Method for quickly generating emergency plan of sudden highway traffic accident

A technology for traffic accidents and emergency plans, applied in data processing applications, instruments, calculations, etc., can solve the problems of general handling countermeasures, inability to quickly and effectively solve sudden traffic accidents, and poor practicability, so as to facilitate retrieval and generation, and avoid accidents Omission of information or content distortion, effect of improving retrieval efficiency

Inactive Publication Date: 2012-04-04
SOUTHEAST UNIV
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AI Technical Summary

Benefits of technology

This technology helps prevent accidents caused by unexpectedly occurring roadside vehicles on roads during peak hours without compromising safety measures for other drivers involved. It uses similar characteristics from both types of crashes - that are considered important when identifying potential causes like car collisions at night time. By comparing these features against previous data stored in databases, it becomes easier to find out if there's any problem related to this type of event happening around them.

Problems solved by technology

This patented technology describes how accident situations involving vehicles may lead to damage or even loss of lives during times when there were no other way out without first responders being sent back down roads. Existing methods either took longer than necessary or did little at improving upon them due to lack of realistic data about these types of crashes.

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  • Method for quickly generating emergency plan of sudden highway traffic accident
  • Method for quickly generating emergency plan of sudden highway traffic accident
  • Method for quickly generating emergency plan of sudden highway traffic accident

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Embodiment Construction

[0019] A method for quickly generating an emergency plan for sudden traffic accidents on highways, the specific steps of the method are:

[0020] Step 1) Collect road sudden traffic accidents and sort them out, and obtain the characteristic values ​​x corresponding to i road sudden traffic accident characteristic attributes and i road sudden traffic accident characteristic attributes respectively ni Case X composed of and emergency response plan n , where x ni is the eigenvalue corresponding to the i-th feature attribute of the n-th case, 1≤i≤14, and thus constructed to obtain the construction history case library X:

[0021] X={X 1 , X 2 ,...,X n ,...,X N},

[0022] x 1 , X 2 ,...,X n ,...,X N Respectively for each case collected, X n is any case in the historical case library X, N is the total number of cases in the historical case library X, 1≤n≤N,

[0023] Step 2) Determine the eigenvalue y corresponding to the characteristic attribute of the target sudden traf...

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Abstract

The invention discloses a method for quickly generating emergency plan of sudden highway traffic accident, which relates to a method for quickly generating emergency plan of sudden target traffic accident in combination with sudden target traffic accident information by collecting emergency treatment plans of sudden highway traffic accidents. The specific method comprises the following steps of: collecting sudden highway traffic accidents and collating to create a historical case library; according to received alarm result, determining characteristic value corresponding to feature attribute of the sudden target traffic accident; using K nearest neighbor method to retrieve cases in the historical case library, and determining reference cases; and judging if the sudden target traffic accidents are completely matched with the reference cases, if so, taking emergency treatment part in the reference cases as the emergency plan of treating the sudden target traffic accident, and if not, taking the emergency treatment part in the reference cases as the reference emergency plan of treating the sudden target traffic accident, and adjusting the reference emergency plan to completely treat the sudden target traffic accident.

Description

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Claims

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Application Information

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Owner SOUTHEAST UNIV
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