The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from au...The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from automatic fare collection(AFC) system as the real time observed passenger flow counts. For lacking of measurable passenger flow information, the proposed model employs priori O-D matrices and travel time distribution from historical travel records in AFC system to establish the dynamic system equations. An arriving rate based on travel time distribution is defined to identify the dynamic interrelations between time-varying O-D flows and observed flows, which greatly decreases the computational complexity and improve the model's applicability for large-scale network. This methodology is tested in a real transit network from Beijing subway network in China through comparing the predicted matrices with the true matrices. Case study results indicate that the proposed model is effective and applicative for estimating dynamic O-D matrices for large-scale rail transit network.展开更多
Developing an understanding of the socio-economic factors that can be used to generate truck trip productions and attractions in small and medium sized communities can be used to improve travel models and provide bett...Developing an understanding of the socio-economic factors that can be used to generate truck trip productions and attractions in small and medium sized communities can be used to improve travel models and provide better information upon which infrastructure decisions are made. Unfortunately, it is difficult to collect this data in a timely, cost-effective manner. This paper presents a methodology that uses matrix estimation techniques from existing traffic counts to develop origin/destination pairs that can be used to statistically develop truck trip generation models. A case study is presented and a model is presented for one smaller urban community.展开更多
为提高通勤者使用公交出行的比例,有效缓解城市交通拥堵,对应用智能公交系统数据(Advanced Public Transportation Systems,APTS)获得公交通勤出行需求的方法进行研究.采集APTS数据,通过对公交IC卡数据和智能调度系统数据的关联获得公...为提高通勤者使用公交出行的比例,有效缓解城市交通拥堵,对应用智能公交系统数据(Advanced Public Transportation Systems,APTS)获得公交通勤出行需求的方法进行研究.采集APTS数据,通过对公交IC卡数据和智能调度系统数据的关联获得公交乘客的上车站点信息.根据早、晚高峰的出行频率判断公交通勤乘客,利用通勤出行的时间和空间特征确定居住地点和工作地点.以此基本思路,提出公交卡乘客通勤OD分布估计算法,并应用海量APTS系统数据对算法进行了试验和分析.最后,通过与基于'出行链'的方法进行比较,分析了算法的精度.本文提出的方法具有精度高、可操作性强的优点,为快速、经济地获取公交通勤OD分布提供了一种新的途径.展开更多
基金Project(51478036)supported by the National Natural Science Foundation of ChinaProject(20120009110016)supported by Research Fund for Doctoral Program of Higher EducationChina
文摘The major objective of this work was to establish a structural state-space model to estimate the dynamic origin-destination(O-D) matrices for urban rail transit network, using in- and out-flows at each station from automatic fare collection(AFC) system as the real time observed passenger flow counts. For lacking of measurable passenger flow information, the proposed model employs priori O-D matrices and travel time distribution from historical travel records in AFC system to establish the dynamic system equations. An arriving rate based on travel time distribution is defined to identify the dynamic interrelations between time-varying O-D flows and observed flows, which greatly decreases the computational complexity and improve the model's applicability for large-scale network. This methodology is tested in a real transit network from Beijing subway network in China through comparing the predicted matrices with the true matrices. Case study results indicate that the proposed model is effective and applicative for estimating dynamic O-D matrices for large-scale rail transit network.
文摘Developing an understanding of the socio-economic factors that can be used to generate truck trip productions and attractions in small and medium sized communities can be used to improve travel models and provide better information upon which infrastructure decisions are made. Unfortunately, it is difficult to collect this data in a timely, cost-effective manner. This paper presents a methodology that uses matrix estimation techniques from existing traffic counts to develop origin/destination pairs that can be used to statistically develop truck trip generation models. A case study is presented and a model is presented for one smaller urban community.
文摘为提高通勤者使用公交出行的比例,有效缓解城市交通拥堵,对应用智能公交系统数据(Advanced Public Transportation Systems,APTS)获得公交通勤出行需求的方法进行研究.采集APTS数据,通过对公交IC卡数据和智能调度系统数据的关联获得公交乘客的上车站点信息.根据早、晚高峰的出行频率判断公交通勤乘客,利用通勤出行的时间和空间特征确定居住地点和工作地点.以此基本思路,提出公交卡乘客通勤OD分布估计算法,并应用海量APTS系统数据对算法进行了试验和分析.最后,通过与基于'出行链'的方法进行比较,分析了算法的精度.本文提出的方法具有精度高、可操作性强的优点,为快速、经济地获取公交通勤OD分布提供了一种新的途径.
