Trip mode identification method based on GPS trajectory data

Abstract

The invention discloses a trip mode identification method based on GPS trajectory data. For trip modes lack of a GPS signal and having an incomplete signal, a subway identification method based on a rule is adopted; and, for other trip modes having normal GPS signal records, a random forest classifier is adopted, and modeling and verification are performed through a combination with the GPS trajectory data. Before trip modes are identified, 4 kinds of characteristic parameters related to mode identification are screened through a characteristic selection process, and all the real trip modes can be accurately identified. The method is not limited by the GPS data and not relied on other data sources, and the method has the advantages of high universality, simple calculation and accurate and reliable identification results; and the method is suitable for trip mode identification based on the GPS trajectory data, and is in favor of large-scale promotion of trip survey based on intelligent mobile phones.

Description

technical field [0001] The invention relates to computer identification technology, in particular to a travel mode identification method based on GPS trajectory data. Background technique [0002] With the popularization of smart phones and the development of GPS positioning technology, more and more attention has been paid to the GPS travel survey based on smart phones. This method can make up for the deficiencies in many traditional residents' travel surveys. Investigators have less burden and so on. [0003] The collected GPS trajectory data needs to be processed by a specific algorithm to obtain the information required for travel research. The identification of travel mode is the most critical step. At present, many researchers use data such as GPS, GIS, GIS+GPS, and accelerometers to identify travel modes, and the identification methods used are mainly based on rules and calculation methods. However, because GIS data is relatively difficult to obtain in China, and w...

AI Technical Summary

Problems solved by technology

However, because GIS data is relatively difficult to obtain in China, and when using GIS data and GPS trajectory matching to identify travel modes such as bus mode identification, the calculation is complicated, the efficiency is low, and the identification effect is not good

The rule-based method is relatively dependent on the data. Once the data source changes, the obtained rules are no longer applicable, and the method has poor versatility. Relevant feature parameters are applied to the same recognition model and overfitting occurs, resulting in a decrease in recognition accuracy

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