Simulation models of traction driver systems were established using SIMULINK,according to the actual structure and parameters of China Railway High-Speed 2 (CRH2) and China Railway High-Speed 3 (CRH3) trains.In these ...Simulation models of traction driver systems were established using SIMULINK,according to the actual structure and parameters of China Railway High-Speed 2 (CRH2) and China Railway High-Speed 3 (CRH3) trains.In these models,the traction motor adopts transient current control and an indirect rotor magnetic field orientation vector control strategy,and the traction converter uses sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) methods.After these models are transformed in VC++ program,and a friendly interface and data processing system are constructed,simulation software is obtained for CRH2 and CRH3 traction driver systems.On this basis,the operational performance of a traction converter was simulated and analyzed at different train speeds and in different conditions.The simulation results can provide a reference for the actual design and production of a traction converter.展开更多
The advanced driver assistance system(ADAS)primarily serves to assist drivers in monitoring the speed of the car and helps them make the right decision,which leads to fewer fatal accidents and ensures higher safety.In...The advanced driver assistance system(ADAS)primarily serves to assist drivers in monitoring the speed of the car and helps them make the right decision,which leads to fewer fatal accidents and ensures higher safety.In the artificial Intelligence domain,machine learning(ML)was developed to make inferences with a degree of accuracy similar to that of humans;however,enormous amounts of data are required.Machine learning enhances the accuracy of the decisions taken by ADAS,by evaluating all the data received from various vehicle sensors.This study summarizes all the critical algorithms used in ADAS technologies and presents the evolution of ADAS technology.Initially,ADAS technology is introduced,along with its evolution,to understand the objectives of developing this technology.Subsequently,the critical algorithms used in ADAS technology,which include face detection,head-pose estimation,gaze estimation,and link detection are discussed.A further discussion follows on the impact of ML on each algorithm in different environments,leading to increased accuracy at the expense of additional computing,to increase efficiency.The aim of this study was to evaluate all the methods with or without ML for each algorithm.展开更多
To date,many previous studies have been proposed for driver authentication;however,these solutions have many shortcomings and are still far from practical for real-world applications.In this paper,we tackle the shortc...To date,many previous studies have been proposed for driver authentication;however,these solutions have many shortcomings and are still far from practical for real-world applications.In this paper,we tackle the shortcomings of the existing solutions and reach toward proposing a lightweight and practical authentication system,dubbed DriveMe,for identifying drivers on cars.Our novelty aspects are 1⃝Lightweight scheme that depends only on a single sensor data(i.e.,pressure readings)attached to the driver’s seat and belt.2⃝Practical evaluation in which one-class authentication models are trained from only the owner users and tested using data collected from both owners and attackers.3⃝Rapid Authentication to quickly identify drivers’identities using a few pressure samples collected within short durations(1,2,3,5,or 10 s).4⃝Realistic experiments where the sensory data is collected from real experiments rather than computer simulation tools.We conducted real experiments and collected about 13,200 samples and 22,800 samples of belt-only and seat-only datasets from all 12 users under different settings.To evaluate system effectiveness,we implemented extensive evaluation scenarios using four one-class detectors One-Class Support Vector Machine(OCSVM),Local Outlier Factor(LOF),Isolation Forest(IF),and Elliptic Envelope(EE),three dataset types(belt-only,seat-only,and fusion),and four different dataset sizes.Our average experimental results show that the system can authenticate the driver with an F1 score of 93.1%for seat-based data using OCSVM classifier,an F1 score of 98.53%for fusion-based data using LOF classifier,an F1 score of 91.65%for fusion-based data using IF classifier,and an F1 score of 95.79%for fusion-based data using EE classifier.展开更多
In recent years,soil acidification has been expanding in many areas of Asia due to increasing reactive nitrogen inputs and industrial activities,which may seriously affect the performance of various ecosystem function...In recent years,soil acidification has been expanding in many areas of Asia due to increasing reactive nitrogen inputs and industrial activities,which may seriously affect the performance of various ecosystem functions.However,the underlying patterns and processes of ecosystem multifunctionality(EMF)are largely unknown at different levels of pH,limiting our understanding of how EMF respond to drivers.This study aims to explore threshold of pH on changes in EMF and differences in the drivers for the changes in EMF on either side of each of the determined pH thresholds.We collected nutrient and environmental databases for raster-level sampling data,totaling 4,000 sampling points.Averaging and cluster-multiple-threshold approach were used to calculate EMF,then quadratic and generalized additive models and Mann-Whitney U were used to determine and test the pH thresholds for changes in EMF,structural equation modellings and variance partitioning analysis were used to explore the main drivers on changes in EMF.The pH threshold for EMF changes in Chinese terrestrial ecosystems is 6.0.When pH<6.0,climate was consistently more important in controlling the variation of EMF than other variables;when pH≥6.0,soil was consistently more important in controlling the variation of EMF than other variables.Specifically,when pH<6.0,mean annual temperature was the main factor in regulating the EMF variation;when pH≥6.0,soil moisture was the main factor in regulating the EMF variation.Our study provides important scientific value for the mechanism of maintaining EMF under global change.For example,with further increases in global nitrogen deposition,leading to increased soil acidification,there are different impacts on EMF in different regions.It may lead to a decrease in EMF in acidic soils and an increase in EMF in alkaline soils.This suggests different management strategies for different regions to maintain EMF stability in the context of future global changes.In the future,more attention should be paid to the biological mechanisms regulating EMF.展开更多
Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,th...Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,this study proposes a Climate-Induced Productivity Index(CIPI)based on the Super Slack-Based Measure(Super-SBM)model using remote sensing data from 2001 to 2020.The results reveal persistently low CIPI values(0.47-0.53)across major ecosystem types,indicating widespread vulnerability to climatic variability.Among these ecosystems,forests exhibit the highest CIPI(0.55),followed by shrublands(0.54),croplands(0.53),grasslands(0.51),and barelands(0.43).The Theil index analysis further demonstrates significant intra-group disparities,suggesting that extreme climatic events amplify CIPI heterogeneity.Moreover,the dominant environmental drivers differ among ecosystem types:the Palmer Drought Severity Index(PDSI)primarily constrains grassland productivity,solar radiation(SRAD)strongly influences shrub and cropland systems,whereas subsurface factors exert greater control in forested regions.This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.展开更多
A hardware/software field programmable gate array （FPGA）-based driver system was proposed and demonstrated for the KAF-39000 large area high resolution charge coupled device （CCD）. The requirements of the KAF-3900...A hardware/software field programmable gate array （FPGA）-based driver system was proposed and demonstrated for the KAF-39000 large area high resolution charge coupled device （CCD）. The requirements of the KAF-39000 driver system were analyzed. The structure of ＂microprocessor with application specific integrated circuit （ASIC） chips＂ was implemented to design the driver system. The system test results showed that dual channels of imaging analog data were obtained with a frame rate of 0.87frame/s. The frequencies of horizontal timing and vertical timing were 22.9MHz and 28.7kHz, respectively, which almost reached the theoretical value of 24 MHz and 30kHz, respectively.展开更多
Today,fatalities,physical injuries,and significant economic losses occur due to car accidents.Among the leading causes of car accidents is drowsiness behind the wheel,which can affect any driver.Drowsiness and sleepin...Today,fatalities,physical injuries,and significant economic losses occur due to car accidents.Among the leading causes of car accidents is drowsiness behind the wheel,which can affect any driver.Drowsiness and sleepiness often have associated indicators that researchers can use to identify and promptly warn drowsy drivers to avoid potential accidents.This paper proposes a spatiotemporal model for monitoring drowsiness visual indicators from videos.This model depends on integrating a 3D convolutional neural network(3D-CNN)and long short-term memory(LSTM).The 3DCNN-LSTM can analyze long sequences by applying the 3D-CNN to extract spatiotemporal features within adjacent frames.The learned features are then used as the input of the LSTM component for modeling high-level temporal features.In addition,we investigate how the training of the proposed model can be affected by changing the position of the batch normalization(BN)layers in the 3D-CNN units.The BN layer is examined in two different placement settings:before the non-linear activation function and after the non-linear activation function.The study was conducted on two publicly available drowsy drivers datasets named 3MDAD and YawDD.3MDAD is mainly composed of two synchronized datasets recorded from the frontal and side views of the drivers.We show that the position of the BN layers increases the convergence speed and reduces overfitting on one dataset but not the other.As a result,the model achieves a test detection accuracy of 96%,93%,and 90%on YawDD,Side-3MDAD,and Front-3MDAD,respectively.展开更多
Driver identification in intelligent transport systems has immense demand,considering the safety and convenience of traveling in a vehicle.The rapid growth of driver assistance systems(DAS)and driver identification sy...Driver identification in intelligent transport systems has immense demand,considering the safety and convenience of traveling in a vehicle.The rapid growth of driver assistance systems(DAS)and driver identification system propels the need for understanding the root causes of automobile accidents.Also,in the case of insurance,it is necessary to track the number of drivers who commonly drive a car in terms of insurance pricing.It is observed that drivers with frequent records of paying“fines”are compelled to pay higher insurance payments than drivers without any penalty records.Thus driver identification act as an important information source for the intelligent transport system.This study focuses on a similar objective to implement a machine learning-based approach for driver identification.Raw data is collected from in-vehicle sensors using the controller area network(CAN)and then converted to binary form using a one-hot encoding technique.Then,the transformed data is dimensionally reduced using the Principal Component Analysis(PCA)technique,and further optimal parameters from the dataset are selected using Whale Optimization Algorithm(WOA).The most relevant features are selected and then fed into a Convolutional Neural Network(CNN)model.The proposed model is evaluated against four different use cases of driver behavior.The results show that the best prediction accuracy is achieved in the case of drivers without glasses.The proposed model yielded optimal accuracy when evaluated against the K-Nearest Neighbors(KNN)and Support Vector Machines(SVM)models with and without using dimensionality reduction approaches.展开更多
The key technology of open architecture CNC systems kernel device driver,including the interrupt mechanism, I/O subsystem, the structure of device driver and the communication between the driver and the application p...The key technology of open architecture CNC systems kernel device driver,including the interrupt mechanism, I/O subsystem, the structure of device driver and the communication between the driver and the application program, is discussed in the paper and a specific application is given at the end.展开更多
Deforestation and forest degradation has been observed to be rampant in Masito-Ugalla ecosystem, Kigoma Region, western part of Tanzania. This paper therefore, intended to assess the extent of deforestation and forest...Deforestation and forest degradation has been observed to be rampant in Masito-Ugalla ecosystem, Kigoma Region, western part of Tanzania. This paper therefore, intended to assess the extent of deforestation and forest degradation in the area, and to determine their causes. A total of 101 respondents were considered as the sample size for this study. The methods used for data collection were household questionnaire interviews, in-depth interviews, focus group discussions, analysis of satellite images and direct observation. The findings indicated that deforestation was occurring in the study area. Satellite data revealed diminished closed woodland, bushed grassland, forest and thickets between 1990 and 2014. On the contrary, settlement area, cultivated land and open woodland had increased during the same time frame. Proximate factors causing deforestation and forest degradation included agricultural expansion, wood extraction and expansion of settlement area. Underlying factors included population growth, poverty, poor levels of education, lack of employment, corruption and embezzlement of public funds by politicians and senior government officials;and high demand for fuel-wood. Biophysical drivers like incidences of unplanned wildfires and socio trigger events notably civil strife were also important. In order to minimize the problem and based on the factors augmenting deforestation and forest degradation in the Masito-Ugalla ecosystem and their coupled negative consequences, effective environmental conservation education, increased patrols, effective law enforcement and provision of alternative energy sources are necessary.展开更多
This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies ...This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies and highlights the safety motivations for smart in-car embedded systems. An algorithm is presented that processes RGB image data, extracts relevant pixels, filters the image, labels prospective traffic signs and evaluates them against template traffic sign images. A reconfigurable hardware system is described which uses the Virtex-5 Xilinx FPGA and hardware/software co-design tools in order to create an embedded processor and the necessary hardware IP peripherals. The implementation is shown to have robust performance results, both in terms of timing and accuracy.展开更多
Real-time detection of driver fatigue status is of great significance for road traffic safety.In this paper,a proposed novel driver fatigue detection method is able to detect the driver’s fatigue status around the cl...Real-time detection of driver fatigue status is of great significance for road traffic safety.In this paper,a proposed novel driver fatigue detection method is able to detect the driver’s fatigue status around the clock.The driver’s face images were captured by a camera with a colored lens and an infrared lens mounted above the dashboard.The landmarks of the driver’s face were labeled and the eye-area was segmented.By calculating the aspect ratios of the eyes,the duration of eye closure,frequency of blinks and PERCLOS of both colored and infrared,fatigue can be detected.Based on the change of light intensity detected by a photosensitive device,the weight matrix of the colored features and the infrared features was adjusted adaptively to reduce the impact of lighting on fatigue detection.Video samples of the driver’s face were recorded in the test vehicle.After training the classification model,the results showed that our method has high accuracy on driver fatigue detection in both daytime and nighttime.展开更多
Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lan...Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lane departure warning (LDW), blind spot warning (BSW), over speed warning (OSW), forward collision warning (FCW), lane keep assist (LKA), adaptive cruise control (ACC), cooperative ACC (CACC), and automated emergency braking (AEB) are designed to assist with, or in some cases take over, certain driving maneuvers. They can be broadly categorized into advanced driver assistance system (ADAS) and automated features. Each of these advanced features focuses on addressing a particular task of driving, thereby, aiding the driver, influencing their behavior, and enhancing safety. Many vehicles with these advanced features are penetrating into the market, yet the total reported number of crashes has increased in recent years. This paper presents a systematic review of these advanced features on driver behavior and safety. The review is categorized into 1) survey and mathematical methods to assess driver behavior, 2) field test methods to assess driver behavior, 3) microsimulation methods to assess driver behavior, 4) driving simulator methods to assess driver behavior, and 5) driver understanding and the effectiveness of advanced features. It is followed by conclusions, knowledge gaps, and need for further research.展开更多
Traffic accidents are mainly caused by human error. In an aging society, the number of accidents attributed to elderly drivers is increasing. One noteworthy reason for this is operation misapplication. Studies have be...Traffic accidents are mainly caused by human error. In an aging society, the number of accidents attributed to elderly drivers is increasing. One noteworthy reason for this is operation misapplication. Studies have been conducted on the use of human</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">-</span></span></span><span><span><span style="font-family:""><span style="font-family:Verdana;">machine interfaces (HMIs) to inform the driver when he or she makes an error and encourage appropriate actions. However, the driver state during the erroneous action has not been investigated. The pur</span><span style="font-family:Verdana;">pose of this study is to clarify the difference in the driver’s state between</span><span style="font-family:Verdana;"> normal and surprising situations in a misapplication scenario, utilizing multimodal information such as biometric information and driver operation. We found significant changes in the interaction of components between the nor</span><span style="font-family:Verdana;">mal and the surprised driving state. The results could provide basic know</span><span style="font-family:Verdana;">ledge for the future development of a driver assistance system and driver state estimation using data acquired from multiple sensors in the vehicle.展开更多
The pursuit of human needs and demands is placing more pressure on land resources than ever before. The challenge of feeding 7 billion people is increasingly competing with rising demands for materials and biofuels. D...The pursuit of human needs and demands is placing more pressure on land resources than ever before. The challenge of feeding 7 billion people is increasingly competing with rising demands for materials and biofuels. Deforestation and land degradation are among the pressing outcomes of these trends. Drivers of environmental change—including population growth, economic activity, consumption, urbanization, trade, conflict, and governance—clearly play a role in aggravating or mitigating these pressures on land. Despite advances in understanding causality in complex systems, navigating the interactions between these drivers remains a major challenge. This paper analyzes and visualizes the relationships between multiple, interacting drivers of environmental change and specific pressures on land-based ecosystems. Drawing on experience from the development of the Drivers and Land chapters of the UN Environment Programme’s Fifth Global Environment Outlook report (GEO-5), we use a series of Kiviat diagrams to illustrate the relative influence of key drivers on selected pressures on land. When individual diagrams are overlaid, patterns of influence emerge that can provide insight into where policy responses might best be targeted. We propose that, subject to some limitations, the Kiviat exercise can provide an accessible and potentially valuable “knowledge-intermediary” tool to help link science-based information to policy action.展开更多
Background: The number of older people is increasing. Many of them expect to maintain a rich social life and to continue driving at an older age. Objective: The present study investigates the mechanisms behind self-re...Background: The number of older people is increasing. Many of them expect to maintain a rich social life and to continue driving at an older age. Objective: The present study investigates the mechanisms behind self-regulation and driving cessation in order to suggest development of support systems to prolong older drivers’ safe mobility. Method: Three focus groups were conducted with 19 older active drivers aged 65+ who were divided according to annual mileage driven. Results: A content analysis revealed broad self-regulatory behaviour as already reported in the literature, e.g., avoiding driving at rush hour and at night. The participants also reported difficulty in finding the way to their final destination and an increasing need to plan their travelling. Co-piloting was a behaviour applied by couples to cope with difficulties encountered in traffic. A large part of the discussion was focused on emerging feelings of stress, anxiety and fear when driving in recent years, a feeling induced by external factors e.g., other road users’ behaviour, traffic density or high speed. Apart from health problems, high levels of stress could explain driving cessation, especially for women. An increased feeling of safety and comfort could be achieved by an increased use of support systems specifically designed to respond to older drivers’ needs. Conclusion: Support systems for older drivers should increase comfort and decrease their stress levels. New systems, such as co-pilot function and more developed Global Positioning System (GPS) supporting of the entire travel from door to door, should be developed to respond to the market needs.展开更多
As an universal bus technology at present time,I^(2)C has been widely used in the interface between CPU and other devices such as EEPROM,RTC and small LCD.The architecture of I^(2)C driver,the relationship of some imp...As an universal bus technology at present time,I^(2)C has been widely used in the interface between CPU and other devices such as EEPROM,RTC and small LCD.The architecture of I^(2)C driver,the relationship of some important data structure and the operation mechanism of the I^(2)C driver have been analyzed.Finally,by taking an EEPROM chip named AT24C08 as a specific example,the flow of how to develop an I^(2)C device driver is illustrated.In addition,the design of a new driver mode of single device with multi-drivers is realized.展开更多
Presented in this paper is the development of the driver for the data acquisition card with a peripheral component interconnection （PCI） local bus on the ion cyclotron range of frequency heating （1CRH） system. The...Presented in this paper is the development of the driver for the data acquisition card with a peripheral component interconnection （PCI） local bus on the ion cyclotron range of frequency heating （1CRH） system. The driver is mainly aimed at the embedded VxWorks system （real-time operating system） which is widely used in various fields of real-time systems. An efficient way is employed to develop this driver, which will advance the real-time control of the ICRH system on the experimental advanced superconductor tokamak （EAST）. The driver is designed using the TORNADO integrated development environment （IDE）, and implemented in C plus language. The details include the hardware configuration, analogue/digital （A/D） and digital/analogue （D/A） conversion, input and output （I/O） operation of the driver to support over five cards. The data acquisition card can be manipulated in a low-level program and meet the requirements of A/D conversion and D/A outputs.展开更多
Dear editor,This letter presents a user study to explore the effectiveness of gesture interaction in driver assistance system(DAS).Distracted driving is a specific form of driver inattention and distraction occurs whe...Dear editor,This letter presents a user study to explore the effectiveness of gesture interaction in driver assistance system(DAS).Distracted driving is a specific form of driver inattention and distraction occurs when the drivers'attention is diverted from the driving to other activities.展开更多
As the overall population ages, driving-related accidents and injuries, associated with elderly drivers, have risen. Existing research about elderly drivers mainly focuses on factual data collection and analysis, indi...As the overall population ages, driving-related accidents and injuries, associated with elderly drivers, have risen. Existing research about elderly drivers mainly focuses on factual data collection and analysis, indicating the elderly＇s growing fatal accident rates and their different behaviours compared to younger drivers. However, few research has focused on design-led practical solutions to mitigate the elderly＇s growing fatal accidents, by consid- ering their usability and body conditions, afflicting the elderly, such as decreased vision, hearing, and reaction times. In this paper, first, current worldwide situations on growing fatal accident rates for elderly drivers is reviewed and the key impact factors are identified and discussed with regarding to usability and design trend in the automotive technology for elderly. Second, existing smart vehicle technology-based solutions to promote safe driving are explored and their pros and cons are discussed and anal- ysed. Most of solutions are not created by people with driving difficulties, which are caused by health problems most commonly afflicting the elderly. Thirdly, diverse design-led research activities are taken, such as a survey, observation, and interviews to gain new understanding of what kinds of driving problems elderly drivers have and demonstrate how new system concepts could be developed for the elderly＇s benefits. Finally, it is found that the elderly＇s low vision and late reaction are main factors causing their driving difficulties. Based on this finding, usable vehicle system design ideas have been proposed, by utilising facial expression sensing technology as a solution. The proposed solutions would ensure reducing both the elderly＇s driving problems and high fatal accident rates and provide a more enjoyable driving environment for the elderly population.展开更多
基金Project supported by the National Natural Science Foundation of China(No.50877070)the National Key Technology R&D Program of China(No.2009BAG12A01-A04-2)+1 种基金the Technological R&D Programs of the Ministry of Chinese Railways(No.2010J011-E)the Fundamental Research Funds for the Central Universities(No.2009QNA4016),China
文摘Simulation models of traction driver systems were established using SIMULINK,according to the actual structure and parameters of China Railway High-Speed 2 (CRH2) and China Railway High-Speed 3 (CRH3) trains.In these models,the traction motor adopts transient current control and an indirect rotor magnetic field orientation vector control strategy,and the traction converter uses sinusoidal pulse width modulation (SPWM) and space vector pulse width modulation (SVPWM) methods.After these models are transformed in VC++ program,and a friendly interface and data processing system are constructed,simulation software is obtained for CRH2 and CRH3 traction driver systems.On this basis,the operational performance of a traction converter was simulated and analyzed at different train speeds and in different conditions.The simulation results can provide a reference for the actual design and production of a traction converter.
文摘The advanced driver assistance system(ADAS)primarily serves to assist drivers in monitoring the speed of the car and helps them make the right decision,which leads to fewer fatal accidents and ensures higher safety.In the artificial Intelligence domain,machine learning(ML)was developed to make inferences with a degree of accuracy similar to that of humans;however,enormous amounts of data are required.Machine learning enhances the accuracy of the decisions taken by ADAS,by evaluating all the data received from various vehicle sensors.This study summarizes all the critical algorithms used in ADAS technologies and presents the evolution of ADAS technology.Initially,ADAS technology is introduced,along with its evolution,to understand the objectives of developing this technology.Subsequently,the critical algorithms used in ADAS technology,which include face detection,head-pose estimation,gaze estimation,and link detection are discussed.A further discussion follows on the impact of ML on each algorithm in different environments,leading to increased accuracy at the expense of additional computing,to increase efficiency.The aim of this study was to evaluate all the methods with or without ML for each algorithm.
基金supported by the Institute of Information&Communications Technology Planning&Evaluation(1ITP)(Project Nos.RS-2024-00438551,30%,2022-11220701,30%,2021-0-01816,30%)the National Research Foundation of Korea(NRF)grant funded by the Korean Government(Project No.RS2023-00208460,10%).
文摘To date,many previous studies have been proposed for driver authentication;however,these solutions have many shortcomings and are still far from practical for real-world applications.In this paper,we tackle the shortcomings of the existing solutions and reach toward proposing a lightweight and practical authentication system,dubbed DriveMe,for identifying drivers on cars.Our novelty aspects are 1⃝Lightweight scheme that depends only on a single sensor data(i.e.,pressure readings)attached to the driver’s seat and belt.2⃝Practical evaluation in which one-class authentication models are trained from only the owner users and tested using data collected from both owners and attackers.3⃝Rapid Authentication to quickly identify drivers’identities using a few pressure samples collected within short durations(1,2,3,5,or 10 s).4⃝Realistic experiments where the sensory data is collected from real experiments rather than computer simulation tools.We conducted real experiments and collected about 13,200 samples and 22,800 samples of belt-only and seat-only datasets from all 12 users under different settings.To evaluate system effectiveness,we implemented extensive evaluation scenarios using four one-class detectors One-Class Support Vector Machine(OCSVM),Local Outlier Factor(LOF),Isolation Forest(IF),and Elliptic Envelope(EE),three dataset types(belt-only,seat-only,and fusion),and four different dataset sizes.Our average experimental results show that the system can authenticate the driver with an F1 score of 93.1%for seat-based data using OCSVM classifier,an F1 score of 98.53%for fusion-based data using LOF classifier,an F1 score of 91.65%for fusion-based data using IF classifier,and an F1 score of 95.79%for fusion-based data using EE classifier.
基金This work was supported by the Tianshan Programme of Excellence(2022TSYCCX0001)the National Key Program for Basic Research and Development(973 Program)(2012CB417101)。
文摘In recent years,soil acidification has been expanding in many areas of Asia due to increasing reactive nitrogen inputs and industrial activities,which may seriously affect the performance of various ecosystem functions.However,the underlying patterns and processes of ecosystem multifunctionality(EMF)are largely unknown at different levels of pH,limiting our understanding of how EMF respond to drivers.This study aims to explore threshold of pH on changes in EMF and differences in the drivers for the changes in EMF on either side of each of the determined pH thresholds.We collected nutrient and environmental databases for raster-level sampling data,totaling 4,000 sampling points.Averaging and cluster-multiple-threshold approach were used to calculate EMF,then quadratic and generalized additive models and Mann-Whitney U were used to determine and test the pH thresholds for changes in EMF,structural equation modellings and variance partitioning analysis were used to explore the main drivers on changes in EMF.The pH threshold for EMF changes in Chinese terrestrial ecosystems is 6.0.When pH<6.0,climate was consistently more important in controlling the variation of EMF than other variables;when pH≥6.0,soil was consistently more important in controlling the variation of EMF than other variables.Specifically,when pH<6.0,mean annual temperature was the main factor in regulating the EMF variation;when pH≥6.0,soil moisture was the main factor in regulating the EMF variation.Our study provides important scientific value for the mechanism of maintaining EMF under global change.For example,with further increases in global nitrogen deposition,leading to increased soil acidification,there are different impacts on EMF in different regions.It may lead to a decrease in EMF in acidic soils and an increase in EMF in alkaline soils.This suggests different management strategies for different regions to maintain EMF stability in the context of future global changes.In the future,more attention should be paid to the biological mechanisms regulating EMF.
基金National Key R&D Program of China,No.2022YFF1302401National Natural Science Foundation of China,No.42271007。
文摘Ecosystems along the eastern margin of the Qinghai-Tibet Plateau(EQTP)are highly fragile and extremely sensitive to climate change and human disturbances.To quantitatively assess climate-induced ecosystem responses,this study proposes a Climate-Induced Productivity Index(CIPI)based on the Super Slack-Based Measure(Super-SBM)model using remote sensing data from 2001 to 2020.The results reveal persistently low CIPI values(0.47-0.53)across major ecosystem types,indicating widespread vulnerability to climatic variability.Among these ecosystems,forests exhibit the highest CIPI(0.55),followed by shrublands(0.54),croplands(0.53),grasslands(0.51),and barelands(0.43).The Theil index analysis further demonstrates significant intra-group disparities,suggesting that extreme climatic events amplify CIPI heterogeneity.Moreover,the dominant environmental drivers differ among ecosystem types:the Palmer Drought Severity Index(PDSI)primarily constrains grassland productivity,solar radiation(SRAD)strongly influences shrub and cropland systems,whereas subsurface factors exert greater control in forested regions.This study provides a quantitative framework for evaluating climate-ecosystem interactions and offers a scientific basis for long-term ecological monitoring and security planning across the EQTP.
文摘A hardware/software field programmable gate array （FPGA）-based driver system was proposed and demonstrated for the KAF-39000 large area high resolution charge coupled device （CCD）. The requirements of the KAF-39000 driver system were analyzed. The structure of ＂microprocessor with application specific integrated circuit （ASIC） chips＂ was implemented to design the driver system. The system test results showed that dual channels of imaging analog data were obtained with a frame rate of 0.87frame/s. The frequencies of horizontal timing and vertical timing were 22.9MHz and 28.7kHz, respectively, which almost reached the theoretical value of 24 MHz and 30kHz, respectively.
文摘Today,fatalities,physical injuries,and significant economic losses occur due to car accidents.Among the leading causes of car accidents is drowsiness behind the wheel,which can affect any driver.Drowsiness and sleepiness often have associated indicators that researchers can use to identify and promptly warn drowsy drivers to avoid potential accidents.This paper proposes a spatiotemporal model for monitoring drowsiness visual indicators from videos.This model depends on integrating a 3D convolutional neural network(3D-CNN)and long short-term memory(LSTM).The 3DCNN-LSTM can analyze long sequences by applying the 3D-CNN to extract spatiotemporal features within adjacent frames.The learned features are then used as the input of the LSTM component for modeling high-level temporal features.In addition,we investigate how the training of the proposed model can be affected by changing the position of the batch normalization(BN)layers in the 3D-CNN units.The BN layer is examined in two different placement settings:before the non-linear activation function and after the non-linear activation function.The study was conducted on two publicly available drowsy drivers datasets named 3MDAD and YawDD.3MDAD is mainly composed of two synchronized datasets recorded from the frontal and side views of the drivers.We show that the position of the BN layers increases the convergence speed and reduces overfitting on one dataset but not the other.As a result,the model achieves a test detection accuracy of 96%,93%,and 90%on YawDD,Side-3MDAD,and Front-3MDAD,respectively.
基金This work is supported by the Research on Big Data Application Technology of Smart Highway(No.2016Y4)Analysis and Judgment Technology and Application of Highway Network Operation Situation Based on Multi-source Data Fusion(No.2018G6)+1 种基金Highway Multisource Heterogeneous Data Reconstruction,Integration,and Supporting and Sharing Packaged Technology(No.2019G-2-12)Research onHighway Video Surveillance and Perception Packaged Technology Based on Big Data(No.2019G1).
文摘Driver identification in intelligent transport systems has immense demand,considering the safety and convenience of traveling in a vehicle.The rapid growth of driver assistance systems(DAS)and driver identification system propels the need for understanding the root causes of automobile accidents.Also,in the case of insurance,it is necessary to track the number of drivers who commonly drive a car in terms of insurance pricing.It is observed that drivers with frequent records of paying“fines”are compelled to pay higher insurance payments than drivers without any penalty records.Thus driver identification act as an important information source for the intelligent transport system.This study focuses on a similar objective to implement a machine learning-based approach for driver identification.Raw data is collected from in-vehicle sensors using the controller area network(CAN)and then converted to binary form using a one-hot encoding technique.Then,the transformed data is dimensionally reduced using the Principal Component Analysis(PCA)technique,and further optimal parameters from the dataset are selected using Whale Optimization Algorithm(WOA).The most relevant features are selected and then fed into a Convolutional Neural Network(CNN)model.The proposed model is evaluated against four different use cases of driver behavior.The results show that the best prediction accuracy is achieved in the case of drivers without glasses.The proposed model yielded optimal accuracy when evaluated against the K-Nearest Neighbors(KNN)and Support Vector Machines(SVM)models with and without using dimensionality reduction approaches.
文摘The key technology of open architecture CNC systems kernel device driver,including the interrupt mechanism, I/O subsystem, the structure of device driver and the communication between the driver and the application program, is discussed in the paper and a specific application is given at the end.
文摘Deforestation and forest degradation has been observed to be rampant in Masito-Ugalla ecosystem, Kigoma Region, western part of Tanzania. This paper therefore, intended to assess the extent of deforestation and forest degradation in the area, and to determine their causes. A total of 101 respondents were considered as the sample size for this study. The methods used for data collection were household questionnaire interviews, in-depth interviews, focus group discussions, analysis of satellite images and direct observation. The findings indicated that deforestation was occurring in the study area. Satellite data revealed diminished closed woodland, bushed grassland, forest and thickets between 1990 and 2014. On the contrary, settlement area, cultivated land and open woodland had increased during the same time frame. Proximate factors causing deforestation and forest degradation included agricultural expansion, wood extraction and expansion of settlement area. Underlying factors included population growth, poverty, poor levels of education, lack of employment, corruption and embezzlement of public funds by politicians and senior government officials;and high demand for fuel-wood. Biophysical drivers like incidences of unplanned wildfires and socio trigger events notably civil strife were also important. In order to minimize the problem and based on the factors augmenting deforestation and forest degradation in the Masito-Ugalla ecosystem and their coupled negative consequences, effective environmental conservation education, increased patrols, effective law enforcement and provision of alternative energy sources are necessary.
文摘This paper presents the implementation of an embedded automotive system that detects and recognizes traffic signs within a video stream. In addition, it discusses the recent advances in driver assistance technologies and highlights the safety motivations for smart in-car embedded systems. An algorithm is presented that processes RGB image data, extracts relevant pixels, filters the image, labels prospective traffic signs and evaluates them against template traffic sign images. A reconfigurable hardware system is described which uses the Virtex-5 Xilinx FPGA and hardware/software co-design tools in order to create an embedded processor and the necessary hardware IP peripherals. The implementation is shown to have robust performance results, both in terms of timing and accuracy.
基金The work of this paper was supported by the National Natural Science Foundation of China under grant numbers 61572038 received by J.Z.in 2015.URL:https://isisn.nsfc.gov.cn/egrantindex/funcindex/prjsearch-list。
文摘Real-time detection of driver fatigue status is of great significance for road traffic safety.In this paper,a proposed novel driver fatigue detection method is able to detect the driver’s fatigue status around the clock.The driver’s face images were captured by a camera with a colored lens and an infrared lens mounted above the dashboard.The landmarks of the driver’s face were labeled and the eye-area was segmented.By calculating the aspect ratios of the eyes,the duration of eye closure,frequency of blinks and PERCLOS of both colored and infrared,fatigue can be detected.Based on the change of light intensity detected by a photosensitive device,the weight matrix of the colored features and the infrared features was adjusted adaptively to reduce the impact of lighting on fatigue detection.Video samples of the driver’s face were recorded in the test vehicle.After training the classification model,the results showed that our method has high accuracy on driver fatigue detection in both daytime and nighttime.
文摘Driver errors contribute to more than 94% of traffic crashes. Automotive companies are striving to enhance their vehicles to eliminate driver errors and reduce the number of crashes. Various advanced features like lane departure warning (LDW), blind spot warning (BSW), over speed warning (OSW), forward collision warning (FCW), lane keep assist (LKA), adaptive cruise control (ACC), cooperative ACC (CACC), and automated emergency braking (AEB) are designed to assist with, or in some cases take over, certain driving maneuvers. They can be broadly categorized into advanced driver assistance system (ADAS) and automated features. Each of these advanced features focuses on addressing a particular task of driving, thereby, aiding the driver, influencing their behavior, and enhancing safety. Many vehicles with these advanced features are penetrating into the market, yet the total reported number of crashes has increased in recent years. This paper presents a systematic review of these advanced features on driver behavior and safety. The review is categorized into 1) survey and mathematical methods to assess driver behavior, 2) field test methods to assess driver behavior, 3) microsimulation methods to assess driver behavior, 4) driving simulator methods to assess driver behavior, and 5) driver understanding and the effectiveness of advanced features. It is followed by conclusions, knowledge gaps, and need for further research.
文摘Traffic accidents are mainly caused by human error. In an aging society, the number of accidents attributed to elderly drivers is increasing. One noteworthy reason for this is operation misapplication. Studies have been conducted on the use of human</span></span><span style="font-family:Verdana;"><span style="font-family:Verdana;"><span style="font-family:Verdana;">-</span></span></span><span><span><span style="font-family:""><span style="font-family:Verdana;">machine interfaces (HMIs) to inform the driver when he or she makes an error and encourage appropriate actions. However, the driver state during the erroneous action has not been investigated. The pur</span><span style="font-family:Verdana;">pose of this study is to clarify the difference in the driver’s state between</span><span style="font-family:Verdana;"> normal and surprising situations in a misapplication scenario, utilizing multimodal information such as biometric information and driver operation. We found significant changes in the interaction of components between the nor</span><span style="font-family:Verdana;">mal and the surprised driving state. The results could provide basic know</span><span style="font-family:Verdana;">ledge for the future development of a driver assistance system and driver state estimation using data acquired from multiple sensors in the vehicle.
文摘The pursuit of human needs and demands is placing more pressure on land resources than ever before. The challenge of feeding 7 billion people is increasingly competing with rising demands for materials and biofuels. Deforestation and land degradation are among the pressing outcomes of these trends. Drivers of environmental change—including population growth, economic activity, consumption, urbanization, trade, conflict, and governance—clearly play a role in aggravating or mitigating these pressures on land. Despite advances in understanding causality in complex systems, navigating the interactions between these drivers remains a major challenge. This paper analyzes and visualizes the relationships between multiple, interacting drivers of environmental change and specific pressures on land-based ecosystems. Drawing on experience from the development of the Drivers and Land chapters of the UN Environment Programme’s Fifth Global Environment Outlook report (GEO-5), we use a series of Kiviat diagrams to illustrate the relative influence of key drivers on selected pressures on land. When individual diagrams are overlaid, patterns of influence emerge that can provide insight into where policy responses might best be targeted. We propose that, subject to some limitations, the Kiviat exercise can provide an accessible and potentially valuable “knowledge-intermediary” tool to help link science-based information to policy action.
基金We acknowledge SAFER,Vehicle and Traffic Safety Centre at Chalmers,Gothenburg,Sweden,for funding this researchthe participants from the pensioner or-ganisations PRO and SPF in Jönköping,Sweden.
文摘Background: The number of older people is increasing. Many of them expect to maintain a rich social life and to continue driving at an older age. Objective: The present study investigates the mechanisms behind self-regulation and driving cessation in order to suggest development of support systems to prolong older drivers’ safe mobility. Method: Three focus groups were conducted with 19 older active drivers aged 65+ who were divided according to annual mileage driven. Results: A content analysis revealed broad self-regulatory behaviour as already reported in the literature, e.g., avoiding driving at rush hour and at night. The participants also reported difficulty in finding the way to their final destination and an increasing need to plan their travelling. Co-piloting was a behaviour applied by couples to cope with difficulties encountered in traffic. A large part of the discussion was focused on emerging feelings of stress, anxiety and fear when driving in recent years, a feeling induced by external factors e.g., other road users’ behaviour, traffic density or high speed. Apart from health problems, high levels of stress could explain driving cessation, especially for women. An increased feeling of safety and comfort could be achieved by an increased use of support systems specifically designed to respond to older drivers’ needs. Conclusion: Support systems for older drivers should increase comfort and decrease their stress levels. New systems, such as co-pilot function and more developed Global Positioning System (GPS) supporting of the entire travel from door to door, should be developed to respond to the market needs.
文摘As an universal bus technology at present time,I^(2)C has been widely used in the interface between CPU and other devices such as EEPROM,RTC and small LCD.The architecture of I^(2)C driver,the relationship of some important data structure and the operation mechanism of the I^(2)C driver have been analyzed.Finally,by taking an EEPROM chip named AT24C08 as a specific example,the flow of how to develop an I^(2)C device driver is illustrated.In addition,the design of a new driver mode of single device with multi-drivers is realized.
文摘Presented in this paper is the development of the driver for the data acquisition card with a peripheral component interconnection （PCI） local bus on the ion cyclotron range of frequency heating （1CRH） system. The driver is mainly aimed at the embedded VxWorks system （real-time operating system） which is widely used in various fields of real-time systems. An efficient way is employed to develop this driver, which will advance the real-time control of the ICRH system on the experimental advanced superconductor tokamak （EAST）. The driver is designed using the TORNADO integrated development environment （IDE）, and implemented in C plus language. The details include the hardware configuration, analogue/digital （A/D） and digital/analogue （D/A） conversion, input and output （I/O） operation of the driver to support over five cards. The data acquisition card can be manipulated in a low-level program and meet the requirements of A/D conversion and D/A outputs.
基金supported by the Key-Area Research and Development Program of Guangdong Province(2019B010149001)the National Natural Science Foundation of China(61960206007,62002018,62007001)the 111 Project(B18005)。
文摘Dear editor,This letter presents a user study to explore the effectiveness of gesture interaction in driver assistance system(DAS).Distracted driving is a specific form of driver inattention and distraction occurs when the drivers'attention is diverted from the driving to other activities.
文摘As the overall population ages, driving-related accidents and injuries, associated with elderly drivers, have risen. Existing research about elderly drivers mainly focuses on factual data collection and analysis, indicating the elderly＇s growing fatal accident rates and their different behaviours compared to younger drivers. However, few research has focused on design-led practical solutions to mitigate the elderly＇s growing fatal accidents, by consid- ering their usability and body conditions, afflicting the elderly, such as decreased vision, hearing, and reaction times. In this paper, first, current worldwide situations on growing fatal accident rates for elderly drivers is reviewed and the key impact factors are identified and discussed with regarding to usability and design trend in the automotive technology for elderly. Second, existing smart vehicle technology-based solutions to promote safe driving are explored and their pros and cons are discussed and anal- ysed. Most of solutions are not created by people with driving difficulties, which are caused by health problems most commonly afflicting the elderly. Thirdly, diverse design-led research activities are taken, such as a survey, observation, and interviews to gain new understanding of what kinds of driving problems elderly drivers have and demonstrate how new system concepts could be developed for the elderly＇s benefits. Finally, it is found that the elderly＇s low vision and late reaction are main factors causing their driving difficulties. Based on this finding, usable vehicle system design ideas have been proposed, by utilising facial expression sensing technology as a solution. The proposed solutions would ensure reducing both the elderly＇s driving problems and high fatal accident rates and provide a more enjoyable driving environment for the elderly population.
