Virtual speed sensors based algorithm for expressway traffic state estimation

Science China Technological Sciences

Volumn 55, Issue 5, 2012, Pages 1381-1390

  Xu, Dong Wei ^a   Dong, Hong Hui ^a   Jia, Li Min ^a   Qin, Yong ^a  

^a BEIJING JIAOTONG UNIVERSITY   (China)

Author keywords

Average travel speed; Expressway; Traffic state; Virtual speed sensor

Indexed keywords

DATA MINING; DECISION MAKING; GEOMAGNETISM; SPATIAL DISTRIBUTION; STATE ESTIMATION; TIME SERIES; TRAFFIC CONTROL;

ACCURATE ESTIMATION; AVERAGE TRAVEL SPEED; EXPERIMENT ANALYSIS; EXPRESSWAY; TRAFFIC MANAGERS; TRAFFIC STATE; TRAFFIC STATE ESTIMATION; VIRTUAL SPEED SENSORS;

SPEED;

EID: 84863397281     PISSN: 16747321     EISSN: 18691900     Source Type: Journal    
DOI: 10.1007/s11431-012-4814-9     Document Type: Article

References (15)

1. Nanthawichit C, Nakatsuji T, Suzuki H. Application of probe vehicle data for real-time traffic state estimation and short-term travel time prediction on a freeway. In: 82nd Annual Meeting Preprint CD-ROM. Washington DC: Transport Res Board, 2003. 49-59
2. Wang Y, Papageorgiou M. An adaptive freeway traffic state estimator and its real-data testing-part II: adaptive capabilities. In: Proceedings of the 8th International IEEE Conference on Intelligent Transportation Systems. Vienna, Austria: IEEE, 2005. 537-548
3. Wang Y, Papageorgiou M. Real-time freeway traffic state estimation based on extended kalman filter: a case study. Transport Sci, 2007, 41(2): 167-181
4. Wang Y, Papageorgiou M. Real-time freeway traffic state estimation based on extended kalman filter: A general approach. Transport Res B, 2005, 39(2): 141-167 (Pubitemid 40032216)
5. Xu T D, Tomeh O, Sun L J. Urban expressway real-time traffic state estimation and travel time prediction within ekf framework. In: Transportation and Development Innovative Best Practices. ASCE, 2008. 192-197
6. Pueboobpaphan R, Nakatsuji T. Unscented kalman filter-based real-time traffic state estimation. In: Transportation Research Board 86th Annual Meeting. Washington DC: Transport Res Board, 2007. 128-136
7. Mihaylova L, Boel R. A particle filter for freeway traffic estimation. In: Proc 43rd IEEE Conference on Decision and Control. IEEE, 2004. 2106-2111 (Pubitemid 40291269)
8. Cheng P, Qiu Z, Ran B. Particle filter based traffic state estimation using cell phone network data. In: 2006 IEEE Intelligent Transportation Systems Conference. IEEE, 2006. 1047-1052 (Pubitemid 351492309)
9. Antoniou C, Ben-Akiva M, Koutsopoulos H N. Nonlinear kalman filtering algorithms for on-line calibration of dynamic traffic assignment models. IEEE Trans Intell Transport Syst, 2007, 8(4): 661-670 (Pubitemid 350231643)
10. Sun X, Munoz L, Horowitz R. Mixture kalman filter based highway congestion mode and vehicle density estimator and its application. In: 2004 American Control Conference Proceedings. Boston, Massachusetts: IEEE, 2004. 2098-2103
11. Juan C H, Alexandre M B. Incorporation of lagrangian measurements in freeway traffic state estimation. Transport Res B, 2010, 44: 460-481
12. Zhang X L, Zhang K, Liu H, et al. Urban expressway traffic state estimation based on fcm-rough set. In: Proceedings of the 10th International Conference of Chinese Transportation Professionals. ASCE, 2010. 2159-2168
13. Lendek Z, Babuska R, De Schutter B. Fuzzy models and observers for freeway traffic state tracking. In: Proceedings of the Ninth IEEE International Conference on Fuzzy Systems. Baltimore, Maryland: IEEE, 2010. 2278-2283
14. Wang J J, Xie C F, Chang Z W, et al. The analysis of traffic flow state on foggy expressway based on fuzzy clustering. In: Proceedings of the Ninth International Conference of Chinese Transportation Professionals. ASCE, 2009. 398-404
15. Deng C, Wang F, Shi H M, et al. Real-time freeway traffic state estimation based on cluster analysis and multiclass support vector machine. In: The 1st International Workshop Intelligent Systems and Applications. IEEE, 2009. 1-4