基于云模型的高速公路隧道车辆位置估计

为实现对高速公路隧道照明系统的节能控制，提出基于云模型的车辆速度与位置估计方法。结合正向云与逆向云算法，对车辆通过线圈时的脉冲波形数据进行处理，获得均速估计值。将车速估计结果与行车时间作为车辆行驶位置的判定依据，采用云推理估计车辆的行驶位置。对云估计误差进行实时修正，从而精确判断车辆行驶的位置。仿真和实验结果表明，该方法能实现对高速公路隧道内车辆位置的正确估计，且估计精度高达99．2309％，可提高云模型算法在实际应用中的效率，适用于高速公路隧道照明系统的节能控制。

Position Evaluation .of Highway Tunnel Vehicle Based on Cloud Model

In order to achieve lighting energy saving of highway tunnel, the method of speed and position evaluation based on cloud model is proposed. It uses positive cloud with the combination of reverse cloud algorithm, processes the pulse waveform data when the vehicle goes through coil to obtain the estimation of average speed. It keeps the speed estimation results and time as the decision basis of vehicle＇s position, and adopts cloud reasoning estimate vehicle＇s position. It makes cloud estimation error real-time correct, so as to judge the position of vehicle accurately. The simulation and experimental results show that the algorithm is able to realize the estimation of vehicle＇s position inside the highway tunnel, and the accuracy of which can reach 99.230 9%, so as to improve efficiency in practical application of the cloud model algorithm, suitable for the energy saving control of lighting system in highway tunnel.