## 5 Experimental Results and Analysis
### PTV Quantitative Evaluation Algorithm  
#### 5.3.1 Determination of Characteristic Parameters  
The PTV evaluation of the expressway comprehensively considers several evaluation indexes, among which the membership function based on a fuzzy set is used to quantitatively evaluate different PTVs. To ensure the rationality of the evaluation, it is necessary to determine the segmented value interval of the membership function, which has a direct impact on the accuracy of PTV evaluation. Therefore, in order to scientifically and reasonably set these parameters, we have comprehensively considered the following two factors. Firstly, feature analysis of evaluation indicators is crucial. The evaluation indicator characteristics of PTV are usually contained in a large amount of data, so we adopt effective data mining methods to analyze the distribution of indicators from a statistical perspective. Through in-depth mining and analysis of data, we can better understand the essential characteristics of indicators and determine the corresponding interval of segmented function values. Figure 11: Visualization of vehicle traffic speed prediction. Secondly, we combine the limitations of traffic laws and regulations. The main purpose of traffic regulations is to regulate driving behavior, reduce economic losses caused by traffic accidents, and improve the safety level of roads. Therefore, when setting the value range of the membership function, we must comply with relevant traffic regulations and ensure that the set parameters not only accurately reflect the performance of PTV, but are also consistent with traffic regulations to ensure the legality and operability of the evaluation results. By comprehensively considering the above two factors, we can set reasonable segmented value intervals for the membership function on a scientific basis, thereby ensuring the accuracy and reliability of expressway PTV evaluation. The adoption of this method will make the evaluation results more credible and provide a useful decision-making basis for the management and planning of expressway. The experiment selected data from the Fu-xia section for statistical analysis, and the results are shown in Figure 12.  
The probability curve of vehicle speed distribution shown in Figure 12a shows proper normal distribution characteristics and reaches the highest point at 90 km/h, providing a reference for OS feature threshold setting. Due to the dynamic nature of PTV evaluation, which is relative to over-the-horizon vehicles, the degree of danger of its OS characteristics needs to be compared with the speed of over-the-horizon vehicles. If there is a significant difference in speed between vehicles traveling on the road and over-the-horizon vehicles, it will have a certain impact on driving safety. The speed difference between vehicles can easily lead to lateral accidents and rear-end collisions. Some scholars have studied accident data, and [PERSON] et al. [38] used statistical regression methods to study the relationship between the speed difference between large and small vehicles and the accident rate. They concluded that there is a positive correlation between the speed difference and the accident rate, that is, as the average speed difference increases, the accident rate gradually increases, and accidents caused by the speed difference together account for one-third of the total number of accidents. Therefore, the threshold is set for vehicle speeds greater than those of over-the-horizon vehicles. The probability curve of vehicle driving duration distribution shown in Figure 12b shows that by referring to the definition of sleep-deprived driving duration in China (driving duration is more than 4 consecutive hours, and rest time is less than 20 min, or driving duration in a working day is more than 8 h), combined with the distribution curve, the driving duration drops sharply after more than 4 h. Therefore, it can be inferred that the driving duration of most drivers is usually less than 4 h, which is also the most suitable time parameter.