自动驾驶不同工况避障模型（perscan、simulink、carsim联仿），能够避开预设的（静态）障碍物
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自动驾驶不同工况避障模型（perscan、simulink、carsim联仿），能够避开预设的（静态）障碍物 <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/89867543/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/89867543/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">标题<span class="ff2">：</span>基于<span class="_ _0"> </span><span class="ff3">Perscan<span class="ff4">、</span>Simulink<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>联合仿真的智能驾驶工况避障模型研究</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span>本文通过结合<span class="_ _0"> </span><span class="ff3">Perscan<span class="ff4">、</span>Simulink<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>等仿真工具<span class="ff2">，</span>研究了一种自动驾驶系统在不</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">同工况下对障碍物进行避让的模型<span class="ff4">。</span>该模型能够精确地避开预设的静态障碍物<span class="ff2">，</span>并且能够通过后期优</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">化进一步提升性能<span class="ff4">。</span>本研究将重点探讨系统的建模过程<span class="ff4">、</span>算法设计及仿真结果<span class="ff2">，</span>并通过实验证明该模</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">型的可行性和有效性<span class="ff4">。</span></div><div class="t m0 x1 h2 y6 ff3 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">引言</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">随着智能驾驶技术的快速发展<span class="ff2">，</span>自动驾驶系统的安全性和可靠性成为了研究的焦点之一<span class="ff4">。</span>针对不同工</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">况下的避障问题<span class="ff2">，</span>本文提出了一种基于<span class="_ _0"> </span><span class="ff3">Perscan<span class="ff4">、</span>Simulink<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>联合仿真的智能驾驶工况</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">避障模型<span class="ff4">。</span></div><div class="t m0 x1 h2 ya ff3 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span><span class="ff1">模型建立及算法设计</span></div><div class="t m0 x1 h2 yb ff3 fs0 fc0 sc0 ls0 ws0">2.1.<span class="_"> </span>Perscan<span class="_ _1"> </span><span class="ff1">仿真工具介绍</span></div><div class="t m0 x1 h2 yc ff3 fs0 fc0 sc0 ls0 ws0">Perscan<span class="_ _1"> </span><span class="ff1">是一款用于模拟障碍物感知的仿真工具<span class="ff2">，</span>它能够生成传感器的感知数据<span class="ff2">，</span>为自动驾驶系统提</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">供输入<span class="ff4">。</span></div><div class="t m0 x1 h2 ye ff3 fs0 fc0 sc0 ls0 ws0">2.2.<span class="_"> </span>Simulink<span class="_ _1"> </span><span class="ff1">仿真工具介绍</span></div><div class="t m0 x1 h2 yf ff3 fs0 fc0 sc0 ls0 ws0">Simulink<span class="_ _1"> </span><span class="ff1">是一款广泛应用于系统级仿真的工具<span class="ff2">，</span>它可以快速搭建系统模型<span class="ff2">，</span>并进行仿真和分析<span class="ff4">。</span></span></div><div class="t m0 x1 h2 y10 ff3 fs0 fc0 sc0 ls0 ws0">2.3.<span class="_"> </span>Carsim<span class="_ _1"> </span><span class="ff1">仿真工具介绍</span></div><div class="t m0 x1 h2 y11 ff3 fs0 fc0 sc0 ls0 ws0">Carsim<span class="_ _1"> </span><span class="ff1">是一款用于车辆动力学仿真的工具<span class="ff2">，</span>它能够模拟车辆在不同路况下的运动行为<span class="ff4">。</span></span></div><div class="t m0 x1 h2 y12 ff3 fs0 fc0 sc0 ls0 ws0">2.4.<span class="_"> </span><span class="ff1">智能驾驶工况避障模型设计</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">基于<span class="_ _0"> </span><span class="ff3">Perscan<span class="ff4">、</span>Simulink<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>联合仿真<span class="ff2">，</span>本文提出了一种智能驾驶工况避障模型<span class="ff4">。</span>该模型</div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">首先利用<span class="_ _0"> </span><span class="ff3">Perscan<span class="_ _1"> </span></span>生成的传感器数据进行障碍物感知<span class="ff2">，</span>然后通过<span class="_ _0"> </span><span class="ff3">Simulink<span class="_ _1"> </span></span>将感知数据输入到模型</div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">中进行处理<span class="ff2">，</span>并最终采用<span class="_ _0"> </span><span class="ff3">Carsim<span class="_ _1"> </span></span>模拟车辆的运动行为<span class="ff4">。</span></div><div class="t m0 x1 h2 y16 ff3 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">仿真实验及结果分析</span></div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">为了验证所提出的工况避障模型的性能<span class="ff2">，</span>本文进行了大量的仿真实验<span class="ff4">。</span>通过改变工况参数和障碍物位</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">置等因素<span class="ff2">，</span>分析模型在不同场景下的避障效果<span class="ff4">。</span></div><div class="t m0 x1 h2 y19 ff3 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span><span class="ff1">后期优化与模型改进</span></div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">基于仿真实验结果<span class="ff2">，</span>可以发现当前模型在避障时还存在一定的局限性<span class="ff4">。</span>因此<span class="ff2">，</span>本文提出了一种后期优</div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">化方法<span class="ff2">，</span>通过进一步改进模型的算法和参数配置<span class="ff2">，</span>提升模型的避障性能<span class="ff4">。</span></div><div class="t m0 x1 h2 y1c ff3 fs0 fc0 sc0 ls0 ws0">5.<span class="_ _2"> </span><span class="ff1">结论</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>