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Personalized detection of lane changing behavior using multisensor data fusion

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Abstract

Side swipe accidents occur primarily when drivers attempt an improper lane change, drift out of lane, or the vehicle loses lateral traction. In this paper, a fusion approach is introduced that utilizes multiple differing modality data, such as video data, GPS data, wheel odometry data, potentially IMU data collected from data logging device (DL1 MK3) for detecting driver’s behavior of lane changing by using a novel dimensionality reduction model, collaborative representation optimized projection classifier (CROPC). The criterion of CROPC is maximizing the collaborative representation based between-class scatter and minimizing the collaborative representation based within-class scatter in the transformed space simultaneously. For lane change detection, both feature-level fusion and decision-level fusion are considered. In the feature-level fusion, features generated from multiple differing modality data are merged before classification while in the decision-level fusion, an improved Dempster–Shafer theory based on correlation coefficient, DST-CC is presented to combine the classification outcomes from two classifiers, each corresponding to one kind of the data. The results indicate that the introduced fusion approach using a CROPC performs significantly better in terms of detection accuracy, in comparison to other state-of-the-art classifiers.

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Acknowledgements

This research is supported in part by Research Grants from Toyota Research Institute (TRI).

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Authors and Affiliations

  1. School of Logistics Engineering, Wuhan University of Technology, Wuhan, 430063, China

    Jun Gao & Honghui Zhu

  2. Department of Electrical and Computer Engineering, University of Michigan-Dearborn, Dearborn, MI, 48128, USA

    Jun Gao & Yi Lu Murphey

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  1. Jun Gao
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  2. Yi Lu Murphey
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  3. Honghui Zhu
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Correspondence to Jun Gao.

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Gao, J., Murphey, Y.L. & Zhu, H. Personalized detection of lane changing behavior using multisensor data fusion. Computing 101, 1837–1860 (2019). https://doi.org/10.1007/s00607-019-00712-9

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  • DOI: https://doi.org/10.1007/s00607-019-00712-9

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