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To solve those traffic accidents during conscious lane change of vehicles on highway under dangerous conditions, a new safety lane change model is established on the basis of the lane departure warning system which Jilin University has developed. This model is studied under a typical scenario on highway, and also considered with the actual driver behavior that most vehicles always accelerate during...
Driver's fatigue and spirit distraction has become one of the most important causes for traffic accidents. The detection of drivers mouth state could offer a useful distinguish criterion for judge whether the driver is fatigue or spirit distraction. Based on our research foundation, a new method with certain environmental robustness for driver's face detection and location, mouth detection and location...
Preceding vehicle detection is a major research field of safety assistant driving system. This paper proposed a preceding vehicle detection method based on multi-characteristics fusion. First, the areas of interesting for preceding vehicles are established by using the bottom shadows. Then the preceding vehicles are identified through the fusion of vehicle margin characteristics, texture characteristics...
The vision based cybercar named JLUIV-V is an electric automatic intelligent vehicle developed by Jilin University. This paper first describes the system structure, the design of the navigation line and the numerals. Then, the image segmentation algorithms for variable illuminations and the BP neural network algorithm classifier are introduced. Some image segmentation results of different images under...
For intelligent vehicle and driving assistant system, pedestrian detection technology is an important research held to avoid dangerous traffic accidents. This article puts forward a pedestrian detection algorithm based on edge symmetry. First, lane recognition method is used to get area of interest (AOI) ahead of vehicle. Second, as pedestrian legs have prominent vertical edge symmetry, their symmetrical...
In order to identify navigation lane for an intelligent vehicle more rapidly and exactly, the lane mark edge lines are firstly detected based on Zernike moments, and then lane mark feature points are gained according to certain characters. Based on these points, lane mark line parameters can be acquired rapidly and exactly by using linear regression algorithm. Finally lane mark real-time tracking...
In this paper the vehicle structure, performance parameters and dynamic model of JLUIV5-CyberCar are discussed. An optimal controller is designed to achieve the line path tracking ability, while the curve path tracking ability is guaranteed by a fuzzy controller. To improve the tracking performance of the vehicle steering system in different conditions, controller output collections of JLUIV5-CyberCar...
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