Freeway incident detection using hybrid fuzzy neural network

IET Intelligent Transport Systems

Volumn 1, Issue 4, 2007, Pages 249-259

  Srinivasan, D ^a   Sanyal, S ^a   Sharma, V ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

ALGORITHMS; FUZZY RULES; NEURAL NETWORKS; STATISTICAL METHODS;

GAUSSIAN MEMBERSHIP; TRAFFIC INCIDENT DETECTION; TRAINING DATA;

HIGHWAY SYSTEMS;

EID: 36349007522     PISSN: 1751956X     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-its:20070003     Document Type: Article

References (23)

1. Oh, C., Oh, J.-S., and Ritchie, S.G.: ' Real-time hazardous traffic condition warning system: framework and evaluation ', IEEE Trans. Intell. Transp. Syst., 2005, 6, (3), p. 265-272 1524-9050
2. Kamijo, S., Matsushita, Y., Ikeuchi, K., and Sakauchi, M.: ' Traffic monitoring and accident detection at intersections ', IEEE Trans. Intell. Transp. Syst., 2000, 1, (2), p. 108-118 1524-9050
3. Tang, S., and Gao, H.: ' Traffic-incident detection-algorithm based on nonparametric regression ', IEEE Trans. Intell. Transp. Syst., 2005, 6, (1), p. 38-42 1524-9050
4. Mahmassani, H.S., Haas, C., Zhou, S., and Peterman, J.: ' Evaluation of incident detection methodologies ', (Centre for Transport Research, 1998), FHWA/TX_00/1795-1
5. ' Development and testing of incident detection algorithms ', 1976, 2 Federal Highway Administration
6. Ahmed, S.R., and Cook, A.R.: ' Application of time-series analysis techniques to freeway incident detection ', Transp. Res. Rec., 1982, 841, p. 19-21
7. Wang, X., and Zhang, J.: ' A traffic incident detection method based on wavelet Mallat algorithm ', IEEE Mid-Summer Workshop on Soft Computing in Industrial Applications, June, 2005, p. 166-172, SMCia/05
8. Srinivasan, D., Jin, X., and Cheu, R.L.: ' Evaluation of adaptive neural network models for freeway incident detection ', IEEE Trans. Intell. Transp. Syst., 2004, 5, (1), p. 1-11 1524-9050
9. Lee, S.J., and Ouyang, C.J.: ' A neuro-fuzzy system modelling with self-constructing rule generation and hybrid SVD-based learning ', IEEE Trans. Fuzzy Syst., 2003, 11, (3), p. 341-353 1063-6706
10. Haykin, S.: ' Neural networks: a comprehensive foundation ', (Prentice Hall, Eaglewood Cliffs, NJ, 1992)
11. Cheu, R.L., Srinivasan, D., and Loo, W.H.: ' Training neural networks to detect freeway incidents by using particle swarm optimization ', Transp. Res. Rec., 2004, p. 11-18
12. Srinivasan, D., Cheu, R.L., and Poh, Y.P.: ' Hybrid fuzzy logic-genetic algorithm technique for automated detection of traffic incidents on freeways ', IEEE Int. Conf. Intelligent Transportation Systems, Oakland, California, USA, 2001, August)
13. Cheu, R.L., Srinivasan, D., and Tian, E.: ' The support vector machine models for freeway incident detection ', IEEE Int. Conf. Intelligent Transportation Systems, Oakland, California, USA, 2001, August), 1, p. 238-243
14. Dia, H., and Rose, G.: ' The impact of data quantity on the performance of neural network freeway incident detection models' in 'Neural networks in transport application ', p. 311-340, Part D
15. Browne, R., Foo, S., Huynh, S., Abdulhai, B., and Hall, F.: ' Comparison and analysis tool for automatic incident detection ', Freeway Operations, High-Occupancy Vehicle Systems, Traffic Signal Systems, and Regional Transportation Systems Management 2005 Transportation Research Record, 1925), 2005, p. 58-65
16. Teng, H.H., Qi, Y.G., and Martinelli, D.R.: ' Developed incident detection algorithm compared with neural network algorithms ', Initiatives In Information Technology and Geospatial Science for Transportation, Transportation Research Record (1836), 2003), p. 83-92
17. Roy, P., and Abdulhai, B.: ' GAID - genetic adaptive incident detection for freeways ', Freeways, High-Occupancy Vehicle Systems, and Traffic Signal Systems 2003, (Transportation Research Record (1856), 2003), p. 96-105
18. Shuming, T., and Haijun, G.: ' Traffic-incident detection-algorithm based on nonparametric regression ', IEEE Trans. Intell. Transp. Syst., 2005, 6, (1), p. 38-42 1524-9050
19. Wang, Y., Papageorgiou, M., and Messmer, A.: ' A real-time freeway network traffic surveillance tool ', IEEE Trans. Control Syst. Technol., 2006, 14, (1), p. 18-32 1063-6536
20. Zhang, K., and Taylor, M.A.P.: ' Towards universal freeway incident detection algorithms ', Transp. Res. C. Emerg. Technol., 2006, 14, (2), p. 68-80 0968-090X
21. Abdulhai, B., and Ritchie, S.G.: ' Enhancing the universality and transferability of freeway incident detection using a Bayesian-based neural network ', Transp. Res. C. Emerg. Technol., 1999, 7, (5), p. 261-280 0968-090X
22. Oh, C., Oh, J., Ritchie, S.G., and Chang, M.: ' Real-time estimation of freeway accident likelihood ', Proc. 80th Annual Meeting of Transportation Research Board, January, 7-11, 2001
23. Abdulhai, B., and Ritchie, S.G.: ' Preprocessor feature extractor and postprocessor probabilistic output interpreter for improved freeway incident detection ', Transp. Res. Rec., 1999, 1678, p. 277-286