Mechanical Sciences
Mechanical Sciences
Mechanical Sciences
Articles | Volume 15, issue 1
Articles | Volume 15, issue 1
https://doi.org/10.5194/ms-15-17-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/ms-15-17-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 15, issue 1
Research article
 | 
18 Jan 2024
Research article |  | 18 Jan 2024

Development of pedestrian collision avoidance strategy based on the fusion of Markov and social force models

Bin Tang, Zhengyi Yang, Haobin Jiang, and Zitian Hu

Viewed

Total article views: 708 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
576 107 25 708 22 20
  • HTML: 576
  • PDF: 107
  • XML: 25
  • Total: 708
  • BibTeX: 22
  • EndNote: 20
Views and downloads (calculated since 18 Jan 2024)
Cumulative views and downloads (calculated since 18 Jan 2024)

Viewed (geographical distribution)

Total article views: 669 (including HTML, PDF, and XML) Thereof 669 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 15 Nov 2024
Download
Short summary
A pedestrian motion fusion model is constructed to predict pedestrian trajectory by the fusion of a Markov model and an improved social force model with a multiple linear regression algorithm. The parameters in the model are calibrated by the maximum likelihood estimation method. Based on pedestrian trajectory prediction, a longitudinal and lateral collision avoidance control strategy is developed. The results show that the proposed strategy can effectively ensure the safety of pedestrians.
Read more