In this paper, the concept of the Shortest-Route Traffic Matrix(SRTM) was first presented, and the generalized formula for computing ring capacity requirement in use of SRTM is given. Then, a new capacity design algor...In this paper, the concept of the Shortest-Route Traffic Matrix(SRTM) was first presented, and the generalized formula for computing ring capacity requirement in use of SRTM is given. Then, a new capacity design algorithm which is based on SRTM was presented for Synchronous Digital Hierarchical(SDH) Bi-directional Self-Healing Ring (BSHR). The algorithm simulation results demonstrate that this algorithm is very efficient for SDH BSHR capacity design and can make less project investment and make high utilization of lines and equipment. By means of the algorithm in this paper, capacity optimization assignment for SDH Hierarchical Self-Healing Ring (HSHR) and for ATM Virtual Path (VP)-based Self-Healing Ring (SHR) is also discussed.展开更多
Currently, there are kinds of algorithms in order to detect real-time urban traffic condition. Most of these approaches consider speed of vehicles as a main metric to describe traffic situation. In this paper, we find...Currently, there are kinds of algorithms in order to detect real-time urban traffic condition. Most of these approaches consider speed of vehicles as a main metric to describe traffic situation. In this paper, we find out two important observations through several experiments. (1) In urban city, the speed of vehicles is influenced significantly by some factors such as traffic lights delay and road condition. The actual situation rarely satisfy hypothesis required for these solutions. Therefore, these traditional algorithms do not work well in practical environment. (2) Traffic volume on a road segment shows strong pattern and changes smoothly at adjacent time. This feature of traffic volume inspires us to define a metric: traffic-rate, which is used to detect traffic condition in real time. In our solution, we develop a novel traffic-detection algorithm based on original- destination (OD) matrix. We illustrate our approach and measure its performance in real environment. The performance evaluations confirm the effectiveness of our algorithm.展开更多
轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成...轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成乘客特征—时序(FeatureTemporal,F-T)矩阵;通过改进的欧氏距离计算F-T矩阵间的相似性,实现F-T矩阵的相似性度量;提出一种基于相似度矩阵的K-Means聚类和层次聚类相结合的两步聚类方法(Two-step Clustering of K-Means Clustering and Hierarchical Clustering,KMHC)划分乘客影响群体,分析影响乘客出行转移的因素;以新冠肺炎疫情期间上海轨道交通11号线昆山段停运作为实例,对本文方法进行验证。研究结果表明:昆山段停运后,常乘客呈现出5种主要的出行转移影响群体,占常乘客总数的94.4%;各影响群体的转移距离、通勤时间和出行频率差异明显,是影响区段停运后常乘客出行选择的重要因素。本文方法可为其他计划性停运场景提供借鉴和参考,也可为区段停运后的网络客流变化预测,行车和客运组织方案优化提供支撑。展开更多
针对目标检测算法在交通标志检测中存在的不足,文中提出了一种融合感受野增强模块和注意力机制的交通标志检测算法。该算法在YOLOv5(You Only Look Once version 5)算法的基础上改进,选用感受野模块(Receptive Field Block,RFB)替换原...针对目标检测算法在交通标志检测中存在的不足,文中提出了一种融合感受野增强模块和注意力机制的交通标志检测算法。该算法在YOLOv5(You Only Look Once version 5)算法的基础上改进,选用感受野模块(Receptive Field Block,RFB)替换原骨干网络中的空间金字塔池化(Spatial Pyramid Pooling,SPP)模块,在特征融合网络中嵌入高效通道注意模块(Efficient Channel Attention Module,ECAM)和卷积块注意模块(Convolutional Block Attention Module,CBAM),选用矩阵非极大值抑制(Matrix Non-Maximum Suppression,Matrix NMS)筛选候选框以提升算法的检测精度和检测速度。实验结果表明,在模型参数量与原网络相比未变化的前提下,该算法的均值平均精度达到了82.31%,与原算法相比提升了8.59%,检测速度达到了51.89 frame·s^(-1),且该算法在各个测试场景中未出现错检漏检现象,证明其泛化能力优于原算法,可以实时检测交通标志。展开更多
this paper develops a real-time traffic signal timing model which is to be integrated into a single intersection for urban road, thereby solving the problem of traffic congestion. We analyze the current situation of t...this paper develops a real-time traffic signal timing model which is to be integrated into a single intersection for urban road, thereby solving the problem of traffic congestion. We analyze the current situation of the traffic flow with release matrix firstly, and then put forward the basic models to minimize total delay time of vehicles at the intersection. The optimal real-time signal timing model (non-fixed cycle and non-fixed split) is built with the Webster split optimal model. At last, the simulated results, which are compared with conventional model, manifest the promising properties of proposed model.展开更多
对实时车辆流量、平均车道占用率等各种交通监控数据的完整获取,是建设智能交通系统、提高交通管理运行效率的重要基础。文章提出一种融合类信息的函数型矩阵填充方法(Functional Matrix Completion Method with Class Information,CFMC...对实时车辆流量、平均车道占用率等各种交通监控数据的完整获取,是建设智能交通系统、提高交通管理运行效率的重要基础。文章提出一种融合类信息的函数型矩阵填充方法(Functional Matrix Completion Method with Class Information,CFMC)。在函数型数据分析框架下,基于非负矩阵分解构造函数型矩阵填充模型,在此基础上通过聚类划分引入样本类信息,借助类内样本相关性插补缺失值,并采用自加权集成学习算法动态赋权计算得到最终插补值。在公共交通数据集PeMS上进行插补实验,结果表明:当缺失率为15%~70%时,CFMC方法相较于K近邻算法、MICE、PACE等10种插补方法,均方根误差(RMSE)、平均绝对误差(MAE)和平均绝对百分比误差(MAPE)分别降低了10.75%~81.69%、0.34%~84.48%和12.5%~81.08%,且耗时可控。所提CFMC方法插补精度高、鲁棒性好,能够保证插补的有效性和准确性。展开更多
基金Supported by Key Project for the Ninth Five-Years Programming of Ministry of Posts and Telecommunications of China
文摘In this paper, the concept of the Shortest-Route Traffic Matrix(SRTM) was first presented, and the generalized formula for computing ring capacity requirement in use of SRTM is given. Then, a new capacity design algorithm which is based on SRTM was presented for Synchronous Digital Hierarchical(SDH) Bi-directional Self-Healing Ring (BSHR). The algorithm simulation results demonstrate that this algorithm is very efficient for SDH BSHR capacity design and can make less project investment and make high utilization of lines and equipment. By means of the algorithm in this paper, capacity optimization assignment for SDH Hierarchical Self-Healing Ring (HSHR) and for ATM Virtual Path (VP)-based Self-Healing Ring (SHR) is also discussed.
文摘Currently, there are kinds of algorithms in order to detect real-time urban traffic condition. Most of these approaches consider speed of vehicles as a main metric to describe traffic situation. In this paper, we find out two important observations through several experiments. (1) In urban city, the speed of vehicles is influenced significantly by some factors such as traffic lights delay and road condition. The actual situation rarely satisfy hypothesis required for these solutions. Therefore, these traditional algorithms do not work well in practical environment. (2) Traffic volume on a road segment shows strong pattern and changes smoothly at adjacent time. This feature of traffic volume inspires us to define a metric: traffic-rate, which is used to detect traffic condition in real time. In our solution, we develop a novel traffic-detection algorithm based on original- destination (OD) matrix. We illustrate our approach and measure its performance in real environment. The performance evaluations confirm the effectiveness of our algorithm.
文摘轨道交通网络中乘客的出行受网络结构和运营状况变化的影响,个体出行偏好对这些变化的响应也各异。为分析轨道交通远郊区段计划性停运对常乘客的出行转移影响,本文提出考虑转移类型和转移比例的乘客出行特征刻画方法,结合时段属性生成乘客特征—时序(FeatureTemporal,F-T)矩阵;通过改进的欧氏距离计算F-T矩阵间的相似性,实现F-T矩阵的相似性度量;提出一种基于相似度矩阵的K-Means聚类和层次聚类相结合的两步聚类方法(Two-step Clustering of K-Means Clustering and Hierarchical Clustering,KMHC)划分乘客影响群体,分析影响乘客出行转移的因素;以新冠肺炎疫情期间上海轨道交通11号线昆山段停运作为实例,对本文方法进行验证。研究结果表明:昆山段停运后,常乘客呈现出5种主要的出行转移影响群体,占常乘客总数的94.4%;各影响群体的转移距离、通勤时间和出行频率差异明显,是影响区段停运后常乘客出行选择的重要因素。本文方法可为其他计划性停运场景提供借鉴和参考,也可为区段停运后的网络客流变化预测,行车和客运组织方案优化提供支撑。
文摘针对目标检测算法在交通标志检测中存在的不足,文中提出了一种融合感受野增强模块和注意力机制的交通标志检测算法。该算法在YOLOv5(You Only Look Once version 5)算法的基础上改进,选用感受野模块(Receptive Field Block,RFB)替换原骨干网络中的空间金字塔池化(Spatial Pyramid Pooling,SPP)模块,在特征融合网络中嵌入高效通道注意模块(Efficient Channel Attention Module,ECAM)和卷积块注意模块(Convolutional Block Attention Module,CBAM),选用矩阵非极大值抑制(Matrix Non-Maximum Suppression,Matrix NMS)筛选候选框以提升算法的检测精度和检测速度。实验结果表明,在模型参数量与原网络相比未变化的前提下,该算法的均值平均精度达到了82.31%,与原算法相比提升了8.59%,检测速度达到了51.89 frame·s^(-1),且该算法在各个测试场景中未出现错检漏检现象,证明其泛化能力优于原算法,可以实时检测交通标志。
文摘this paper develops a real-time traffic signal timing model which is to be integrated into a single intersection for urban road, thereby solving the problem of traffic congestion. We analyze the current situation of the traffic flow with release matrix firstly, and then put forward the basic models to minimize total delay time of vehicles at the intersection. The optimal real-time signal timing model (non-fixed cycle and non-fixed split) is built with the Webster split optimal model. At last, the simulated results, which are compared with conventional model, manifest the promising properties of proposed model.
文摘对实时车辆流量、平均车道占用率等各种交通监控数据的完整获取,是建设智能交通系统、提高交通管理运行效率的重要基础。文章提出一种融合类信息的函数型矩阵填充方法(Functional Matrix Completion Method with Class Information,CFMC)。在函数型数据分析框架下,基于非负矩阵分解构造函数型矩阵填充模型,在此基础上通过聚类划分引入样本类信息,借助类内样本相关性插补缺失值,并采用自加权集成学习算法动态赋权计算得到最终插补值。在公共交通数据集PeMS上进行插补实验,结果表明:当缺失率为15%~70%时,CFMC方法相较于K近邻算法、MICE、PACE等10种插补方法,均方根误差(RMSE)、平均绝对误差(MAE)和平均绝对百分比误差(MAPE)分别降低了10.75%~81.69%、0.34%~84.48%和12.5%~81.08%,且耗时可控。所提CFMC方法插补精度高、鲁棒性好,能够保证插补的有效性和准确性。
