![]()
LINJA II
Project: Fuzzy control for public transport priorities and areal traffic signal
control (ID 106)
Project description
New methods, like fuzzy logic
and neural networks are coming into the field of adaptive traffic signal
control. Nowadays, the aim at the Helsinki University of Technology, Laboratory
of Transportation Engineering, is to apply fuzzy logic in adaptive traffic
signal control. The main goals of our FUSICO-research project are theoretical
analysis of fuzzy traffic signal control, generalized fuzzy rules for traffic
signal control using linguistic variables, validation of fuzzy control
principles and calibration of membership functions, and development of a fuzzy
adaptive signal controller. The vehicle-actuated control strategies, like SOS,
MOVA and LHOVRA, are the control algorithms of the first generation. The fuzzy
control algorithm can be one of the algorithms of the second generation, the
generation of artificial intelligence (AI). The fuzzy control is capable of
handling multi-objective, multi-dimensional and complicated traffic situations,
like traffic signalling. The typical advantages of fuzzy control are simple
process, effective control and better quality.
Project results
The results of this project
have indicated that fuzzy signal control is the potential control method for
isolated intersections. The comparison results of Pappis-Mamdani control, fuzzy
isolated pedestrian crossing and fuzzy two-phase control are good. The results
of isolated pedestrian crossing indicate that the fuzzy control provides the
effective compromise between the two opposing objectives, minimum pedestrian
delay and minimum vehicle delay. The results of two-phase control and
Pappis-Mamdani control indicate that the application area of fuzzy control is
very wide. The maximum delay improvement was more than 20 %, which means that
the efficiency of fuzzy control can be better than the efficiency of traditional
vehicle-actuated control.
According to these results,
we can say that the fuzzy signal control can be multi-objective and more
efficient than conventional adaptive signal control nowadays. The biggest
benefits can, probably, be achieved in more complicated intersections and
environments. The FUSICO-project continues. The aim is to move step by step to
more complicated traffic signals and to continue the theoretical work of fuzzy
control. The first example will be the public transport priorities.
Timetable
The research project has
been implemented during 1998-1999.
Researchers and contacts