According to the traffic flow features of intersections in downtown of urban,and considering the vehicle queues of the controlled phase and the relative neighboring phases comprehensively,a multi-phase adaptive control algorithm is put forward based on the learning ability of fuzzy neural control.This adaptive control algorithm does fuzzy reasoning by two preconditions and with the improved BP algorithm,a 3-layer neural network is constructed to realize the adaptive fuzzy controller in road intersection by considering the length of the queue on the contiguous phase lanes.Finally,compared with the similar results in references,simulation research shows that the fuzzy neural controller can not only decrease the average vehicle delay but also adjust the signal period automatically,and this means that the adaptive control algorithm presented in this paper can be popularized in urban intersection intelligent control.