Hybrid fuzzy logic-genetic algorithm technique for automated detection of traffic incidents on freeways

IEEE Conference on Intelligent Transportation Systems, Proceedings, ITSC

Volumn , Issue , 2001, Pages 352-357

  Srinivasan, D ^a   Cheu, R L ^a   Poh, Y P ^a  

^a NATIONAL UNIVERSITY OF SINGAPORE   (Singapore)

Author keywords

Fuzzy logic; Genetic algorithms; Incident detection

Indexed keywords

FUZZY CONTROL; FUZZY SETS; GENETIC ALGORITHMS; HIGHWAY SYSTEMS;

FUZZY CONTROLLERS; INCIDENT DETECTION;

TRAFFIC SURVEYS;

EID: 0034779494     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (15)

1. Development and testing of incident detection algorithms
2. Application of time-series analysis techniques to freeway incident detection
3. Dynamic model-based techniques for the detection of incidents on freeways
4. Neural network models for automated incident detection of lane-blocking incidents on freeways
5. Congestion identification aspects of the McMaster incident detection algorithm
6. Application of filtering techniques for incident detection
7. Neural networks: A comprehensive foundation
8. Genetic algorithms in search optimization, and machine learning
9. Investigations of a neural network model for freeway incident detection
10. A neuro-genetic-based universally transferable freeway incident detection framework
11. Full design of fuzzy controllers using genetic algorithms
12. Design of sophisticated fuzzy logic controllers using genetic algorithms
13. Automated detection of lane-blocking freeway incidents using artificial neural networks
14. Artificial intelligence techniques in the development of freeway incident detection systems