Detection method of driver's dangerous driving behavior in night environment

被引：0

作者：

Wang Y. ^{[1
]}

Zou Y. ^{[1
]}

Zhang M.J. ^{[1
]}

Ding P. ^{[1
]}

机构：

[1] College of Automobile and Transportation, Wuxi Institute of Technology, Wuxi

来源：

Advances in Transportation Studies | 2021年 / 2021卷 / Special Issue 3期

关键词：

Dangerous driving behavior; Feature extraction; Least squares ellipse fitting; Night environment;

D O I：

10.53136/97912599449625

中图分类号：

学科分类号：

摘要：

Aiming at the problems of low detection rate and high false alarm rate of traditional driver dangerous driving behavior detection methods, this paper proposes a driver dangerous driving behavior detection method in night driving environment based on least square ellipse fitting algorithm. Based on four dangerous driving behaviors: Sharp turn, continuous lane change, emergency obstacle avoidance and emergency braking, the characteristics of drivers' dangerous driving behavior are extracted. Based on the feature extraction results, the least square ellipse fitting algorithm is used to detect the driver's dangerous driving behavior at night. The experimental results show that the detection rate of this method is high and the false alarm rate is low, which can effectively ensure the driving safety in the night environment. © 2021, Aracne Editrice. All rights reserved.

引用

页码：43 / 54

页数：11

共 21 条

[1]

Atiquzzaman M., Qi Y., Fries R., Real-Time Detection of Drivers' Texting and Eating Behavior Based on Vehicle Dynamics, Transportation Research Part F Traffic Psychology and Behaviour, 58, pp. 594-604, (2018)

[2]

Chen L.W., Chen H.M., Driver Behavior Monitoring and Warning with Dangerous Driving Detection Based on the Internet of Vehicles, IEEE Transactions on Intelligent Transportation Systems, 99, pp. 1-10, (2020)

[3]

Dronseyko V., Pakhomova A., Shalagina E., Driving danger coefficient as a method of evaluating the driver's behavior in road traffic, Transportation Research Procedia, 36, pp. 129-134, (2018)

[4]

Geng L., Yuan F., Xiao Z., Driver Fatigue Detection Method Based on Facial Behavior Analysis, Computer Engineering, (2018)

[5]

Kashevnik A., Lashkov I., Gurtov A., Methodology and Mobile Application for Driver Behavior Analysis and Accident Prevention, IEEE Transactions on Intelligent Transportation Systems, 99, pp. 1-10, (2019)

[6]

Km A., Aa A., Analysis on Characteristics of Dangerous Driving Events via Recorded Data of Drive-Recorder - ScienceDirect, Transportation Research Procedia, 48, pp. 1342-1363, (2020)

[7]

Kovalenko K.E., Kuzmina A.S., Kovalenko N.E., The role of legal consciousness in the implementation of preparedness for the dangerous driving of road drivers, Estagao Cientffica (UNIFAP), 9, 2, pp. 63-70, (2019)

[8]

Liu G., The formulation and implementation mechanism of urban traffic policy based on group behavior, Advances in Transportation Studies, 2021, pp. 45-56, (2021)

[9]

Long J.Y., Zhou H., Dangerous driving behavior detection system based on embedded Neural Networks, Intelligent Computer and Applications, 10, 3, pp. 299-302, (2020)

[10]

Ma L., Chen K., Wang M., A Study on Driver Behavior Identification Method Under Environment of Vehicle-Road Integration, Qiche Gongcheng/Automotive Engineering, 40, 11, pp. 1330-1338, (2018)

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