Driving Behavior Analysis of Intelligent Vehicle System for Lane Detection Using Vision-Sensor

Dewangan, Deepak Kumar; Sahu, Satya Prakash

doi:10.1109/jsen.2020.3037340

Cited by 49 publications

(10 citation statements)

References 36 publications

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“…The pooling layer is also based on a fixed size. The scale is downsampling, so that the receptive field of the feature image can be enlarged according to the scale [8,9]. Then, the obtained feature information is mapped to a fixed-length feature vector through the fully connected layer to achieve the effect of classification.…”

Section: Mutation Detection and Functional Study Inmentioning

confidence: 99%

Mutation Detection and Functional Analysis of MSX1, PAX9, AXIN2, and BMP in Nonsyndromic Congenital Missing Teeth Based on Intelligent Image Detection

Yao

Zhang

Gao

et al. 2022

BioMed Research International

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Due to the complexity of clinical manifestations and the lack of standardized diagnostic criteria, it is still difficult to distinguish the etiological types of congenital edentulousness corresponding to genetic defects. This paper studies the application of deep learning image processing and digital image processing in medical images in detail and analyzes the functions of congenital edentulous hotspot genes. The cases in the control group and the study group were collected, and the gene mutations of direct sequence MSX1, PAX9, AXIN2, and BMP were analyzed, and new pathogens were found. The experimental results suggest that PAX9 and MSX1 genes may have a synergistic effect in nonsyndromic congenital edentulous patients. In severely missing teeth, the role of PAX9 may be greater than that of MSX1. The experimental results will help us lay the foundation for further understanding of the disease in the future.

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Section: Mutation Detection and Functional Study Inmentioning

confidence: 99%

Mutation Detection and Functional Analysis of MSX1, PAX9, AXIN2, and BMP in Nonsyndromic Congenital Missing Teeth Based on Intelligent Image Detection

Yao

Zhang

Gao

et al. 2022

BioMed Research International

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show abstract

“…The main purpose of fitting is to depict the lane markings on a picture and to display the location in the road image [27]. In laneline clustering and fitting algorithms, the commonly used road models are linear, linear parabola, least-squares (LS) curve fitting, cubic curve, and Bezier curve fitting [28,29].…”

Section: Clustering Andmentioning

confidence: 99%

A Real-Time Complex Road AI Perception Based on 5G-V2X for Smart City Security

Yi-nong

et al. 2022

Wireless Communications and Mobile Computing

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The Internet of Vehicles and information security are key components of a smart city. Real-time road perception is one of the most difficult tasks. Traditional detection methods require manual adjustment of parameters, which is difficult, and is susceptible to interference from object occlusion, light changes, and road wear. Designing a robust road perception algorithm is still challenging. On this basis, we combine artificial intelligence algorithms and the 5G-V2X framework to propose a real-time road perception method. First, an improved model based on Mask R-CNN is implemented to improve the accuracy of detecting lane line features. Then, the linear and polynomial fitting methods of feature points in different fields of view are combined. Finally, the optimal parameter equation of the lane line can be obtained. We tested our method in complex road scenes. Experimental results show that, combined with 5G-V2X, this method ultimately has a faster processing speed and can sense road conditions robustly under various complex actual conditions.

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“…After introducing the working principle of each module in the system, the information transmission relationship between each module is given [18]. In order to predict the behavior of intelligent vehicles to other vehicles at intersections, Dewangan and Sahu designed finite state machine models for straight-ahead and turning-through intersections, and then combined with safety judgment rules, and realized the safe passage of intelligent vehicles at intersections [19]. Li et al simulated the control method in the second simulation software and analyzed the applicable conditions of the control method in the single-intersection multiphase signal control through the obtained evaluation data [20].…”

Section: Related Workmentioning

confidence: 99%

Game Algorithm of Intelligent Driving Vehicle Based on Left-Turn Scene of Crossroad Traffic Flow

Guo

Sun

Zhang

2022

Computational Intelligence and Neuroscience

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Vehicle networking and autonomous driving are hot areas of scientific research today, and they complement each other and play an important role in people’s intelligent travel. Intelligent driving vehicle can enhance road safety, effectively reduce traffic flow and fuel consumption, and promote the overall social development. It has great application value in urban traffic system. The traffic condition of a city directly affects the economic development of the city and the improvement of people’s quality of life. As the “core” of the urban traffic network, intersections are the frequent places where traffic jams occur. Game theory, as a win-win theory, mainly solves the problem of multiperson and multi-objective with contradictory objective functions and can be used to study the optimal signal control strategy. Aiming at this problem, the potential conflict behaviors of intelligent driving vehicles when turning left at urban intersections are analyzed and a decision model is established. A long-term trajectory prediction model of straight vehicles is established based on the Gaussian process regression model (GPR) considering the vehicle motion pattern. Combined with trajectory prediction, a decision-making process (model) for intelligent driving vehicles based on conflict resolution and a multifactor driving action selection method are proposed. A coordination algorithm based on game theory is designed for conflicting vehicles. The proposed algorithm is verified by the self-developed intelligent vehicle hardware simulation platform. The simulation results show that the PID method based on digital identification and positioning makes the intelligent vehicle obtain good system step response, can improve the disturbance tracking ability of intersection turning analysis, meet the requirements of turning control system, and reduce the complexity and randomness of parameter design, which is better than the traditional fuzzy control method.

show abstract

Driving Behavior Analysis of Intelligent Vehicle System for Lane Detection Using Vision-Sensor

Cited by 49 publications

References 36 publications

Mutation Detection and Functional Analysis of MSX1, PAX9, AXIN2, and BMP in Nonsyndromic Congenital Missing Teeth Based on Intelligent Image Detection

Mutation Detection and Functional Analysis of MSX1, PAX9, AXIN2, and BMP in Nonsyndromic Congenital Missing Teeth Based on Intelligent Image Detection

A Real-Time Complex Road AI Perception Based on 5G-V2X for Smart City Security

Game Algorithm of Intelligent Driving Vehicle Based on Left-Turn Scene of Crossroad Traffic Flow

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