Study of Ramp Control Method for Urban Expressways Using Improvised ALINEA Algorithm

The traditional ALINEA (asservissement linéaire d'entrée autoroutière) ramp control algorithm does not take into consideration the ramp queue overflow of urban expressways, and may thus cause traffic congestion at the apposite expressway intersection. By incorporating the classical ALINEA ramp control algorithm, a new on-ramp control method for urban expressways has been proposed, based on traffic-flow prediction for urban expressways. The proposed method focuses on developing a wavelet neural network optimized by a genetic algorithm (GA-WNN) for predicting the traffic-flow of an urban expressway. The gap acceptance theory and the grading principle of ramp queues have also been introduced in the proposed methodology, thus leading to the realization of dynamic regulation of the ramp control rate for urban expressways. The control effects of the classical ALINEA and the proposed algorithm were compared through a micro-simulation experiment, and the results show that the proposed model can effectively improve the capacity of the arterial road, and can reduce the average trip time of the ramp by approximately 24.8%.