# Dynamic Tensor Modeling for Missing Data Completion in Electronic Toll Collection Gantry Systems
## 4 Results
### ETC Gantry Plate Data Preprocessing
After identifying and initially repairing the abnormal data, the quality of the ETC gantry plate recognition data is evaluated. The data quality of the G50 Nanjing section ETC gantry for January is illustrated in Figure 7.  
The quality of the ETC gantry data was generally high, with the monthly quality level exceeding 85% and an average data quality level of 90.4% for the month. There were 11 days in the month when the ETC gantry data quality fell below 90% (referred to as poor data quality), which is already superior to the detection effects of most detectors on highways. Utilizing meteorological data from the ETC gantry system's built-in weather detection equipment and referencing weather data, an investigation was conducted on  
Figure 7: The data quality of the G50 Nanjing section’s ETC gantry for January. the meteorological conditions in January 2022 in the area of the G50 Nanjing section (Suzhou). The region experienced minimal variation in January temperatures, with an average temperature of 7.93 \({}^{\circ}\)C, including an outlier of 1.4 \({}^{\circ}\)C. The region's precipitation for the month was 74.8 mm over 9 days of rainfall, with the specific weather conditions shown in Figure 8 below. Given the minor fluctuations in regional temperatures and its location in the south, where there are no cold temperatures, it can be inferred that temperature has a minimal impact on the ETC gantry's detection ability. This paper primarily analyzed the quality of ETC gantry data under poor visibility conditions, such as overcast and rainy days. By comparing the meteorological conditions on dates when the ETC gantry data quality was above 90% with those below 90%, it was found that the proportion of rainy days with poor quality was 77.78% of the total number of rainy days and 63.64% of the total number of days with poor quality. This suggests that the quality of the ETC gantry data is affected by adverse weather conditions such as rainfall. The accuracy and reliability of the ETC plate recognition data directly impact the operation of highway toll collection. An analysis of the actual usage of the G50 Nanjing section's ETC gantry data reveals the following advantages: (1) Quick updates, with a large volume of data accumulating over a short period of time. Millions of vehicle passage data can be generated daily. Moreover, the data have high consistency, strong structure, and low update costs. (2) Rich dimensions of ETC gantry data provide multiple perspectives for traffic data analysis. The ETC gantry system includes static data, such as vehicle information, toll station information, pass card information, and toll system information, as well as dynamic data, like travel information, charging information, and system verification information. The collection, transmission, and storage of plate recognition data require a multitude of devices and network services, which introduces the possibility of missed captures and identification errors: (1) Evasion tactics such as covering license plates, along with unstable equipment conditions, can result in missing fields and data anomalies within ETC gantry data, making it impossible to guarantee data quality. Concurrently, improper use by drivers, such as excessive speed, loss of ETC electronic tags, the application of special windshield films, and small vehicles being obscured by larger vehicles in tow, can lead to detection failures at the gantry, impacting data accuracy and leading to issues such as transaction anomalies, nonrecognition of vehicles, and missing vehicle statistics in the G50 Nanjing section ETC gantry. (2) The ETC gantry span in the G50 Nanjing section reaches up to 9 km, with insufficient monitoring of traffic flow between gantries. Additionally, the uneven and sparse distribution of ETC gantry detectors may lead to biases in the description of vehicle  
Figure 8: Meteorological conditions in the Suzhou Area of the G50 Nanjing Section. behavior.