The distribution of passenger car flow on intercity highways is crucial for traffic planning and management, and analyzing its intrinsic influencing factors is also urgent for solving various traffic problems. In this paper, the Random Forest algorithm is used to identify the key factors affecting the distribution of different passenger car flows, and the degree of dependence of the distribution of different types of passenger car flows on different factors is further analyzed through visualization. The results show that: tertiary gross product and urban population are the significant features affecting the traffic volume of small-sized buses; gross product and urban population are the significant features affecting the traffic volume of medium-sized buses; tertiary gross product and urban population are also the significant features affecting the traffic volume of large-sized buses.
Highway freight transport emissions provide a high contribution to carbon emissions in the transport industry, and analysing the driving factors is conducive to building a low-carbon transport structure. This paper explores the indicators of economic dynamic series level, traffic development and energy consumption structure that affect the carbon emissions of the transport industry by using the pathway analysis, and analyses the dependence of carbon emissions on the truck model through visualisation. The results show that the direct throughput coefficients of GDP of the secondary industry, freight turnover, and the structure of truck models are 0.590, 0.317, and 0.204, respectively, indicating that the economic growth has a positive pulling effect on the carbon emissions of the transport industry, and the reliance on the other two types of indicators is small. The indirect throughput coefficients were 0.358, 0.619 and 0.613, indicating that transport development and model structure are highly dependent on the economy, and that adjusting the model structure with the help of economic development can effectively promote the implementation of emission reduction measures.
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