一种数据驱动的上坡行人双足步态与社会力耦合仿真方法
By constructing a bipedal social force coupling model and calibrating key parameters, the problems of insufficient slope adaptability and parameter reliability in existing uphill pedestrian simulation models are solved, achieving high-precision simulation of uphill pedestrian movement and supporting safety assessment and facility design.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SICHUAN UNIV
- Filing Date
- 2025-12-24
- Publication Date
- 2026-07-17
AI Technical Summary
Existing technologies cannot accurately simulate the gait changes and social force effects of pedestrians when going uphill, resulting in insufficient slope adaptability and parameter reliability of simulation models, and thus failing to effectively assess pedestrian safety risks in uphill scenarios.
By collecting gait dynamics data of pedestrians under different uphill slopes, a bipedal social force coupling model is constructed. Combined with optimization algorithms to calibrate key parameters, a high-precision simulation of pedestrian movement is achieved, including the dynamic generation of center of mass movement and bipedal alternation mechanism and the calculation of social forces.
It achieves high-precision simulation of pedestrian movement uphill, improves biomechanical realism and slope adaptability, provides a reliable engineering application basis, and supports ramp facility design and pedestrian safety assessment.
Smart Images
Figure CN121997552B_ABST