滴滴2026未来精英-自动驾驶感知和定位技术挑战
校招全职自动驾驶地点:北京状态:招聘
任职要求
感知团队的职责是根据传感器和高精地图的信息,对周围环境进行物体识别和场景理解,并对自车进行定位。在这里,你将研究和设计相关领域前沿算法,包括目标检测、占据网络、跟踪、场景理解、定位、数据挖掘与合成、蒸馏、半监督自监督、传感器标定等算法,直接赋能L4自动驾驶车的应用,创造社会价值和商业价值。一些项目包括:【感知大模型】 基于多模态传感器(激光雷达、相机、毫米波雷达)的多任务大模型,提供常见物体识别能力,包括检测、分割、道路元素等。【占据网络】 通用障碍物检测方法,识别开放世界层出不穷的异形物体,为感知进行兜底,保证自车安全。【端到端跟踪】用基于深度学习的方法,替代经典的匈牙利匹配+卡尔曼滤波算法,提升跟踪能力上限。【场景理解】基于传感器信息或环境中智能体和地图的交互关系,使用VLM或其他算法,实现场景级别的理解 (如风险区域、施工区域、事故场景、特殊天气、传感器异常等),直接影响自车行为(前进、避让、停止等)。【定位】通过自车识别的道路元素和高精地图语义信息的匹配、以及GNSS/IMU/Canbus等信号,提升定位精度和鲁棒性,保证自车安全。【数据挖掘与合成】调研和应用各种大模型(如GroundingDINO、SAM、Stable Diffusion等),挖掘和合成高价值场景,提升模型相应场景表现。【蒸馏】基于离线大模型,蒸馏小模型,并部署至车端,提升自车智能。【半监督自监督】调研和开发各种高效算法,降低模型对标注数据的依赖。
工作职责
无
包括英文材料
算法+
https://roadmap.sh/datastructures-and-algorithms
Step by step guide to learn Data Structures and Algorithms in 2025
https://www.hellointerview.com/learn/code
A visual guide to the most important patterns and approaches for the coding interview.
https://www.w3schools.com/dsa/
数据挖掘+
https://www.youtube.com/watch?v=-bSkREem8dM
Database vs Data Warehouse vs Data Lake
https://www.youtube.com/watch?v=7rs0i-9nOjo
自动驾驶+
https://www.youtube.com/watch?v=_q4WUxgwDeg&list=PL05umP7R6ij321zzKXK6XCQXAaaYjQbzr
Lecture: Self-Driving Cars (Prof. Andreas Geiger, University of Tübingen)
https://www.youtube.com/watch?v=NkI9ia2cLhc&list=PLB0Tybl0UNfYoJE7ZwsBQoDIG4YN9ptyY
You will learn to make a self-driving car simulation by implementing every component one by one. I will teach you how to implement the car driving mechanics, how to define the environment, how to simulate some sensors, how to detect collisions and how to make the car control itself using a neural network.
大模型+
https://www.youtube.com/watch?v=xZDB1naRUlk
You will build projects with LLMs that will enable you to create dynamic interfaces, interact with vast amounts of text data, and even empower LLMs with the capability to browse the internet for research papers.
https://www.youtube.com/watch?v=zjkBMFhNj_g
深度学习+
https://d2l.ai/
Interactive deep learning book with code, math, and discussions.
智能体+
https://learn.microsoft.com/en-us/shows/ai-agents-for-beginners/
In this 10-lesson course we take you from concept to code while covering the fundamentals of building AI agents.
https://www.ibm.com/think/ai-agents
Your one-stop resource for gaining in-depth knowledge and hands-on applications of AI agents.
Stable Diffusion+
https://course.fast.ai/Lessons/lesson9.html
This lesson starts with a tutorial on how to use pipelines in the Diffusers library to generate images.
https://www.youtube.com/watch?v=dMkiOex_cKU
earn how to use Stable Diffusion to create art and images in this full course.
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