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
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
随着高清摄像设备在城市交通领域的普及,交通卡口采集的过车信息呈现爆发式增长态势。这些海量数据为构建交通起讫点(Origin Destination,OD)矩阵提供了丰富的基础资源。然而,面对庞大的数据体量,传统的串行计算模式存在处理速度慢、响...随着高清摄像设备在城市交通领域的普及,交通卡口采集的过车信息呈现爆发式增长态势。这些海量数据为构建交通起讫点(Origin Destination,OD)矩阵提供了丰富的基础资源。然而,面对庞大的数据体量,传统的串行计算模式存在处理速度慢、响应时间长等问题,难以适应实时分析的业务要求。针对这一瓶颈,文章设计了基于Spark平台的交通OD矩阵计算(Spark-based Calculation of Traffic OD Matrix,Spark-CoTODM)方法,该方法利用Spark平台的分布式并行计算能力,对OD矩阵生成过程进行并行化改造,从而大幅缩短运算周期。测试结果表明,当处理大规模数据集时,所提方法的执行效率得到明显改善。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.
文摘随着高清摄像设备在城市交通领域的普及,交通卡口采集的过车信息呈现爆发式增长态势。这些海量数据为构建交通起讫点(Origin Destination,OD)矩阵提供了丰富的基础资源。然而,面对庞大的数据体量,传统的串行计算模式存在处理速度慢、响应时间长等问题,难以适应实时分析的业务要求。针对这一瓶颈,文章设计了基于Spark平台的交通OD矩阵计算(Spark-based Calculation of Traffic OD Matrix,Spark-CoTODM)方法,该方法利用Spark平台的分布式并行计算能力,对OD矩阵生成过程进行并行化改造,从而大幅缩短运算周期。测试结果表明,当处理大规模数据集时,所提方法的执行效率得到明显改善。
