Unreasonable path planning will make the vehicle prone to traffic accidents when driving at a limited maximum speed in the case of the low-speed situation and large curvature curve conditions. Considering the defects of neural network model based on the data-driven may cause unexpected results, an improved driver model was proposed to enhance driving safety. In this paper, the Dempster/Shafer evidence theory was used to detect critical features of lane lines for situation detection. And an observer was established to observe and analyze the model output based on the vehicle space motion safety and driving stability characteristics. Then, an optimizer was established to optimize the output and provide the optimal driving trajectory according to the analyzed situations. Finally, it is verified that the proposed algorithm can help the vehicle safely pass the ample curvature curves by the simulation platform and real vehicle in the laboratory.
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