GAID: Genetic Adaptive Incident Detection for Freeways

Transportation Research Record

Volumn , Issue 1856, 2003, Pages 96-105

  Roy, Prasenjit ^a   Abdulhai, Baher ^a  

^a UNIVERSITY OF TORONTO   (Canada)

Author keywords

[No Author keywords available]

Indexed keywords

GENETIC ALGORITHMS; HIGHWAY TRAFFIC CONTROL; NEURAL NETWORKS; NUMERICAL ANALYSIS; OPTIMIZATION; PROBABILITY DISTRIBUTIONS;

DETECTION RATE (DR); FALSE ALARM RATE (FAR); GENETIC ADAPTIVE INCIDENT DETECTOR (GAID); INTELLIGENT TRANSPORTATION SYSTEM (ITS);

HIGHWAY SYSTEMS;

EID: 2142702918     PISSN: 03611981     EISSN: None     Source Type: Journal    
DOI: 10.3141/1856-10     Document Type: Conference Paper

References (14)

1. Abdulhai, B., and S. G. Ritchie. Development of a Universally Transferable Freeway Incident Detection Framework. Presented at the 76th Annual Meeting of the Transportation Research Board, Washington, D.C., 1997.
2. Abdulhai, B. A Neuro-Genetic-Based Universally Transferable Freeway Incident Detection Framework. Ph.D. dissertation. University of California, Irvine, 1996.
3. Abdulhai, B., and S. G. Ritchie. Performance of Artificial Neural Networks for Incident Detection in ITS. Transportation Congress, Vol. 1, 1995, pp. 227-238.
4. Masters, T. Advanced Algorithms for Neural Networks. A C++ Sourcebook. John Wiley and Sons, Inc., Toronto, Ontario, Canada, 1995.
5. Parzen, E. On Estimation of Probability Function and Mode. Annals of Mathematical Statistics, Vol. 33, 1962, pp. 1065-1076.
6. Abdulhai, B., and S. G. Ritchie. Preprocessor Feature Extractor and Post Processor Probabilistic Output Interpreter for Improved Freeway Incident Detection. In Transportation Research Record: Journal of the Transportation Research Board, No. 1678, TRB, National Research Council, Washington, D.C., 1999, pp. 277-286.
7. Abdulhai, B., S. G. Ritchie, and M. Iyer. Implementation of Advanced Techniques for Automated Freeway Incident Detection. Partners for Advanced Transit and Highways Research Report UCB-ITS-PRR-99-42, California PATH Program, Institute of Transportation Studies, University of California, Berkeley, 1999.
8. Gall, A. I., and F. L. Hall. Distinguishing Between Incident Congestion and Recurrent Congestion: A Proposed Logic. In Transportation Research Record 1232, TRB, National Research Council, Washington, D.C., 1989, pp. 1-8.
9. Persaud, B. N., F. L. Hall, and L. M. Hall. Congestion Identification Aspects of the McMaster Incident Detection Algorithm. In Transportation Research Record 1287, TRB, National Research Council, Washington, D.C., 1990, pp. 167-175.
10. Hall, F. L., Y. Shi, and G. Atala. On-Line Testing of the McMaster Incident Detection Algorithm Under Recurrent Congestion. In Transportation Research Record 1394, TRB, National Research Council, Washington, D.C., 1993, pp. 1-7.
11. Cacoullos, T. Estimation of Multivariate Density. Annals of the Institute of Statistical Mathematics (Tokyo), Vol. 18, No. 2, 1966, pp. 179-189.
12. Specht, D. F. Enhancement to Probabilistic Neural Networks. IEEE International Joint Conference on Neural Networks, Vol. I, Location? 1992, pp. 761-768.
13. Specht, D. F., and H. Romsdahl. Experience with Adaptive Probabilistic Neural Networks and Adaptive General Regression Neural Networks. IEEE International Conference on Neural Networks, Vol. II, Orlando, Fl., 1994, pp. 1203-1208.
14. Roy, P. GAID: Genetic Adaptive Incident Detection for Freeways. Master's thesis. University of Toronto, Ontario, Canada, 2002.