## 1 Introduction  
With the scientific and technological progress, technologies related to unmanned driving have become a research hotspot in the field of intelligent vehicle technology (IVT). Autonomous valet parking (AVP) can effectively save people's driving time, reduce the difficulty of parking, and greatly improve the utilization rate of empty parking spaces in the parking lot, helping to realize the \"last kilometer\" task of unmanned driving. Therefore, research and development of AVP systems are of essential significance. Many efforts have been undertaken widely by scholars at home and abroad, resulting in much attention directed towards intelligent automobile manufacturers. The technology of AVP is mainly realized by the vehicle's automatic driving function, the comprehensive regulation of the parking lot management system and the communication technology between the vehicle and the parking lot [1]. After the parking lot management system senses the real-time status information of the parking space in the field, it sends the corresponding parking space and recommended driving path information to the vehicle through the communication network. Then the vehicle automatically moves to the designated parking space according to the recommended path for parking. In the current research and application, the AVP technology is mainly realized through in-vehicle and infrastructure-based system. [PERSON] and [PERSON] [2; 3] realized the AVP function of multi-level parking structure through the on-board laser scanner and inertial measurement unit (IMU). [PERSON] [4] proposed a method to realize AVP through camera and odometer positioning with automotive grade sensors. [PERSON] [5] finished vehicle positioning in parking lot only through visual information by use of implementing an intelligent vehicle system for AVP service in low speed limited parking area. [PERSON] and [PERSON] [6; 7] made use of cameras and ultrasonic radar sensors to navigate in the parking lot without using global position system (GPS) to realize the AVP function. [PERSON] [8] just relied on cameras and ultrasonic sensors to complete AVP, which pushed visual localization, environment perception and automated parking to centimeter precision. [PERSON] [9] realized the identification of the vertical parking scene by using machine vision and pattern recognition technology to improve the utilization of parking spaces and the convenience of parking. The implementation above-mentioned requires high-accuracy sensors. In parking space recognition, ultrasonic radar sensors depend much on obstacles on both sides of the parking space. The camera cannot detect worn parking lines, especially in dimly lit condition. Moreover, the recognition accuracy of the parking space boundary is not precise, and accurate parking space perception can not be achieved. The infrastructure-based system has evolved from a simple parking guidance system in the early stage to a system relying on high-precision sensors installed in the parking lot. The vehicle only needs the systems of electronic braking, automatic gear shifting, electronic power steering and remote inter-connection functions. [PERSON] [10] proposed a hierarchical parking guidance model based on roadside guidance display, which can help the driver choose parking spaces and remotely monitor the states of the vehicle. [PERSON] [11] devised a model of a large-scale parking lot guidance information system that used ant colony optimization algorithm to complete the path guidance in the parking lot. [PERSON] [12] utilized ZigBee network and geomagnetic sensors to realize an intelligent parking guidance system to complete AVP. [PERSON] [13] developed a new system for intelligent navigation system used in parking lots. After he had modeled the parking lot with a time-varying graph, the proposed system was applied in a time-varying shortest path algorithm and dynamically tuned arc transit times based on planned vehicle routes, as well as traffic flow sensor data.