基于蚁群算法的智能停车场引导系统

针对传统停车场存在的人工管理效率低，停车不方便等问题，利用物联网相关技术，将软件、硬件相结合实现停车场自动化管理系统.停车场内利用超声波传感器对停车场内车位状态检测，并将车位信息通过ZigBee无线传输方式传输至上位机，上位机通过蚁群算法对停车场实际车位的情况求解最优停车位路线.传统的蚁群算法在求解过程中容易出现死锁、停滞甚至无解的情况，本文根据停车场建立的结构模型改进基本蚁群算法，利用改进过的蚁群算法求解停车场的最优停车位.最后上位机根据得到的最优结果通过TCP/IP通信方式向显示屏发送左、前、右指令来诱导驾驶者行驶至最佳停车位置.

Intelligent Parking Guidance System Based on Ant Colony Algorithm

The purpose of this study is to solve the problems existing in the traditional parking lots, such as inefficient parking, inconvenient parking, and so on, using IoT-related technologies, combining software and hardware to realize the parking automation management system. In the parking lot, ultrasonic parking sensors check parking status and transmit parking status information to the host computer through ZigBee wireless network. According to the actual parking status information, the upper computer uses ant colony algorithm to calculate the best parking route for best parking space. Deadlock, stagnant or even no solution situation is easy to appear in the traditional ant colony algorithm''s solving process. Therefore, in this study, the traditional ant colony algorithm is improved according to the structural model established by the parking lot in solving the optimal parking space in parking lot. Finally, according to best parking route, the upper computer via TCP/IP network protocol sends the instructions of left, front, or right to display to the driver to the best parking position.