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Crowd safety risk assessment based on Seq2Seq-attention network
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Shuchao CAO1, Weibin GE1, Conghui LI1, Jun ZHANG2
China Safety Science Journal | 2025, 35(12) : 196 - 203
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China Safety Science Journal | 2025, 35(12): 196-203
Public safety
Crowd safety risk assessment based on Seq2Seq-attention network
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Shuchao CAO1, Weibin GE1, Conghui LI1, Jun ZHANG2
Affiliations
  • 1School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang Jiangsu 212013, China
  • 2State Key Laboratory of Fire Science, University of Science and Technology of China, Heifei Anhui 230027, China
Published: 2025-12-28 doi: 10.16265/j.cnki.issn1003-3033.2025.12.1477
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In order to explore the safety of interactions between pedestrian groups moving in different directions, a risk assessment method for pedestrian safety was proposed based on a Seq2Seq network integrated with an AM. By analyzing the interactions among pedestrians, local density was introduced as an additional input feature to better characterize dynamic interpersonal behaviors. The observed sequential features of pedestrians within a continuous time window were fed into an LSTM-based encoder-decoder architecture, and AM was employed to capture multidimensional critical information during motion, enabling the reconstruction of complex crowd movement patterns across various scenarios. Furthermore, pedestrian safety risks were quantified by introducing a crowd pressure metric, and the pressure value ranges corresponding to three typical movement states were calculated to enable risk stratification. The results show that the average displacement error (ADE) and final displacement error (FDE) in trajectory prediction are less than 0.3 m under both unidirectional and bidirectional flow conditions at different densities, indicating the model's high accuracy in trajectory prediction. Based on the risk variation observed in bidirectional flow scenarios, it is found that the probability of accidents increases significantly when pedestrians' velocities change abruptly under high-density conditions. Therefore, timely warnings of crowd states and proactive intervention measures are required to mitigate potential safety risks.

sequence to sequence (Seq2Seq)  /  crowd safety  /  risk assessment  /  trajectory prediction  /  attention mechanism(AM)  /  crowd pressure
Shuchao CAO, Weibin GE, Conghui LI, Jun ZHANG. Crowd safety risk assessment based on Seq2Seq-attention network[J]. China Safety Science Journal, 2025 , 35 (12) : 196 -203 . DOI: 10.16265/j.cnki.issn1003-3033.2025.12.1477
Year 2025 volume 35 Issue 12
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Article Info
doi: 10.16265/j.cnki.issn1003-3033.2025.12.1477
  • Receive Date:2025-07-17
  • Online Date:2026-07-09
  • Published:2025-12-28
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  • Received:2025-07-17
  • Revised:2025-09-25
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Affiliations
    1School of Automotive and Traffic Engineering, Jiangsu University, Zhenjiang Jiangsu 212013, China
    2State Key Laboratory of Fire Science, University of Science and Technology of China, Heifei Anhui 230027, China
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小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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