A perception centred self-driving system without HD Maps
This paper proposes a new self-driving system to solve the localization and lines detection problem with the scalability under consideration. The proposed system is HD Map unrelated. All path planning is based on a rebuilt scene based on a topological map, and the traffic lines detection result from our detection subsystem. The proposed lines detection subsystem achieves a state of the art performance without using deep learning. The proposed localization subsystem relies on neither GPS nor IMU and provide a human level localization result by counting the stop lines and intersections. The system was tested on diverse datasets covering complicated urban situations. It is proved to be robust and easy to implement on a large scale.
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