{"id":66320,"date":"2026-01-26T16:33:00","date_gmt":"2026-01-26T08:33:00","guid":{"rendered":"https:\/\/www.wsisp.com\/helps\/66320.html"},"modified":"2026-01-26T16:33:00","modified_gmt":"2026-01-26T08:33:00","slug":"%e6%96%87%e7%8c%ae%e9%98%85%e8%af%bb%e7%af%8713%ef%bc%9a%e8%87%aa%e5%8a%a8%e9%a9%be%e9%a9%b6%e4%b8%ad%e7%9a%84%e5%9f%ba%e7%a1%80%e6%a8%a1%e5%9e%8b%ef%bc%9a%e5%9c%ba%e6%99%af%e7%94%9f%e6%88%90","status":"publish","type":"post","link":"https:\/\/www.wsisp.com\/helps\/66320.html","title":{"rendered":"\u6587\u732e\u9605\u8bfb\u7bc7#13\uff1a\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b\uff1a\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0\uff084\uff09"},"content":{"rendered":"

\u6587\u7ae0\u6807\u9898：Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis<\/h2>\n

（\u7ffb\u8bd1）\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b：\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0<\/p>\n

\u6587\u7ae0\u53d1\u8868\u4e8e\u9884\u5370\u672c：Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis<\/p>\n

\u7eed：\u6587\u732e\u9605\u8bfb\u7bc7#10：\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b：\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0（1）-CSDN\u535a\u5ba2\u00a0&\u00a0\u6587\u732e\u9605\u8bfb\u7bc7#11：\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b：\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0（2）-CSDN\u535a\u5ba2\u00a0&\u00a0\u6587\u732e\u9605\u8bfb\u7bc7#12：\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b：\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0（3）-CSDN\u535a\u5ba2<\/p>\n

\u4e94\u3001\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b (MLLMs)<\/h2>\n

\u672c\u8282\u4ece\u591a\u6a21\u6001\u5927\u6a21\u578b（MLLM）\u7684\u53d1\u5c55\u5f00\u59cb，\u91cd\u70b9\u4ecb\u7ecd\u5176\u67b6\u6784\u6f14\u53d8\u548c\u9002\u5e94\u6280\u672f，\u5982\u6a21\u6001\u6865\u63a5\u548c\u6307\u4ee4\u8c03\u4f18\u3002\u968f\u540e，\u8ba8\u8bba\u4e86\u4ece\u591a\u6a21\u6001\u8f93\u5165\u751f\u6210\u573a\u666f\u4ee5\u53ca\u573a\u666f\u5206\u6790\u4efb\u52a1，\u5305\u62ec\u89c6\u89c9\u95ee\u7b54（VQA）\u3001\u573a\u666f\u7406\u89e3\u548c\u81ea\u52a8\u9a7e\u9a76\u73af\u5883\u4e2d\u7684\u98ce\u9669\u8bc4\u4f30\u3002（\u8be5\u7ae0\u8282\u7684\u603b\u7ed3）<\/span><\/p>\n

A. \u591a\u6a21\u6001\u5927\u578b\u8bed\u8a00\u6a21\u578b\u7684\u53d1\u5c55<\/h3>\n

MLLMs \u901a\u8fc7\u5f15\u5165\u66f4\u591a\u7684\u611f\u77e5\u7f16\u7801\u5668\u6269\u5c55\u4e86\u9884\u8bad\u7ec3\u7684 LLMs，\u4f7f\u7cfb\u7edf\u80fd\u591f\u5904\u7406\u66f4\u4e30\u5bcc\u7684\u4f20\u611f\u5668\u8f93\u5165\u3002\u65e9\u671f\u6a21\u578b\u5982 BLIP-2 [113] \u548c Video-LLaMA [164]（\u5728\u9644\u5f55 A \u90e8\u5206\u8ba8\u8bba）\u4f7f\u7528\u51bb\u7ed3\u7684\u89c6\u89c9\u9aa8\u5e72\u7f51\u7edc，\u5e76\u901a\u8fc7\u8bf8\u5982 Q-Former \u7684\u9002\u914d\u5668\u8fde\u63a5\u5230 LLMs\u3002\u8fd1\u671f\u7684 MLLMs \u8f6c\u5411\u66f4\u7d27\u5bc6\u7684\u89c6\u89c9\u2013\u8bed\u8a00\u6574\u5408<\/span>，\u5c06 LLM \u4f5c\u4e3a\u6838\u5fc3\u63a8\u7406\u5f15\u64ce\u3002MiniGPT-4 [165] \u548c LLaVA [29] \u901a\u8fc7\u8f7b\u91cf\u6295\u5f71\u5668\u5c06\u89c6\u89c9\u7f16\u7801\u5668（\u5982 CLIP）\u5bf9\u9f50\u5230 LLaMA [99]，\u5e76\u5e94\u7528\u6307\u4ee4\u8c03\u4f18\u3002\u7136\u800c，\u5b83\u4eec\u4e3b\u8981\u5904\u7406\u81ea\u7136\u56fe\u50cf，\u4f8b\u5982\u5178\u578b\u7684\u6444\u5f71\u573a\u666f，\u5e76\u4e14\u7f3a\u4e4f\u5bf9\u4f20\u611f\u5668\u878d\u5408\u6216\u65f6\u7a7a\u63a8\u7406\u7684\u652f\u6301\u3002（\u662f\u4f55\u5f02\u4e8eVLM？？？）<\/span><\/p>\n

\u76f8\u6bd4\u4e4b\u4e0b，\u50cf GPT-4V [166] \u548c GPT-4o \u8fd9\u6837\u7684\u6a21\u578b\u96c6\u6210\u4e86\u4e13\u6709\u7684\u89c6\u89c9\u7f16\u7801\u5668，\u5e76\u5728\u56fe\u50cf-\u6587\u672c-\u97f3\u9891<\/span>\u6570\u636e\u4e0a\u8fdb\u884c\u8bad\u7ec3\u3002\u867d\u7136\u5b83\u4eec\u80fd\u591f\u5904\u7406\u56fe\u50cf\u548c\u89c6\u9891，\u4f46\u4ecd\u7136\u5728\u81ea\u7136\u56fe\u50cf\u8303\u5f0f\u4e0b\u5de5\u4f5c，\u672a\u63a5\u89e6\u5230\u8bf8\u5982 LiDAR \u4f20\u611f\u5668\u6570\u636e\u3001BEV \u5730\u56fe\u6216\u9a7e\u9a76\u65e5\u5fd7\u7b49\u7279\u5b9a\u9886\u57df\u7684\u8f93\u5165\u3002\u50cf Google Gemini [167] \u548c Qwen-VL [168] \u8fd9\u6837\u7684\u6a21\u578b\u901a\u8fc7\u66f4\u5f3a\u7684\u89c6\u89c9-\u8bed\u8a00\u6574\u5408\u6269\u5c55\u4e86\u591a\u6a21\u6001\u63a8\u7406\u80fd\u529b，\u652f\u6301\u5f00\u653e\u5f0f\u7684\u89c6\u9891\u548c\u56fe\u8868\u7406\u89e3\u3002\u867d\u7136\u8fd9\u4e9b\u6a21\u578b\u5728\u901a\u7528\u89c6\u89c9-\u8bed\u8a00\u4efb\u52a1\u4e2d\u8868\u73b0\u51fa\u8272，\u4f46\u5728\u81ea\u52a8\u9a7e\u9a76\u9886\u57df\u4ecd\u663e\u4e0d\u8db3，\u56e0\u4e3a\u81ea\u52a8\u9a7e\u9a76\u9700\u8981\u5bf9\u7ed3\u6784\u5316\u8f93\u5165（\u5982\u65f6\u95f4\u5bf9\u8c61\u8f68\u8ff9\u3001BEV \u5e03\u5c40\u548c\u8003\u8651\u4ea4\u4e92\u7684\u8fd0\u52a8\u6a21\u5f0f）\u8fdb\u884c\u63a8\u7406\u3002（\u6bd4VLM\u66f4\u8fdb\u4e86\u4e00\u6b65）<\/span><\/p>\n

\u4e3a\u4e86\u5e94\u5bf9\u81ea\u52a8\u9a7e\u9a76\u7684\u72ec\u7279\u9700\u6c42，\u6700\u8fd1\u7684\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLM）\u67b6\u6784\u5df2\u7ecf\u5f00\u59cb\u5f15\u5165\u7ed3\u6784\u5316\u7684\u3001\u7279\u5b9a\u9886\u57df\u7684\u6a21\u6001，\u5982\u591a\u89c6\u89d2\u89c6\u9891\u3001\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u548c\u4fef\u89c6\u56fe（BEV）\u5e03\u5c40\u3002\u8fd9\u4e9b\u65b0\u589e\u6a21\u6001\u4f7f\u6a21\u578b\u80fd\u591f\u8fdb\u884c\u7a7a\u95f4\u548c\u65f6\u95f4\u7684\u5b9a\u4f4d，\u4ece\u800c\u8ba9\u5927\u8bed\u8a00\u6a21\u578b\u80fd\u591f\u66f4\u6709\u6548\u5730\u63a8\u7406\u590d\u6742\u7684\u9a7e\u9a76\u573a\u666f\u548c\u591a\u667a\u80fd\u4f53\u52a8\u6001 [169]\u3002（\u6bd4\u524d\u9762\u53c8\u8fdb\u4e86\u4e00\u6b65）<\/span><\/p>\n

\u5728\u6784\u5efa\u4e8eVLM\u6280\u672f\u7684\u57fa\u7840\u4e0a，MLLMs\u88ab\u6539\u9020\u4ee5\u652f\u6301\u5bf9\u81ea\u52a8\u9a7e\u9a76\u81f3\u5173\u91cd\u8981\u7684\u66f4\u5e7f\u6cdb\u7684\u6a21\u6001，\u4f8b\u5982\u89c6\u9891\u3001LiDAR\u70b9\u4e91\u3001BEV\u5730\u56fe\u548c\u9ad8\u6e05（HD）\u8bed\u4e49\u7279\u5f81\u3002\u5982\u56fe6\u6240\u793a，\u8fd9\u4e9b\u7cfb\u7edf\u901a\u5e38\u7531\u4e13\u95e8\u7684\u6a21\u6001\u7f16\u7801\u5668（\u5982BEVFormer [170]\u3001CLIP-ViT [171]\u3001VoxelNet [172]）\u3001\u7528\u4e8e\u5bf9\u9f50\u591a\u6a21\u6001\u7279\u5f81\u7684\u6295\u5f71\u6a21\u5757（\u5982MLPs\u3001Q-Former\u3001\u4ea4\u53c9\u6ce8\u610f\u529b）\u4ee5\u53ca\u9488\u5bf9\u4efb\u52a1\u7684\u8bad\u7ec3\u7b56\u7565\u7ec4\u6210\u3002MLLMs\u901a\u5e38\u4f1a\u4fdd\u6301\u611f\u77e5\u548c\u8bed\u8a00\u9aa8\u5e72\u7f51\u7edc\u51bb\u7ed3，\u9002\u914d\u4e3b\u8981\u96c6\u4e2d\u5728\u8f7b\u91cf\u7ea7\u6865\u63a5\u548c\u4e0b\u6e38\u9a7e\u9a76\u76f8\u5173\u4efb\u52a1\u7684\u6307\u4ee4\u5fae\u8c03\u3002\u4e3b\u8981\u7684\u9002\u914d\u7b56\u7565\u5c06\u5728\u4e0b\u6587\u8ba8\u8bba\u3002（\u63d0\u51fa\u4e86\u6a21\u6001\u7f16\u7801\u5668\u7684\u91cd\u8981\u6027）<\/span><\/p>\n

\"\"<\/p>\n

\u56fe6. \u81ea\u52a8\u9a7e\u9a76\u4e2d\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLMs）\u9002\u914d\u6280\u672f\u6982\u89c8\u3002\u7f16\u7801\u5668\u4ece\u7279\u5b9a\u6a21\u6001\u7684\u8f93\u5165\u4e2d\u63d0\u53d6\u7279\u5f81\u3002\u6295\u5f71\u5668\u662f\u53ef\u8bad\u7ec3\u6a21\u5757，\u5c06\u7279\u5f81\u6620\u5c04\u5230\u5927\u8bed\u8a00\u6a21\u578b\u7684\u5d4c\u5165\u7a7a\u95f4，\u4ee5\u5b9e\u73b0\u8de8\u6a21\u6001\u5bf9\u9f50\u3002\u5927\u8bed\u8a00\u6a21\u578b\u4f5c\u4e3a\u63a8\u7406\u6838\u5fc3，\u53ef\u4ee5\u6839\u636e\u53ef\u7528\u8d44\u6e90\u548c\u4efb\u52a1\u9700\u6c42\u9009\u62e9\u51bb\u7ed3\u6216\u53ef\u8bad\u7ec3，\u4f7f\u7528\u5fae\u8c03\u6280\u672f\u8fdb\u884c\u4f18\u5316\u3002（\u56fe\u6ce8）<\/span><\/p>\n

\u6a21\u6001\u5bf9\u9f50\u6a21\u5757：<\/h4>\n

\u8fd9\u4e9b\u6a21\u5757\u4f5c\u4e3a\u975e\u6587\u672c\u6a21\u6001\u4e0e\u5927\u578b\u8bed\u8a00\u6a21\u578b（LLM）\u6807\u8bb0\u7a7a\u95f4\u4e4b\u95f4\u7684\u6865\u6881\u3002\u4e3b\u8981\u7684\u6a21\u6001\u5bf9\u9f50\u6a21\u5757\u5305\u62ec：<\/p>\n

（1） \u7ebf\u6027\u6295\u5f71\u5668：\u4e00\u4e2a\u5355\u4e00\u7ebf\u6027（\u5373\u5b8c\u5168\u8fde\u63a5）\u7684\u795e\u7ecf\u5c42，\u7528\u4e8e\u5c06\u7279\u5b9a\u6a21\u6001\u7279\u5f81\u6295\u5c04\u5230LLM\u7684\u5d4c\u5165\u7a7a\u95f4\u3002\u5b83\u63d0\u4f9b\u4e86\u8f7b\u91cf\u7ea7\u6620\u5c04\u7b56\u7565，\u5e38\u7528\u4e8e\u65e9\u671fVLM\u6216\u4e0e\u9884\u8bad\u7ec3\u7f16\u7801\u5668\u7ed3\u5408\u4f7f\u7528[173]，[174]\u3002（2） MLP \u6295\u5f71：\u5c06\u89c6\u89c9\u6216\u7a7a\u95f4\u7f16\u7801\u5668（\u5982 ViT\u3001BEVFormer）\u7684\u9ad8\u7ef4\u7279\u5f81\u6295\u5c04\u5230 VOLUME\u3001OJ Logo LLM \u7684\u4ee4\u724c\u7a7a\u95f4\u3002\u7528\u4e8eBLIP-2 [113]\u7b49\u6a21\u578b\u548c\u4ee5\u9a7e\u9a76\u4e3a\u4e2d\u5fc3\u7684\u9002\u914d\u5668\u5982P-Adapter [175]，\u8fd9\u4e9b\u9002\u914d\u5668\u5c06BEV\u6216LiDAR\u529f\u80fd\u5bf9\u9f50\u4ee5\u5b9e\u73b0\u57fa\u4e8e\u8bed\u8a00\u7684\u63a8\u7406\u3002（3）\u65f6\u7a7a（ST）\u9002\u914d\u5668：\u8f7b\u91cf\u7ea7\u65f6\u95f4\u9002\u914d\u5668\u6a21\u5757\u7528\u4e8e\u6269\u5c55\u57fa\u4e8e\u56fe\u50cf\u7684\u591a\u5c42\u6b21\u591a\u5c42\u8bed\u8a00\u6a21\u578b（MLLM）\u4ee5\u5904\u7406\u987a\u5e8f\u89c6\u9891\u8f93\u5165 [170]， [175]\u3002\u5b83\u5b9e\u73b0\u4e86\u65f6\u7a7a\u5efa\u6a21，\u800c\u65e0\u9700\u4fee\u6539\u6838\u5fc3\u7684LLM\u6743\u91cd\u3002（4） \u4ea4\u53c9\u6ce8\u610f\u529b：\u5229\u7528\u53ef\u5b66\u4e60\u7684\u67e5\u8be2\u901a\u8fc7\u56fe\u50cf\u6216\u70b9\u4e91\u6807\u8bb0\u8fdb\u884c\u5173\u6ce8，\u5b9e\u73b0\u591a\u6a21\u6001\u878d\u5408，\u9002\u7528\u4e8e\u7a7a\u95f4\/\u65f6\u95f4\u57fa\u7840\u5316\u3001\u8bed\u4e49\u5bf9\u9f50\u548c\u6307\u4ee4\u8ddf\u8e2a\u7b49\u4efb\u52a1 [176]， [177]\u3002（5） Q-Former：\u57fa\u4e8e\u53d8\u6362\u5668\u7684\u67e5\u8be2\u6a21\u5757，\u5229\u7528\u4ea4\u53c9\u6ce8\u610f\u529b\u4ece\u591a\u6a21\u6001\u8f93\u5165\u4e2d\u63d0\u70bc\u51fa\u4efb\u52a1\u76f8\u5173\u7684\u5d4c\u5165\u3002\u8fd9\u4e9b\u6a21\u5757\u5e94\u7528\u4e8eBLIP-2 [113]\u3001InternDrive [178]\u548cNuInstruct [170]，\u7528\u4e8e\u8de8\u89c6\u9891\u3001\u6fc0\u5149\u96f7\u8fbe\u548cBEV\u8f93\u5165\u7684\u7ed3\u6784\u5316\u805a\u53d8\u3002（6） \u805a\u53d8\u53d8\u538b\u5668：\u4e13\u95e8\u8bbe\u8ba1\u7528\u4e8e\u6574\u5408\u591a\u6d41\u7279\u6027\u7684\u6ce8\u610f\u529b\u5757，\u5982BEV\u5730\u56fe\u3001\u591a\u89c6\u56fe\u89c6\u9891\u6216\u6fc0\u5149\u96f7\u8fbe\u70b9\u4e91\u3002\u50cfBEV-Injection [170]\u8fd9\u6837\u7684\u6a21\u5757\u901a\u8fc7\u5bf9\u9f50\u548c\u6ce8\u5165\u591a\u6a21\u6001\u7279\u5f81（\u4f8b\u5982\u56fe\u50cf\u6216\u6fc0\u5149\u96f7\u8fbe）\u5230\u7edf\u4e00\u7684BEV\u8868\u793a\u4e2d，\u4f5c\u4e3a\u878d\u5408\u53d8\u6362\u5668\u3002\u8fd9\u4e9b\u901a\u5e38\u7528\u4e8e\u4ee5\u9a7e\u9a76\u4e3a\u4e2d\u5fc3\u7684MLLMs\u3002（7） \u7ed3\u6784\u611f\u77e5\u7f16\u7801\u5668：\u4e00\u4e2a\u6a21\u5757，\u5c06\u7ed3\u6784\u5316\u611f\u77e5\u8f93\u5165（\u5982\u4e09\u7ef4\u8fb9\u754c\u6846[172]）\u3001\u573a\u666f\u56fe\u6216\u8fd0\u52a8\u8f68\u8ff9\u8f6c\u6362\u4e3a\u9002\u5408\u57fa\u4e8e\u8bed\u8a00\u63a8\u7406\u7684\u4ee4\u724c\u5d4c\u5165\u3002<\/p>\n

（\u6587\u7ae0\u603b\u7ed3\u4e86\u4e03\u79cd\u591a\u6a21\u6001\u5bf9\u9f50\u7684\u6a21\u5757\u548c\u65b9\u6cd5）<\/span><\/p>\n

\u591a\u6a21\u6001\u5fae\u8c03：（\u548cVLM\u90e8\u5206\u7684\u4e00\u6837）<\/span><\/h4>\n

\u4e00\u65e6\u5b9e\u73b0\u4e86\u6a21\u6001\u5bf9\u9f50，\u5c31\u53ef\u4ee5\u4f7f\u7528\u6210\u5bf9\u7684\u6307\u4ee4\u6570\u636e（\u5982 VQA）\u8bad\u7ec3\u591a\u6a21\u6001\u5927\u6a21\u578b（MLLM）\u4ee5\u9075\u5faa\u7279\u5b9a\u4efb\u52a1\u7684\u63d0\u793a\u3002\u8fd9\u4e2a\u9636\u6bb5\u6559\u4f1a\u6a21\u578b\u5728\u591a\u6a21\u6001\u73af\u5883\u4e2d\u8fdb\u884c\u63a8\u7406\u5e76\u751f\u6210\u6709\u4f9d\u636e\u7684\u8f93\u51fa\u3002\u4e0e\u89c6\u89c9\u8bed\u8a00\u6a21\u578b（VLM）\u7c7b\u4f3c，\u901a\u5e38\u91c7\u7528\u4e24\u79cd\u4e3b\u8981\u7b56\u7565\u6765\u5b9e\u73b0\u8fd9\u79cd\u9002\u5e94：<\/p>\n

(1) PEFT：PEFT \u7b56\u7565\u901a\u8fc7\u53ea\u66f4\u65b0\u6a21\u578b\u7684\u4e00\u5c0f\u90e8\u5206\u53c2\u6570\u6765\u9002\u5e94\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLM），\u901a\u5e38\u4fdd\u6301 LLM \u51bb\u7ed3\u3002\u867d\u7136\u7ecf\u5178\u7684 PEFT \u65b9\u6cd5\u5982\u9002\u914d\u5668\u5c42\u3001LoRA \u548c\u63d0\u793a\u8c03\u4f18（\u5982\u4e0b\u6240\u8ff0）\u5728 LLM \u5185\u90e8\u64cd\u4f5c，\u4f46\u6700\u8fd1\u5728\u81ea\u52a8\u9a7e\u9a76\u9886\u57df\u7684\u7814\u7a76\u5f80\u5f80\u5c06 PEFT \u5e94\u7528\u4e8e\u6a21\u6001\u5bf9\u9f50\u6a21\u5757 [170]\u3002\u4f8b\u5982，\u50cf ST-Adapters \u548c Q-Formers \u8fd9\u6837\u7684\u7ec4\u4ef6\u88ab\u8bad\u7ec3\u7528\u4e8e\u5c06\u89c6\u89c9\u6216\u7a7a\u95f4\u8f93\u5165\u6865\u63a5\u5230 LLM，\u4ece\u800c\u5728\u4e0d\u4fee\u6539\u6838\u5fc3\u8bed\u8a00\u6a21\u578b\u7684\u60c5\u51b5\u4e0b\u5b9e\u73b0\u4efb\u52a1\u9002\u5e94\u3002<\/p>\n

Adapter layers：\u8f7b\u91cf\u7ea7\u53ef\u8bad\u7ec3\u6a21\u5757，\u63d2\u5165\u5728\u5927\u578b\u8bed\u8a00\u6a21\u578b（LLM）\u7684\u5404\u5c42\u4e4b\u95f4，\u901a\u5e38\u4f7f\u7528\u4e0b\u6295\u5f71\u548c\u4e0a\u6295\u5f71\u7ed3\u6784\u3002\u5b83\u4eec\u7528\u4e8e LLaMA Adapter V2 [179] \u548c InternDrive [178]\u3002<\/p>\n

LoRA：\u5bf9\u6ce8\u610f\u529b\u548c\u524d\u9988\u6a21\u5757\u5e94\u7528\u4f4e\u79e9\u66f4\u65b0\u3002\u5e38\u7528\u4e8e\u9a71\u52a8\u6a21\u578b，\u5982 DriveGPT4 [173]\u3002<\/p>\n

PEFT-\u6a21\u6001\u5bf9\u9f50 (MA)：\u4ec5\u5fae\u8c03 MA \u6a21\u5757（\u4f8b\u5982 Q-Former\u3001ST-Adapter），\u540c\u65f6\u4fdd\u6301\u5927\u8bed\u8a00\u6a21\u578b（LLM）\u7684\u6743\u91cd\u51bb\u7ed3\u3002<\/p>\n

(2) FFT：\u5168\u91cf\u5fae\u8c03\u4f1a\u66f4\u65b0\u6240\u6709\u6a21\u578b\u53c2\u6570，\u5305\u62ec\u89c6\u89c9\u7f16\u7801\u5668\u3001\u7a7a\u95f4\u7f16\u7801\u5668\u548c\u5927\u8bed\u8a00\u6a21\u578b（LLM）\u3002\u867d\u7136\u8fd9\u79cd\u65b9\u6cd5\u901a\u5e38\u80fd\u591f\u5b9e\u73b0\u6700\u9ad8\u7684\u7279\u5b9a\u4efb\u52a1\u6027\u80fd，\u4f46\u8ba1\u7b97\u6210\u672c\u5f88\u9ad8\u3002\u4e3a\u4e86\u964d\u4f4e\u8ba1\u7b97\u6210\u672c，\u4e00\u4e9b\u7814\u7a76\u5c06\u5168\u91cf\u5fae\u8c03\u5e94\u7528\u4e8e\u8f83\u5c0f\u7684\u6a21\u578b，\u4f8b\u5982\u4f7f\u7528 Qwen2-0.5B [180]\u3002<\/p>\n

B. \u57fa\u4e8e MLLM \u7684\u573a\u666f\u751f\u6210<\/h3>\n

\u591a\u6a21\u6001\u5927\u578b\u8bed\u8a00\u6a21\u578b（MLLMs）\u53ef\u4ee5\u8054\u5408\u5904\u7406\u6765\u81ea\u8f66\u8f86\u4f20\u611f\u5668\u6216\u4eba\u7c7b\u6765\u6e90\u7684\u591a\u6837\u5316\u89c6\u89c9\u8f93\u5165，\u4ece\u800c\u5b9e\u73b0\u5bf9\u590d\u6742\u9a7e\u9a76\u73af\u5883\u7684\u5168\u9762\u7406\u89e3\u3002\u5b83\u4eec\u6574\u5408\u591a\u79cd\u6a21\u6001\u7684\u80fd\u529b\u4e5f\u6709\u52a9\u4e8e\u751f\u6210\u66f4\u771f\u5b9e\u3001\u5177\u6709\u60c5\u5883\u611f\u77e5\u7684\u573a\u666f\u3002\u4ee5\u4e0b，\u6211\u4eec\u5c06 MLLMs \u7684\u4f7f\u7528\u5206\u4e3a\u4e24\u7c7b，\u603b\u7ed3\u5982\u8868 6 \u6240\u793a\u3002（\u4e0d\u591a）<\/span><\/p>\n

\"\"<\/p>\n

\u5b89\u5168\u5173\u952e\u60c5\u666f\u751f\u6210：<\/h4>\n

\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLMs）\u901a\u8fc7\u5229\u7528\u89c6\u9891\u3001GPS\u3001\u4e8b\u6545\u62a5\u544a\u4ee5\u53ca\u6f5c\u5728\u7684LiDAR\u70b9\u4e91\u7b49\u591a\u6837\u5316\u6a21\u6001，\u5b9e\u73b0\u66f4\u4e30\u5bcc\u7684\u573a\u666f\u751f\u6210，\u4ece\u800c\u80fd\u591f\u8fdb\u884c\u8d85\u8d8a\u57fa\u4e8e\u56fe\u50cf\u7684\u5927\u8bed\u8a00\u89c6\u89c9\u6a21\u578b（VLMs）\u9650\u5236\u7684\u98ce\u9669\u611f\u77e5\u5408\u6210\u3002（\u4ecb\u7ecd）<\/span><\/p>\n

AutoScenario [181] \u63d0\u51fa\u4e86\u4e00\u79cd\u751f\u6210\u771f\u5b9e\u89d2\u843d\u6848\u4f8b\u7684\u6d41\u7a0b，\u4f7f\u7528\u6765\u81ea NHTSA \u7684\u591a\u6a21\u6001\u4e8b\u6545\u6570\u636e，\u5305\u62ec\u6587\u672c\u3001\u56fe\u50cf\u3001\u89c6\u9891\u548c\u534a\u7ed3\u6784\u5316\u62a5\u544a\u3002\u4ed6\u4eec\u4f7f\u7528\u5e26\u6709 CoT \u7684 GPT-4o \u751f\u6210\u7ed3\u6784\u5316\u573a\u666f\u63cf\u8ff0，\u7136\u540e\u7528\u4e8e\u5728 SUMO \u4e2d\u751f\u6210\u9053\u8def\u7f51\u7edc\u548c\u5728 CARLA \u4e2d\u751f\u6210\u4ee3\u7406\u884c\u4e3a\u3002\u4ed6\u4eec\u7684\u573a\u666f\u4f18\u5316\u901a\u8fc7 GPS \u8f68\u8ff9\u548c\u6a21\u62df\u573a\u666f\u4e0e\u771f\u5b9e\u573a\u666f\u7684\u9010\u5e27\u76f8\u4f3c\u6027\u8fdb\u884c\u6307\u5bfc，\u4ee5\u786e\u4fdd\u4e0e\u539f\u59cb\u4e8b\u6545\u4e8b\u4ef6\u7684\u826f\u597d\u5339\u914d\u3002\u4e00\u4e2a\u6709\u524d\u666f\u7684\u672a\u6765\u65b9\u5411\u662f\u5f15\u5165\u7a7a\u95f4\u6a21\u6001，\u4f8b\u5982 LiDAR \u70b9\u4e91\u6216 BEV \u5730\u56fe，\u4ee5\u5b9e\u73b0\u66f4\u7cbe\u786e\u7684\u573a\u666f\u51e0\u4f55\u548c\u4ee3\u7406\u5b9a\u4f4d，\u4ece\u800c\u589e\u5f3a\u73b0\u5b9e\u611f，\u8d85\u8d8a\u4ec5\u51ed\u4e8c\u7ef4\u89c6\u9891\u548c\u6df1\u5ea6\u611f\u6d4b\u6240\u80fd\u63d0\u4f9b\u7684\u6548\u679c\u3002（\u51e0\u4e2a\u4f8b\u5b50）<\/span><\/p>\n

ADAS \u6d4b\u8bd5\u573a\u666f\u751f\u6210：<\/h4>\n

\u4e3a\u9ad8\u7ea7\u9a7e\u9a76\u8f85\u52a9\u7cfb\u7edf（ADAS）\u751f\u6210\u6d4b\u8bd5\u573a\u666f\u7684\u76ee\u7684\u662f\u5728\u5178\u578b\u4f46\u591a\u6837\u7684\u6761\u4ef6\u4e0b\u9a8c\u8bc1\u81ea\u52a8\u9a7e\u9a76\u529f\u80fd\u3002<\/p>\n

LEADE [183] \u4ece HDD \u6570\u636e\u96c6 [182] \u7684\u771f\u5b9e\u4ea4\u901a\u89c6\u9891\u4e2d\u751f\u6210 ADAS \u6d4b\u8bd5\u573a\u666f\u3002\u5173\u952e\u5e27\u5728\u591a\u6a21\u6001 ICL \u548c GPT-4V \u7684 CoT \u63d0\u793a\u4e2d\u88ab\u4f7f\u7528，\u4ee5\u521b\u5efa\u62bd\u8c61\u573a\u666f，\u7136\u540e\u5c06\u5176\u8f6c\u6362\u4e3a\u53ef\u5728 LGSVL \u4eff\u771f\u5668 [93] \u4e2d\u6267\u884c\u7684\u7a0b\u5e8f\u3002Apollo ADAS \u5806\u6808 [184] \u8fd0\u884c\u81ea\u8f66，\u901a\u8fc7\u53cc\u5c42\u641c\u7d22\u8bc6\u522b\u8bed\u4e49\u7b49\u4ef7\u7684\u573a\u666f，\u4ece\u800c\u63ed\u793a Apollo \u4e0e\u4eba\u7c7b\u9a7e\u9a76\u5458\u7684\u884c\u4e3a\u5dee\u5f02\u3002\u672a\u6765\u7684\u5de5\u4f5c\u53ef\u4ee5\u4f7f\u573a\u666f\u751f\u6210\u4e0e ADAS \u6d4b\u8bd5\u6807\u51c6\u4fdd\u6301\u4e00\u81f4，\u4ece\u800c\u5b9e\u73b0\u7b26\u5408\u89c4\u8303\u7684\u573a\u666f\u5408\u6210\u3002\u5f15\u5165\u4ea4\u901a\u89c4\u5219\u548c\u7ed3\u6784\u5316\u5148\u9a8c\u4e5f\u5c06\u6539\u5584\u53ef\u63a7\u6027\u548c\u6d4b\u8bd5\u8986\u76d6\u8303\u56f4\u3002（\u51e0\u4e2a\u4f8b\u5b50）<\/span><\/p>\n

C. \u57fa\u4e8e MLLM \u7684\u60c5\u666f\u5206\u6790<\/h3>\n

\u672c\u8282\u8ba8\u8bba\u4e86\u4f7f\u7528\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLMs）\u8fdb\u884c\u81ea\u52a8\u9a7e\u9a76（AD）\u573a\u666f\u5206\u6790\u7684\u8bba\u6587\u3002\u6211\u4eec\u5c06\u73b0\u6709\u5de5\u4f5c\u5f52\u7c7b\u4e3a\u4e09\u4e2a\u4e3b\u8981\u4efb\u52a1，\u5982\u88687\u6240\u793a\u3002<\/p>\n

\"\"<\/p>\n

1 \u89c6\u9891：FPV=\u7b2c\u4e00\u4eba\u79f0\u89c6\u89d2；BEV=\u9e1f\u77b0\u89c6\u89d2； 2 \u89d2\u8272：Exec.=\u6267\u884c；Aug.=\u589e\u5f3a；Gen.=\u751f\u6210；Under.=\u7406\u89e3；Capt.=\u5b57\u5e55\u751f\u6210；Eval.=\u8bc4\u4f30；Extract.=\u63d0\u53d6； 3 \u6280\u672f：\u53ea\u5173\u6ce8\u7528\u4e8e\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLMs）\u7684\u6280\u672f\u3002Projector=\u7ebf\u6027\u6295\u5f71\u5668；MLP=\u591a\u5c42\u611f\u77e5\u673a\u6295\u5f71；QueryTrans=\u67e5\u8be2\u53d8\u6362\u5668；FusionTrans=\u878d\u5408\u53d8\u6362\u5668；PEFT-Adapter=\u9002\u914d\u5668\u5c42；Fft=\u5168\u91cf\u5fae\u8c03；PEFT-MA=\u53ea\u8bad\u7ec3\u6a21\u6001\u5bf9\u9f50\u6a21\u5757\u4e14\u5927\u8bed\u8a00\u6a21\u578b\u51bb\u7ed3；Encoder=\u7ed3\u6784\u611f\u77e5\u7f16\u7801\u5668；CP=\u4e0a\u4e0b\u6587\u63d0\u793a；ICL=\u4e0a\u4e0b\u6587\u5b66\u4e60；CoT=\u94fe\u5f0f\u601d\u7ef4\u63d0\u793a； 4 \u5173\u6ce8：STReasoning=\u65f6\u7a7a\u63a8\u7406\u3002<\/p>\n

\u89c6\u89c9\u95ee\u7b54（VQA）：<\/h4>\n

\u4e0e\u57fa\u4e8e VQA \u7684 VLM \u60c5\u666f\u5206\u6790\u76f8\u6bd4，MLLM \u5177\u5907\u5904\u7406\u591a\u6a21\u6001\u4f20\u611f\u5668\u6570\u636e\u7684\u6269\u5c55\u80fd\u529b，\u5982\u89c6\u9891\u3001LiDAR \u70b9\u4e91\u548c\u9ad8\u6e05\u5730\u56fe[197]，\u9664\u4e86\u56fe\u50cf\u548c\u6587\u672c\u3002\u6839\u636e\u4efb\u52a1\u548c\u6570\u636e\u6a21\u6001，\u73b0\u6709\u7684 VQA \u6570\u636e\u96c6\u53ef\u5206\u4e3a\u56db\u7c7b：（\u600e\u4e48\u83ab\u540d\u5176\u5999\u5f00\u59cb\u8bb2\u6570\u636e\u96c6\u4e86？？？\u96be\u9053\u8fd9\u662f\u552f\u4e00\u533a\u522bVLM\u7684\u5730\u65b9\u4e86\u5417？？）<\/span><\/p>\n

(I) \u901a\u7528\u81ea\u52a8\u9a7e\u9a76\u4efb\u52a1\u2014\u2014\u611f\u77e5\u3001\u63a8\u7406\u4e0e\u63a7\u5236：\u591a\u4e2a\u6570\u636e\u96c6\u9488\u5bf9\u6838\u5fc3\u81ea\u52a8\u9a7e\u9a76\u4efb\u52a1，\u5305\u62ec\u89c6\u89c9\u611f\u77e5\u3001\u63a8\u7406\u548c\u51b3\u7b56\u3002DriveGPT4 [173] \u63a8\u51fa\u4e86\u9996\u4e2a\u9488\u5bf9\u9a7e\u9a76\u7684\u89c6\u9891\u8d28\u91cf\u4fdd\u8bc1\u98ce\u683c\u6307\u4ee4\u8ddf\u968f\u6570\u636e\u96c6，\u4f7f\u7528 GPT-4 \u751f\u6210，\u8f93\u5165\u7ed3\u6784\u5316，\u5305\u62ec\u7269\u4f53\u68c0\u6d4b\u8fb9\u754c\u6846\u3001\u8bf4\u660e\u6587\u5b57\u548c\u63a7\u5236\u4fe1\u53f7\u3002\u5b83\u901a\u8fc7\u5fae\u8c03\u7ed3\u5408 CLIP \u548c LLaMA2 \u7684 MLLM，\u5e76\u642d\u914d LoRA \u9002\u914d\u5668，\u751f\u6210\u6587\u672c\u89e3\u91ca\u548c\u63a7\u5236\u8f93\u51fa\u3002\u540c\u65f6，\u6df7\u5408\u5fae\u8c03\u7b56\u7565\u5c06\u901a\u7528\u89c6\u89c9\u6307\u4ee4\u6570\u636e\u4e0e\u9a7e\u9a76\u7279\u5b9a\u6837\u672c\u5408\u5e76，\u4ee5\u63d0\u5347\u63a8\u7406\u548c\u6027\u80fd\u3002VLAAD [174] \u5f15\u5165\u4e86\u4e00\u6b3e\u591a\u6a21\u6001\u81ea\u52a8\u9a7e\u9a76\u52a9\u624b，\u57fa\u4e8e\u57fa\u4e8e BDD-X \u548c HDD \u89c6\u9891\u7684\u6307\u4ee4\u8ddf\u8e2a\u6570\u636e\u96c6\u8bad\u7ec3，QA \u5bf9\u901a\u8fc7 GPT-4 \u589e\u5f3a\u3002\u8be5\u6a21\u578b\u57fa\u4e8e Video-LLaMA \u6784\u5efa，\u7ed3\u5408\u4e86\u57fa\u4e8e BLIP-2 \u7684\u89c6\u89c9\u7f16\u7801\u5668\u3001\u7528\u4e8e\u65f6\u95f4\u5efa\u6a21\u7684 Video Q-Former \u4ee5\u53ca\u51bb\u7ed3\u7684 LLaMA-2-7B \u8bed\u8a00\u6a21\u578b\u3002PEFT-MA\u4ec5\u5e94\u7528\u4e8eQ-Forform\u548c\u6295\u5f71\u5c42，\u4f7f\u6a21\u578b\u80fd\u591f\u9ad8\u6548\u6267\u884c\u8bf8\u5982VQA\u3001\u81ea\u7531\u5f62\u5f0fQA\u3001\u81ea\u6211-\u610f\u56fe\u9884\u6d4b\u548c\u573a\u666f\u5c42\u63a8\u7406\u7b49\u4efb\u52a1\u3002LingoQA [129] \u63d0\u4f9b\u4e86\u4e00\u4e2a\u6db5\u76d6\u611f\u77e5\u3001\u63a8\u7406\u548c\u884c\u52a8\u7684\u81ea\u52a8\u9a7e\u9a76 VQA \u6570\u636e\u96c6\u3002\u5b83\u5305\u542b\u4e00\u4e2a\u7528 GPT-3.5 \u6ce8\u91ca\u7684\u52a8\u4f5c\u96c6\u548c\u4e00\u4e2a\u7531 GPT-4 \u4f7f\u7528 CoT \u751f\u6210\u7684\u573a\u666f\u96c6\u3002\u57fa\u7ebf\u6a21\u578b\u4f7f\u7528CLIP\u548cQ-Former\u5904\u7406\u89c6\u9891\u5e27，\u5e76\u914d\u5907\u7ebf\u6027\u6295\u5f71\u4eea\u5c06\u7279\u5f81\u4e0eVicuna-1.5-7B\u7684\u4ee4\u724c\u7a7a\u95f4\u5bf9\u9f50\u3002\u5728\u5fae\u8c03\u8fc7\u7a0b\u4e2d，PEFT-MA\u5e94\u7528\u5230Q-Former\u548c\u6295\u5f71\u4eea\u4e0a，LLM\u4fdd\u6301\u51bb\u7ed3\u72b6\u6001\u3002\u8bc4\u4f30\u4f7f\u7528\u65b0\u9896\u7684Lingo-Judge\u5206\u7c7b\u5668\u8fdb\u884c，\u8be5\u5206\u7c7b\u5668\u901a\u8fc7LoRA\u8bad\u7ec3\u3002（\u5305\u62ec\u89c6\u89c9\u611f\u77e5\u3001\u63a8\u7406\u548c\u51b3\u7b56\u7684VQA\u6570\u636e\u96c6）<\/span><\/p>\n

(II) \u65f6\u7a7a\u63a8\u7406：\u8fd9\u4e00\u7c7b\u7684\u6570\u636e\u96c6\u4fa7\u91cd\u4e8e\u5bf9\u9a7e\u9a76\u573a\u666f\u4e2d\u7684\u667a\u80fd\u4f53\u8fd0\u52a8\u3001\u65f6\u95f4\u4f9d\u8d56\u6027\u548c\u4e8b\u4ef6\u8bed\u4e49\u8fdb\u884c\u63a8\u7406\u3002TUMTraffic-VideoQA [180] \u63d0\u51fa\u4e86\u4e00\u4e2a\u591a\u9879\u9009\u62e9\u7684\u89c6\u9891\u95ee\u7b54\u6570\u636e\u96c6，\u9488\u5bf9\u8def\u8fb9\u4ea4\u901a\u573a\u666f\u4e2d\u7684\u65f6\u7a7a\u63a8\u7406，\u91cd\u70b9\u5173\u6ce8\u8fd0\u52a8\u3001\u5bf9\u8c61\u4ea4\u4e92\u548c\u4e8b\u4ef6\u8bed\u4e49\u3002\u89c6\u89c9\u5143\u6570\u636e\u4f7f\u7528\u6807\u51c6\u68c0\u6d4b\u5668\u8fdb\u884c\u63d0\u53d6，\u5e76\u7531\u73b0\u6210\u7684\u89c6\u89c9\u8bed\u8a00\u6a21\u578b（VLMs）\u751f\u6210\u63cf\u8ff0，\u540c\u65f6 GPT-4o-mini \u901a\u8fc7\u6a21\u677f\u589e\u5f3a\u63d0\u793a\u751f\u6210\u95ee\u7b54\u5bf9\u3002\u57fa\u7ebf\u6a21\u578b（TUMTraffic-Qwen）\u4f7f\u7528 SigLIP \u8fdb\u884c\u89c6\u89c9\u7f16\u7801，\u901a\u8fc7 MLP \u6295\u5f71\u5668\u5b9e\u73b0\u6a21\u6001\u5bf9\u9f50，\u5e76\u4f7f\u7528 Qwen2（0.5B\/7B）\u4f5c\u4e3a\u5927\u8bed\u8a00\u6a21\u578b（LLM），\u8be5\u6a21\u578b\u7ecf\u8fc7\u5b8c\u5168\u5fae\u8c03\u4ee5\u8fdb\u884c\u6307\u4ee4\u5f0f\u95ee\u7b54\u3002NuPlanQA [169] \u63d0\u51fa\u4e86\u4e00\u4e2a\u57fa\u4e8e nuPlan \u7684\u89c6\u9891\u95ee\u7b54\u6570\u636e\u96c6，\u4f7f\u7528 GPT-4o \u751f\u6210\u81ea\u7531\u5f62\u5f0f\u7684\u95ee\u7b54\u5bf9\u7528\u4e8e\u8bad\u7ec3，\u5e76\u751f\u6210\u591a\u9879\u9009\u62e9\u95ee\u7b54\u7528\u4e8e\u8bc4\u4f30\u3002\u4e3a\u4e86\u5229\u7528\u8fd9\u4e9b\u6570\u636e，\u4f5c\u8005\u63d0\u51fa\u4e86 BEV-LLM，\u4e00\u79cd\u591a\u6a21\u6001\u5927\u6a21\u578b（MLLM），\u901a\u8fc7 BEV \u7f16\u7801\u5668\u3001BEV \u878d\u5408\u6a21\u5757\u548c MLP \u6295\u5f71\u5668\u6574\u5408\u591a\u89c6\u89d2\u56fe\u50cf\u548c BEV \u7279\u5f81\u3002\u8be5\u6a21\u578b\u4f7f\u7528 LLaMA-3.2-Vision \u4f5c\u4e3a\u51bb\u7ed3\u9aa8\u5e72，\u4ec5\u5bf9 BEV \u878d\u5408\u6a21\u5757\u548c\u6295\u5f71\u5c42\u8fdb\u884c\u8bad\u7ec3，\u9075\u5faa PEFT-MA \u7b56\u7565\u3002（\u5173\u6ce8\u667a\u80fd\u4f53\u8fd0\u52a8\u3001\u65f6\u95f4\u4f9d\u8d56\u6027）<\/span><\/p>\n

(III) \u98ce\u9669\u611f\u77e5\u63a8\u7406：\u4e3a\u4e86\u89e3\u51b3\u5b89\u5168\u5173\u952e\u7684\u7406\u89e3\u95ee\u9898，\u4e00\u4e9b\u6570\u636e\u96c6\u4e13\u6ce8\u4e8e\u98ce\u9669\u8bc6\u522b\u3001\u610f\u56fe\u4f30\u8ba1\u548c\u4e0e\u89c4\u5212\u76f8\u5173\u7684\u67e5\u8be2\u3002NuInstruct [170] \u5f15\u5165\u4e86\u591a\u89c6\u89d2\u89c6\u9891\u95ee\u7b54\u6570\u636e\u96c6，\u6db5\u76d6\u611f\u77e5\u3001\u9884\u6d4b\u3001\u98ce\u9669\u548c\u89c4\u5212\u4efb\u52a1\u3002\u95ee\u7b54\u901a\u8fc7\u7ed3\u6784\u5316\u7684 SQL \u6d41\u6c34\u7ebf\u751f\u6210\u3002\u4f5c\u8005\u63d0\u51fa\u4e86 BEV-InMLLM，\u901a\u8fc7\u4f7f\u7528 ST-Adapters \u548c BEV-Injection \u6a21\u5757，\u6216\u8005\u901a\u8fc7\u878d\u5408\u591a\u89c6\u89d2\u89c6\u9891\u7a7a\u95f4\u7279\u5f81\u7684 Fusion Transformer \u6765\u6269\u5c55 MLLMs（\u5982 Video-LLaMA），\u4ece\u800c\u5728\u6574\u4f53\u81ea\u52a8\u9a7e\u9a76\u4efb\u52a1\u4e0a\u53d6\u5f97\u4e86\u6027\u80fd\u63d0\u5347\u3002HiLM-D [175] \u5f15\u5165\u4e86 DRAMA-ROLISP，\u8fd9\u662f\u4e00\u4e2a\u7528\u4e8e\u98ce\u9669\u8bc4\u4f30\u7684\u98ce\u9669\u611f\u77e5 VQA \u6570\u636e\u96c6，\u5e76\u901a\u8fc7 GPT-4 \u8fdb\u884c\u589e\u5f3a\u3002\u6a21\u578b\u5229\u7528 MiniGPT-4 \u8fdb\u884c\u5fae\u8c03，\u7ed3\u5408\u7528\u4e8e\u89c6\u9891\u8f93\u5165\u7684 ViT \u548c ST-Adapter\u3001\u57fa\u4e8e ResNet \u7684\u7f16\u7801\u5668\u4ee5\u53ca\u7528\u4e8e\u7a7a\u95f4\u878d\u5408\u7684 P-Adapter\u3002Query-Aware Detector \u6574\u5408\u8f93\u51fa，\u7528\u4e8e\u98ce\u9669\u5bf9\u8c61\u5b9a\u4f4d\u548c\u610f\u56fe\u63a8\u7406\u3002LLM \u672c\u8eab\u4fdd\u6301\u51bb\u7ed3，\u4ec5\u5fae\u8c03\u9002\u914d\u5668\u3001\u878d\u5408\u5c42\u548c\u6295\u5f71\u5c42\u3002DVBench [187] \u63d0\u51fa\u4e86\u4e00\u5957\u5168\u9762\u7684\u89c6\u9891\u57fa\u4e8e VQA \u7684\u5b89\u5168\u5173\u952e\u81ea\u52a8\u9a7e\u9a76\u57fa\u51c6，\u5efa\u7acb\u5728 SHRP2 [186] \u884c\u8f66\u8bb0\u5f55\u4eea\u6570\u636e\u4e4b\u4e0a\u3002\u591a\u9009\u95ee\u7b54\u5bf9\u901a\u8fc7 GPT-4o \u548c Qwen2.5-72B \u751f\u6210\u548c\u4f18\u5316，\u6db5\u76d6\u611f\u77e5\u548c\u63a8\u7406\u4efb\u52a1，\u5e76\u5206\u7c7b\u4e3a 11 \u4e2a\u5b50\u7c7b\u522b\u3002\u8be5\u57fa\u51c6\u4f7f\u7528\u81ea\u5b9a\u4e49\u6307\u6807\u8bc4\u4f30 14 \u4e2a MLLMs，\u8be5\u6307\u6807\u901a\u8fc7\u65cb\u8f6c\u7b54\u6848\u4f4d\u7f6e\u6765\u8bc4\u4f30\u9c81\u68d2\u6027\u3002\u4f5c\u8005\u8fd8\u6bd4\u8f83\u4e86 Qwen2-VL-2B\/7B \u5728 DVBench \u6570\u636e\u96c6\u4e0a\u5168\u91cf\u5fae\u8c03\u4e0e\u5426\u7684\u6027\u80fd\u5dee\u5f02\u3002（\u4e13\u6ce8\u4e8e\u98ce\u9669\u8bc6\u522b\u3001\u610f\u56fe\u4f30\u8ba1）<\/span><\/p>\n

(IV) \u57fa\u4e8e LiDAR \u7684\u591a\u6a21\u6001\u6269\u5c55（\u6709\/\u65e0\u9ad8\u6e05\u5730\u56fe）：\u4e3a\u4e86\u8d85\u8d8a RGB \u6570\u636e\u7684\u63a8\u7406\u80fd\u529b，\u4e00\u4e9b\u6570\u636e\u96c6\u5f15\u5165\u4e86 3D \u70b9\u4e91\u6216\u9ad8\u6e05\u5730\u56fe\u3002LiDAR-LLM [172] \u9996\u5148\u5904\u7406\u57fa\u4e8e LiDAR \u70b9\u4e91\u7684 3D \u63cf\u8ff0\u3001\u5b9a\u4f4d\u548c\u89c6\u89c9\u95ee\u7b54\u4efb\u52a1\u3002\u5b83\u901a\u8fc7\u4f53\u7d20\u7f16\u7801\u5668\u63d0\u53d6 BEV \u7279\u5f81，\u4f7f\u7528\u5177\u6709\u53ef\u5b66\u4e60\u67e5\u8be2\u7684\u89c6\u89d2\u611f\u77e5 Transformer \u5bf9\u5176\u8fdb\u884c\u5d4c\u5165，\u8be5 Transformer \u4f5c\u4e3a\u5148\u9a8c\u7684\u5206\u8bcd\u5668，\u7136\u540e\u901a\u8fc7 MLP \u5c06\u5176\u6295\u5c04\u5230\u8bed\u8a00\u7a7a\u95f4\u3002\u5728 LLM \u5185\u90e8，\u5bf9\u9002\u914d\u5c42\u8fdb\u884c\u5fae\u8c03\u4ee5\u652f\u6301 3D \u573a\u666f\u7406\u89e3\u3002MAPLM [146] \u5f15\u5165\u4e86\u5927\u89c4\u6a21\u591a\u6a21\u6001\u57fa\u51c6\u548c VQA \u6570\u636e\u96c6，\u4e3b\u8981\u5173\u6ce8\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u611f\u77e5\u548c\u9ad8\u6e05\u5730\u56fe\u7406\u89e3\u3002\u5b83\u5305\u542b\u5168\u666f 2D \u56fe\u50cf\u3001\u6765\u81ea LiDAR \u70b9\u4e91\u7684 BEV \u6295\u5f71，\u4ee5\u53ca\u4ece\u9ad8\u6e05\u5730\u56fe\u63d0\u53d6\u7684\u6587\u672c\u63cf\u8ff0\u3002\u57fa\u7ebf\u6a21\u578b\u4f7f\u7528\u9884\u8bad\u7ec3\u7684 CLIP \u7f16\u7801\u5668\u548c\u8f7b\u91cf\u7ea7\u6295\u5f71\u9002\u914d\u5c42\u6765\u5bf9\u9f50\u89c6\u89c9\u7279\u5f81，\u5e76\u5c06\u5176\u6620\u5c04\u5230 LLM \u7684\u5d4c\u5165\u7a7a\u95f4\u3002\u901a\u8fc7\u5728 Vicuna \u6216 LLaMA-2 \u4e0a\u4f7f\u7528 LoRA \u8fdb\u884c\u6307\u4ee4\u5fae\u8c03，\u4f7f\u6a21\u578b\u80fd\u591f\u5728\u591a\u6a21\u6001\u4e0b\u6267\u884c\u6709\u6548\u7684\u573a\u666f\u7ea7\u63a8\u7406\u3002V2V-LLM [188] \u8fdb\u4e00\u6b65\u5c06\u57fa\u4e8e LiDAR \u7684\u591a\u6a21\u6001\u63a8\u7406\u6269\u5c55\u5230\u534f\u4f5c\u9a7e\u9a76，\u901a\u8fc7\u878d\u5408\u6765\u81ea\u591a\u8f86\u8054\u7f51\u8f66\u8f86\u7684\u70b9\u4e91\u7279\u5f81\u3002\u5b83\u57fa\u4e8e\u6570\u636e\u96c6 V2X-Real [198],[199] \u6784\u5efa\u4e86\u8f66\u8f86\u95f4\u95ee\u7b54\u6570\u636e\u96c6，\u7528\u4e8e\u611f\u77e5\u548c\u89c4\u5212\u3002\u8be5\u6a21\u578b\u901a\u8fc7\u5c06 RGB \u7f16\u7801\u5668\u66ff\u6362\u4e3a LiDAR \u68c0\u6d4b\u5668\u6765\u6539\u9020 LLaVA，\u5e76\u901a\u8fc7 MLP \u6295\u5c04\u5668\u548c\u5fae\u8c03\u7684 LoRA \u5c42\u5bf9\u573a\u666f\u7ea7\u548c\u5bf9\u8c61\u7ea7\u7279\u5f81\u8fdb\u884c\u5bf9\u9f50\u3002（3D \u70b9\u4e91\u6216\u9ad8\u6e05\u5730\u56fe）<\/span><\/p>\n

\u5728\u81ea\u52a8\u9a7e\u9a76\u4e2d，VQA \u7684\u4e00\u4e2a\u5173\u952e\u4e0b\u4e00\u6b65\u662f\u8bc4\u4f30\u6a21\u578b\u5728\u5206\u5e03\u5916\u6761\u4ef6\u4e0b\u7684\u9c81\u68d2\u6027\u3002\u76ee\u524d\u7684\u6570\u636e\u96c6\u5927\u591a\u6db5\u76d6\u5e38\u89c1\u7684\u9a7e\u9a76\u573a\u666f\u548c\u7ed3\u6784\u826f\u597d\u7684\u95ee\u9898，\u5bfc\u81f4\u6a21\u578b\u5728\u7f55\u89c1\u4e8b\u4ef6\u3001\u4e0d\u719f\u6089\u7684\u7269\u4f53\u6216\u591c\u95f4\u3001\u96ea\u5929\u6216\u65bd\u5de5\u533a\u7b49\u6311\u6218\u6027\u6761\u4ef6\u4e0b\u51e0\u4e4e\u6ca1\u6709\u7ecf\u8fc7\u6d4b\u8bd5\u3002\u5f00\u53d1\u660e\u786e\u5305\u542b\u8fd9\u4e9b\u8fb9\u7f18\u60c5\u51b5\u7684\u57fa\u51c6，\u5e76\u8bc4\u4f30\u6a21\u578b\u5728\u8fd9\u4e9b\u60c5\u51b5\u4e0b\u7684\u6cdb\u5316\u80fd\u529b，\u5bf9\u4e8e\u5728\u5b89\u5168\u5173\u952e\u7684\u771f\u5b9e\u73af\u5883\u4e2d\u90e8\u7f72 VQA \u7cfb\u7edf\u81f3\u5173\u91cd\u8981\u3002（\u5b58\u5728\u7684\u4e00\u4e9b\u95ee\u9898）<\/span><\/p>\n

\u573a\u666f\/\u60c5\u5883\u7406\u89e3：<\/h4>\n

\u672c\u5c0f\u8282\u533a\u5206\u4e86\u573a\u666f\u7406\u89e3，\u5b83\u4fa7\u91cd\u4e8e\u9759\u6001\u7684\u3001\u57fa\u4e8e\u56fe\u50cf\u7684\u611f\u77e5，\u4ee5\u53ca\u60c5\u5883\u7406\u89e3，\u5b83\u6355\u6349\u65f6\u95f4\u52a8\u6001\u3001\u4e3b\u4f53\u4ea4\u4e92\u548c\u4e0d\u65ad\u53d1\u5c55\u7684\u56e0\u679c\u4e8b\u4ef6\u3002（\u573a\u666f\u60c5\u666f\u4e3b\u8981\u662f\u9759\u6001\u548c\u52a8\u6001\u7684\u533a\u522b）<\/span><\/p>\n

(I) \u573a\u666f\u7406\u89e3：InternDrive [178] \u548c Jain \u7b49\u4eba [190] \u4fa7\u91cd\u4e8e\u4f7f\u7528\u57fa\u4e8e\u56fe\u50cf\u7684\u8f93\u5165\u8fdb\u884c\u9759\u6001\u573a\u666f\u7406\u89e3\u3002InternDrive \u63d0\u51fa\u4e86\u4e00\u79cd\u9a7e\u9a76\u573a\u666f\u7406\u89e3\u6846\u67b6，\u6db5\u76d6\u611f\u77e5\u3001\u9884\u6d4b\u548c\u63a8\u7406，\u4f7f\u7528\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLM）\u3002\u5b83\u5229\u7528 GPT-4o \u4ece nuScenes \u751f\u6210\u95ee\u7b54\u5bf9，\u7136\u540e\u8fdb\u884c\u4eba\u5de5\u6821\u6b63，\u5e76\u901a\u8fc7 LoRA \u5728\u8fd9\u4e9b\u6807\u6ce8\u4e0a\u5fae\u8c03 MLLM InternVL-1.5\u3002\u751f\u6210\u7684\u6a21\u578b\u901a\u8fc7\u89c6\u89c9\u6307\u4ee4\u8c03\u4f18，\u4ece\u7b2c\u4e00\u4eba\u79f0\u89c6\u89d2（FPV）\u56fe\u50cf\u5206\u6790\u9a7e\u9a76\u573a\u666f\u3002Jain \u7b49\u4eba [190] \u4f7f\u7528\u6765\u81ea KITTI \u548c nuScenes \u7684\u95ee\u7b54\u5bf9，\u5728\u4e94\u4e2a\u7c7b\u522b\u4e2d\u8bc4\u4f30 MLLM \u5bf9\u5b89\u5168\u5173\u952e\u573a\u666f\u7684\u7406\u89e3\u80fd\u529b\u3002\u4ed6\u4eec\u4f7f\u7528\u878d\u5408\u7684\u56fe\u50cf\u5e27\u548c\u6587\u672c\u5316\u7684 LiDAR \u6458\u8981\u5bf9 Video-LLaVA \u548c GPT-4V \u8fdb\u884c\u57fa\u51c6\u6d4b\u8bd5，\u91c7\u7528 CoT 22 \u63d0\u793a\u65b9\u6cd5\u63d0\u5347\u591a\u6a21\u6001\u63a8\u7406\u80fd\u529b，\u800c\u4e0d\u9700\u8981\u771f\u5b9e\u7684\u65f6\u95f4\u5efa\u6a21\u3002（\u4e00\u822c\u7684\u573a\u666f\u7406\u89e3\u6848\u4f8b）<\/span><\/p>\n

(II) \u60c5\u666f\u7406\u89e3：\u76f8\u6bd4\u4e4b\u4e0b，DOLPHINS [176]\u3001Ishaq \u7b49 [171]\u3001WTS [191] \u548c V3LMA [192] \u4e13\u6ce8\u4e8e\u60c5\u666f\u7406\u89e3，\u5176\u4e2d\u65f6\u95f4\u4e0a\u4e0b\u6587\u3001\u4e3b\u4f53\u4ea4\u4e92\u548c\u56e0\u679c\u63a8\u7406\u662f\u6838\u5fc3\u3002DOLPHINS [176] \u63d0\u51fa\u4e86\u4e00\u79cd\u57fa\u4e8e MLLM \u7684\u7cfb\u7edf，\u7528\u4e8e\u5bf9\u9a7e\u9a76\u573a\u666f\u548c\u884c\u4e3a\u8fdb\u884c\u7c7b\u4f3c\u4eba\u7c7b\u7684\u7406\u89e3\u3002\u8be5\u6a21\u578b\u6784\u5efa\u5728 OpenFlamingo \u4e4b\u4e0a，\u9996\u5148\u901a\u8fc7\u56fe\u50cf\u2013\u6307\u4ee4\u5bf9\u8fdb\u884c\u6307\u4ee4\u5fae\u8c03，\u91c7\u7528 Grounded Chain of Thought (GCoT)，\u5176\u4e2d\u6bcf\u4e00\u6b65\u63a8\u7406\u90fd\u660e\u786e\u5173\u8054\u89c6\u89c9\u8bc1\u636e，\u4ee5\u786e\u4fdd\u89c6\u89c9\u9a71\u52a8\u7684\u573a\u666f\u63a8\u7406\u3002\u968f\u540e，\u6a21\u578b\u901a\u8fc7 VideoMAE \u548c Ada-002 \u68c0\u7d22\u7684\u4e0a\u4e0b\u6587\u793a\u4f8b\u9002\u914d\u5230\u9a7e\u9a76\u89c6\u9891\u3002\u5728\u8bad\u7ec3\u8fc7\u7a0b\u4e2d，\u4ec5\u66f4\u65b0\u611f\u77e5\u91cd\u91c7\u6837\u5668\u3001\u95e8\u63a7\u4ea4\u53c9\u6ce8\u610f\u529b\u548c LoRA \u6a21\u5757，\u4f7f\u6846\u67b6\u9ad8\u6548\u8fd0\u884c，\u540c\u65f6\u652f\u6301\u591a\u79cd\u9a7e\u9a76\u4efb\u52a1\u3002Ishaq \u7b49 [171] \u63d0\u51fa\u4e86\u4e00\u79cd\u573a\u666f\u7ea7\u7a7a\u95f4\u7406\u89e3\u6846\u67b6，\u5c06\u77ed\u89c6\u9891\u7247\u6bb5\u3001\u9a7e\u9a76\u8f68\u8ff9\u6587\u672c\u4ee5\u53ca\u6587\u672c\u67e5\u8be2\u6574\u5408\u5728\u4e00\u8d77\u3002\u4ed6\u4eec\u4f7f\u7528\u8f68\u8ff9\u7f16\u7801\u5668\u548c\u67e5\u8be2\u751f\u6210\u5668\u6765\u878d\u5408\u591a\u6a21\u6001\u4fe1\u606f，\u968f\u540e\u4f20\u5165\u5e26\u6709\u9002\u914d\u5668\u5c42\u7684\u51bb\u7ed3 LLaMA-2 \u6a21\u578b\u3002\u901a\u8fc7\u8bad\u7ec3\u67e5\u8be2\u751f\u6210\u5668\u548c\u9002\u914d\u5668，\u6a21\u578b\u53ef\u4ee5\u9ad8\u6548\u5730\u8fdb\u884c\u591a\u6a21\u6001\u63a8\u7406\u3002（\u66f4\u8fdb\u4e00\u6b65\u7684\u60c5\u666f\u7406\u89e3\u6848\u4f8b）<\/span><\/p>\n

\u5177\u4f53\u6765\u8bf4，WTS [191] \u548c V3LMA [192] \u5173\u6ce8\u573a\u666f\u63cf\u8ff0，\u5176\u4e2d WTS \u5f3a\u8c03\u53ef\u89c2\u5bdf\u7684\u5143\u7d20\u3001\u63a8\u7406\u76ee\u6807\u7a7a\u95f4-\u65f6\u95f4\u5173\u7cfb\u3001\u610f\u56fe\u63a8\u65ad\u548c\u56e0\u679c\u5206\u6790\u3002WTS [191] \u5916\u90e8\u4f7f\u7528 GPT-3.5 \u751f\u6210\u4eba\u5de5\u5f15\u5bfc\u7684\u771f\u5b9e\u63cf\u8ff0，\u5e76\u901a\u8fc7 LLMScore \u5bf9\u6a21\u578b\u8f93\u51fa\u8fdb\u884c\u8bc4\u4f30，\u8be5\u8bc4\u5206\u8861\u91cf\u8bed\u4e49\u548c\u53e5\u6cd5\u76f8\u4f3c\u6027\u3002\u6240\u63d0\u51fa\u7684 Instance-VideoLLM \u7ed3\u5408\u4e86 CLIP ViT-L\/14\u3001Video Q-Former \u548c Vicuna-7B，\u5e76\u5bf9\u9002\u914d\u5668\u548c Q-Former \u8fdb\u884c\u4e86\u5fae\u8c03\u3002\u8be5\u6a21\u578b\u5728\u589e\u5f3a\u7684\u89c6\u9891\u8f93\u5165\u4e0a\u8bad\u7ec3，\u8fd9\u4e9b\u8f93\u5165\u5305\u542b\u8fb9\u754c\u6846\u3001\u6ce8\u89c6\u6570\u636e\u548c\u573a\u666f\u4e0a\u4e0b\u6587，\u5e76\u4e0e\u5176\u4ed6\u73b0\u6210\u7684\u591a\u6a21\u6001\u5927\u578b\u6a21\u578b（MLLMs）\u8fdb\u884c\u6bd4\u8f83\u3002V3LMA [192] \u63d0\u51fa\u4e86\u4e00\u79cd\u878d\u5408\u65b9\u6cd5，\u5c06\u9884\u8bad\u7ec3\u7684 LLMs \u548c VLMs \u7ed3\u5408，\u4ee5\u589e\u5f3a\u96f6\u6837\u672c 3D \u573a\u666f\u7406\u89e3\u3002\u4ed6\u4eec\u4f7f\u7528\u73b0\u6210\u5de5\u5177\u8fdb\u884c\u5b9a\u4f4d\u3001\u76ee\u6807\u68c0\u6d4b\u548c\u6df1\u5ea6\u4f30\u8ba1，\u4ee5\u751f\u6210\u7ed3\u6784\u5316\u573a\u666f\u63cf\u8ff0，\u7136\u540e\u8f93\u5165\u5230 LLM \u4e2d\u3002MLLM \u7684\u89c6\u89c9\u7279\u5f81\u968f\u540e\u5728\u7279\u5f81\u7ea7\u522b\u6216\u5206\u7c7b\u5934\u8fdb\u884c\u878d\u5408\u3002\u5c3d\u7ba1\u662f\u96f6\u6837\u672c，\u6a21\u578b\u4ecd\u53d6\u5f97\u4e86\u5177\u6709\u7ade\u4e89\u529b\u7684\u6027\u80fd，\u53ef\u4e0e\u7ecf\u8fc7\u5fae\u8c03\u7684 MLLMs \u76f8\u5ab2\u7f8e\u3002（\u8be6\u7ec6\u8bf4\u660e\u60c5\u666f\u7406\u89e3\u7684\u63d0\u5230\u7684\u51e0\u4e2a\u6848\u4f8b）<\/span><\/p>\n

\u76ee\u524d\u7528\u4e8e\u573a\u666f\u548c\u60c5\u666f\u7406\u89e3\u7684\u591a\u6a21\u6001\u5927\u6a21\u578b\u4e3b\u8981\u5173\u6ce8\u77ed\u671f\u65f6\u95f4\u4e0a\u4e0b\u6587\u548c\u7cbe\u5fc3\u8bbe\u8ba1\u7684\u95ee\u7b54\u4efb\u52a1，\u8fd9\u5728\u771f\u5b9e\u7684\u73b0\u5b9e\u73af\u5883\u4e2d\u7f3a\u4e4f\u9a8c\u8bc1\u3002\u4e3a\u4e86\u671d\u7740\u66f4\u5168\u9762\u7684\u60c5\u666f\u7406\u89e3\u53d1\u5c55，\u672a\u6765\u7684\u5de5\u4f5c\u5e94\u63a2\u7d22\u957f\u65f6\u95f4\u8de8\u5ea6\u7684\u65f6\u95f4\u5efa\u6a21\u3001\u4e8b\u4ef6\u5e8f\u5217\u95f4\u7684\u56e0\u679c\u63a8\u65ad，\u4ee5\u53ca\u5bf9\u5206\u5e03\u5916\u573a\u666f\u7684\u9c81\u68d2\u5904\u7406\u3002（\u5b58\u5728\u7684\u4e00\u4e9b\u95ee\u9898）<\/span><\/p>\n

\u98ce\u9669\u8bc4\u4f30：<\/h4>\n

\u591a\u6a21\u6001\u8bed\u8a00\u5927\u6a21\u578b（MLLMs）\u7684\u76ee\u6807\u5305\u62ec\u98ce\u9669\u68c0\u6d4b\u548c\u8fdd\u89c4\u63a8\u65ad\u4ee5\u9884\u5224\u5371\u9669\u3001\u63a8\u7406\u548c\u573a\u666f\u7ea7\u5b89\u5168\u8bc4\u5206\u4ee5\u5206\u6790\u4e8b\u6545，\u4ee5\u53ca\u53ef\u6267\u884c\u5efa\u8bae\u7684\u751f\u6210\u3002<\/p>\n

\u4e00\u79cd\u98ce\u9669\u8bc4\u4f30\u65b9\u6cd5\u5f3a\u8c03\u901a\u8fc7\u53ef\u89e3\u91ca\u7684\u60c5\u666f\u7406\u89e3\u8fdb\u884c\u4e3b\u52a8\u7684\u5371\u5bb3\u7f13\u89e3\u3002\u4f8b\u5982，AccidentGPT [194] \u5c06\u591a\u6a21\u6001\u611f\u77e5（\u5982\u56fe\u50cf\u30013D \u68c0\u6d4b\u3001BEV \u7279\u5f81\u548c\u8f68\u8ff9）\u4e0e GPT-4V \u7ed3\u5408，\u7528\u4e8e\u57fa\u4e8e\u6570\u636e\u96c6 DeepAccident [193] \u7684\u96f6\u6837\u672c\u60c5\u666f\u63cf\u8ff0；\u540c\u65f6\u5229\u7528 GPT-4 \u901a\u8fc7 CoT \u548c CP \u8fdb\u884c\u8fdb\u4e00\u6b65\u7684\u5b89\u5168\u8bc4\u4f30\u3002\u5b83\u652f\u6301\u5b9e\u65f6\u4e8b\u6545\u9884\u9632\u3001\u4e8b\u6545\u540e\u7684\u5206\u6790\u4ee5\u53ca\u901a\u8fc7\u53ef\u89e3\u91ca\u63a8\u7406\u8fdb\u884c\u7684\u4e92\u52a8\u5b89\u5168\u51b3\u7b56\u3002（\u53ef\u89e3\u91ca\u7684\u60c5\u666f\u7406\u89e3\u8fdb\u884c\u4e3b\u52a8\u7684\u5371\u5bb3\u7f13\u89e3）<\/span><\/p>\n

\u5176\u4ed6\u5de5\u4f5c\u5219\u4fa7\u91cd\u4e8e\u5b9e\u73b0\u4ea4\u4e92\u5f0f\u5b89\u5168\u611f\u77e5\u548c\u53cd\u9988\u3002MLLM-SUL [177] \u4f7f\u7528 ResNet-101 \u548c Swin-L \u878d\u5408\u591a\u5c3a\u5ea6\u89c6\u89c9\u8f93\u5165\u4ee5\u83b7\u53d6\u4f4e\u5206\u8fa8\u7387\u548c\u9ad8\u5206\u8fa8\u7387\u7279\u5f81，\u901a\u8fc7 Query Formers \u548c Gate-Attention \u7ed3\u5408，\u57fa\u4e8e HiLM-D [175] \u63d0\u4f9b\u7684\u6570\u636e\u96c6 Drama-ROLISP \u548c Drama-SRIS\u3002\u5b83\u901a\u8fc7\u9002\u914d\u5668\u5fae\u8c03 LLaMA2-7B，\u5e76\u5e94\u7528 MLP \u5934\u8fdb\u884c\u573a\u666f\u63cf\u8ff0\u548c\u98ce\u9669\u7269\u4f53\u5b9a\u4f4d\u3002\u7c7b\u4f3c\u5730，ScVLM [195] \u63d0\u51fa\u4e86\u4e00\u4e2a\u57fa\u4e8e\u591a\u9636\u6bb5\u7684 MLLM \u6846\u67b6\u7528\u4e8e\u98ce\u9669\u8bc4\u4f30，\u57fa\u4e8e nuScenes \u6570\u636e\u96c6，\u7ed3\u5408\u4e8b\u4ef6\u7c7b\u578b\u5206\u7c7b\u3001\u51b2\u7a81\u7c7b\u578b\u8bc6\u522b\u548c\u53d9\u4e8b\u751f\u6210\u3002\u5b83\u4f7f\u7528 VideoLLaMA2 \u8fdb\u884c\u96f6\u6837\u672c\u89c6\u89c9\u4e0a\u4e0b\u6587\u63d0\u53d6，\u5e76\u4f7f\u7528 LLaMA 3.1 8B \u6839\u636e FPV \u9a7e\u9a76\u89c6\u9891\u751f\u6210\u5173\u4e8e\u5b89\u5168\u5173\u952e\u4e8b\u4ef6\u7684\u8be6\u7ec6\u63cf\u8ff0\u3002（\u4ea4\u4e92\u5f0f\u5b89\u5168\u611f\u77e5\u548c\u53cd\u9988）<\/span><\/p>\n

\u7b2c\u4e09\u4e2a\u65b9\u5411\u5f3a\u8c03\u901a\u8fc7\u7ed3\u6784\u5316\u95ee\u7b54\u8fdb\u884c\u98ce\u9669\u63a8\u7406\u3002Abu \u7b49\u4eba [196] \u63d0\u51fa\u4e86\u4e00\u79cd\u57fa\u4e8e MLLM \u7684\u6846\u67b6，\u7528\u4e8e\u4f7f\u7528 DRAMA \u6570\u636e\u96c6\u4e2d\u7684 FPV \u89c6\u9891\u8fdb\u884c\u5b89\u5168\u5173\u952e\u4e8b\u4ef6\u68c0\u6d4b\u3002\u4ed6\u4eec\u91c7\u7528\u57fa\u4e8e\u95ee\u7b54\u7684\u98ce\u9669\u5206\u6790\u7ed3\u5408\u4e0a\u4e0b\u6587\u5b66\u4e60，\u6bd4\u8f83\u4e86 Gemini-Pro-V1.5\u3001Gemini-Pro-Video \u548c LLaVA \u7684\u8868\u73b0，\u540c\u65f6\u5229\u7528\u6ed1\u52a8\u7a97\u53e3\u6355\u6349\u548c\u6587\u672c\u4e0a\u4e0b\u6587\u63d0\u793a\u6765\u589e\u5f3a\u98ce\u9669\u4e8b\u4ef6\u68c0\u6d4b\u3002（\u7ed3\u6784\u5316\u95ee\u7b54\u8fdb\u884c\u98ce\u9669\u63a8\u7406）<\/span><\/p>\n

\u7136\u800c，\u4e3a\u4e86\u786e\u4fdd\u5b9e\u9645\u5f71\u54cd，\u5173\u952e\u662f\u8981\u5efa\u7acb\u57fa\u4e8e MLLM \u7684\u98ce\u9669\u8bc4\u4f30\u7684\u53ef\u9760\u6027\u548c\u786e\u5b9a\u6027\u3002\u8fd9\u4ecd\u7136\u662f\u4e00\u4e2a\u4e3b\u8981\u6311\u6218，\u56e0\u4e3a MLLM \u7684\u884c\u4e3a\u672c\u8d28\u4e0a\u662f\u968f\u673a\u7684，\u53ef\u80fd\u4f1a\u4ea7\u751f\u4e0d\u4e00\u81f4\u7684\u8f93\u51fa\u3002（\u5b58\u5728\u7684\u95ee\u9898）<\/span><\/p>\n

D. \u5c40\u9650\u6027\u4e0e\u672a\u6765\u65b9\u5411<\/h3>\n

\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLMs）\u901a\u8fc7\u5229\u7528\u5176\u591a\u6a21\u6001\u80fd\u529b，\u80fd\u591f\u751f\u6210\u548c\u5206\u6790\u5404\u79cd\u60c5\u666f\u3002\u7136\u800c，\u76ee\u524d\u5c1a\u4e0d\u5b58\u5728\u4e13\u95e8\u9488\u5bf9\u81ea\u52a8\u9a7e\u9a76（AD）\u5e76\u7ed3\u5408\u6fc0\u5149\u96f7\u8fbe\u3001\u6444\u50cf\u5934\u548c\u96f7\u8fbe\u7b49\u4e92\u8865\u4f20\u611f\u5668\u6a21\u6001\u7684\u9884\u8bad\u7ec3MLLM\u3002\u4f5c\u4e3a\u672a\u6765\u7684\u65b9\u5411，\u8fd9\u51f8\u663e\u4e86\u5bf9\u5927\u89c4\u6a21\u591a\u6a21\u6001\u6570\u636e\u96c6\u4ee5\u53ca\u9488\u5bf9\u81ea\u52a8\u9a7e\u9a76\u5b9a\u5236\u7684\u9884\u8bad\u7ec3MLLM\u7684\u9700\u6c42\u3002（\u603b\u7ed3\u5c40\u9650\u548c\u65b9\u5411）<\/span><\/p>\n

\u57fa\u4e8eMLLM\u7684\u573a\u666f\u751f\u6210：<\/h4>\n

\u5982\u88686\u6240\u793a，\u53ea\u6709\u4e24\u9879\u7814\u7a76\u63a2\u7d22\u4e86\u57fa\u4e8eMLLM\u7684\u60c5\u666f\u751f\u6210：\u4e00\u9879\u9488\u5bf9\u5b89\u5168\u5173\u952e\u60c5\u666f，\u53e6\u4e00\u9879\u4fa7\u91cd\u4e8eADAS\u6d4b\u8bd5\u3002\u8fd9\u51f8\u663e\u4e86\u4e00\u4e2a\u663e\u8457\u7684\u7814\u7a76\u7a7a\u767d，\u5e76\u8868\u660eVOLUME\u548cMLLM\u5728\u8fd9\u4e00\u9886\u57df\u7684\u66f4\u5e7f\u6cdb\u6f5c\u529b\u4ecd\u7136 largely \u672a\u88ab\u63a2\u7d22\u3002\u672a\u6765\u7684\u5de5\u4f5c\u53ef\u4ee5\u6269\u5c55\u5230\u5176\u4ed6\u5e94\u7528，\u5982\u9a7e\u9a76\u7b56\u7565\u8bc4\u4f30\u3001\u95ed\u73af\u60c5\u666f\u751f\u6210\u4ee5\u53ca\u590d\u6742\u771f\u5b9e\u9a7e\u9a76\u4e8b\u4ef6\u7684\u91cd\u5efa\u3002（\u6570\u91cf\u5c11，\u5e94\u7528\u7a84）<\/span><\/p>\n

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\u57fa\u4e8eMLLM\u7684\u60c5\u666f\u5206\u6790：<\/h4>\n

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\u4ece\u5e94\u7528\u7684\u89d2\u5ea6\u6765\u770b，\u6709\u524d\u666f\u7684\u65b9\u5411\u5305\u62ec\u5229\u7528\u591a\u6a21\u6001\u5927\u8bed\u8a00\u6a21\u578b（MLLMs）\u8fdb\u884c\u9ad8\u4fdd\u771f\u4f20\u611f\u5668\u6a21\u62df，\u4ee5\u53ca\u5efa\u6a21\u591a\u79cd\u4ea4\u901a\u53c2\u4e0e\u8005\u4e4b\u95f4\u7684\u590d\u6742\u4ea4\u4e92，\u5982\u8f66\u8f86\u3001\u884c\u4eba\u548c\u9a91\u884c\u8005\u3002\u6b64\u5916，\u5728\u8fb9\u7f18\u90e8\u7f72MLLMs\u4ee5\u652f\u6301\u5b9e\u65f6\u6001\u52bf\u611f\u77e5\u548c\u534f\u4f5c\u4eba\u673a\u4ea4\u4e92，\u4ee3\u8868\u4e86\u672a\u6765\u7814\u7a76\u4e2d\u4e00\u4e2a\u6709\u4ef7\u503c\u4e14\u5c1a\u672a\u5145\u5206\u63a2\u7d22\u7684\u673a\u4f1a\u3002（\u5e94\u7528\u4e0a\u7684\u5c40\u9650）<\/p>\n","protected":false},"excerpt":{"rendered":"

\u6587\u7ae0\u6807\u9898：Foundation Models in Autonomous Driving: A Survey on Scenario Generation and Scenario Analysis
\n（\u7ffb\u8bd1）\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b：\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0 \u6587\u7ae0\u53d1\u8868\u4e8e\u9884\u5370\u672c：Foundation Models in Autonomous Driving: A Survey on Scenario Genera<\/p>\n","protected":false},"author":2,"featured_media":66317,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[1],"tags":[50,207,2051],"topic":[],"class_list":["post-66320","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-server","tag-50","tag-207","tag-2051"],"yoast_head":"\n\u6587\u732e\u9605\u8bfb\u7bc7#13\uff1a\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b\uff1a\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0\uff084\uff09 - \u7f51\u7855\u4e92\u8054\u5e2e\u52a9\u4e2d\u5fc3<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.wsisp.com\/helps\/66320.html\" \/>\n<meta property=\"og:locale\" content=\"zh_CN\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"\u6587\u732e\u9605\u8bfb\u7bc7#13\uff1a\u81ea\u52a8\u9a7e\u9a76\u4e2d\u7684\u57fa\u7840\u6a21\u578b\uff1a\u573a\u666f\u751f\u6210\u4e0e\u573a\u666f\u5206\u6790\u7efc\u8ff0\uff084\uff09 - 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