智慧交通及认知计算实验室 | ITCCL

智慧客流场景


项目简介

实现包括列车车厢和司机室(列车人工驾驶端)内部的视频监控无死角全覆盖;在清客指令下达之后,对车厢内是否有乘客或其他异常物体滞留实现实时快速检测; 在异常发生时,实时传输现场图像,准确定位异常发生位置,为运营人员及时排除异常提供数据支持。在列车车厢内部实现视频监控无死角全覆盖;采用多摄像头融合技术,实时提取列车车厢中乘客人数级别,判断车厢的拥挤程度;结合出入站客流统计,监测不同地铁线路之间的换乘客流、特定地铁线内实时区间客流,从大数据可视化图像中更直观的呈现客流时空分布特点和地理分布特点;对车厢内部的典型异常事件包括个人摔倒和两人或多人暴力事件进行检测和报警。



项目图集


学术成果
1、L. Bai, C. Wu, Y. Wang, etc., "Overcrowding Detection Based on Crowd-gathering Pattern Model", IntelliSys, September 3 - 4, 2020 2、C. Wang; C. Wu; Y. Wang, etc., "Optimization of Time-frequency Resource Management based on Probabilistic Graphical Models in Railway Internet of Things Networking", IEEE Internet of Things Journal, vol. 8, no. 6, pp. 4778 - 4801, Mar 15, 2021 3、J Sheng, C. Wu*, Y. Wang, etc., "Game Theory-based Multi-objective Optimization Interference Alignment Algorithm for HSR5G Heterogeneous Ultra-Dense Network", IEEE Transactions on Vehicular Technology, Vol. 69, No. 11, pp. 13371 - 13382, Nov. 2020 4、J. Sheng, C. Wu, Y. Wang, etc., "An Improved Interference Alignment Algorithm with User Mobility Prediction for High-Speed Railway Wireless Communication Networks", IEEE Access, Vol. 8, No. 1, pp. 80468 - 80479, December, 2020