TRAFFIC RESPONSIVE SIGNAL CONTROL SYSTEM UNDER MIXED TRAFFIC CONDITIONS

Abstract

This paper develops an adaptive traffic signal control model based on a stepwise genetic fuzzy logic controller (SGFLC). The proposed model considers traffic flows and queue lengths of cars and motorcycles as state variables and extension of green time as control variable towards the minimization of total vehicle delays. For the learning efficiency of SGFLC and the capability in capturing traffic behaviors of Asian urban streets where mixed traffic of cars and motorcycles is prevailing, mixed traffic cell transmission model (MCTM) is also proposed to replicate traffic behaviors. To validate the performance of the proposed SGFLC model, comparisons to two enumeration pre-timed signal timing plans and two adaptive signal timing models are conducted. Results show that our proposed SGFLC model almost achieves the optimal control. As traffic flows vary more noticeably, the SGFLC model performs even better, suggesting that the proposed SGFLC signal control model is effective, robust and applicable.