Predicting intersection queue with neural network models

Transportation Research Part C

Volumn 3, Issue 3, 1995, Pages 175-191

  Chang, Gang Len ^a   Su, Chih Chiang ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0001528567     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/0968-090X(95)00005-4     Document Type: Article

References (26)

1. Estimation of traffic flow parameters in urban traffic networks
2. Discrete time point processes in urban traffic queue estimation
3. Discrete time point processes in urban traffic queue estimation
4. Recent enhancements to SCOOT—version 2.4
5. On-line estimation of traffic densities from time-series of flow and speed data
6. The PRODYN real time traffic algorithm
7. SCOOT—a traffic responsive method of coordinating signals
8. Dynamic prediction of traffic volume through Kalman filtering theory
9. A comparison of predictor algorithms for computerized traffic control systems
10. Factors affecting the relative performance of traffic responsive and time-of-day traffic signal control
11. Modelling of traffic flow at signalized links
12. UTOPIA
13. The prediction of traffic flow volumes based on spectral analysis
14. Time series analysis of local fluctuations in traffic parameters
15. Learning logic
16. Learning representations by backpropagating errors
17. Optimization network of traffic signals in real time—The SCOOT method
18. Adaptive response for exponential smoothing Comparative system analysis
19. Improved control logic for use with computer-controlled traffic
20. Modeling and analysis of traffic queue dynamics at signalized intersections
21. Improved estimation of traffic flow for real time control
22. Beyond regression