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浙江大学学报(工学版)
浙江大学学报(工学版)  2026, Vol. 60 Issue (3): 513-526    DOI: 10.3785/j.issn.1008-973X.2026.03.007
计算机技术、控制工程     
自动驾驶综合仿真平台的现状与展望
吕君陶1(),祁珏瑜1,于淏辰1,马雷2,马惠敏1,胡天宇1,*()
1. 北京科技大学 计算机与通信工程学院，北京 100083
2. 北京大学 未来技术学院，北京 100080
Current status and future prospect of integrated simulation platform for autonomous driving
Juntao LV1(),Jueyu QI1,Haochen YU1,Lei MA2,Huimin MA1,Tianyu HU1,*()
1. School of Computer and Communication Engineering, University of Science and Technology Beijing, Beijing 100083, China
2. College of Future Technology, Peking University, Beijing 100080, China
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摘要：

自动驾驶仿真平台在自动驾驶系统的研发、测试与验证过程中发挥着至关重要的作用. 系统综述了当前主流自动驾驶仿真平台的分类与关键技术路径, 包括环境建模、传感器模拟、车辆动力学建模、感知算法测试、V2X通信、云仿真等方面, 重点分析合成数据生成、低成本算法训练、跨域迁移能力、平台可扩展性等核心挑战与研究进展, 分析具体的基于计算机视觉和人工智能的自动驾驶仿真技术，展望了该技术的发展趋势. 随着生成式AI、神经渲染、多模态学习等新兴技术的发展, 仿真平台正向高真实感、可交互、闭环式验证方向演进, 逐步形成数据生成、算法训练、性能评估的全流程闭环. 未来, 仿真平台将在提升自动驾驶系统的泛化能力、加速产品部署进程以及构建标准化测试验证体系等方面持续发挥支撑作用.
关键词： 自动驾驶;  计算机视觉;  算法测试;  数据生成    
Abstract:

Autonomous driving simulation platforms play a vital role in the development, testing and validation of autonomous driving systems. A systematic review of the classification and key technical pathways of mainstream simulation platforms was presented, covering aspects such as environment modeling, sensor simulation, vehicle dynamics modeling, perception algorithm evaluation, V2X communication and cloud-based simulation. Core challenges and research progress related to synthetic data generation, cost-effective algorithm training, cross-domain generalization and platform scalability were analyzed, emphasizing simulation technologies based on computer vision and artificial intelligence. Future development trends were discussed. Simulation platforms are evolving toward higher realism, interactivity and closed-loop validation with the advancement of emerging technologies such as generative AI, neural rendering and multimodal learning, gradually forming a comprehensive pipeline that integrates data generation, algorithm training and performance evaluation. Simulation platforms will continue to play an essential role in enhancing the generalization capability of autonomous driving system, accelerating product deployment, and establishing standard testing and validation framework in the future.
Key words: autonomous driving    computer vision    algorithm testing    data generation
收稿日期: 2025-07-14 出版日期: 2026-02-04
:  TP 393  
基金资助: 国家自然科学基金资助项目(62172036); 科技创新2030-“新一代人工智能”重大资助项目(2022ZD0116305).
通讯作者: 胡天宇     E-mail: 17721026029@163.com;tianyu@ustb.edu.cn
作者简介: 吕君陶（2002—），男，硕士生，从事计算机视觉和大语言模型的研究. orcid.org/0009-0006-3374-047X.E-mail：17721026029@163.com
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引用本文:

吕君陶,祁珏瑜,于淏辰,马雷,马惠敏,胡天宇. 自动驾驶综合仿真平台的现状与展望[J]. 浙江大学学报(工学版), 2026, 60(3): 513-526.

Juntao LV,Jueyu QI,Haochen YU,Lei MA,Huimin MA,Tianyu HU. Current status and future prospect of integrated simulation platform for autonomous driving. Journal of ZheJiang University (Engineering Science), 2026, 60(3): 513-526.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2026.03.007    或    https://www.zjujournals.com/eng/CN/Y2026/V60/I3/513

图 1  生成模型及AIGC的发展历程
图 2  仿真平台与ADS任务中各组件的关系
图 3  自动驾驶仿真平台的基本流程
图 4  Carla-Apollo Bridge软件界面[55]
图 5  现有自动驾驶仿真平台与技术之间的关系
平台开源状况建模技术接口特点
CarSim闭源VehicleSim SolversMATLAB, Simulink, Python, C++支持多种车型的建模, 扩展性和兼容性强, 于1996年发布
Carmaker闭源UnigineMATLAB, Simulink, Python, C++支持 27自由度多体动力学模型及多种极端情况模拟, 于1999年发布, 目前已更新至14.0
Prescan闭源Unreal EngineMATLAB, Simulink支持与多方第三款软件集成, 精准呈现驾驶员的操控, 2002年由TASS发布, 后被Siemens收购, 持续更新中
VI-Grade闭源Unreal EngineMATLAB, Simulink提供从静态桌面解决方案到全尺寸动态模拟器的多种配置, 支持模块化组装和快速原型开发, 发布于2005年, 近期推出了云功能
CARLA开源Unreal EngineROS, Python, ApolloClient-Server架构, 支持多种传感器仿真, 发布于2017年, 持续更新中
Airsim开源Unreal Engine
/Unity		Python, C++, ROS, Simulink, Apollo能实时处理深度、实例分割, 支持软件在环仿真, 适用于多个下游任务, 发布于2017年, 但已停止更新
DeepDrive开源Unreal EngineROS, Python环境交互灵活, 集成深度学习框架, 发布于2018年, 已停止更新
TAD Sim开源Unreal EngineROS, Python高真实度场景仿真, 高精度车辆动力学模型, 高效的测试工具, 支持云仿真, 发布于2018年
Panosim闭源UnityMATLAB, Simulink高精度建模, 一体化仿真工具链, 2019年发布正式版本5.0
LGSVL开源UnityROS, Apollo, Autoware, Python, C++支持多种传感器仿真、多种高精度地图格式、V2X通信仿真, 发布于2019年, 2022年已停止更新
MetaDrive开源Panda3DPython轻量化, 提供精确的物理模拟, 支持多种传感器仿真, 2021年发布
DriveSim闭源OmniverseROS, Python, C++结合RTX技术和可微渲染, 支持多种传感器仿真, 发布于2021年
SimOne闭源SimOne-
Bus/Car/Truck		ROS, Simulink, Python, C++全链闭环仿真, 支持多种常用数据接口, 发布于2021年
表 1  现有自动驾驶仿真平台的比较
图 6  AirSim的仿真界面
图 7  Carla仿真平台的用户界面
图 8  LGSVL的控制界面
图 9  Prescan场景仿真
图 10  SimOne自动驾驶仿真平台UI
图 11  用于训练感知算法的DriveSim
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