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driving style Recognition System Using Smartphone Sensors Based on Fuzzy Logic

Computers, Materials & Continua 2021年第11期69卷 1967-1978页

作者： Nidhi Kalra Raman Kumar Goyal Anshu Parashar Jaskirat Singh Gagan Singla Department of Computer Science and Engineering Thapar Institute of Engineering and TechnologyPatiala147001PunjabIndia Computer Science and Engineering University Institute of Engineering and TechnologyPanjab University160014ChandigarhIndia

Every 24 seconds,someone dies on the road due to road accidents and it is the 8th leading cause of death and the first among children aged 15–29 years.1.35 million people globally die every year due to road traffic crashes.An additional 20–50 million suffer from non-fatal injuries,often resulting in longterm disabilities.This costs around 3%of Gross Domestic Product to most countries,and it is a considerable economic loss.The governments have taken various measures such as better road infrastructures and strict enforcement of motor-vehicle laws to reduce these accidents.However,there is still no remarkable reduction in the number of accidents.To ensure driver safety and achieve vision of zero accidents,there is a great need to monitor drivers’driving styles.Most of the existing driving behavior monitoring solutions are based on expensive hardware sensors.As most people are using smartphones in the modern era,a system based on mobile application is proposed,which can reduce the cost for developing intelligent transport systems(ITS)to a large extent.In this paper,we utilize the accelerometer sensor data and the global positioning system(GPS)sensor deployed in smartphones to recognize driving and speeding events.A driving style recognition system based on fuzzy logic is designed to classify different driving styles and control reckless driving by taking the longitudinal/lateral acceleration and speed as input parameters.Thus,the proposed system uses fuzzy logic rather than taking the crisp values of the sensors.Results indicate that the proposed system can classify reckless driving based on fuzzy logic and,therefore,reduce the number of accidents.

关键词： Fuzzy logic accelerometer global positioning system driving style

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Study on the driving style Adaptive Vehicle Longitudinal Control Strategy

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IEEE/CAA Journal of Automatica Sinica 2020年第4期7卷 1107-1115页

作者： Jing Huang Yimin Chen Xiaoyan Peng Lin Hu Dongpu Cao the State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangsha 410082China the Department of Mechanical and Mechatronics Engineering University of WaterlooWaterlooON N2L3G1Canada the College of Mechanical&Vehicle Engineering Hunan UniversityChangsha 410082China the School of Automotive and Mechanical Engineering and Hunan Province Key Laboratory of Safety Design and Reliability Technology for Engineering VehicleChangsha University of Science and TechnologyChangsha 410114China

This paper presents a fusion control strategy of adaptive cruise control(ACC) and collision avoidance(CA),which takes into account a driver’s behavioral style. First, a questionnaire survey was performed to identify driver type, and the corresponding driving behavioral data were collected via driving simulator experiments, which served as the template data for the online identification of driver type. Then, the driveradaptive ACC/CA fusion control strategy was designed, and its effect was verified by virtual experiments. The results indicate that the proposed control strategy could achieve the fusion control of ACC and CA successfully and improve driver adaptability and comfort.

关键词： Adaptive cruise control collision avoidance driving simulator experiment driving style fusion control

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An Iterative Optimization Algorithm for Vehicle Speed Prediction Considering driving style and Historical Data Effects

An Iterative Optimization Algorithm for Vehicle Speed Predic...

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第40届中国控制会议

作者： Hui Xie Dong Hu Kang Song Tianjin University

For vehicles, knowledge of the complete route characteristics at the beginning of a trip is beneficial for improving the driving safety, mobility, and energy efficiency. However, prediction of vehicle speed is difficult due to limited information about driver behaviors and traffic flow. In this paper, an iterative optimization algorithm for vehicle speed prediction is proposed. First,the global speed is predicted based on historical data, utilizing multiple Gaussian process regression（GPR） for different driving styles. Then the multiple GPR sub-models are integrated adaptively by learning from the real driving scenarios. A local speed prediction algorithm for a few seconds ahead is developed based on the long short-term memory（LSTM） neural network. Finally,the local and global prediction results are fused to form compound speed by the Markov transition probability matrix. The proposed algorithm is validated in experiments over to a 300 meters route ahead of a traffic light. Results show that the proposed solution can gradually improve the prediction performance, and up to 70.67% reduction in prediction error can be achieved relative to conventional GPR based solution.

关键词： Speed prediction driving style GPR LSTM Markov transition probability matrix

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Safety Evaluation of Commercial Vehicle driving Behavior Using the AHP–CRITIC Algorithm

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 126-135页

作者：庞娜罗文广吴若园蓝红莉覃永新苏琦 School of Electrical and Information Engineering Guangxi Key Laboratory of Auto Parts and Vehicle TechnologyGuangxi University of Science and TechnologyLiuzhou 545006GuangxiChina Liuzhou OVM Machinery Co. Ltd.Liuzhou 545005GuangxiChina

To prevent and reduce road traffic accidents and improve driver safety awareness and bad driving be-haviors,we propose a safety evaluation method for commercial vehicle driving behavior.Three driving style clas-sification indexes were extracted using driving data from commercial vehicles and four primary and ten secondary safety evaluation indicators.Based on the stability of commercial vehicles transporting goods,the acceleration index is divided into three levels according to the statistical third quartile,and the evaluation expression of the safety index evaluation is established.Drivers were divided into conservative,moderate,and radical using K-means++.The weights corresponding to each index were calculated using a combination of the analytic hierarchy process(AHP)and criteria importance through intercriteria correlation(CRITIC),and the driving behavior scores of various drivers were calculated according to the safety index score standard.The established AHP-CRITIC safety evaluation model was verified using the actual driving behavior data of commercial vehicle drivers.The calculation results show that the proposed evaluation model can clearly distinguish between the types of drivers with different driving styles,verifying its rationality and validity.The evaluation results can provide a reference for transportation management departments and enterprises.

关键词： commercial vehicle driving behavior analytic hierarchy process(AHP) criteria importance through intercriteria correlation(CRITIC) safety evaluation driving style

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Real-time comprehensive driving ability evaluation algorithm for intelligent assisted driving

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Green Energy and Intelligent Transportation 2023年第2期2卷 40-55页

作者： Fang Liu Feng Xue Wanru Wang Weixing Su Yang Liu Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tiangong UniversityTianjin 300387China BBT-E-6 Complete Vehicle BMW Brilliance Automotive Ltd.Shenyang Liaoning 110098China

To meet the needs of the human-machine co-driving decision problem in the intelligent assisted driving system for real-time comprehensive driving ability evaluation of drivers,this paper proposes a real-time comprehensive driving ability evaluation method that integrates driving skill,driving state,and driving style.Firstly,by analyzing the driving experiment data obtained based on the intelligent driving simulation platform(the experiment can effectively distinguish the driver's driving skills and avoid the interference of driving style),the feature values that significantly represent driving skills and driving state are selected,and the time correlation between driving state and driving skills is pointed out.Furthermore,the concept of relativity in comprehensive driving ability evaluation is further proposed.Under this concept,the natural driving trajectory dataset-HighD is used to establish the distribution map of feature values of the human driver group as the evaluation benchmark to realize the relative evaluation of driving skill and driving state.Similarly,HighD is used to establish a distribution map of human driver style feature values as an evaluation benchmark to achieve relative driving style evaluation.Finally,a comprehensive driving ability evaluation model with a“punishment”and“affirmation”mechanism is proposed.The experimental comparative analysis shows that the evaluation algorithm proposed in this paper can take into account the driver's driving skill,driving state,and driving style in the real-time comprehensive driving ability evaluation,and draw differential evaluation conclusions based on the“punishment”and“affirmation”mechanism model to achieve a comprehensive and objective evaluation of the driver's driving ability.It can meet the needs of human-machine shared driving decisions for driver's driving ability evaluation.

关键词： driving ability evaluation driving style Unsupervised decision tree Gaussian kernel function Human-machine shared control

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Effect of gender and personality characteristics on the speed tendency based on advanced driving assistance system(ADAS)evaluation

Journal of Intelligent and Connected Vehicles

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Journal of Intelligent and Connected Vehicles 2021年第1期4卷 28-37页

作者： Cunshu Pan Jin Xu Jinghou Fu Chongqing Jiaotong University ChongqingChina

Purpose–This study aims to explore the relationship between speed behavior of participants and driving styles on interchange ramps.A spiral interchange in Chongqing was selected as an experimental road to carry outﬁeld driving experiment.Design/methodology/approach–The continuous operating speed during experiment was selected by Mobile Eye,and the driving style was selected via two inventories.Findings–Different driving behaviors showed great differences in age,driving mileage and driving experience.During driving process,male pursued driving stimulation more,whereas female pursued driving steadiness more.Therefore,driving characteristics of male were more disadvantageous to driving safety than that of female.Except for the large speed difference at the entrance and exit of the ramps,the differences at other positions were small.And the operating speed of male was slightly higher than that of female.The difference between different genders at the ascending end position achieved 4–5 kph,and the difference at other feature points were mostly 1–2 kph.During driving process,risky participants were more likely to pursue driving stimulation,and the poor speed control behavior was reﬂected in wide range of desired operating speed.Based on the results of analyzing at feature points,melancholy and sanguine participants more tended to take a high operating speed,and the poor speed control behavior was reﬂected in the most widely desired speed range.The speed control behavior of mixed participants was more cautious.Originality/value–Advanced driving assistance system combined with two inventories was used to explore difference of speed behavior.

关键词： driving style Interchange MDSI-C Speed behavior TTI

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基于车联网大数据的车险费率因子分析

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统计与精算 2018年第3期 90-100页

作者：高光远孟生旺

随着车联网技术的不断成熟，车联网数据的应用价值日渐凸显。车联网大数据中包含着丰富的驾驶行为信息，这些信息对于改进传统的汽车保险定价模型具有重要的应用价值。如何从车联网大数据中提取出具有实际应用价值的信息，尚需进行大量... 详细信息

随着车联网技术的不断成熟，车联网数据的应用价值日渐凸显。车联网大数据中包含着丰富的驾驶行为信息，这些信息对于改进传统的汽车保险定价模型具有重要的应用价值。如何从车联网大数据中提取出具有实际应用价值的信息，尚需进行大量细致的研究工作。本文基于车联网记录的速度—加速度数据，应用核密度估计和主成分分析，提取了一个驾驶行为因子，并在泊松分布假设下建立了索赔频率的广义可加模型。实证研究结果表明，本文提取的驾驶行为因子对被保险车辆的索赔频率具有十分显著的非线性影响，为汽车保险定价提供了一个新的费率因子，有助于进一步提高汽车保险定价结果的准确性和合理性。

关键词：车联网大数据汽车保险费率因子驾驶行为索赔频率　　telematics big data car insurance rating factor driving style claims frequencies

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