A Survey on Visual Traffic Simulation: Models, Evaluations, and Applications in Autonomous Driving,Computer Graphics Forum

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A Survey on Visual Traffic Simulation: Models, Evaluations, and Applications in Autonomous Driving
Computer Graphics Forum ( IF 2.7 ) Pub Date : 2019-07-15 , DOI: 10.1111/cgf.13803
Qianwen Chao _{1,

2} , Huikun Bi _{3,

4,

5} , Weizi Li ₆ , Tianlu Mao ₃ , Zhaoqi Wang ₃ , Ming C. Lin ₇ , Zhigang Deng ₅

Affiliation

Virtualized traffic via various simulation models and real‐world traffic data are promising approaches to reconstruct detailed traffic flows. A variety of applications can benefit from the virtual traffic, including, but not limited to, video games, virtual reality, traffic engineering and autonomous driving. In this survey, we provide a comprehensive review on the state‐of‐the‐art techniques for traffic simulation and animation. We start with a discussion on three classes of traffic simulation models applied at different levels of detail. Then, we introduce various data‐driven animation techniques, including existing data collection methods, and the validation and evaluation of simulated traffic flows. Next, we discuss how traffic simulations can benefit the training and testing of autonomous vehicles. Finally, we discuss the current states of traffic simulation and animation and suggest future research directions.

中文翻译：

视觉交通仿真调查：自动驾驶中的模型、评估和应用

通过各种模拟模型和真实世界交通数据的虚拟交通是重建详细交通流的有前途的方法。各种应用程序都可以从虚拟交通中受益，包括但不限于视频游戏、虚拟现实、交通工程和自动驾驶。在本次调查中，我们对最先进的交通模拟和动画技术进行了全面回顾。我们首先讨论应用于不同细节级别的三类交通仿真模型。然后，我们介绍了各种数据驱动的动画技术，包括现有的数据收集方法，以及模拟交通流的验证和评估。接下来，我们讨论交通模拟如何有利于自动驾驶汽车的训练和测试。最后，

更新日期：2019-07-15

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