## 1 Introduction
The multiple-detection problem will cause the number of spaces and total space time to be incorrectly calculated and the coordinated adaptive traffic control strategy of the SCATS will be affected. Simultaneously, the speed of vehicles entering and leaving the parking lot are generally less than 20 km/h, the multiple-detection problem will lead to large statistical errors. The error-detection of the parking spaces' status will bring certain difficulties to the managers of the parking lot. What is more, the detection result of most vehicle detectors is transmitted through the wireless channels, the wrong detection result will increase the transmission times which resulting in much higher power consumption of the vehicle detector and probability of wireless channel collision with the other vehicle detectors. This problem is much more obvious on the industrial district roads and suburban roads where large vehicles account for a larger proportion of total traffic flows. In order to solve the multiple-detection problem in detecting those vehicles running at low speed on roads or error-detection problem in the case of the stopping position of the vehicle is not standard when waiting for the traffic light to change caused by the blind zone of geomagnetic signals in vehicle detection procedure, the multi-sensor data fusion detection methods of combining with optical sensor [12] and acceleration sensor [13] were proposed, experiments results showed that those methods did improve vehicle detection accuracy. However, the optical sensor can be easily affected by environmental conditions, such as dust, rain and fog, etc., which leads to misjuddment of the state of vehicles. The vibration signal generated by vehicles is so weak that an expensive high-resolution acceleration sensor was required. The electromagnetic waves exist widely and always affect our lives. A novel radio-based vehicle detection method was proposed in the literature [14]. A lot of Wi-Fi APs (Access Point) were deployed on a roadside by the authors of the literature. And the vehicle detection and speed estimation methodsare realized by analyzing the change in received signal strength of Wi-Fi signal collected by the laptops placed on the other roadside. The literature has provided a new way for vehicle detection methods. In order to improve the detection accuracy in detecting long wheelbase and high chassis large vehicles running at low speed or stopping at non-standard positions when waiting for the traffic light to change on a road or parking on a parking lot, we add a FM (Frequency Modulation) radio module in the traditional single magnetism-based vehicle detector, propose a two-sensors data fusion vehicle detection method which is realized through combining the received signal strength collected by the FM radio module and the geomagnetism around vehicles sampled by a geomagnetic sensor. We build test scenarios to verify the performance of the proposed method by installed vehicle detectors with the proposed method and traditional single magnetism-based method on the same road. The experiment results show that our proposed two-sensors data fusion vehicle detection method bring higher detection accuracy than the traditional single magnetism-based detection method. The method we proposed has the advantages of easy implementation and low cost, which is very suitable for vehicle detection applications. The higher detection accuracy of vehicle detector will lay the foundation for intelligent decision making in intelligent transportation systems.