A multi-scenario lane departure warning system and method

Abstract

The invention discloses a multi-scene lane departure early warning decision-making method. The early warning decision-making method divides a vehicle early warning environment into three scenes, including a high-speed curve, a low-speed curve and a low-speed straight road according to different current road situations and vehicle driving speeds; according to advantages and disadvantages in a process that various algorithms are applied and according to the early warning requirement of the practical running of the vehicle, a proper early warning decision-making algorithm is selected to realize alane departure early warning applied to multiple scenes, false alarms brought since a traditional early warning method adopts a single lane departure early warning decision-making algorithm are greatly reduced, the driving behaviors of drivers during high-speed driving can be effectively normalized, and early warning accuracy when the vehicle is driven on the curve is increased.

Description

technical field [0001] The invention belongs to the technical field of automobile active safety, and in particular relates to a multi-scenario lane departure warning system and method. Background technique [0002] The increasingly significant influence of traffic safety issues has given birth to and promoted the continuous development of the field of automotive active safety technology. , the system makes a judgment in advance and warns the driver) Intelligently judges the deviation state of the target vehicle through the vehicle electronic control system, and warns the driver in advance, thus greatly reducing the risk caused by driver fatigue, long-term driving or The lane departure caused by the loss of control of the steering system can reduce the occurrence of collision accidents. [0003] Most of the existing lane departure systems use a single algorithm combined with other vehicles or road conditions to judge the departure state of the target vehicle, and there is a ...

AI Technical Summary

Problems solved by technology

[0003] Most of the existing lane departure systems use a single algorithm combined with other vehicles or road conditions to judge the deviation state of the target vehicle, and there is a certain judgment bias; most of the estimation algorithms used are based on time or distance to calculate the threshold, and do not consider the driver's curve crossing. Driving habits, in which there are certain false alarms, causing the driver's driving troubles; at the same time, the system is not suitable for complex road environments where it is difficult to detect lane lines such as unstructured roads

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