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Road Boundaries Detection based on Modified Occupancy Grid Map Using Millimeter-wave Radar

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Abstract

Road region detection is a hot spot research topic in autonomous driving field. It requires to give consideration to accuracy, efficiency as well as prime cost. In that, we choose millimeter-wave (MMW) Radar to fulfill road detection task, and put forward a novel method based on MMW which meets real-time requirement. In this paper, a dynamic and static obstacle distinction step is firstly conducted to estimate the dynamic obstacle interference on boundary detection. Then, we generate an occupancy grid map using modified Bayesian prediction to construct a 2D driving environment model based on static obstacles, while a clustering procedure is carried out to describe dynamic obstacles. Next, a Modified Random Sample Consensus (Modified RANSAC) algorithm is presented to estimate candidate road boundaries from static obstacle maps. Results of our experiments are presented and discussed at the end. Note that, all our experiments in this paper are run in real-time on an experimental UGV (unmanned ground vehicle) platform equipped with Continental ARS 408-21 radar.

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Acknowledgements

This work was supported by the National Key Scientific Instrument and Equipment Development Projects of China (Grant Number: 61727802) and National Natural Science Foundation of China (Grant Number: 61703209, 61773215).

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  1. Nanjing University of Science and Technology, Nanjing, China

    Fenglei Xu, Huan Wang, Bingwen Hu & Mingwu Ren

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  1. Fenglei Xu
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  2. Huan Wang
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  3. Bingwen Hu
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  4. Mingwu Ren
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Correspondence to Mingwu Ren.

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Grant Number: 61727802, 61703209, 61773215

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Xu, F., Wang, H., Hu, B. et al. Road Boundaries Detection based on Modified Occupancy Grid Map Using Millimeter-wave Radar. Mobile Netw Appl 25, 1496–1503 (2020). https://doi.org/10.1007/s11036-019-01378-5

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  • DOI: https://doi.org/10.1007/s11036-019-01378-5

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