Autonomous driving paper index
A Study on Autonomous Driving Simulation Using a Deep Learning Process Model
One-line summary
Along with artificial intelligence technologies, deep learning technology, which has recently received a great deal of attention, has been studied on the basis of developed artificial neural networks.
Engineering notes
Key topics: autonomous driving system, autonomous driving, lidar, carla, prediction, control. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Along with artificial intelligence technologies, deep learning technology, which has recently received a great deal of attention, has been studied on the basis of developed artificial neural networks. This thesis deals with the detection, recognition, judgment, and control that are included in the basic technologies of the autonomous driving subsystems to achieve fully autonomous driving. And this work solves many problems in this area. The use of the CARLA simulation in this project is the development of a deep learning intelligent autonomous driving system in the road environment. Autonomous driving recognizes the situation by processing the data collected through images from multiple sensors or lidars and cameras in real-time. In the cloud server process using real data, explore various deep learning models for traffic flow prediction, return the model trained onboard, perform the prediction and solve the problem of fully autonomous driving, including a module of control, which is a CARLA simulation.
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