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面向混合交通流的自动驾驶汽车换道模型研究2针对多智能网联汽车协同换道策略进行研究，考虑到混合交通流中智能网联汽车存在不同的渗透率，针对多智能网联汽车渗透率较高的情况下车辆间协作换道方法展开研究：以车辆纵向动力学模型为基础，以安全性和舒适性为约束，以最小化对目标车道后方车辆的影响为目标构建出一种新的换道模型。所提出的模型在97461种场景中进行了测试，相比传统换道模型，所提出的协同式换道模型可以提高36.7%的换道成功率，并且大幅度减小了由车辆换道所引发的目标车道后方车辆队列的速度波动。(a) 所提出的协同换道模型示意图（上：无协同换道；下：协同换道）    (b) 与无协同换道模型的量化对照（左：换道成功率；右：速度平顺性）图2 多自动驾驶汽车协同换道模型针对于驾驶员注意力机制及行为特性方面，研究3通过开展实车实验对驾驶员跟随自动驾驶汽车过程中的行为特征进行分析，进而揭示了不同驾驶员对于自动驾驶车辆的不同态度及反应机制。该项研究的实验数据进行了公开，已为多项研究提供了数据基础。图3 分析驾驶员跟随自动驾驶汽车过程中的行为特征研究内容三：智能网联汽车整车在环测试    以多自由度整车在环测试台架为基础，研究数字孪生测试场景构建方法、典型自动驾驶传感器模型、行为评价方法等。    欢迎有志于从事自动驾驶汽车、智能网联汽车相关理论和技术研究的同学报考本人研究生","王振，副教授，博士生导师，硕士生导师。先后入选中国科协青年托举人才、山东省泰山创新领军人才、陕西省三秦特支青年拔尖人才、陕西省青年科技新星。长期从事智能网联汽车高精度定位、轨迹规划与控制、整车在环测试等方面的理论研究和产业化应用。先后主持和参与多项国家重点研发计划项目、自然基金项目、陕西省重点研发项目，发表高水平SCI论文20余篇，获得授权发明专利30余项，其中美国发明专利3项，承担本科生教学课程10门次。课题组简介：课题组招收人工智能、自动驾驶、车路协同、计算机视觉、智能汽车方向的博士生和硕士生，课题组为研究生提供如下条件：1. 一流的科研环境：优良的科研场地、配备计算机等基础科研条件；2. 一流的设备设施：自动驾驶实车2辆、小比例自动驾驶车辆平台3辆、高性能计算机算力平台、自动驾驶整车在环测试大型装备（全国高校唯一）、多种自动驾驶传感器。3. 每月发放科研劳务补助；4. 全额资助论文发表，全额资助参加国内外学术会议；5. 1对1的技术开发\u002F论文写作指导；6. 友好的科研和学习氛围，互帮互助，不定期团建；7. 头部企业实习和内推机会；课题组研究生就业情况：2026届：刘**，博世汽车部件（苏州）有限公司，雷达感知 AI 算法工程师，年薪35W+；陈**，广州文远知行科技有限公司，系统测试工程师（国际），年薪40W+；代*，深圳锐明科技，嵌入式软件开发工程师，年薪30W+；课题组新闻：2026.08：盛*博士的学术论文被计算机领域TOP期刊Applied Soft Computing录用；2026.08：获批陕西省科技厅重点研发计划项目；2026.07：盛*博士的学术论文被中科院一区TOP期刊Expert Systems with Applications录用；2026.06：代*硕士获批中国发明专利1项；2026.06：陈**硕士获批中国发明专利1项；2026.05：陈**硕士的学术论文被中科院一区TOP期刊Transportation Research Part E录用；2026.05：盛*博士获批中国发明专利1项；2026.05：入选陕西省三秦特支青年拔尖人才；2026.04：李**博士获批中国发明专利1项；2026.02：彭*博士的学术论文被顶级国际会议ICRA录用；2025.12：课题组研究生的论文被国际会议EILM录用；2025.10：课题组研究生授权自动驾驶测试领域发明专利1项；2025.09：课题组3位研究生的论文被国际会议ICEMCE录用；2025.08：课题组研究成果荣获全球道路联合会（IRF Global）全球道路成就奖（GRAA）；2025.08：5位研究生申请的软件著作权获批授权；2025.07：课题组研究生的论文被国际会议ACM International Conference on Multimedia录用（CCF-A）；2025.06：课题组研究生在IEEE Sensors Letters期刊发表论文《Efficient Critical Data Generation Framework      for Vision Sensors of Autonomous Vehicle Perception System》；2025.05：课题组研究生在IEEE Transactions on Intelligent Transportation Systems期刊发表论文（TOP期刊）；2025.05：课题组出版专著《自动驾驶整车在环测试评价理论与方法》；2025.05：课题组研究生参加“挑战杯”学术作品竞赛，获陕西省二等奖；2025.03：课题组获批美国发明专利1项；2025.02：入选中国科协青年托举人才（长安大学年度唯一一项）；2024.11：课题组研究生在IEEE Transactions on Intelligent Transportation Systems期刊发表论文（TOP期刊）；2024.06：课题组研究生在Advanced Intelligent Systems期刊发表论文； \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     1. 编委任职《AI and Autonomous Systems》期刊编委；《汽车工程学报》期刊青年编委；《International Journal of Environmental Research and Public Health》期刊Guest Editor；2. 期刊审稿人《Nature Communications》《IEEE Transactions on Intelligent Transportation Systems》《Transportation Research Part C Emerging Technologies》《Expert Systems with Applications》《Communications in Transportation Research》《Transportation Research Part E: Logistics and Transportation  Review》《Automatica》《IEEE Internet of Things Journal》《IEEE Transactions on Vehicular Technology》3. 会议审稿人《AAAI - 26》《TRB - 2025》《IEEE Virtual Reality》《International Joint Conference on Artificial Intelligence》《IEEE International Conference on Robotics and Automation》","陕西",false,"http:\u002F\u002Fjs.chd.edu.cn\u002Fxxgcxy\u002Fwz7\u002Flist.htm",true,[],[],{"id":402,"name":403,"orgName":388,"school":389,"gender":390,"title":404,"degree":392,"honor":10,"position":10,"researchDirection":405,"intro":406,"province":395,"completeness":229,"avatarAuthorized":396,"sourceUrl":407,"nameValid":398,"tags":408,"tagNames":409},"f0a52cbc-a780-c433-9d00-d092c7e5c433","王珂","讲师","研究领域：具身智能、智能车（机器人）自主环境感知、神经辐射场、视觉深度估计、动态场景信息捕捉部分研究成果：1. 基于LiDAR和IMU融合的高精度实时定位与建图（SLAM）    智能车（机器车）同时定位与建图技术，是智能车在未知环境完成特定任务的关键基础。此视频展示了智能车从长安大学北门体育场出发，绕学校主环道一圈，完成实时点云构图。为了便于可视化右侧（局部地图）视角升高，视频左下角图示实时定位建图鸟瞰图（BEV），左上角为车辆第一视角，蓝色线条为车辆自定位轨迹。其中1分46秒进入信息学院彩虹桥。Your user agent does not support the HTML5 Video element.2. 基于车路协同的车辆全局定位    在全球卫星导航信号（GNSS）拒制环境下，车辆难以实现高效全局定位，进而无法获取自身在地球坐标系（如高德地图）下的位置，通过同时考虑路侧传感信息与车侧局部定位信息，可以实现车辆的全场景全局定位。此视频展示了智能车在长安大学自动驾驶封闭测试的视频。绿色线条为车辆真值轨迹，青色线条为车辆自定位轨迹，可以看出在车辆进入路侧辅助区域（无线标号区域）时，车辆自定位坐标系和全局坐标系对齐。Your user agent does not support the HTML5 Video element.3. 基于RGB-D相机的语义目标级同时定位与建图    受益于深度学习技术的快速发展，机器人在未知环境在实时自定位的同时，可以实现对周围环境的语义建图，其难点在于（1）未知环境中的目标具有多样性，而常规深度学习模型存在识别目标已知；（2）因为部分观测等原因，时序语义识别结果存在非一致性，即上一时刻的椅子在下一时刻可能变为桌子；（3）一般深度学习模型存在跨数据域性能快速退化的问题。此研究工作结合大模型与贝叶斯推导，实现同一个模型对未知应用场景的定位与语义建图。Your user agent does not support the HTML5 Video element.4. 基于点云数据的场景流估计    场景流估计技术是指从两个点云场景中估计场景运动的技术。由于场景流具有相互独立的特性，可以用来处理复杂动态场景中的感知问题。精确的场景流可以提高智能车轨迹规划、障碍物规避、虚拟现实等技术的性能。下图图示了自动驾驶场景两个相邻时刻点云帧之间的场景流估计结果。5. 基于卷帘相机对的双目深度估计    双目深度估计方法大多基于全局快门相机，较少研究如何从卷帘快门相机中估计深度。此视频展示了基于卷帘相机的瞬时双目深度估计方法。Your user agent does not support the HTML5 Video element","王珂，博士，硕士生导师，毕业于香港科技大学机器人所，导师为沈劭劼教授，现担任信息工程学院软件系副主任。于2023年获批海外青年人才引进计划*****项目。长期从事具身智能、智能车自主环境感知、视觉深度估计、车路协同感知等方面的研究工作。研究生招生公告：    现招收2027级研究生1名，课题组科研氛围良好，研究方向就业面广、薪资待遇高，欢迎联系沟通，(QQ:305365447, email:kwangdd@chd.edu.com)。    优秀对口同学可推荐至行业知名企业实习。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     担任机器人国际顶会IEEE ICRA副编辑（AE）ICRA\u002FIROS\u002FRAL\u002FTIM等会议期刊长期审稿人交通运输协会青年委员会委员世界交通运输大会技术委员会委员","http:\u002F\u002Fjs.chd.edu.cn\u002Fxxgcxy\u002Fwk1\u002Flist.htm",[],[],{"id":411,"name":412,"orgName":413,"school":389,"gender":414,"title":404,"degree":392,"honor":10,"position":10,"researchDirection":415,"intro":416,"province":395,"completeness":417,"avatarAuthorized":396,"sourceUrl":418,"nameValid":398,"tags":419,"tagNames":420},"062e5dc9-3fe0-407c-c5dd-2e3f2c35bf39","魏延","长安大学工程机械学院","女","机械工程专业，智能机器人与人机共融课题组智能制造与机器人、自动化、人工智能领域：机器人系统设计-轻量化\u002F模块化结构+新材料、高自由度机械臂系统研发；机器人智能导航与运动规划-环境感知与建模、激光\u002FRGB-D 融合 SLAM、人机共融环境下路径规划算法设计；静态与动态环境下的路径优化算法（A*、Dijkstra，、RRT及其改进版 、蚁群、遗传算法、Q-learning等运动规划算法研究与优化）；复杂高维任务中的轨迹生成（如机械臂抓取路径优化）；人机共融与协作-人体舒适空间建模、行为预测与主动协助策略、多模态交互、机器人行为调节、人类操作员与机器人联合完成复杂任务；机器人智能控制-动力学建模与控制：高自由度机械臂与仿人机器人的非线性建模与鲁棒控制、自适应控制算法在复杂任务中的应用、模型预测控制（MPC）与强化学习结合、基于模糊控制与神经网络的自学习控制策略；多智能体编队控制-分布式任务规划算法、动态环境下的实时任务调整与冲突解决；编队保持与队形控制：基于虚拟结构、行为学和Leader-Follower模型的队形生成、复杂队形切换与断裂后重建机制；跨平台、多形态机器人编队（如无人机与移动机器人协作）；工业-移动-仿人-康复-护理-助理六大机器人场景全覆盖• 工业机器人：高速装配闭环控制，在线重规划应对产线换型• 移动机械臂：激光+RGB-D 实时 SLAM 抓取，动态障碍下重规划，提高分拣成功率；• 仿人双臂：7-DoF×2 协调，基于力-位混合阻抗控制，实现插拔、开关门等仿人任务零示教迁移；• 康复&护理：EMG+IMU 人体意图建模，个性化轨迹生成，训练效率提升；• 助理服务：家庭\u002F办公环境中的情境感知与用户行为预测，改善任务规划延迟。技术基础• 深度强化学习：端到端感知-决策-控制，Sim→Real； • 协同仿真：Gazebo + ROS2，多机器人并行测试","魏延，博士，硕导，讲师。2012年6月，获得北京航空航天大学工程力学专业学士学位；2015年1月，获得北京航空航天大学控制科学与工程专业硕士学位；2018年11月，获得法国里尔中央理工自动化、计算机工程、信号与图像处理专业博士学位。精通语言：汉语，英语，法语。2019年1月至今，在长安大学机械设计制造及其自动化、智能制造与机器人专业任教，主讲《机电一体化技术》、《工业机器人（双语）》、《工业机器人（留学生）》、《现代机器人技术》、《工程运筹管理》、《制造过程故障诊断》等专业技术课程。隶属智能机器人与人机共融课题组，主要从事智能制造与机器人方向的研究，具体包括：移动机器人、工业机器人、移动机械臂、双臂机器人、康复机器人、护理机器人和助理服务机器人等相关的机器人结构设计、机器人智能导航与运动规划、机器人智能控制、多智能体编队控制等研究工作。主持\u002F参与各类基金项目十余项，在国内外期刊会议发表论文SCI+EI十余篇，授权国家发明专利2项，申请国家发明专利（受理）3项,软件著作权2项。 \n                                \n                                \n                                    \n                                         社会职务 \n                                    \n                                     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