Study on the Relatedness between Arterial Highway Freight Volume and GDP

There is a deviation from the actual condition of freight transport and ‘volume of freight transport by vehicles’ counted by the current highway and waterway industry statistical statement system of China at the provincial or municipal level. This paper puts forward the concept of ‘volume of freight transport in regions’, uses survey data and administrative data to calculate the Grey relational degree between arterial highway freight volume and the GDP of the three industries. The quantitative analysis of the calculation results shows that the results are consistent with the actual situation, which is of certain practical significance. The variation trend of the arterial highway freight volume can reflect the economic development of the region.


Introduction
According to the current highway and waterway industry statistical statement system of China, the traffic volume completed by commercial trucks that registered in some city is taken as the traffic volume of highway goods in that city, which is called "volume of freight transport by vehicles". The "volume of freight transport by vehicles" can reflect the actual condition of goods transport at the national level, but there is a deviation from the actual condition of goods transport at the provincial or municipal level, especially in the economically developed areas and less developed areas. The freight transport in the economically developed areas has certain characteristics. In addition to local trucks, there are also a considerable number of non-local trucks participating in road transport, and the transport volume completed by these non-local trucks is not included in the statistical category of the capacity, the contribution to economic development should not be underestimated.

Data Acquisition Method
Since the "volume of freight transport by vehicles" cannot directly reflect the economic situation of a certain region, we will adopt a certain method to obtain the data of truck transport in a certain place, called the "volume of freight transport in regions".
The data studied in this paper can be divided into two parts according to their sources and acquisition methods: active survey and non-active survey. Active survey is the way to obtain the data for the study through field sampling survey, while non-active survey is the way to obtain administrative statistics through certain technical means. The highway freight transport data system is shown in Figure 1.

Data Calculation Method
Arterial highway freight volume refers to the volume of freight completed by trucks from all over the country on arterial Highway. It includes both trucks whose license plate is registered in the region and those registered in the outer region. Considering the freight turnover can fully reflect the information of freight volume and driving volume of freight transport, this paper uses the freight turnover as arterial highway freight volume for analysis and calculation. Arterial Highway freight turnover consists of expressway freight turnover and freight turnover of national and provincial highway. The calculation method is described below.

Volume of Freight Transport of Expressway
Expressway toll collection data is a full-caliber statistics, using expressway toll collection data for analysis can be counted all the freight traffic data of all the trucks passing through the expressway of a certain area, the data accuracy error is small, easy to grasp the actual situation of the development of freight transport.
Expressway freight turnover is the sum of the product of the tonnage of goods and the distance they are transported by all trucks on the expressway network. The calculation is as follows. The calculation method of driving volume on national highways is as follows.  Vol. 7, No. 3, 2020 putted into equations (2.4) and (2.5). After calculation, the annual freight turnover of national highway and provincial highway can be obtained.
Finally, the arterial highway freight volume can be obtained from equation (2.6).

Calculation Method of Relatedness
Grey Relational Analysis is a common method for analyzing multi-factor dynamic correlation.
Compared with regression analysis, variance analysis and other methods, grey relational Analysis has fewer constraints and can analyze the development trend. It has no excessive requirements on sample size and low requirements on data regularity. This paper will analyze the correlation between the arterial highway freight volume and the GDP through this method.

B-type Grey Relational Grade
B-type Grey Relational Grade examined the similarity and proximity between the relational factors.
The similarity means that the closer the geometric shapes are, the closer the development trend is.
Proximity refers to the fact that the functional curves of Relational factors are not completely similar, but there is little difference in each moment. This phenomenon indicates that relational factors are closely related to each other, on the contrary, they are not very closely related.
The B-type grey relational grade of discrete functions can be expressed as follows.

Grey Absolute Correlation Degree
The principle of grey absolute correlation degree is to calculate the correlation degree according to the approximate degree between the changing trend of the time series curve of the factors. For the discrete data column, the closeness of two curves is determined by the proximity of curves' slopes in corresponding time periods of two time series. If the slope of two curves is the same or the difference is small in each period, the correlation coefficient is high; otherwise, it is low.
The slope of the curve at each point in time is obtained through IAGO. (1) Then the correlation coefficient of each time point is Grey absolute correlation degree is 0.6 r > and close to 1, the two factors are considered to be strongly correlated. If 0.5 r < and close to 0, the correlation between the two is considered weak.
3.3Gray trend relational degree 0 X is reference sequence and i X is compare sequence. After initializing original data, the grey trend correlation degree of the two sequences is constructed as follows.    Table 1. The arterial highway freight volume of Ningbo is taken as the reference sequence 0 X in grey correlation analysis. The GDP index of the three industries is taken as the compare sequence.
, ( 1, 2, 3) i X i = . The B-type grey relational grade, grey absolute correlation degree and gray trend relational degree are used to calculate the grey correlation degree respectively. The results can be used to quantitatively analyze the correlation between the arterial highway freight volume and each industry.
It is necessary to nondimensionalize the original data because the dimension of the original data is different. The dimensionless treatment with the initial value transformation can make the growth trend more obvious and the result more persuasive. The results of dimensionless treatment are shown in  After dimensionless processing of the original data, the three kind of grey correlation degrees of arterial highway freight volume and GDP of the three industries in Ningbo are calculated, and the correlation degrees of the arterial highway freight volume and GDP of the primary industry, the secondary industry and the tertiary industry are calculated as 01 R , 02 R and 03 R respectively. According to the calculation results, the arterial highway freight volume has a strong correlation with the GDP of the three industries. Obviously, the ranking result of correlation degree calculated by three grey relational models are same.
The results of quantitative analysis show that the correlation degree between the arterial highway freight volume and the development of the secondary industry is the highest, and the correlation degree with the tertiary industry is slightly lower than that of the secondary industry, but the correlation degree with each industry is not much different, and the correlation degree with the primary industry is weaker than that of the secondary and tertiary industries.

Discussion
In this paper, the calculation results of the correlation degree between arterial highway freight volume and GDP of the three industries are consistent with the actual situation. This calculation method can be extended to other provinces and cities to facilitate the timely obtaining of the status of freight transport in this region and provide support for regional economic development.