Computational Framework for Verifiable Decisions of Self-Driving Vehicles

Computational Framework for Verifiable Decisions of Self-Driving Vehicles
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自动驾驶车辆可验证决策的计算框架

DOI:
10.1109/ccta.2018.8511432
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发表时间:
2018
期刊:
2018 IEEE Conference on Control Technology and Applications (CCTA)
影响因子:
--
通讯作者:
S. Veres
S. Veres
中科院分区:
--
文献类型:
--
作者:
Mohammed Al;Hongyang Qu;S. Veres

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提出了一个框架,通过检查代理的不稳定性和不一致性的逻辑,在自动驾驶应用程序的代理的决策验证。该框架验证了在自然语言编程(NLP)中实现的理性代理的决策,并基于使用sEnglish和Jason代码的信念-愿望-意图(BDI)范式。主要结果是验证方法的正确性实时代理决策表示在计算树逻辑(CTL)公式。该方法依赖于多智能体系统(MCMAS)的模型验证工具。为了测试新的验证系统,自主车辆(AV)已建模和仿真,这是能够规划,导航,物体检测和避障使用理性代理。智能体的决策基于从单摄像机和LiDAR传感器接收的信息,这些信息输入AV的基于逻辑的决策。AV及其环境的模型已在机器人操作系统(ROS)和凉亭虚拟现实模拟器中实现。
A framework is presented for the verification of an agent's decision making in autonomous driving applications by checking the logic of the agent for instability and inconsistency. The framework verifies the decisions of a rational agent implemented in Natural Language Programming (NLP) and based on a belief-desire-intention (BDI) paradigm using sEnglish and Jason code. The main results are methods of verification for the correctness of real-time agent decisions expressed in computational tree logic (CTL) formulae. The methods rely on the Model Checker for Multi-Agent Systems (MCMAS) verification tool. To test the new verification system, an autonomous vehicle (AV) has been modelled and simulated, which is capable of planning, navigation, objects detection and obstacle avoidance using a rational agent. The agent's decisions are based on information received from mono-cameras and LiDAR sensor that feed into logic-based decisions of the AV. The model of the AV and its environment has been implemented in the Robot Operating System (ROS) and the Gazebo virtual reality simulator.
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