Title :
Adaptive signal control expert by artificial neural network training
Author :
Chang, Amoeba T S
Author_Institution :
Dept. of Transportation Sci. & Management, Tamkang Univ., Taipei, Taiwan
Abstract :
An advanced signal system, named INTELS (with subsystems, ITSS, IMSS, and MCC), has been proposed for several years and has been upgraded recently. Originally, it only used an expert system to generate a suitable phase during each beginning state of the timing determination; thus no cycle with a steady sequence was possible. Except for the above function, the system is being remodeled to possess the capability of planning optimal timing by using a reasonable traffic forecasting model via an artificial neural network. This paper describes the system´s framework, executing process, and the abstract control structure, including the phase generation and the timing design
Keywords :
adaptive control; control system synthesis; expert systems; learning (artificial intelligence); neurocontrollers; optimal control; road traffic; signalling; traffic control; INTELS; abstract control structure; adaptive signal control; artificial neural network; executing process; expert system; optimal timing; phase generation; planning; road traffic management; timing design; timing determination; traffic forecasting model; training; Adaptive control; Adaptive signal detection; Artificial neural networks; Control systems; Data communication; Programmable control; Signal generators; Timing; Traffic control; Vehicle detection;
Conference_Titel :
Vehicle Navigation and Information Systems Conference, 1995. Proceedings. In conjunction with the Pacific Rim TransTech Conference. 6th International VNIS. 'A Ride into the Future'
Conference_Location :
Seattle, WA
Print_ISBN :
0-7803-2587-7
DOI :
10.1109/VNIS.1995.518815
