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Driving behavior recognition method based on adaptive resonance theory mutation algorithm

An adaptive and behavioral technology, applied in the field of driving behavior recognition, can solve the problems of not considering the driver's influence and low recognition rate

Active Publication Date: 2017-02-01
HEFEI UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although the existing technical methods can effectively realize driving behavior recognition, they mainly analyze and study the driver's behavior characteristics and behavior recognition, and do not consider the influence of the driver's individual characteristics on driving behavior recognition, resulting in a low actual recognition rate.

Method used

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  • Driving behavior recognition method based on adaptive resonance theory mutation algorithm
  • Driving behavior recognition method based on adaptive resonance theory mutation algorithm
  • Driving behavior recognition method based on adaptive resonance theory mutation algorithm

Examples

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Embodiment Construction

[0064] In this example, if figure 1 As shown, a driving behavior recognition method based on adaptive resonance theory variant algorithm is carried out as follows:

[0065] Step 1. Use the on-board sensors to collect N sets of original manipulation data with a duration of T for the driver's H types of driving behavior, denoted as U H×N ; The driving behavior involved in the specific implementation process includes four types of acceleration (deceleration), steering, merging, and overtaking, that is, H=4; the value of T is the average of the driver's longest time-consuming driving behavior manipulation Duration, the unit is s; thus obtain H×N groups of original manipulation data with a duration of T;

[0066] Step 2. The nth group of raw manipulation data of the collected hth driving behavior carry out preprocessing; Represents the k-th type of manipulation action data in the n-th group of original manipulation data of the h-th type of driving behavior; and has Indicat...

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Abstract

The invention discloses a driving behavior recognition method based on an adaptive resonance theory mutation algorithm. The driving behavior recognition method comprises the following steps of: 1) utilizing a vehicle-mounted sensor to collect the driving behavior manipulation data of a driver, preprocessing the driving behavior manipulation data, and extracting corresponding driving manipulation action; 2) constructing the driving behavior manipulation mode of the driver; 3) constructing the driving behavior recognition method based on the adaptive resonance theory mutation algorithm; 4) independently inputting all driving behavior manipulation modes into a network to finish the memorization of all driving behaviors in one time; and 5: inputting any driving behavior manipulation mode, and then, identifying the corresponding driving behavior by the network so as to exhibit the characteristic of on-line increment self learning. The driving behavior recognition method can more approach to the personality characteristics of the driving manipulation of drivers so as to improve the recognition rate of the driving behavior.

Description

technical field [0001] The invention is a driving behavior recognition method based on a variant algorithm of adaptive resonance theory, which is used to solve the inconsistency between the traditional driving behavior recognition technology and the driver's individual characteristics, and belongs to the technical field of driving behavior recognition. Background technique [0002] The statistical results of the causes of traffic accidents show that 80%-90% of traffic accidents are caused by the driver's individual factors, while the traffic accidents caused by vehicles and environmental factors only account for 10-20%. The data fully demonstrates the core position and role of drivers in traffic accident prevention. Drivers are not only information processors and decision makers of the road traffic system, but also regulators and controllers. Whether their behavior is safe or not has a major impact on the state of the entire system . However, in the actual driving process, ...

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Application Information

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IPC IPC(8): G06K9/00G06N3/02
CPCG06N3/02G06V20/597
Inventor 肖献强周凌侃王家恩殷延杰
Owner HEFEI UNIV OF TECH
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