摘要
城市智能交通信息系统所产生的原始交通数据中存在有大量的可供城市道路安全管理使用的未知模式信息,为了有效利用这些数据,提出一种针对特定车辆潜在群体的行驶轨迹预测方法(SVPG-TP)。该方法主要利用所提出的特定车辆潜在群体搜索算法及序列模式发现与贝叶斯网络互补预测的方式,有效地解决了目前城市道路安全中最为关注的潜在群体发现以及行驶轨迹预测这两大问题。通过实验测试验证所提出的算法在城市道路安全管理中的有效性及实用性,并实现软件系统,为保障城市道路安全提供可靠的技术手段。
There are a lot of unknown patterns within the large amounts of raw traffic data generated by the urban intelligent traffic information system which can be used in urban road safety management. In order to effectively use these data,this paper proposed a method of prediction on driving track of specific vehicles in potential group（SVPG-TP）. This method leveraged the proposed searching algorithm to potential group of specific vehicles and sequential pattern discovery and Bayesian networks complementary predictable pattern,effectively addressed the two big problems of the most concerned that both the potential group finding and driving track in the current urban road safety,in order to assure that the reliable technological means provided in urban road safety. Finally,the real system built for experimental test verifies the effectiveness and practicality of the proposed algorithm on potential group of specific vehicles traveling trajectory prediction in urban road safety management.
出处
《计算机应用研究》
CSCD
北大核心
2014年第7期1951-1955,共5页
Application Research of Computers
基金
中国科学院先导专项课题(XDA06040100)
关键词
序列模式发现
潜在群体
轨迹预测
贝叶斯网络
sequential pattern mining
potential group
trajectory prediction
Bayesian networks
