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Autonomous Driving Control for ITS by Using Learning Automaton Network with Multiple Environments

机译：基于多环境学习自动机网络的ITs自主驾驶控制

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Kazuaki Shiraishi; Tomoki Hamagami; Seiichi Koakutsu; Hironori Hirata;
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年度 2015
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1. Autonomous Driving Control for ITS by Using Learning Automaton Network with Multiple Environments [J] . KAZUAKI SHIRAISHI, TOMOKI HAMAGAMI, SEIICHI KOAKUTSU, Electrical engineering in Japan . 2005,第4期

机译：利用多环境学习自动机网络实现ITS的自动驾驶控制
2. Deep Learning Model Predictive Control for Autonomous Driving in Unknown Environments [J] . Fatemeh Mohseni, Sergii Voronov, Erik Frisk IFAC PapersOnLine . 2018,第22期

机译：未知环境中自主驾驶的深度学习模型预测控制
3. The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing [J] . Baer Andreas, Loehdefink Jonas, Kapoor Nikhil, IEEE Signal Processing Magazine . 2021,第1期

机译：语义分割网络对自主驾驶中的对抗攻击的脆弱性：增强广泛的环境传感
4. Deep Learning Model Predictive Control for Autonomous Driving in Unknown Environments [C] . Fatemeh Mohseni, Sergii Voronov, Erik Frisk IFAC Symposium on Robot Control . 2019

机译：未知环境中自主驾驶的深度学习模型预测控制
5. A learning automaton approach to trajectory learning and control system design using dynamic recurrent neural networks. [D] . Condarcure, Thomas A. 1993

机译：一种使用动态递归神经网络进行轨迹学习和控制系统设计的学习自动机方法。
6. Time-Sensitive Network (TSN) Experiment in Sensor-Based Integrated Environment for Autonomous Driving [O] . Juho Lee, Sungkwon Park 2019

机译：基于传感器的自动驾驶集成环境中的时敏网络（TSN）实验
7. A learning automaton approach to trajectory learning and control system design using dynamic recurrent neural networks [O] . Condarcure Thomas A. 1952- 1993

机译：动态递归神经网络的学习自动机轨迹学习与控制系统设计

Autonomous Driving Control for ITS by Using Learning Automaton Network with Multiple Environments

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