Kalman filtering based dynamic OD matrix estimation and prediction for traffic systems

被引：0

作者：

Lin, Y ^{[1
]}

Cai, YL ^{[1
]}

Huang, YX ^{[1
]}

机构：

[1] Xian Jiaotong Univ, Syst Engn Inst, Sch Elect & Informat Engn, Xian 710049, Peoples R China

来源：

2003 IEEE INTELLIGENT TRANSPORTATION SYSTEMS PROCEEDINGS, VOLS. 1 & 2 | 2003年

关键词：

dynamic OD matrix; estimation; Kalman filtering; RLS algorithm;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, a state space model is proposed so that the dynamic OD matrix can be estimated through the surveillance of flows and traveling time on links in a traffic network. To eliminate the influence of slow time-variant parameters, a Recursive Least Square (RLS) algorithm is introduced to identify the system matrix online. Moreover, an analytical formula to calculate the key assignment matrix is presented. With the sequential Kalman Filtering method, the fast and real-time OD estimation and prediction algorithm is established. The algorithm is proven to be very effective and efficient with simulation test.

引用

页码：1515 / 1520

页数：6

共 50 条

[21] Collaborative Kalman Filtering for Dynamic Matrix Factorization
Sun, John Z.
Parthasarathy, Dhruv
Varshney, Kush R.
[J]. IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2014, 62 (14) : 3499 - 3509
[22] Accurate OD Traffic Matrix Estimation Based on Resampling of Observed Flow Data
Kase, Simon
Tsuru, Masato
Uchida, Masato
[J]. 2018 ASIA-PACIFIC SIGNAL AND INFORMATION PROCESSING ASSOCIATION ANNUAL SUMMIT AND CONFERENCE (APSIPA ASC), 2018, : 1574 - 1579
[23] OD-matrix Estimation Based on a Dual Formulation of Traffic Assignment Problem
Krylatov, Alexander Yu.
Shirokolobova, Anastasiia P.
Zakharov, Victor V.
[J]. INFORMATICA-JOURNAL OF COMPUTING AND INFORMATICS, 2016, 40 (04): : 393 - 398
[24] Self-Similar Traffic Prediction Algorithm Based on An Improved Kalman Filtering
Na, Zhenyu
Gao, Zihe
[J]. JOURNAL OF INTERNET TECHNOLOGY, 2011, 12 (03): : 399 - 405
[25] Research of Short-term Traffic Volume Prediction Based on Kalman Filtering
Gong Yi-shan
Zhang Yi
[J]. 2013 6TH INTERNATIONAL CONFERENCE ON INTELLIGENT NETWORKS AND INTELLIGENT SYSTEMS (ICINIS), 2013, : 99 - 102
[26] Dynamic shape estimation using Kalman filtering
Lively, PS
Atalla, MJ
Hagood, NW
[J]. SMART STRUCTURES AND MATERIAL 2000: SMART STRUCTURES AND INTEGRATED SYSTEMS, 2000, 3985 : 521 - 532
[27] Dynamic traffic diversion model based on dynamic traffic demand estimation and prediction
Jiao Peng-peng
Li Yi-gang
Li Dong-yue
[J]. IET INTELLIGENT TRANSPORT SYSTEMS, 2018, 12 (09) : 1123 - 1130
[28] Urban Traffic Dynamic OD Prediction Based on Multi-Source Data
Ye, Qianqian
Li, Zhaoliang
Wu, Junyi
Cheng, Lijing
[J]. CICTP 2022: INTELLIGENT, GREEN, AND CONNECTED TRANSPORTATION, 2022, : 844 - 854
[29] Traffic Matrix Prediction Based on Deep Learning for Dynamic Traffic Engineering
Liu, Zhifeng
Wang, Zhiliang
Yin, Xia
Shi, Xingang
Guo, Yingya
Tian, Ying
[J]. 2019 IEEE SYMPOSIUM ON COMPUTERS AND COMMUNICATIONS (ISCC), 2019, : 219 - 225
[30] State Estimation in Power Distribution Systems Based on Ensemble Kalman Filtering
Carquex, Come
Rosenberg, Catherine
Bhattacharya, Kankar
[J]. IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (06) : 6600 - 6610

← 1 2 3 4 5 →