{"version":"1.0","provider_name":"Reinforcement Learning for Noise Steering in Diffusion-Based Driving Models","provider_url":"https:\/\/mscvprojects.ri.cmu.edu\/2025fteam24","title":"Experiments - Reinforcement Learning for Noise Steering in Diffusion-Based Driving Models","type":"rich","width":600,"height":338,"html":"<blockquote class=\"wp-embedded-content\" data-secret=\"AvRyUO7E02\"><a href=\"https:\/\/mscvprojects.ri.cmu.edu\/2025fteam24\/experiments\/\">Experiments<\/a><\/blockquote><iframe sandbox=\"allow-scripts\" security=\"restricted\" src=\"https:\/\/mscvprojects.ri.cmu.edu\/2025fteam24\/experiments\/embed\/#?secret=AvRyUO7E02\" width=\"600\" height=\"338\" title=\"&#8220;Experiments&#8221; &#8212; Reinforcement Learning for Noise Steering in Diffusion-Based Driving Models\" data-secret=\"AvRyUO7E02\" frameborder=\"0\" marginwidth=\"0\" marginheight=\"0\" scrolling=\"no\" class=\"wp-embedded-content\"><\/iframe><script>\n\/*! This file is auto-generated *\/\n!function(d,l){\"use strict\";l.querySelector&&d.addEventListener&&\"undefined\"!=typeof URL&&(d.wp=d.wp||{},d.wp.receiveEmbedMessage||(d.wp.receiveEmbedMessage=function(e){var t=e.data;if((t||t.secret||t.message||t.value)&&!\/[^a-zA-Z0-9]\/.test(t.secret)){for(var s,r,n,a=l.querySelectorAll('iframe[data-secret=\"'+t.secret+'\"]'),o=l.querySelectorAll('blockquote[data-secret=\"'+t.secret+'\"]'),c=new RegExp(\"^https?:$\",\"i\"),i=0;i<o.length;i++)o[i].style.display=\"none\";for(i=0;i<a.length;i++)s=a[i],e.source===s.contentWindow&&(s.removeAttribute(\"style\"),\"height\"===t.message?(1e3<(r=parseInt(t.value,10))?r=1e3:~~r<200&&(r=200),s.height=r):\"link\"===t.message&&(r=new URL(s.getAttribute(\"src\")),n=new URL(t.value),c.test(n.protocol))&&n.host===r.host&&l.activeElement===s&&(d.top.location.href=t.value))}},d.addEventListener(\"message\",d.wp.receiveEmbedMessage,!1),l.addEventListener(\"DOMContentLoaded\",function(){for(var e,t,s=l.querySelectorAll(\"iframe.wp-embedded-content\"),r=0;r<s.length;r++)(t=(e=s[r]).getAttribute(\"data-secret\"))||(t=Math.random().toString(36).substring(2,12),e.src+=\"#?secret=\"+t,e.setAttribute(\"data-secret\",t)),e.contentWindow.postMessage({message:\"ready\",secret:t},\"*\")},!1)))}(window,document);\n\/\/# sourceURL=https:\/\/mscvprojects.ri.cmu.edu\/2025fteam24\/wp-includes\/js\/wp-embed.min.js\n<\/script>\n","description":"Benchmark Non-Reactive AV Simulation NAVSIM simulates the ego vehicle\u2019s future motion using kinematic equations, without modeling reactions from surrounding agents. This makes the evaluation stable, deterministic, and efficient while still reflecting realistic vehicle dynamics. NuPlan-Based Data The scenarios in NAVSIM are constructed from the NuPlan real-world driving dataset, which provides rich information about surrounding traffic [&hellip;]","thumbnail_url":"https:\/\/i.imgur.com\/pC47tcS.png"}