Core Viewpoint - The article emphasizes the importance of end-to-end production in the automotive industry, highlighting the scarcity of qualified talent and the need for comprehensive training programs to address various challenges in this field [1][3]. Group 1: Course Overview - The course is designed to cover essential algorithms related to end-to-end production, including one-stage and two-stage frameworks, reinforcement learning applications, and trajectory optimization [3][9]. - It aims to provide practical experience and insights into production challenges, focusing on real-world applications and expert guidance [3][6]. Group 2: Course Structure - The course consists of eight chapters, each addressing different aspects of end-to-end production, such as task overview, algorithm frameworks, navigation information applications, and trajectory output optimization [9][10][11][12][13][14][15][16]. - The final chapter will share production experiences from various perspectives, including data, models, and strategies for system enhancement [16]. Group 3: Target Audience and Requirements - The course is aimed at advanced learners with a background in autonomous driving, reinforcement learning, and programming, although those with weaker foundations can still participate [17][18]. - Participants are required to have access to a GPU with recommended specifications and familiarity with relevant algorithms and programming languages [18].

点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 论文作者 | Lin Liu等 编辑 | 自动驾驶之心 今年学术界和工业界很大的精力都投入在Action的建模上，也就是自车轨迹的输出。先前的MLP只能输出单模 的轨迹，实际使用中无法满足下游不确定性的需求。所以从去年开始，我们看到了生成式的很多算法问世。 经过这一年的发展，生成式的算法进一步收敛到Diffusion和Flow matching两个方向上。 自动驾驶之心了解到 上半年有不少公司都在尝试将这两种方法落地量产，期间坎坷无需多言。 今天为大家分享的是一篇北交&轻舟智航等团队最新的工作，提出一种基于Constrained Flow Matching的新型规 划框架 GuideFlow ，整体效果还不错。 具体而言，GuideFlow显式建模流匹配过程，该过程本质上可缓解模态坍塌的问题，并能灵活融合多种条件信 号的引导。本文的核心贡献在于， 将显式约束直接嵌入流匹配生成过程 ，而非依赖隐式约束编码。关键创新 点在于， GuideFlow将流匹配与Ene ...

以下文章来源于上海交大智能网联汽车创新中心 ，作者请关注 上海交大智能网联汽车创新中心 . 中心立足国家战略需求，聚焦汽车 "智能化、网联化、电动化、共享化" 核心领域，汇聚多学科科研力量，打造国际化创新枢纽，全力铸就交通强国之基。 原文链接： 学术成果丨综述：面向自动驾驶的局部矢量化高精地图构建 点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 01 研 究 背 景 Re s e a r c h Ba c k g r o u n d 随着自动驾驶迈入产业化关口，厘米级环境表征正成为决定安全与智能上限的关键因素。传统全局高精地图依赖昂贵的测绘车与人工后处理，更新周 期长、维护成本高，难以匹配城市场景的快速演化，"无图"方案因此呼声渐高。然而，完全摒弃先验信息又使感知系统陷入"单帧幻觉"困境，尤其在 复杂路口、施工区域等强语义场景中，实时生成局部、可扩展、实例级高精地图的需求愈发迫切。 车载相机与激光雷达的算力红利，使"边行驶边建图"成为可行路线：通过传感器在线感知，在鸟瞰视角下即时恢复车道线、路缘、交通标志等矢量要 素，从而既保留高精地图的几何—语义一致性， ...

Core Viewpoint - The article emphasizes the need for deeper technical exploration and collaboration in the autonomous driving industry, highlighting recent technological advancements from companies like Tesla, Xiaopeng, and Li Auto [2]. Group 1: Industry Direction - The main focus areas for the autonomous driving sector include but are not limited to: autonomous driving product management, 4D annotation/data loop, world models, VLA, autonomous driving large models, reinforcement learning, and end-to-end systems [4]. Group 2: Recruitment and Collaboration - The company is seeking to expand its team with talented individuals, particularly for roles related to autonomous driving training partnerships targeting both enterprises and educational institutions, as well as content creation for students and job seekers [5]. - Interested parties are encouraged to reach out for discussions regarding compensation and collaboration methods [6].

Core Viewpoint - The article emphasizes the importance of imitation in academic writing, particularly for students aiming to publish in high-impact journals. It suggests that by following a structured approach of mimicking established papers and utilizing AI tools for editing, students can efficiently produce their initial drafts [1]. Group 1: Writing Strategy - The article outlines two core principles for writing papers: avoid innovation and refrain from perfectionism, focusing instead on replicating successful frameworks and content from existing literature [1]. - It proposes a three-step process for creating a draft: imitate classic SCI paper structures, copy high-similarity literature, and use AI tools for reducing similarity [1]. Group 2: Service Offerings - The company, "自动驾驶之心," claims to be the largest AI technology media platform in China, providing extensive academic resources and support for students in fields like autonomous driving and robotics [4]. - It offers personalized guidance from over 300 experienced instructors, with a high success rate of 96% for students in getting their papers accepted [4][10]. Group 3: Target Audience and Requirements - The program is designed for students with a background in PyTorch and those looking to enhance their research capabilities, particularly in areas such as 3D reconstruction, computer vision, and robotics [6]. - The service is suitable for students aiming for various publication levels, including CCF-A/B/C and SCI 1-4 zones, providing comprehensive support from topic selection to submission [10]. Group 4: Additional Benefits - Students who excel in the program may receive recommendations to prestigious institutions and direct job placements in leading tech companies [14]. - The company offers a satisfaction guarantee for initial meetings with instructors, allowing students to switch mentors if they are not satisfied [14].

Core Viewpoint - The article emphasizes the growing demand for skills in end-to-end and VLA (Vision-Language-Action) autonomous driving, highlighting the saturation of job opportunities in these areas and the urgency for newcomers to acquire relevant knowledge and skills quickly [1]. Course Offerings - The "End-to-End and VLA Autonomous Driving Course" is designed to provide comprehensive training in VLA, covering topics from VLM as an autonomous driving interpreter to modular and integrated VLA, and current mainstream inference-enhanced VLA [1]. - The "Autonomous Driving VLA and Large Model Practical Course" focuses on foundational theories and practical applications, including Vision/Language/Action modules, reinforcement learning, and diffusion models, with a special section on building VLA models and datasets from scratch [1]. Instructor Team - The course is led by experts from both academia and industry, including individuals with extensive research and practical experience in multimodal perception, autonomous driving VLA, and large model frameworks [6][8][11]. Target Audience - The courses are aimed at individuals with a foundational understanding of autonomous driving, familiarity with key technologies such as transformer models and reinforcement learning, and a basic knowledge of probability and linear algebra [12][13].

Core Viewpoint - The article introduces the GeoScan S1, a highly cost-effective handheld 3D laser scanner designed for various applications, emphasizing its advanced features and capabilities in real-time 3D mapping and data collection [3][11]. Group 1: Product Features - GeoScan S1 offers a lightweight design with a one-button start for efficient 3D scanning solutions, achieving centimeter-level precision in real-time scene reconstruction [3][6]. - The device can generate point clouds at a rate of 200,000 points per second, with a maximum measurement distance of 70 meters and 360° coverage, suitable for large scenes over 200,000 square meters [3][31]. - It integrates multiple sensors, including RTK, IMU, and high-resolution cameras, enabling high-precision mapping and data collection in complex environments [24][36]. Group 2: Technical Specifications - The GeoScan S1 operates on Ubuntu 20.04 and supports various data export formats such as PCD, LAS, and PLY, with relative accuracy better than 3 cm and absolute accuracy better than 5 cm [24][29]. - The device dimensions are 14.2 cm x 9.5 cm x 45 cm, weighing 1.3 kg without the battery and 1.9 kg with the battery, and it has a battery capacity of 88.8 Wh, providing approximately 3 to 4 hours of operation [24][25]. - It features a 5.5-inch touchscreen and supports wireless connectivity via Wi-Fi and Bluetooth, along with multiple external expansion options [25][24]. Group 3: Applications and Market Position - GeoScan S1 is suitable for various applications, including urban planning, construction monitoring, and environmental surveying, capable of operating in diverse settings such as office buildings, industrial parks, tunnels, and forests [40][49]. - The product is positioned as the most cost-effective option in the market, with a starting price of 19,800 yuan for the basic version, catering to a wide range of user needs [11][60]. - The device supports cross-platform integration, making it compatible with drones, unmanned vehicles, and robotic systems for automated operations [47][49].

点击下方 卡片 ，关注" 自动驾驶之心 "公众号 戳我-> 领取 自动驾驶近30个 方向 学习 路线 >>自动驾驶前沿信息获取 → 自动驾驶之心知识星球 编辑 | 自动驾驶之心 论文作者 | Liuhan Yin等 与自动驾驶中预测自车固定候选轨迹集的判别式方法不同，扩散模型等生成式方法能够学习未来运动的潜在分布，实现更灵活的轨迹预测。然而由于这些方法通常依 赖于对人工设计的轨迹锚点或随机噪声进行去噪处理，其性能仍有较大提升空间。 浙江大学&纽劢的团队提出一种全新的两阶段轨迹预测框架DiffRefiner ：第一阶段采用基于Transformer的proposal解码器，通过对传感器输入进行回归，利用预定义轨 迹锚点生成粗粒度轨迹预测；第二阶段引入扩散Refiner，对初始预测结果进行迭代去噪与优化。通过融合判别式轨迹proposal模块，本文为生成式精炼过程提供了强有 力的引导，显著提升了基于扩散模型的规划性能。此外，本文设计了细粒度去噪解码器以增强场景适应性，通过加强与周围环境的对齐，实现更精准的轨迹预测。实 验结果表明，DiffRefiner达到了当前最优性能：在NAVSIM v2数据集上达到87.4的 ...

Core Viewpoint - A significant outflow of automotive talent from Shanghai has been observed since 2023, marking a shift from the city's historical role as a hub for the automotive industry in China [11][12]. Group 1: Historical Context - Shanghai has been the cradle of China's automotive industry, with major joint ventures like Shanghai Volkswagen and Shanghai General Motors attracting talent for over four decades [3][6]. - At its peak, Shanghai was home to approximately 50,000 high-end automotive R&D and marketing professionals [10][13]. Group 2: Recent Developments - The decline of new car manufacturers in Shanghai, starting with the shutdown of WM Motor in December 2022, has led to a significant reduction in job opportunities [11][12]. - Traditional automakers like SAIC Volkswagen and SAIC General Motors have seen their sales drop to about 60% of their peak levels, resulting in multiple rounds of layoffs [12][20]. Group 3: Talent Migration - The automotive job market in Shanghai has shifted from a surplus of opportunities to a situation where job seekers outnumber available positions, leading to a talent migration to other regions [15][17]. - Many former employees have relocated to cities like Wuhu, Hangzhou, and Ningbo, while some have even moved abroad to work for Chinese brands [18][19]. Group 4: Competitive Landscape - While Shanghai's automotive industry contracts, companies from other provinces, such as BYD, Geely, and Chery, are experiencing rapid growth, with sales increasing by 30% to 50% [15][16]. - These companies, previously offering lower salaries, are now able to match or exceed the compensation packages of Shanghai's new car manufacturers due to improved sales and profitability [16]. Group 5: Future Outlook - Despite current challenges, the long-term outlook for the automotive industry remains positive, with significant growth potential in developing countries where car ownership rates are still low [25][26].

Core Viewpoint - The article emphasizes the importance of high-quality research papers for students, especially those pursuing master's and doctoral degrees, as a means to enhance their academic and career prospects. It highlights the challenges faced by students in producing quality research due to lack of guidance and the need for professional assistance in the research process [1][5]. Group 1: Challenges Faced by Students - Many students struggle to secure jobs due to average research outcomes and seek to pursue further studies to alleviate employment pressure, but their master's performance significantly influences their doctoral applications [1]. - Students often encounter difficulties in research paper writing, such as topic selection, framework confusion, and weak argumentation, especially when left without proper mentorship [1][9]. Group 2: Services Offered - The company provides professional guidance for research paper writing, including personalized support from experienced mentors, to help students navigate the research process effectively [4][12]. - The structured program includes defining research directions, literature review, experimental design, data collection, drafting, and submission, ensuring a comprehensive approach to research paper development [4][12]. Group 3: Expertise and Success Rate - The company boasts a team of over 300 dedicated instructors specializing in fields like autonomous driving and robotics, with a high acceptance rate of 96% for students they have guided in the past three years [5]. - The instructors are affiliated with top global universities and have published numerous papers in prestigious conferences and journals, ensuring high-quality mentorship [5]. Group 4: Target Audience - The services are tailored for students in computer science and related fields who face challenges such as lack of guidance, need for research experience, or aspirations for academic advancement [10][9]. - The program is suitable for those aiming to publish in high-impact journals or conferences, as well as for students looking to enhance their resumes for further studies or job applications [10][12].