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Lane Boundary Detection Algorithm Based on Vector Fuzzy Connectedness

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Abstract

In most actual autonomous guided vehicles (AGV), path finding and navigational control systems are usually implemented using images captured by cameras mounted on the vehicles. This paper presents and discusses a lane boundary detection technique that is necessary for the task of autonomous driving. In this paper, a new method called vector fuzzy connectedness (VFC) is presented to detect and estimate road lane boundaries. First, a preprocessed technique is used to obtain a skeleton image. Based on the result, the curvatures of the left and right lane boundaries are estimated, and the control points are found by the VFC method. Finally, the non-uniform b-spline (NUBS) interpolation method is introduced to construct the road lane boundaries. The proposed VFC method integrates the vector concept and fuzzy connectedness into the lane boundary detection algorithm. As shown in the example results, the proposed method can extract various road lane shapes and types from real road frames even under complex road environments. For navigation tasks, it is necessary to determine the position of the vehicle relative to the road. These results prove that the proposed detection method can assist in a number of actual AGV assistant applications. In the future, some intelligent techniques will be applied to test the AGV system with obstacle avoidance conditions on real world roads.

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Authors and Affiliations

  1. Department of Computer and Information Technology, Liaoning Normal University, Dalian City, Liaoning Province, 116029, China

    Lingling Fang & Xianghai Wang

  2. College of Information and Communication Engineering, Dalian University of Technology, Dalian City, Liaoning Province, 116024, China

    Lingling Fang

Authors
  1. Lingling Fang
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  2. Xianghai Wang
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Correspondence to Lingling Fang.

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Funding

This study was funded by the Education Department of Liaoning Province (grant number L2014423), and the Natural Science Foundation of China (grant number 41671439, 61402214).

Ethical Approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Conflict of Interest

The authors declare that they have no conflict of interest.

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Fang, L., Wang, X. Lane Boundary Detection Algorithm Based on Vector Fuzzy Connectedness. Cogn Comput 9, 634–645 (2017). https://doi.org/10.1007/s12559-017-9483-3

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  • DOI: https://doi.org/10.1007/s12559-017-9483-3

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