How the traffic jams in crossroads can be relieved if the signals are smarter?
_
As recent years
many cities are harassed by the problem of traffic jams, the waiting time
drivers and passengers spend on queuing in front of a traffic signal is
becoming more and more intolerant. Anyone who ever had the experience of living
in big cities would undoubtedly haunted by the "nightmare" of traffic
jams. It is revealed that most traffic jams are caused, or at least aggravated
severely by crossroads. If the traffic signals are more intelligent, we
assume that less terrifying jams and annoying delays can hopefully be avoided.
The vast developing image processing and artificial intelligence has provides a potential way of solving such problem. To investigate on this, this program mainly concerns on the control algorithm that can reduce the maximum waiting time and average waiting time. The main technique we employed is fuzzy neural networks, which combines the two widely applied intelligent control methods and tested the performance of such methods using different inputs.
The vast developing image processing and artificial intelligence has provides a potential way of solving such problem. To investigate on this, this program mainly concerns on the control algorithm that can reduce the maximum waiting time and average waiting time. The main technique we employed is fuzzy neural networks, which combines the two widely applied intelligent control methods and tested the performance of such methods using different inputs.