Driving behavior modeling analysis method based on online car-hailing data

A modeling method and online car-hailing technology, applied in knowledge-based computer systems, registration/instruction of vehicle operation, data processing applications, etc., can solve driver interference, it is difficult to truly reflect driving behavior, and the experiment is expensive And other issues

Pending Publication Date: 2022-05-13
SOUTHEAST UNIV
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Problems solved by technology

[0003] At present, the methods of modeling driving behavior mainly use driving simulators to obtain the driver's behavior characteristics through driving simulation, but this kind of method is expensive to ...

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  • Driving behavior modeling analysis method based on online car-hailing data
  • Driving behavior modeling analysis method based on online car-hailing data
  • Driving behavior modeling analysis method based on online car-hailing data

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Embodiment Construction

[0055] Below in conjunction with specific embodiment and accompanying drawing, further illustrate the present invention, it should be understood that these embodiments are only used to illustrate the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention Modifications in equivalent forms all fall within the scope defined by the appended claims of this application.

[0056] In one embodiment, such as figure 1 As shown, a driving behavior modeling method based on online car-hailing data is provided, which mainly includes the following steps:

[0057] Step (1): Extract online car-hailing trajectory data and order origin and destination data, perform data preprocessing on the original trajectory and order data, and obtain multiple sets of driving characteristics including vehicle speed, acceleration, latitude and longitude informat...

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Abstract

The invention discloses a driving behavior modeling and analysis method based on online car-hailing data, and the method specifically comprises the steps: extracting online car-hailing trajectory data and order origin-destination data, and carrying out the preprocessing, and obtaining a plurality of groups of driving feature sequence data containing speed and acceleration variables; and carrying out driving behavior modeling by adopting an improved nonparametric Bayesian learning model based on a layered Dirichlet process-hidden semi-Markov, and identifying the driving behavior state of the vehicle. Constructing a state space vector to represent the driving style type of the driver, and clustering the driver by adopting an improved K-means clustering algorithm; according to driving behavior state recognition and driving style classification results, driving behavior states of drivers of different styles and types in different traffic operation states can be analyzed. According to the invention, the vehicle driving behavior state is identified and the driver types are divided, so that the analysis of different types of driver driving behaviors in a specific scene is realized.

Description

technical field [0001] The invention relates to a driving behavior modeling and analysis method, in particular to a driving behavior modeling and analysis method based on online car-hailing data. Background technique [0002] Driven by the scientific and technological revolution represented by artificial intelligence in recent years, advanced technologies such as new-generation mobile communication technologies, big data, cloud platforms, and the Internet of Things are organically combined with urban transportation systems, promoting the development of intelligent networked vehicles and intelligent driving. As an important component of the development of intelligent driving and intelligent transportation systems, driving behavior modeling and analysis has received extensive attention and research. By studying the driving behavior in various scenarios, the driving status of the vehicle can be understood in real time, and the driving safety can be effectively improved. On the ...

Claims

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Application Information

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IPC IPC(8): G06Q10/06G06Q50/30G06N5/00G06K9/62G06F16/215G06F16/2458G06F16/29G07C5/08
CPCG06Q10/0639G06Q50/30G06F16/215G06F16/2474G06F16/2477G06F16/29G07C5/0808G07C5/0841G06N5/01G06F18/23213
Inventor 陆文琦芮一康易紫薇吴任飞冉斌
Owner SOUTHEAST UNIV
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