟踪误差在0.05m以内。 <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/90239811/2/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/90239811/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">自动驾驶控制中的斯坦利算法路径跟踪仿真研究</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff2">、</span>引言</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">随着无人驾驶技术的飞速发展<span class="ff3">，</span>自动驾驶控制算法的研究日益受到关注<span class="ff2">。</span>路径跟踪作为无人驾驶车辆</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">的核心技术之一<span class="ff3">，</span>其性能直接影响到整个自动驾驶系统的稳定性和安全性<span class="ff2">。</span>斯坦利算法作为一种有效</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">的路径跟踪控制算法<span class="ff3">，</span>在自动驾驶控制领域得到了广泛的应用<span class="ff2">。</span>本文将围绕斯坦利算法路径跟踪仿真</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">展开研究<span class="ff3">，</span>并结合<span class="_ _0"> </span><span class="ff4">matlab<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff4">Carsim<span class="_ _1"> </span></span>联合仿真平台<span class="ff3">，</span>实现对双移线<span class="ff2">、</span>圆形以及其他自定义路径的跟</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">踪仿真验证<span class="ff2">。</span></div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff2">、</span>斯坦利算法概述</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">斯坦利算法是一种基于几何路径跟踪的控制算法<span class="ff3">，</span>它通过计算车辆质心与期望路径之间的偏差<span class="ff3">，</span>生成</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">适当的控制指令<span class="ff3">，</span>使车辆能够沿着期望路径行驶<span class="ff2">。</span>该算法具有结构简单<span class="ff2">、</span>响应迅速<span class="ff2">、</span>易于实现等优点</div><div class="t m0 x1 h2 yb ff3 fs0 fc0 sc0 ls0 ws0">，<span class="ff1">在自动驾驶控制领域得到了广泛应用<span class="ff2">。</span></span></div><div class="t m0 x1 h2 yc ff1 fs0 fc0 sc0 ls0 ws0">三<span class="ff2">、<span class="ff4">Matlab<span class="_ _1"> </span></span></span>与<span class="_ _0"> </span><span class="ff4">Carsim<span class="_ _1"> </span></span>联合仿真平台搭建</div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">为了实现对斯坦利算法的仿真验证<span class="ff3">，</span>本文采用<span class="_ _0"> </span><span class="ff4">Matlab<span class="_ _1"> </span></span>与<span class="_ _0"> </span><span class="ff4">Carsim<span class="_ _1"> </span></span>联合仿真平台<span class="ff2">。</span>其中<span class="ff3">，<span class="ff4">Matlab<span class="_ _1"> </span></span></span>作</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">为一款强大的数学计算软件<span class="ff3">，</span>提供了丰富的函数库和工具箱<span class="ff3">，</span>便于进行算法开发和仿真验证<span class="ff3">；</span>而</div><div class="t m0 x1 h2 yf ff4 fs0 fc0 sc0 ls0 ws0">Carsim<span class="_ _1"> </span><span class="ff1">作为一款专业的车辆动力学仿真软件<span class="ff3">，</span>能够模拟真实的车辆行驶环境<span class="ff3">，</span>为斯坦利算法提供真</span></div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">实的车辆动力学模型<span class="ff2">。</span></div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">四<span class="ff2">、</span>斯坦利算法路径跟踪仿真实现</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">在<span class="_ _0"> </span><span class="ff4">Matlab<span class="_ _1"> </span></span>与<span class="_ _0"> </span><span class="ff4">Carsim<span class="_ _1"> </span></span>联合仿真平台上<span class="ff3">，</span>我们实现了对双移线<span class="ff2">、</span>圆形以及其他自定义路径的跟踪仿真</div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">验证<span class="ff2">。</span></div><div class="t m0 x1 h2 y14 ff4 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">双移线路径跟踪仿真</span></div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">双移线路径作为一种典型的复杂路径<span class="ff3">，</span>对于路径跟踪算法来说具有一定的挑战性<span class="ff2">。</span>我们通过斯坦利算</div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">法实现了对双移线路径的准确跟踪<span class="ff3">，</span>跟踪效果良好<span class="ff3">，</span>误差在允许范围内<span class="ff2">。</span></div><div class="t m0 x1 h2 y17 ff4 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">圆形路径跟踪仿真</span></div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">圆形路径跟踪是自动驾驶中的另一项重要技术<span class="ff2">。</span>在仿真实验中<span class="ff3">，</span>我们采用斯坦利算法对圆形路径进行</div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">跟踪<span class="ff3">，</span>实验结果表明<span class="ff3">，</span>斯坦利算法能够实现对圆形路径的准确跟踪<span class="ff3">，</span>且跟踪效果稳定<span class="ff2">。</span></div><div class="t m0 x1 h2 y1a ff4 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">其他自定义路径跟踪仿真</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>