{"id":816,"date":"2024-08-30T10:19:17","date_gmt":"2024-08-30T02:19:17","guid":{"rendered":"http:\/\/110.42.248.92\/onsite-learning-center\/?page_id=816"},"modified":"2025-06-03T10:35:58","modified_gmt":"2025-06-03T02:35:58","slug":"%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b","status":"publish","type":"page","link":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b\/","title":{"rendered":"Start - Prediction"},"content":{"rendered":"<div class=\"fusion-fullwidth fullwidth-box fusion-builder-row-1 fusion-flex-container has-pattern-background has-mask-background nonhundred-percent-fullwidth non-hundred-percent-height-scrolling\" style=\"--awb-border-radius-top-left:0px;--awb-border-radius-top-right:0px;--awb-border-radius-bottom-right:0px;--awb-border-radius-bottom-left:0px;--awb-flex-wrap:wrap;\" ><div class=\"fusion-builder-row fusion-row fusion-flex-align-items-flex-start fusion-flex-content-wrap\" style=\"max-width:1248px;margin-left: calc(-4% \/ 2 );margin-right: calc(-4% \/ 2 );\"><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-0 fusion_builder_column_1_4 1_4 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:25%;--awb-margin-top-large:0px;--awb-spacing-right-large:7.68%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:7.68%;--awb-width-medium:25%;--awb-order-medium:0;--awb-spacing-right-medium:7.68%;--awb-spacing-left-medium:7.68%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-1\"><\/div><nav class=\"awb-menu awb-menu_column awb-menu_em-click mobile-mode-collapse-to-button awb-menu_icons-left awb-menu_dc-yes mobile-trigger-fullwidth-off awb-menu_mobile-toggle mobile-size-full-absolute loading mega-menu-loading awb-menu_desktop awb-menu_v-stacked awb-submenu_cm_accordion\" style=\"--awb-line-height:var(--awb-typography3-line-height);--awb-margin-top:80px;--awb-margin-bottom:80px;--awb-text-transform:var(--awb-typography3-text-transform);--awb-bg:hsla(var(--awb-color5-h),var(--awb-color5-s),var(--awb-color5-l),calc(var(--awb-color5-a) - 95%));--awb-border-radius-top-left:5px;--awb-border-radius-top-right:5px;--awb-border-radius-bottom-right:5px;--awb-border-radius-bottom-left:5px;--awb-gap:20px;--awb-items-padding-top:20px;--awb-items-padding-bottom:20px;--awb-items-padding-left:30px;--awb-color:var(--awb-color8);--awb-letter-spacing:var(--awb-typography3-letter-spacing);--awb-active-color:var(--awb-color5);--awb-active-bg:hsla(var(--awb-color4-h),var(--awb-color4-s),var(--awb-color4-l),calc(var(--awb-color4-a) - 95%));--awb-submenu-sep-color:hsla(var(--awb-color2-h),var(--awb-color2-s),calc(var(--awb-color2-l) - 3%),var(--awb-color2-a));--awb-submenu-items-padding-top:15px;--awb-submenu-items-padding-bottom:15px;--awb-submenu-font-size:var(--awb-typography5-font-size);--awb-submenu-text-transform:var(--awb-typography5-text-transform);--awb-submenu-line-height:var(--awb-typography5-line-height);--awb-submenu-letter-spacing:var(--awb-typography5-letter-spacing);--awb-main-justify-content:center;--awb-sub-justify-content:center;--awb-mobile-nav-button-align-hor:center;--awb-mobile-bg:hsla(var(--awb-color5-h),var(--awb-color5-s),var(--awb-color5-l),calc(var(--awb-color5-a) - 98%));--awb-mobile-trigger-font-size:22px;--awb-mobile-trigger-color:var(--awb-color8);--awb-mobile-nav-trigger-bottom-margin:10px;--awb-mobile-font-size:var(--awb-typography3-font-size);--awb-mobile-text-transform:var(--awb-typography3-text-transform);--awb-mobile-line-height:var(--awb-typography3-line-height);--awb-mobile-letter-spacing:var(--awb-typography3-letter-spacing);--awb-mobile-justify:center;--awb-mobile-caret-left:auto;--awb-mobile-caret-right:0;--awb-box-shadow: 0px 0px ;;--awb-fusion-font-family-typography:var(--awb-typography3-font-family);--awb-fusion-font-weight-typography:var(--awb-typography3-font-weight);--awb-fusion-font-style-typography:var(--awb-typography3-font-style);--awb-fusion-font-family-submenu-typography:var(--awb-typography5-font-family);--awb-fusion-font-weight-submenu-typography:var(--awb-typography5-font-weight);--awb-fusion-font-style-submenu-typography:var(--awb-typography5-font-style);--awb-fusion-font-family-mobile-typography:var(--awb-typography3-font-family);--awb-fusion-font-weight-mobile-typography:var(--awb-typography3-font-weight);--awb-fusion-font-style-mobile-typography:var(--awb-typography3-font-style);\" aria-label=\"Quick Start\" data-breakpoint=\"640\" data-count=\"0\" data-transition-type=\"fade\" data-transition-time=\"300\"><button type=\"button\" class=\"awb-menu__m-toggle\" aria-expanded=\"false\" aria-controls=\"menu-%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\"><span class=\"awb-menu__m-toggle-inner\"><span class=\"collapsed-nav-text\">Menu<\/span><span class=\"awb-menu__m-collapse-icon\"><span class=\"awb-menu__m-collapse-icon-open fa-bars fas\"><\/span><span class=\"awb-menu__m-collapse-icon-close fa-times fas\"><\/span><\/span><\/span><\/button><ul id=\"menu-%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\" class=\"fusion-menu awb-menu__main-ul awb-menu__main-ul_column\"><li  id=\"menu-item-898\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-has-children menu-item-898 awb-menu__li awb-menu__main-li awb-menu__main-li_regular\"  data-item-id=\"898\"><span class=\"awb-menu__main-background-default awb-menu__main-background-default_fade\"><\/span><span class=\"awb-menu__main-background-active awb-menu__main-background-active_fade\"><\/span><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5\/\" class=\"awb-menu__main-a awb-menu__main-a_regular\"><span class=\"menu-text\">Perception<\/span><\/a><button type=\"button\" aria-label=\"Open submenu of Perception\" aria-expanded=\"false\" class=\"awb-menu__open-nav-submenu_mobile awb-menu__open-nav-submenu_click awb-menu__open-nav-submenu_main awb-menu__open-nav-submenu_needs-spacing\"><\/button><ul class=\"awb-menu__sub-ul awb-menu__sub-ul_main\"><li  id=\"menu-item-1537\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1537 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5-%e8%af%ad%e4%b9%89%e5%88%86%e5%89%b2\/\" class=\"awb-menu__sub-a\"><span>Code-Semantic Segmentation<\/span><\/a><\/li><li  id=\"menu-item-1535\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1535 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5-%e6%b7%b1%e5%ba%a6%e4%bc%b0%e8%ae%a1\/\" class=\"awb-menu__sub-a\"><span>Code - Depth Estimation<\/span><\/a><\/li><li  id=\"menu-item-1533\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1533 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5-2d%e7%9b%ae%e6%a0%87%e6%a3%80%e6%b5%8b\/\" class=\"awb-menu__sub-a\"><span>Code-2D Object Detection<\/span><\/a><\/li><li  id=\"menu-item-1566\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1566 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5\/%e5%bc%80%e5%a7%8b-%e6%84%9f%e7%9f%a5-%e7%9b%ae%e6%a0%87%e8%bf%bd%e8%b8%aa\/\" class=\"awb-menu__sub-a\"><span>Code - Goal Tracking<\/span><\/a><\/li><\/ul><\/li><li  id=\"menu-item-1473\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-has-children menu-item-1473 awb-menu__li awb-menu__main-li awb-menu__main-li_regular\"  data-item-id=\"1473\"><span class=\"awb-menu__main-background-default awb-menu__main-background-default_fade\"><\/span><span class=\"awb-menu__main-background-active awb-menu__main-background-active_fade\"><\/span><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b\/\" class=\"awb-menu__main-a awb-menu__main-a_regular\"><span class=\"menu-text\">Prediction<\/span><\/a><button type=\"button\" aria-label=\"Open submenu of Prediction\" aria-expanded=\"false\" class=\"awb-menu__open-nav-submenu_mobile awb-menu__open-nav-submenu_click awb-menu__open-nav-submenu_main awb-menu__open-nav-submenu_needs-spacing\"><\/button><ul class=\"awb-menu__sub-ul awb-menu__sub-ul_main\"><li  id=\"menu-item-1926\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1926 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b%ef%bc%9a%e5%8d%95%e8%bd%a6%e5%8d%95%e6%a8%a1%e6%80%81%e8%bd%a6%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b\/\" class=\"awb-menu__sub-a\"><span>Code \u2013 bicycle trajectory prediction<\/span><\/a><\/li><li  id=\"menu-item-1545\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1545 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-vru%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b\/\" class=\"awb-menu__sub-a\"><span>Code-VRU trajectory prediction<\/span><\/a><\/li><li  id=\"menu-item-1658\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1658 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-%e6%9c%ba%e5%8a%a8%e8%bd%a6%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b-cloned\/\" class=\"awb-menu__sub-a\"><span>Code-Multi-vehicle trajectory prediction<\/span><\/a><\/li><\/ul><\/li><li  id=\"menu-item-897\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-has-children menu-item-897 awb-menu__li awb-menu__main-li awb-menu__main-li_regular\"  data-item-id=\"897\"><span class=\"awb-menu__main-background-default awb-menu__main-background-default_fade\"><\/span><span class=\"awb-menu__main-background-active awb-menu__main-background-active_fade\"><\/span><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e8%a7%84%e5%88%92-%e5%86%b3%e7%ad%96\/\" class=\"awb-menu__main-a awb-menu__main-a_regular\"><span class=\"menu-text\">Decision\/Planning Problems<\/span><\/a><button type=\"button\" aria-label=\"Open submenu of Decision\/Planning Problems\" aria-expanded=\"false\" class=\"awb-menu__open-nav-submenu_mobile awb-menu__open-nav-submenu_click awb-menu__open-nav-submenu_main awb-menu__open-nav-submenu_needs-spacing\"><\/button><ul class=\"awb-menu__sub-ul awb-menu__sub-ul_main\"><li  id=\"menu-item-1530\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1530 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e8%a7%84%e5%88%92-%e5%86%b3%e7%ad%96\/%e5%bc%80%e5%a7%8b-%e5%86%b3%e7%ad%96-%e8%a7%84%e5%88%92-%e8%a1%8c%e4%b8%ba%e5%86%b3%e7%ad%96\/\" class=\"awb-menu__sub-a\"><span>Code-Bike Decisions<\/span><\/a><\/li><li  id=\"menu-item-1742\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1742 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e8%a7%84%e5%88%92-%e5%86%b3%e7%ad%96\/%e5%bc%80%e5%a7%8b-%e5%86%b3%e7%ad%96-%e8%a7%84%e5%88%92-%e5%8d%8f%e5%90%8c%e5%86%b3%e7%ad%96\/\" class=\"awb-menu__sub-a\"><span>Code - Collaborative Decision Making<\/span><\/a><\/li><li  id=\"menu-item-1532\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1532 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e8%a7%84%e5%88%92-%e5%86%b3%e7%ad%96\/%e5%bc%80%e5%a7%8b-%e5%86%b3%e7%ad%96-%e8%a7%84%e5%88%92-%e8%bf%90%e5%8a%a8%e8%a7%84%e5%88%92\/\" class=\"awb-menu__sub-a\"><span>Code-Motion Planning<\/span><\/a><\/li><\/ul><\/li><li  id=\"menu-item-899\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-has-children menu-item-899 awb-menu__li awb-menu__main-li awb-menu__main-li_regular\"  data-item-id=\"899\"><span class=\"awb-menu__main-background-default awb-menu__main-background-default_fade\"><\/span><span class=\"awb-menu__main-background-active awb-menu__main-background-active_fade\"><\/span><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6\/\" class=\"awb-menu__main-a awb-menu__main-a_regular\"><span class=\"menu-text\">Control<\/span><\/a><button type=\"button\" aria-label=\"Open submenu of Control\" aria-expanded=\"false\" class=\"awb-menu__open-nav-submenu_mobile awb-menu__open-nav-submenu_click awb-menu__open-nav-submenu_main awb-menu__open-nav-submenu_needs-spacing\"><\/button><ul class=\"awb-menu__sub-ul awb-menu__sub-ul_main\"><li  id=\"menu-item-1538\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1538 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6-%e6%a8%aa%e5%90%91%e6%8e%a7%e5%88%b6\/\" class=\"awb-menu__sub-a\"><span>Code - Horizontal Control<\/span><\/a><\/li><li  id=\"menu-item-1539\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1539 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6-%e7%ba%b5%e5%90%91%e6%8e%a7%e5%88%b6\/\" class=\"awb-menu__sub-a\"><span>Code-vertical control<\/span><\/a><\/li><li  id=\"menu-item-1540\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-1540 awb-menu__li awb-menu__sub-li\" ><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6\/%e5%bc%80%e5%a7%8b-%e6%8e%a7%e5%88%b6-%e8%80%a6%e5%90%88%e6%8e%a7%e5%88%b6\/\" class=\"awb-menu__sub-a\"><span>Code-coupling control<\/span><\/a><\/li><\/ul><\/li><li  id=\"menu-item-2558\"  class=\"menu-item menu-item-type-post_type menu-item-object-page menu-item-2558 awb-menu__li awb-menu__main-li awb-menu__main-li_regular\"  data-item-id=\"2558\"><span class=\"awb-menu__main-background-default awb-menu__main-background-default_fade\"><\/span><span class=\"awb-menu__main-background-active awb-menu__main-background-active_fade\"><\/span><a  href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e7%ab%af%e5%88%b0%e7%ab%af\/\" class=\"awb-menu__main-a awb-menu__main-a_regular\"><span class=\"menu-text\">End-to-End Autonomous Driving<\/span><\/a><\/li><\/ul><\/nav><\/div><\/div><div class=\"fusion-layout-column fusion_builder_column fusion-builder-column-1 fusion_builder_column_3_4 3_4 fusion-flex-column\" style=\"--awb-bg-size:cover;--awb-width-large:75%;--awb-margin-top-large:0px;--awb-spacing-right-large:2.56%;--awb-margin-bottom-large:20px;--awb-spacing-left-large:2.56%;--awb-width-medium:75%;--awb-order-medium:0;--awb-spacing-right-medium:2.56%;--awb-spacing-left-medium:2.56%;--awb-width-small:100%;--awb-order-small:0;--awb-spacing-right-small:1.92%;--awb-spacing-left-small:1.92%;\"><div class=\"fusion-column-wrapper fusion-column-has-shadow fusion-flex-justify-content-flex-start fusion-content-layout-column\"><div class=\"fusion-text fusion-text-2\" style=\"--awb-font-size:38px;--awb-line-height:var(--awb-typography1-line-height);--awb-letter-spacing:var(--awb-typography1-letter-spacing);--awb-text-transform:var(--awb-typography1-text-transform);--awb-text-font-family:var(--awb-typography1-font-family);--awb-text-font-weight:var(--awb-typography1-font-weight);--awb-text-font-style:var(--awb-typography1-font-style);\"><p>Prediction<\/p>\n<\/div><div class=\"fusion-text fusion-text-3\" style=\"--awb-content-alignment:left;--awb-font-size:18px;--awb-line-height:2;--awb-letter-spacing:var(--awb-typography3-letter-spacing);--awb-text-transform:var(--awb-typography3-text-transform);--awb-text-font-family:&quot;Outfit&quot;;--awb-text-font-style:normal;--awb-text-font-weight:400;\"><p style=\"text-align: left;\">Prediction is a critical component of autonomous driving and directly affects system safety, reliability, and user experience. In complex and changing traffic environments, accurate predictions help autonomous vehicles make decisions and plan ahead, reduce unnecessary emergency braking or evasive maneuvers, and avoid potential collision risks, improving both safety and passenger experience.<\/p>\n<p>Typically, prediction tasks take road users\u2019 recent state information (e.g., positions, velocities, and headings over 1s or 3s) and map information (e.g., lanes, road markings, and traffic lights) as input, and output their future states over a horizon such as 3s or 5s (trajectory coordinates or distributions).<\/p>\n<p>The prediction problem is broken down into:<a href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-%e7%9f%a5%e8%af%86\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-%e6%9c%ba%e5%8a%a8%e8%bd%a6%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b\/\"><span style=\"color: #ff9900;\">Motor-Vehicle Trajectory Prediction Task<\/span><\/a>\u3001<a href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-%e7%9f%a5%e8%af%86\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-vru%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b\/\"><span style=\"color: #ff9900;\">Vulnerable road user (VRU) trajectory prediction task<\/span><\/a>\u3001<a href=\"http:\/\/110.42.248.92\/onsite-learning-center\/en\/%e5%bf%ab%e9%80%9f%e5%bc%80%e5%a7%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b\/%e5%bc%80%e5%a7%8b-%e9%a2%84%e6%b5%8b-%e6%9c%ba%e5%8a%a8%e8%bd%a6%e8%bd%a8%e8%bf%b9%e9%a2%84%e6%b5%8b-cloned\/\"><span style=\"color: #ff9900;\">Multi-target trajectory prediction task<\/span><\/a>\u3002<\/p>\n<\/div><div class=\"fusion-separator fusion-full-width-sep\" style=\"align-self: center;margin-left: auto;margin-right: auto;margin-bottom:30px;width:100%;\"><div class=\"fusion-separator-border sep-double sep-solid\" style=\"--awb-height:20px;--awb-amount:20px;border-color:var(--awb-color3);border-top-width:1px;border-bottom-width:1px;\"><\/div><\/div><div class=\"fusion-content-boxes content-boxes columns row fusion-columns-1 fusion-columns-total-1 fusion-content-boxes-1 content-boxes-icon-with-title content-left\" style=\"--awb-hover-accent-color:var(--awb-color4);--awb-circle-hover-accent-color:var(--awb-color4);--awb-item-margin-bottom:40px;\" data-animationoffset=\"top-into-view\"><div style=\"--awb-backgroundcolor:rgba(255,255,255,0);\" class=\"fusion-column content-box-column content-box-column content-box-column-1 col-lg-12 col-md-12 col-sm-12 fusion-content-box-hover content-box-column-last content-box-column-last-in-row\"><div class=\"col content-box-wrapper content-wrapper link-area-link-icon content-icon-wrapper-yes icon-hover-animation-fade\" data-animationoffset=\"top-into-view\"><div class=\"heading heading-with-icon icon-left\"><div class=\"icon\"><span style=\"height:42px;width:42px;line-height:22px;border-color:rgba(255,255,255,0);border-width:1px;border-style:solid;background-color:var(--awb-color8);box-sizing:content-box;border-radius:50%;\"><i style=\"border-color:var(--awb-color8);border-width:1px;background-color:var(--awb-color7);box-sizing:content-box;height:40px;width:40px;line-height:40px;border-radius:50%;position:relative;top:auto;left:auto;margin:0;border-radius:50%;font-size:20px;\" aria-hidden=\"true\" class=\"fontawesome-icon fa-car-alt fas circle-yes\"><\/i><\/span><\/div><h2 class=\"content-box-heading\" style=\"--h2_typography-font-size:24px;line-height:29px;\">Motor-Vehicle Trajectory Prediction Task<\/h2><\/div><div class=\"fusion-clearfix\"><\/div><div class=\"content-container\">\n<p style=\"line-height: 2; font-size: 17px;\">Motor vehicle trajectory prediction refers to predicting the future trajectories of other motor vehicles on the road. The difficulty of this task is that the behavior of motor vehicles is affected by many factors such as the driver's operating intentions, traffic rules, road conditions, and the surrounding environment. For example, a vehicle may suddenly change lanes, slow down, or accelerate. These behaviors are often sudden and may be affected by the dynamics of the vehicle ahead. In addition, different driving habits and complexity of road conditions will also lead to diversity of vehicle behavior, making prediction more difficult.<\/p>\n<\/div><\/div><\/div><div class=\"fusion-clearfix\"><\/div><\/div><div class=\"fusion-content-boxes content-boxes columns row fusion-columns-1 fusion-columns-total-1 fusion-content-boxes-2 content-boxes-icon-with-title content-left\" style=\"--awb-margin-top:-10%;--awb-hover-accent-color:var(--awb-color4);--awb-circle-hover-accent-color:var(--awb-color4);--awb-item-margin-bottom:40px;\" data-animationoffset=\"top-into-view\"><div style=\"--awb-backgroundcolor:rgba(255,255,255,0);\" class=\"fusion-column content-box-column content-box-column content-box-column-1 col-lg-12 col-md-12 col-sm-12 fusion-content-box-hover content-box-column-last content-box-column-last-in-row\"><div class=\"col content-box-wrapper content-wrapper link-area-link-icon content-icon-wrapper-yes icon-hover-animation-fade\" data-animationoffset=\"top-into-view\"><div class=\"heading heading-with-icon icon-left\"><div class=\"icon\"><span style=\"height:42px;width:42px;line-height:22px;border-color:rgba(255,255,255,0);border-width:1px;border-style:solid;background-color:var(--awb-color8);box-sizing:content-box;border-radius:50%;\"><i style=\"border-color:var(--awb-color8);border-width:1px;background-color:var(--awb-color7);box-sizing:content-box;height:40px;width:40px;line-height:40px;border-radius:50%;position:relative;top:auto;left:auto;margin:0;border-radius:50%;font-size:20px;\" aria-hidden=\"true\" class=\"fontawesome-icon fa-biking fas circle-yes\"><\/i><\/span><\/div><h2 class=\"content-box-heading\" style=\"--h2_typography-font-size:24px;line-height:29px;\">VRU Trajectory Prediction<\/h2><\/div><div class=\"fusion-clearfix\"><\/div><div class=\"content-container\">\n<p style=\"line-height: 2; font-size: 17px;\">VRU trajectory prediction mainly refers to predicting the future movement trajectories of non-motorized vehicles such as bicycles and electric scooters, as well as pedestrians. The challenge is that non-motor vehicles are extremely flexible. Non-motor vehicles are usually not restricted by fixed lanes. The speed and direction of non-motor vehicles change frequently, and their driving routes may be more arbitrary. Drivers' behavior patterns are difficult to predict, and some drivers may lack professional driving skills, resulting in higher uncertainty and unpredictability of behavior. Pedestrian behavior is highly uncertain and diverse. Pedestrians may suddenly change direction, stop, or cross roads, and their behavior is affected by personal purposes, traffic signals, and other factors.<\/p>\n<\/div><\/div><\/div><div class=\"fusion-clearfix\"><\/div><\/div><div class=\"fusion-content-boxes content-boxes columns row fusion-columns-1 fusion-columns-total-1 fusion-content-boxes-3 content-boxes-icon-with-title content-left\" style=\"--awb-margin-top:-10%;--awb-hover-accent-color:var(--awb-color4);--awb-circle-hover-accent-color:var(--awb-color4);--awb-item-margin-bottom:40px;\" data-animationoffset=\"top-into-view\"><div style=\"--awb-backgroundcolor:rgba(255,255,255,0);\" class=\"fusion-column content-box-column content-box-column content-box-column-1 col-lg-12 col-md-12 col-sm-12 fusion-content-box-hover content-box-column-last content-box-column-last-in-row\"><div class=\"col content-box-wrapper content-wrapper link-area-link-icon content-icon-wrapper-yes icon-hover-animation-fade\" data-animationoffset=\"top-into-view\"><div class=\"heading heading-with-icon icon-left\"><div class=\"icon\"><span style=\"height:42px;width:42px;line-height:22px;border-color:rgba(255,255,255,0);border-width:1px;border-style:solid;background-color:var(--awb-color8);box-sizing:content-box;border-radius:50%;\"><i style=\"border-color:var(--awb-color8);border-width:1px;background-color:var(--awb-color7);box-sizing:content-box;height:40px;width:40px;line-height:40px;border-radius:50%;position:relative;top:auto;left:auto;margin:0;border-radius:50%;font-size:20px;\" aria-hidden=\"true\" class=\"fontawesome-icon fa-bezier-curve fas circle-yes\"><\/i><\/span><\/div><h2 class=\"content-box-heading\" style=\"--h2_typography-font-size:24px;line-height:29px;\">Multi-Agent Prediction<\/h2><\/div><div class=\"fusion-clearfix\"><\/div><div class=\"content-container\">\n<p style=\"line-height: 2; font-size: 17px;\">Multi-objective trajectory prediction refers to simultaneously predicting the movement trajectories of multiple different types of road participants (including motor vehicles, non-motor vehicles and pedestrians) in the future in an autonomous driving scenario. The difficulty of this task is that the behavior patterns and movement patterns of different objects vary significantly and are highly dependent on interactions with each other and changes in the surrounding environment. Multi-objective trajectory prediction must also take into account the interactions between different objects. For example, a vehicle may slow down and stop in front of a zebra crossing to give way to pedestrians; a motor vehicle may adjust its speed or change lanes to avoid non-motor vehicles. These complex interaction patterns require that predictive models not only have powerful data processing and learning capabilities, but also need to be able to understand and simulate human behavioral logic and social norms.<\/p>\n<\/div><\/div><\/div><div class=\"fusion-clearfix\"><\/div><\/div><\/div><\/div><\/div><\/div>","protected":false},"excerpt":{"rendered":"","protected":false},"author":5,"featured_media":0,"parent":47,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"100-width.php","meta":{"inline_featured_image":false,"iawp_total_views":3287,"footnotes":""},"class_list":["post-816","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/pages\/816"}],"collection":[{"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/users\/5"}],"replies":[{"embeddable":true,"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/comments?post=816"}],"version-history":[{"count":36,"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/pages\/816\/revisions"}],"predecessor-version":[{"id":2322,"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/pages\/816\/revisions\/2322"}],"up":[{"embeddable":true,"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/pages\/47"}],"wp:attachment":[{"href":"http:\/\/110.42.248.92\/onsite-learning-center\/en\/wp-json\/wp\/v2\/media?parent=816"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}