An Autonomous Intelligent Cruise Control (AICC) has been designed using a feedforward artificial neural network, as an example for utilizing artificial neural networks for nonlinear control problems arising in intelligent transportation systems applications. The AICC is based on a simple nonlinear model of the vehicle dynamics. A Neural Network Controller (NNC) code developed at Argonne National Laboratory to control discrete dynamical systems was used for this purpose. In order to test the NNC, an AICC-simulator containing graphical displays was developed for a system of two vehicles driving in a single lane. Two simulation cases are shown, one involving a lead vehicle with constant velocity and the other a lead vehicle with varying acceleration. More realistic vehicle dynamic models will be considered in future work.
Artificial neural network controller for intelligent transportation systems applications
1996
9 pages
Report
No indication
English
Road Transportation , Transportation , Transportation & Traffic Planning , Traffic Control , Automobiles , Computer Graphics , Computerized Simulation , Mathematical Models , Neural Networks , Nonlinear Problems , Performance Testing , Safety , Theoretical Data , Motor vehicles , Tables(data) , Cruise control , Intelligent Transportation Systems , EDB/320203 , EDB/990200
“ARTIFICIAL INTELLIGENCE IN INTELLIGENT TRANSPORTATION SYSTEMS”
Taylor & Francis Verlag | 1995
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