Adaptive Genetic Fuzzy Logic Signal Controller
Dr. Lawrence W. Lan
Dr. Yu-Chiun Chiou
|關鍵字:||適應性號誌控制;基因模糊邏輯控制;流體近似法;Adaptive signal control;Genetic fuzzy logic controller;Fluid approximation method|
Genetic fuzzy logic controller (GFLC) can overcome the drawbacks of conventional fuzzy logic controller (FLC) which has to subjectively set the logic rules and membership functions. Thus, GFLC can greatly enhance the applicability of FLC. This thesis attempts to construct an adaptive genetic fuzzy logic control model for an isolated intersection signal timing control. This GFLC model uses traffic flow and queue length as state variables and extended green time (EGT) as control variable. The intersection total delay, estimated by fluid approximation method, is used to evaluate the control performance. At the moment of ending of a minimum green time or of the previous EGT inference, the GFLC model is activated for another inference of EGT. If the value of EGT is zero or a maximum green time is reached, then the signal switches to the competing direction. Based on three flow volumes (low, medium and high) and two traffic patterns (uniform and varying arrivals), a total of six scenarios are designed and compared with the Webster pre-timed signal control model to verify the robustness of this GFLC model. In order to further validate the control performance of the GFLC model, a fully enumerative method is employed to solve, respectively, for the optimal single timing plan (only one set of signal timing for a given traffic condition during the simulation period) and for the optimal multiple timing plans (several sets of signal timings depending on varying traffic patterns). The scenario analysis shows that GFLC model can reduce total delay by 0~13.1% in comparison with the Webster’s model. Under uniform arrivals, the total delay of GFLC model is slightly higher than the optimal single timing plan by 0~5.83%. Under varying traffic patterns, the total delay for GFLC model is 0.81~4.68% less than the optimal single timing plan but 1.78~13.5％ higher than the optimal multiple timing plans. It indicates that the proposed GFLC model has better control performance than the Webster model and the optimal single timing plan under varying traffic patterns. However, the GFLC model is inferior to the optimal single timing plan under uniform arrivals as well as the optimal multiple timing plans under varying traffic patterns. It suggests that our proposed GFLC model can still be improved, which deserves to be explored. To validate the applicability of our GFLC model, a field study at the signalized intersection of Zhong-Zheng Road and Wen-Lin Road in Taipei City is conducted. The results show that the total delay of GFLC model is respectively 19% and 16% less than that of the current timing plan and Webster’s model.
|Appears in Collections:||Thesis|