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ETC system used in the parking lot can effectively alleviate the traffic congestion, reduce vehicle traffic delay time and the average queue length, improve the overall lane capacity and service level. Based on the traffic flow characteristics of the parking lot, the vehicle arrival characteristics, vehicle transit process characteristics, the ETC, MTC lane capacities are analyzed. This paper presents an ETC lane capacity calculation model with MTC misappropriation rate. The M/G/K queuing theory model is used to analyze the MTC lane capacity, and the evaluation index and calculation method of parking service fee are set up. Through the actual survey of the parking lot calibration parameters and the use of Vissim simulation model, the traffic and ETC use rates in different proportions, the vehicle traffic parking lot lane average delay time are obtained. For the cases that ETC utilization rates are 30% , 50% , 70% and the traffic volume is 180 pcu/ha, optimal allocation schemes of ETC lane number are put forward, respectively, which can provide reference for the use of ETC system. [ABSTRACT FROM AUTHOR]

Traffic flow prediction is a very important research area of intelligent transportation system, and has a very important academic value and practical significance to improve the traffic congestion problems. Traditional prediction methods which used determined mathematical model would not meet the needs of prediction accuracy and convergence speed during the traffic management control because of nonlinear, complexity and uncertainty of traffic flow. In order to forecast traffic flow accurately, real-timely and efficiently, a new algorithm is proposed by combining wavelet theory and neural network, and constructing an IWNN( improved wavelet neural network) with improved network training methods. At the same time, the initial weights are optimized by GA ( genetic algorithm). It can improve prediction accuracy, speed up the convergence speed and avoid entering local minima. The simulation results show that it can get better prediction results. [ABSTRACT FROM AUTHOR]