Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Network Optimization Based Lane Line Classification Study

Version 1 : Received: 18 September 2021 / Approved: 22 September 2021 / Online: 22 September 2021 (15:20:30 CEST)

How to cite: Wang, H.; Deng, P.; Sun, S.; Tian, G.; Li, S.; Luo, N.; Kong, C.; Zhong, J.; Peng, Y.; Liu, J. Network Optimization Based Lane Line Classification Study. Preprints 2021, 2021090387 (doi: 10.20944/preprints202109.0387.v1). Wang, H.; Deng, P.; Sun, S.; Tian, G.; Li, S.; Luo, N.; Kong, C.; Zhong, J.; Peng, Y.; Liu, J. Network Optimization Based Lane Line Classification Study. Preprints 2021, 2021090387 (doi: 10.20944/preprints202109.0387.v1).

Abstract

Efficient quality evaluation provides support for the timely and good maintenance of the lane line marking. This paper searches and optimizes the back propagation(BP) network model which referred to the analytic hierarchy process(AHP) model structure, as well as the number of nodes in the middle layer network. Based on this, a comprehensive evaluation method of multi-dimensional lane line quality such as shape, color and contrast is established. The experimental results show that the parameters of the model are more simplified, and the scoring and classification results of lane lines are more accurate.

Keywords

lane line; comprehensive evaluation; BP; parameter search; maintenance

Subject

ENGINEERING, Control & Systems Engineering

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