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Grey Markov Model Prediction Method for Regular Pedestrian Movement Trend

  • Xiaoyu Fang
  • Xiaobin Li
  • Tianyang Yu
  • Zhen Guo
  • Tao Ma
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 528)

Abstract

This paper focuses on the problem that mobile vehicles easily collide with regular pedestrians in dangerous area, and the gray prediction algorithm is applied to establish the markov model of regular pedestrian data. Predict their walking trajectory according to the regular pedestrian movement trend, and provide active and safe predictive control for vehicle braking in the region. Taking the coke oven coal transportation area as an example, a set of regular pedestrian trajectory data is selected to verify the model and prediction method. The experimental results show that this method can predict this type of pedestrian trajectory. When it is compared with the results of the traditional gray model prediction, the error is smaller and the accuracy is higher.

Keywords

Regular pedestrian Trend of movement Grey Markov model Trajectory prediction 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  • Xiaoyu Fang
    • 1
  • Xiaobin Li
    • 1
  • Tianyang Yu
    • 1
  • Zhen Guo
    • 1
  • Tao Ma
    • 1
  1. 1.School of Electrical and Electronic EngineeringShanghai Institute of TechnologyShanghaiChina

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