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Open AccessArticle

A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information

School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China
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Sensors 2021, 21(3), 708; https://doi.org/10.3390/s21030708
Received: 30 November 2020 / Revised: 15 January 2021 / Accepted: 18 January 2021 / Published: 21 January 2021
(This article belongs to the Section Intelligent Sensors)
The quality of detected lane lines has a great influence on the driving decisions of unmanned vehicles. However, during the process of unmanned vehicle driving, the changes in the driving scene cause much trouble for lane detection algorithms. The unclear and occluded lane lines cannot be clearly detected by most existing lane detection models in many complex driving scenes, such as crowded scene, poor light condition, etc. In view of this, we propose a robust lane detection model using vertical spatial features and contextual driving information in complex driving scenes. The more effective use of contextual information and vertical spatial features enables the proposed model more robust detect unclear and occluded lane lines by two designed blocks: feature merging block and information exchange block. The feature merging block can provide increased contextual information to pass to the subsequent network, which enables the network to learn more feature details to help detect unclear lane lines. The information exchange block is a novel block that combines the advantages of spatial convolution and dilated convolution to enhance the process of information transfer between pixels. The addition of spatial information allows the network to better detect occluded lane lines. Experimental results show that our proposed model can detect lane lines more robustly and precisely than state-of-the-art models in a variety of complex driving scenarios. View Full-Text
Keywords: lane detection; vertical spatial features; contextual information; complex driving scenes lane detection; vertical spatial features; contextual information; complex driving scenes
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MDPI and ACS Style

Liu, W.; Yan, F.; Zhang, J.; Deng, T. A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information. Sensors 2021, 21, 708. https://doi.org/10.3390/s21030708

AMA Style

Liu W, Yan F, Zhang J, Deng T. A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information. Sensors. 2021; 21(3):708. https://doi.org/10.3390/s21030708

Chicago/Turabian Style

Liu, Wenbo; Yan, Fei; Zhang, Jiyong; Deng, Tao. 2021. "A Robust Lane Detection Model Using Vertical Spatial Features and Contextual Driving Information" Sensors 21, no. 3: 708. https://doi.org/10.3390/s21030708

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