Pattern recognition of vehicle types and reliability analysis of pneumatic tube test data under mixed traffic condition

CAR 2010 - 2010 2nd International Asia Conference on Informatics in Control, Automation and Robotics

Volumn 3, Issue , 2010, Pages 44-47

  Liu, Bohang ^a   Li, Qingbing ^a   Chen, Duiyong ^a   Sun, Hailong ^a  

^a SHIJIAZHUANG TIEDAO UNIVERSITY   (China)

Author keywords

Mixed traffic; Pattern recognition; Reliability analysis

Indexed keywords

MATHEMATICAL STATISTICS; MIXED TRAFFIC; MOTOR VEHICLE; PRESSURE TUBES; PROBABILITY THEORY; TEST DATA; TRAFFIC DATA; TRAFFIC ENVIRONMENT; TRAFFIC FLOW; TRAFFIC INFORMATION; VEHICLE TYPES; WESTERN COUNTRIES;

EQUIPMENT; INFORMATION SCIENCE; INSTRUMENT TESTING; PATTERN RECOGNITION; PNEUMATIC TUBES; PNEUMATICS; QUALITY ASSURANCE; RELIABILITY THEORY; ROBOTICS; STATISTICS; TRAFFIC CONTROL; TRAFFIC SURVEYS;

RELIABILITY ANALYSIS;

EID: 77953077080     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/CAR.2010.5456723     Document Type: Conference Paper

References (6)

1. A.Ali, and E. Dagless, "Vehicle and pedestrian detection and tracking", Proceedings of IEE Colloquium on Image Analysis for Transport Applications. London:1990,12-19
2. E. Nakamura, N. Kehtarnavaz, and T. Urbanik. Quantification of Pedestrian flow Parameters along Crosswalks. Proceedings of the Intelligent Transportation Systems Meeting. Houston, TX, 1996
3. S. Kamijo, Y. Matsushita, K. Ikeuchi et al. Traffic monitoring and accident detection at intersections, IEEE Transactions on Intelligent Transportation Systems. Tokyo, Japan, 2000,108-118
4. C. J. Pai, H.R. Tyan, Y.M. Liang et al. Pedestrian detection and tracking at crossroads, Pattern Recognition, 2004,37(5),1025-1034
5. C. Shao, Y. Zhao, H Yue et al. Study on a vision-based system for Real-time Collection of Mixed Traffic Data. Proceedings of the 5th International Conference on Traffic and Transportation Studies. Xian, PR China,2006, 604-614
6. V. Kastrinaki, M. Zervakis, and K. Kalaitzakis. A survey of video Processing techniques for traffic applications. Image Vision Computing,2003,21(4),359-381