Crashing detecting and warning method based on vehicle network technology

A technology of collision detection and Internet of Vehicles, applied in the direction of collision avoidance system, etc., can solve the problems of collision warning system availability discount, large safety distance error, strict network requirements, etc., to reduce calculation workload, avoid collisions, and make accurate judgments Effect

Inactive Publication Date: 2015-09-02
DONGHUA UNIV
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  • Abstract
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  • Claims
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Problems solved by technology

Although these methods can predict the possibility of vehicle collision, since the shape of the vehicle is generally a rectangle, only the vehicle is regarded as a dot, and the error in judging the safe distance is very large.
In terms of real-time performance, due to the continuo

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  • Crashing detecting and warning method based on vehicle network technology
  • Crashing detecting and warning method based on vehicle network technology
  • Crashing detecting and warning method based on vehicle network technology

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Embodiment Construction

[0035] Below in conjunction with specific embodiment, further illustrate the present invention. It should be understood that these examples are only used to illustrate the present invention and are not intended to limit the scope of the present invention. In addition, it should be understood that after reading the teachings of the present invention, those skilled in the art can make various changes or modifications to the present invention, and these equivalent forms also fall within the scope defined by the appended claims of the present application.

[0036] Embodiments of the present invention relate to a vehicle collision warning method based on VANETS (such as figure 1 As shown), it makes full use of the vehicle's historical driving data, digital map information, real-time vehicle location information and ground information to establish a vehicle trajectory prediction model to predict the possibility of vehicle collisions, and finally reminds the driver of relevant road c...

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Abstract

The invention relates to a crashing detecting and warning method based on vehicle network technology. The method comprises the following steps: collecting vehicle information and driving information; establishing a track model with the assistance of historical driving data and an electronic map of a vehicle and according to current driving information of the vehicle for predicting the track of the vehicle in the future n seconds; and judging if there exists danger of crashing according to a security boundary of the vehicle at a moment in the future, and performing warning if the danger of crashing exists. Track information of surrounding vehicles is known through a wireless receiving-transmitting module for receiving and transmitting a vehicle network broadcast protocol dada packet. According to the invention, a driver can be warned in time to avoid the danger, and the driving efficiency with the precondition of ensured security is improved.

Description

technical field [0001] The invention relates to the technical field of automobile safety, in particular to a collision detection and early warning method based on Internet of Vehicles technology. Background technique [0002] In recent years, with the popularity of automobiles, traffic problems such as vehicle collisions have become more and more serious, and frequent traffic accidents have seriously threatened the safety of people's lives and properties. If the warning can be sent to the driver before the traffic accident occurs, and the driver is reminded to take certain anti-collision measures, the occurrence of traffic accidents can be effectively prevented and reduced, and the efficiency of vehicle traffic can be improved. Therefore, many institutions at home and abroad are researching the automobile collision warning system in order to improve the active safety of automobile driving. [0003] Traditionally, collisions are predicted based on information from radar and ...

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Application Information

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IPC IPC(8): G08G1/16
Inventor 黄秋波刘飞
Owner DONGHUA UNIV
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