Personalized lane keeping assistance method and device based on deep learning

Abstract

The invention discloses a personalized lane keeping assistance method based on deep learning. The method comprises the steps of acquiring vehicle motion state information and road environment information in the driving process of a driver to serve as parameter representation of a track model; based on the parameters of the deep convolution fuzzy system and the trajectory model, establishing the trajectory model; optimizing the trajectory model, and setting constraint conditions according to driving characteristics of a driver; obtaining real-time vehicle motion state information and real-time road environment information, outputting transverse position information of the driver based on the track model, and controlling the vehicle to track the transverse position. The end-to-end method of deep learning is utilized to learn the driving habit of the driver on the track, personalized lane keeping driving assistance is realized, the acceptability of the driver to a lane keeping system can be improved, man-machine conflicts are reduced, the comfort of the driver is improved, the load of an auxiliary system planning layer is reduced, driving safety is guaranteed, and driving efficiency is further improved.

Description

technical field [0001] The invention belongs to the technical field of driving assistance, and in particular relates to a personalized lane keeping assistance method and device based on deep learning. Background technique [0002] Studies have shown that most of the traffic accidents are caused by the lateral movement of vehicles. The European region has conducted research on the occurrence of traffic accidents and pointed out that if all vehicles are equipped with lane keeping assist systems, traffic accidents will be reduced by about 12%. Therefore, the research on the lane keeping assist system of vehicles will help reduce the occurrence of traffic accidents, and at the same time, it can also promote the development of intelligent vehicles. [0003] In the existing research on the lane keeping assist system, the vehicle is mainly controlled to drive on the centerline of the lane. However, in the actual driving process, the human driver's trajectory does not always keep o...

AI Technical Summary

Problems solved by technology

If smart cars always adopt the uniform design of driving along the centerline of the lane, on the one hand, such driving behavior is very different from the expectations of human drivers, which will inevitably make human drivers feel uncomfortable.

On the other hand, there are other human-driven vehicles and pedestrians in the traffic. If the behavior of the smart car is too different from that of other human drivers, it may also cause discomfort and misjudgment by the drivers of other vehicles, resulting in a dangerous situation. happened

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