## 2 Materials and Methods
### Architecture Design  
Because most of the vehicle body belonged to the metal magnetic material, the vehicle may have disturbed the geomagnetic field while driving [8; 9]. This kind of geomagnetic disturbance could be detected by the geomagnetic sensor. In the running process of a vehicle, the vehicle body blocked the light and cast shadows on the road surface, resulting in the change of light intensity on the road surface [10; 11]. The change of light intensity on the road surface could then be detected by the photosensitive element. According to the geomagnetic disturbance caused by the vehicle and the change of road light intensity, the basic parameter information, such as the vehicle length and speed, could be obtained by data processing and data analysis so that some parameters, such as the traffic volume, average speed, and lane occupancy, could be obtained through the driving parameter of a single vehicle [12; 13]. The hardware structure of the method contained the wireless sensor node and the data acquisition and control equipment of a host computer. The wireless sensor node included the sensor data acquisition unit, the wireless communication unit, and the power supply unit. The data acquisition and control equipment of host computer included the microcontroller, the wireless communication unit, and the USB (Universal Serial BUS) interface. The multi in-car sensing equipment sensor was designed by the data acquisition unit. It was set on the roadside or vehicle body to collect traffic flow parameters, which were then transmitted to the data acquisition and control equipment of the host computer through the wireless communication unit, in which the power supply unit was mainly  
Figure 2: The moving object detection algorithm in this paper. responsible for the power supply. The host computer data acquisition control method received the traffic flow detection data through the wireless communication unit and then obtained the details of the moving objects in the traffic flow by the traffic flow detection method based on symmetrical difference. The overall architecture of the method of autonomous detection for the traffic flow parameter of the in-vehicle sensing equipment based on symmetrical difference is shown in Figure 3.  
The wireless communication unit in the architecture adopted a cross-layer pre-balanced safety transmission protocol of VANET. The VANET is a self-organizing communication network which carries on the traffic vehicles. It can provide various services such as vehicle to vehicle communication, traffic information sharing, traffic security and so on. The main design idea was to share the channel state information between the network layer and the physical layer by cross-layer transparent transmission, so that the pre-equalization process of the channel based on channel characteristics for the sending nodes in physical layer could be achieved and the safe channel capacity could be maximized. In the specific implementation, the identity of the malicious node in VANET was divided into two categories: the malicious nodes inside the method architecture and the malicious nodes outside the method architecture [14; 15]. The common point was that they could get the transmission signal from the wireless channel. The difference was that the malicious nodes in the method architecture had detailed communication parameters, so it was difficult to prevent. Through the design of the routing algorithm, the threat of nodes could be effectively reduced. The main design methods: (1) Control the number of known nodes in the process of information transmission and reduce the number of potential malicious nodes in the method architecture; (2) improve the information security transmission capacity by the maximization rule.