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Lane Detection

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Autonomous driving algorithms and Its IC Design

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Abstract

With the development of high-speed computing devices and advanced machine learning theories such as deep learning, end-to-end detection algorithms can be used to solve the problem of lane detection in a more efficient way. However, the key challenge for lane detection systems is to adapt to the demands of high reliability and diverse road conditions. An efficient way to construct a robust and accurate advanced lane detection system is to fuse multimodal sensors and integrate the lane detection system with other object detection systems. In this chapter, we briefly review traditional computer vision solutions and mainly focus on deep learning-based solutions for lane detection. Additionally, we also present a one-lane detection evaluation system, including offline and online systems. Finally, we use one lane detection algorithm and code to show how lane detection works in an autonomous driving system.

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Authors and Affiliations

  1. Google, San Diego, CA, USA

    Jianfeng Ren

  2. Vision Weiye Intelligent Technology Co., Ltd., Changsha, Hunan, China

    Dong **a

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Ren, J., **a, D. (2023). Lane Detection. In: Autonomous driving algorithms and Its IC Design. Springer, Singapore. https://doi.org/10.1007/978-981-99-2897-2_3

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