Abstract
With the development of economic integration, Beijing has become more closely connected with surrounding areas, which gradually formed the Beijing metropolitan area (BMA). The authors define the scope of BMA from two dimensions of space and time. BMA is determined to be the built-up area of Beijing and its surrounding 10 districts. Designed questionnaire survey the personal characteristics, family characteristics, and travel characteristics of residents from 10 districts in the surrounding BMA. The statistical analysis of questionnaires shows that the supply of public transportation is insufficient and cannot meet traffic demand. Further, the travel mode prediction model of Softmax regression machine learning algorithm for BMA (SRBM) is established. To further verify the prediction performance of the proposed model, the Multinomial Logit Model (MNL) and Support Vector Machine (SVM), model are introduced to compare the prediction accuracy. The results show that the constructed SRBM model exhibits high prediction accuracy, with an average accuracy of 88.35%, which is 2.83% and 18.11% higher than the SVM and MNL models, respectively. This article provides new ideas for the prediction of travel modes in the Beijing metropolitan area.
Highlights
With the development of society, between urban and cities, the links between urban and regions are increasingly close
This paper uses Python programming to implement the model training and parameter evaluation of the Softmax regression traffic mode prediction model of Beijing Metropolitan area (SRBM). 3/4 of the data set is selected as the training set, and the remaining data is the validation set
This article defines the scope of the Beijing metropolitan area in terms of time and space
Summary
With the development of society, between urban and cities, the links between urban and regions are increasingly close. Traffic problems in the Metropolitan area have become more intensified. Existing transportation services are difficult to fit the contact and development of the Metropolitan area, leading to severe traffic congestion, greatly affecting the various functional functions in the Metropolitan area. Residents in the Metropolitan area, as an important assumption in urban construction, and urban function operation, are facing more severe traffic issues. They usually close up with the construction, service and operation of the city. For the city of Beijing, With the evacuation of "non-capital functions" in Beijing, the problem of lack of transportation
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