Referenced Items are not available for this document.
Generally the most cost-effective means of achieving optimized vehicle flow through a given road network is by improving the timing of traffic signals at network intersections. This paper uses neural networks (NN) as the bases for the control law. The NN weight estimation occurs real time in closed-loop mode via the simultaneous perturbation stochastic approximation algorithm. The approach results in a net 10-percent reduction in vehicle wait time over the performance of the existing, in-place strategy
Published in:
Neural Networks, 1996., IEEE International Conference on
(Volume:4
)
Date of Conference: 3-6 Jun 1996
- Page(s):
- 2101 - 2106 vol.4
- Meeting Date :
- 03 Jun 1996-06 Jun 1996
- Print ISBN:
- 0-7803-3210-5
- INSPEC Accession Number:
- 5392812
- Conference Location :
- Washington, DC
- Digital Object Identifier :
- 10.1109/ICNN.1996.549226
- Product Type:
- Conference Publications
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