Despite great achievement has been made in autonomous driving technologies,autonomous vehicles(AVs)still exhibit limitations in intelligence and lack social coordination,which is primarily attributed to their reliance...Despite great achievement has been made in autonomous driving technologies,autonomous vehicles(AVs)still exhibit limitations in intelligence and lack social coordination,which is primarily attributed to their reliance on single-agent technologies,neglecting inter-AV interactions.Current research on multi-agent autonomous driving(MAAD)predominantly focuses on either distributed individual learning or centralized cooperative learning,ignoring the mixed-motive nature of MAAD systems,where each agent is not only self-interested in reaching its own destination but also needs to coordinate with other traffic participants to enhance efficiency and safety.Inspired by the mixed motivation of human driving behavior and their learning process,we propose a novel mixed motivation driven social multi-agent reinforcement learning method for autonomous driving.In our method,a multi-agent reinforcement learning(MARL)algorithm,called Social Learning Policy Optimization(SoLPO),which takes advantage of both the individual and social learning paradigms,is proposed to empower agents to rapidly acquire self-interested policies and effectively learn socially coordinated behavior.Based on the proposed SoLPO,we further develop a mixed-motive MARL method for autonomous driving combined with a social reward integration module that can model the mixed-motive nature of MAAD systems by integrating individual and neighbor rewards into a social learning objective for improved learning speed and effectiveness.Experiments conducted on the MetaDrive simulator show that our proposed method outperforms existing state-of-the-art MARL approaches in metrics including the success rate,safety,and efficiency.More-over,the AVs trained by our method form coordinated social norms and exhibit human-like driving behavior,demonstrating a high degree of social coordination.展开更多
This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee dr...This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.展开更多
With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the ch...With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.展开更多
Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster...Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance.展开更多
Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in...Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in Ukraine,particularly in the context of the 2022 Russia-Ukraine conflict.We provide the first comprehensive assessment of both conflict-and non-conflict-related factors that influenced the distribution and productivity of Ukraine’s cropland from 2013 to 2023.In addition,we propose a novel method using machine learning models to isolate the impact of conflict on cropland.Our findings reveal that,prior to the conflict,the spatial pattern of Ukraine’s mean cultivation rate was primarily shaped by natural factors—such as climate,soil properties,and elevation—whereas socio-economic factors(e.g.,GDP and population size)exerted a weaker influence.Interannual dynamics in productive cropland area were largely driven by climate variability.The onset of conflict in 2022 dramatically altered this landscape,with nearly half of the cropland grid cells experiencing a conflict-induced reduction.Notably,almost half of the interannual reduction in productive cropland in 2022 was attributed to climate change.Remarkably,in 2023,the return of displaced populations and favorable climatic conditions in many oblasts contributed to a positive trend in cropland reclamation.Despite this,the total area of productive cropland in 2023 remained below expected levels,due to ongoing conflict and localized droughts.Finally,we highlight the urgent need to adopt a two-pronged approach that addresses both the immediate impacts of conflict and the ongoing threats posed by climate change to ensure the resilience and sustainability of agricultural systems in post-conflict areas.展开更多
Using path analysis, correlation analysis, partial correlation analysis and system dynamics method to study the driving force of cultivated land in Qinghai Lake Area, and using gradually regression analysis to establi...Using path analysis, correlation analysis, partial correlation analysis and system dynamics method to study the driving force of cultivated land in Qinghai Lake Area, and using gradually regression analysis to establish the driving force model of utilized change of cultivated land. Driving factors, action mechanism and process of utilized change of cultivated land were analyzed, and the differences during all factors were compared. The study provides some decision basis for sustainable utilization and management of land resources in Qinghai Lake Area.展开更多
Adverse weather has a considerable impact on the behavior of drivers,which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents.This research examines how drivers'perceived ris...Adverse weather has a considerable impact on the behavior of drivers,which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents.This research examines how drivers'perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment.An expressway road scenario was built in a driving simulator.Eleven types of weather conditions,including clear sky,four levels of fog,four levels of rain and two levels of snow,were designed.Furthermore,to simulate the carfollowing behavior,three car-following situations were designed according to the motion of the lead car.Seven car-following indicators were extracted based on risk homeostasis theory.Then,the entropy weight method was used to integrate the selected indicators into an index to represent the drivers'perceived risk.Multiple linear regression was applied to measure the influence of adverse weather conditions on perceived risk,and the coefficients were considered as indicators.The results demonstrate that both the weather conditions and road type have significant effects on car-following behavior.Drivers'perceived risk tends to increase with the worsening weather conditions.Under conditions of extremely poor visibility,such as heavy dense fog,the measured drivers'perceived risk is low due to the difficulties in vehicle operation and limited visibility.展开更多
Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality te...Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality technology is now a promising alternative to the conventional driving simulations since it provides a more simple, secure and user-friendly environment for data collection. The driving simulator was used to assist novice drivers in learning how to drive in a very calm environment since the driving is not taking place on an actual road. This paper provides new insights regarding a driver’s behavior, techniques and adaptability within a driving simulation using virtual reality technology. The theoretical framework of this driving simulation has been designed using the Unity3D game engine (5.4.0f3 version) and programmed by the C# programming language. To make the driving simulation environment more realistic, the HTC Vive Virtual reality headset, powered by Steamvr, was used. 10 volunteers ranging from ages 19 - 37 participated in the virtual reality driving experiment. Matlab R2016b was used to analyze the data obtained from experiment. This research results are crucial for training drivers and obtaining insight on a driver’s behavior and characteristics. We have gathered diverse results for 10 drivers with different characteristics to be discussed in this study. Driving simulations are not easy to use for some users due to motion sickness, difficulties in adopting to a virtual environment. Furthermore, results of this study clearly show the performance of drivers is closely associated with individual’s behavior and adaptability to the driving simulator. Based on our findings, it can be said that with a VR-HMD (Virtual Reality-Head Mounted Display) Driving Simulator enables us to evaluate a driver’s “performance error”, “recognition errors” and “decision error”. All of which will allow researchers and further studies to potentially establish a method to increase driver safety or alleviate “driving errors”.展开更多
The high-speed reciprocating motion of a detaching roller limits the velocity of a cotton comber and affects the quality of comber slivers. The article has proposed a controllable time-sharing unidirectional hybrid dr...The high-speed reciprocating motion of a detaching roller limits the velocity of a cotton comber and affects the quality of comber slivers. The article has proposed a controllable time-sharing unidirectional hybrid drive mechanism after analyzing detaching roller's current numerical control drive method. The analysis focuses on the detaching roller motion required according to cotton comber's velocity and process. The double-servo motors of the mechanism consists of differential gear trains. The mechanism addresses the problem of increased servo motor power,and failure of promptly responded to the positive inversion process of mechanism driven by servo motors. A velocity calculation model of the detaching roller controllable drive mechanism will be generated by using superposition method and design of differential gear trains. The accuracy of the model will be verified using the test platform. This study has presented a reliable and practical high-speed drive mechanism and can be a reference to future studies on high-speed reciprocating motion drive.展开更多
In recent years, the number of traffic accidents caused by elderly drivers has increased in Japan. However, a car is an important mode of transportation for the elderly. Therefore, to ensure safe driving, a system tha...In recent years, the number of traffic accidents caused by elderly drivers has increased in Japan. However, a car is an important mode of transportation for the elderly. Therefore, to ensure safe driving, a system that can assist elderly drivers is required. In this study, we propose a driver-agent system that provides support to elderly drivers during and after driving and encourages them to improve their driving. This paper describes the prototype system based on the analysis of the teaching records of a human instructor, and the subjective evaluation of driving support to elderly and non-elderly driver from three different agent forms, a voice, visual, and robot. The result revealed that the robot form is more noticeable, familiar, and acceptable to the elderly and non-elderly than other forms.展开更多
This paper presents parametric analysis of driving range of electric vehicles driven by V-type interior permanent magnet motors aiming at maximum driving range,i.e.,minimal total energy consumption of the motors over ...This paper presents parametric analysis of driving range of electric vehicles driven by V-type interior permanent magnet motors aiming at maximum driving range,i.e.,minimal total energy consumption of the motors over a driving cycle.Influence of design parameters including tooth width,slot depth,split ratio(the ratio of inner diameter to outer diameter of the stator),and V-type magnet angle on the energy consumption of the motors and driving range of electric vehicles over a driving cycle is investigated in detail.The investigation is carried out for two typical driving cycles with different characteristics to represent different conditions:One is high-speed,low-torque cycle-Highway Fuel Economy Test and the other is low-speed,high-torque cycle-Artemis Urban Driving Cycle.It shows that for both driving cycles,the same parameters may have different influence on the energy consumption of the motors,as well as driving range of electric vehicles.展开更多
Real-time drive cycles and driving trends have a vital impact on fuel consumption and emissions in a vehicle. To address this issue, an original and alternative approach which incorporates the knowledge about real-tim...Real-time drive cycles and driving trends have a vital impact on fuel consumption and emissions in a vehicle. To address this issue, an original and alternative approach which incorporates the knowledge about real-time drive cycles and driving trends into fuzzy logic control strategy was proposed. A machine learning framework called MC_FRAME was established, which includes two neural networks for self-learning and making predictions. An intelligent fuzzy logic control strategy based on the MC_FRAME was then developed in a hybrid electric vehicle system, which is called FLCS_MODEL. Simulations were conducted to evaluate the FLCS_MODEL using ADVISOR. The simulation results indicated that comparing with the default controller on the drive cycle NEDC, the FLCS_MODEL saves 12.25% fuel per hundred kilometers, with the HC emissions increasing by 22.7%, the CO emissions reducing by 16.5%, the NOx emissions reducing by 37.5% and with the PM emissions reducing by 12.9%. A conclusion can be drawn that the proposed approach realizes fewer fuel consumption and less emissions.展开更多
A three-DOF (degree of freedom) planar robot completely restrained and positioned parallel pulled by four wires was studied. The wire driving properties were analyzed through experiments. The restrained three-DOF plan...A three-DOF (degree of freedom) planar robot completely restrained and positioned parallel pulled by four wires was studied. The wire driving properties were analyzed through experiments. The restrained three-DOF planar platform was established based on slippery course and bearing, and dSPACE real-time control system was used to perform the platform's motion control experiment on robot. Based on the kinematic equation and mechanical balance equation of moving platform, the stiffness of the robot system was analyzed and the calibration scheme of the system considering wire tension was put forward. Position servo control experiments were carried out, position servo tracking precision was analyzed, and real-time wire tension was detected. The results show that the moving error of the moving platform tracking is small (the maximum difference is about 3%), and the rotation error is large (the maximum difference is about 12%). The wire tension has wave properties (the wire tension fluctuation is about 10 N).展开更多
An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation d...An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation duration, variations of fixation points, and the distribution of glance zone. It was found that driving experience had a significant effect on driver eye movement behavior. The percentage of fixation duration to total glance time for inexperienced drivers was 61.5%, while the percentage for experienced drivers was 50.2%. Moreover, the majority of drivers paid attention to the left region of the field of view more frequently than the central and the right regions. This study indicates that it takes inexperienced drivers more time to recognize traffic signs. The findings from this study will assist traffic engineers in designing and installing the traffic signs in an optimal way.展开更多
This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are us...This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are used for the purpose of training and researching driver behavior and characteristics;3) the article addresses driver experience by involving new virtual reality technologies. A simulator has been used to assist novice drivers to learn how to drive in a very safe environment, and researching and collecting data for researchers has become easier due to this secure and user-friendly environment. The theoretical framework of this driving simulation has been designed by using the Unity3D game engine (5.4.f3 version) and was programmed with the C# programming language. To make the driving environment more realistic we, in addition, utilized the HTC Vive Virtual reality headset which is powered by Steamvr. We used Unity Game Engine to design our scenarios and maps because by doing this we are able to be more flexible with designing. In this study, we asked 10 people ranging from ages 19 - 37 to participate in this experiment. Four Japanese divers and six non-Japanese drivers engaged in this study, some of which do not have a driver’s license in Japan. A few Japanese drivers have a license and car, while others have a license but no car. In order to analyze the results of this experiment we are used MatlabR2016b to analyze the gathered data. The result of this research indicates that individual’s behavior and characteristics such as controlling the speed, remaining calm and relaxed when driving, driving at appropriate speeds depending on changes in road structures and etc. can affect their driving performance.展开更多
in this paper, an electromechanically coupled mathematic model of multi-roller driving system for belt conveyor is set up, and the computing equations for dynamic displacement and dynamic tension of the conveyor are a...in this paper, an electromechanically coupled mathematic model of multi-roller driving system for belt conveyor is set up, and the computing equations for dynamic displacement and dynamic tension of the conveyor are also formulated when the hoister is used for straining. Based on the belt conveyor of main inclined shaft in Chengzhuang coal mine, the driving torque, driving power and starting-speed characteristic of each electric motor are studied and measured when multi-roller variable-frequency drive (power distribution 2∶1) is used. The optimal control and the optimal starting-acceleration of the multi-roller variable-frequency drive are determined by a large number of industrial experiments and theoretical calculations.展开更多
To examine the variation law of the driving psychological load in subsea tunnels under different illumination and longitudinal slope conditions,22 drivers were recruited to participate in a real vehicle test in off pe...To examine the variation law of the driving psychological load in subsea tunnels under different illumination and longitudinal slope conditions,22 drivers were recruited to participate in a real vehicle test in off peak hours under similar traffic conditions,and the skin electric signals of the drivers in the free flow state were collected.Considering the skin conductance level(SCL)as the load characteristic index,the influence of the different illuminance and slope conditions on the drivers’skin electrical signals was analyzed,and a measurement model of the relationship between the uphill and downhill slopes,illuminance and driver’s SCL value was constructed.The results indicate that the illuminance change rate and driver’s SCL are positively correlated.A larger illuminance change rate leads to an increase in the SCL and psychological workload of the driver.The influence of the uphill and downhill slopes on the driver’s SCL value in different areas of the subsea tunnel is considerably different.With the increase in the degree of the uphill and downhill slopes,the driver’s SCL value increases,and the maximum SCL appears in a slope range of 3.5%–4%.Moreover,the SCL of the drivers in the downhill section is higher than that in the uphill section,corresponding to a larger driving psychological load.展开更多
125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core...125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core Test Battery (WHO NCTB). The results showed that there were obvious negative mood states such as tension-anxiety and fatigue in AG and drivers with accidents had more poor neurobehavioral performances, especially attention, response speed and perceptual-motor speed than drivers without accidents and controls. We also found that automobile drivers' neurobehavioral functions got weakened with the increase of their age and got strengthened with the elevation of their educational level. And the functions were inversely correlative to the accidents they cuased. The results of our study suggest that WHO NCTB can be an index of researches on driving accidents that automobile drivers caused and can be used in occupational selection and training of drivers.展开更多
Japan has become a more aged society and there are more drivers, 65 years of age and above. Cars represent an important mode of transportation for the elderly;however, in recent years, the number of traffic accidents ...Japan has become a more aged society and there are more drivers, 65 years of age and above. Cars represent an important mode of transportation for the elderly;however, in recent years, the number of traffic accidents caused by elderly drivers has been on the rise, and this has become a social issue. Thus, for the elderly drivers to encourage them to improve their driving, we study a driver agent system which consists of smartphone, communication robot and cloud service and provides the driving support by attention awakening and the feedback support based on driving behavior evaluation. In this paper, we presented a summary of the proposed agent and reported on a set of preliminary experiments using our agent in an actual car environment. From the analysis of subjective evaluations and fixation points during driving, the results revealed the possibility that the drivers accept the agent and supports from the agent during driving and that the agent in an actual car environment did not distract the driver.展开更多
基金supported in part by the National Natural Science Foundation of China(62273135,62373356)the Natural Science Foundation of Hubei Province in China(2025AFA083)+1 种基金the Original Exploration Seed Project of Hubei University(202416403000001)the Postgraduate Education and Teaching Reform Research Project of Hubei University(1190017755).
文摘Despite great achievement has been made in autonomous driving technologies,autonomous vehicles(AVs)still exhibit limitations in intelligence and lack social coordination,which is primarily attributed to their reliance on single-agent technologies,neglecting inter-AV interactions.Current research on multi-agent autonomous driving(MAAD)predominantly focuses on either distributed individual learning or centralized cooperative learning,ignoring the mixed-motive nature of MAAD systems,where each agent is not only self-interested in reaching its own destination but also needs to coordinate with other traffic participants to enhance efficiency and safety.Inspired by the mixed motivation of human driving behavior and their learning process,we propose a novel mixed motivation driven social multi-agent reinforcement learning method for autonomous driving.In our method,a multi-agent reinforcement learning(MARL)algorithm,called Social Learning Policy Optimization(SoLPO),which takes advantage of both the individual and social learning paradigms,is proposed to empower agents to rapidly acquire self-interested policies and effectively learn socially coordinated behavior.Based on the proposed SoLPO,we further develop a mixed-motive MARL method for autonomous driving combined with a social reward integration module that can model the mixed-motive nature of MAAD systems by integrating individual and neighbor rewards into a social learning objective for improved learning speed and effectiveness.Experiments conducted on the MetaDrive simulator show that our proposed method outperforms existing state-of-the-art MARL approaches in metrics including the success rate,safety,and efficiency.More-over,the AVs trained by our method form coordinated social norms and exhibit human-like driving behavior,demonstrating a high degree of social coordination.
基金National Natural Science Foundation of China under Grants No.62171047,U22B2001,62271065,62001051Beijing Natural Science Foundation under Grant L223027BUPT Excellent Ph.D Students Foundation under Grants CX2021114。
文摘This article studies the problem of image segmentation-based semantic communication in autonomous driving.In real traffic scenes,the detecting of objects(e.g.,vehicles and pedestrians)is more important to guarantee driving safety,which is always ignored in existing works.Therefore,we propose a vehicular image segmentation-oriented semantic communication system,termed VIS-SemCom,focusing on transmitting and recovering image semantic features of high-important objects to reduce transmission redundancy.First,we develop a semantic codec based on Swin Transformer architecture,which expands the perceptual field thus improving the segmentation accuracy.To highlight the important objects'accuracy,we propose a multi-scale semantic extraction method by assigning the number of Swin Transformer blocks for diverse resolution semantic features.Also,an importance-aware loss incorporating important levels is devised,and an online hard example mining(OHEM)strategy is proposed to handle small sample issues in the dataset.Finally,experimental results demonstrate that the proposed VIS-SemCom can achieve a significant mean intersection over union(mIoU)performance in the SNR regions,a reduction of transmitted data volume by about 60%at 60%mIoU,and improve the segmentation accuracy of important objects,compared to baseline image communication.
基金The National Social Science Foundation Youth Project of China:Research on the collaborative govemance path of administrative law and criminal law against dangerous driving behaviors in the digital-intelligent society(25CFX108)。
文摘With the continuous progress of automatic driving technology,automatic driving technology standards are gradually affecting the determination of criminal responsibility for traffic accidents in China.At present,the characteristics and tendency of China's automatic driving technology standards present the situation of high policy relevance coexisting with low normative binding,professionalism coexist with barriers,forefront coexist with ambiguity.Therefore,challenges are presented both theoretically and practically on the determination of criminal responsibility based on automatic driving technology standard..In this regard,the misunderstanding should be clarified in theory:The legal order under the automatic driving technology standard has constitutionality and systematic,and there is a balance between the frontier of automatic driving technology development and the lagging of criminal law.The automatic driving technology risk level system should be built to clarify the boundary of the effectiveness of criminal law norms,seeking fora breakthrough in the application of the establishment of a comprehensive judgment system of the risks and accidents and the system of evidence to prove the system,which clarifies the determination of criminal responsibility under the automatic driving technology standard.This essay hopes to pursue breakthroughs in the application-to establish a comprehensive judgment system of risks and accidents as well as an evidence proof system,so as to clarify the determination of criminal responsibility under automatic driving technology standards.
基金Under the auspices of National Natural Science Foundation of China(No.42571219)Key Project of Zhejiang Province Soft Science Research Plan(No.2023C25014)。
文摘Bottom-up and top-down endogenous automobile clusters exhibit distinct evolutionary traits and driving mechanisms,yet their comparative analysis remains understudied.Therefore,using Taizhou automobile industry cluster(TAIC)and Wuhu automobile industry cluster(WAIC)as cases,using historical statistical data and field interview data from the 1980s to 2023,combined with qualitative research methods of thematic and diachronic analysis,and quantitative research methods of social network analysis,we compare both endogenous automobile clusters’evolutionary traits and driving mechanisms.The results confirm both clusters undergo multi-scale spatial reconfiguration,organizational complexification,and intelligent networking technological transformation,yet diverge fundamentally:TAIC evolves through market-driven progressive expansion,transitioning from single to dual-core structures via private enterprise networking,with innovation following market-integrated logic and institutional thickness built on demand-driven evolution.Conversely,WAIC follows planned expansion,maintaining state-led hierarchical single-core stability through policy-driven breakthrough innovation and supply-dominated institutional construction-though both ultimately require formal-informal system synergy.Their coevolution is driven by dynamic interactions of path dependence(weakening influence),learning-innovation(strengthening influence),and relationship selection(inverted U-shaped trajectory),with divergent development paths rooted in TAIC’s grassroots self-organization genes versus WAIC’s top-level design genes,amplified by core enterprises’strategic disparities.The research findings can not only provide decision-making support for China’s industrial upgrading,but also contribute China’s insights to global economic governance.
基金supported in part by the National Natural Science Foundation of China(Grants No.41971284 and 42371321)the Key Research and Development Program of Hubei Province(Grant No.2025BAB024).
文摘Ukraine,as one of the world’s largest agricultural producers and exporters,plays a critical role in global food security.It is essential to understand the spatiotemporal dynamics and drivers of productive cropland in Ukraine,particularly in the context of the 2022 Russia-Ukraine conflict.We provide the first comprehensive assessment of both conflict-and non-conflict-related factors that influenced the distribution and productivity of Ukraine’s cropland from 2013 to 2023.In addition,we propose a novel method using machine learning models to isolate the impact of conflict on cropland.Our findings reveal that,prior to the conflict,the spatial pattern of Ukraine’s mean cultivation rate was primarily shaped by natural factors—such as climate,soil properties,and elevation—whereas socio-economic factors(e.g.,GDP and population size)exerted a weaker influence.Interannual dynamics in productive cropland area were largely driven by climate variability.The onset of conflict in 2022 dramatically altered this landscape,with nearly half of the cropland grid cells experiencing a conflict-induced reduction.Notably,almost half of the interannual reduction in productive cropland in 2022 was attributed to climate change.Remarkably,in 2023,the return of displaced populations and favorable climatic conditions in many oblasts contributed to a positive trend in cropland reclamation.Despite this,the total area of productive cropland in 2023 remained below expected levels,due to ongoing conflict and localized droughts.Finally,we highlight the urgent need to adopt a two-pronged approach that addresses both the immediate impacts of conflict and the ongoing threats posed by climate change to ensure the resilience and sustainability of agricultural systems in post-conflict areas.
基金Supported by The Regional Sustainable Development of the Qing-TibetPlateau(2004)~~
文摘Using path analysis, correlation analysis, partial correlation analysis and system dynamics method to study the driving force of cultivated land in Qinghai Lake Area, and using gradually regression analysis to establish the driving force model of utilized change of cultivated land. Driving factors, action mechanism and process of utilized change of cultivated land were analyzed, and the differences during all factors were compared. The study provides some decision basis for sustainable utilization and management of land resources in Qinghai Lake Area.
基金supported by the National Natural Science Foundation of China project(61672067)Science and Technology Program of Beijing(Z151100002115040)
文摘Adverse weather has a considerable impact on the behavior of drivers,which puts vehicles and drivers in hazardous situations that can easily cause traffic accidents.This research examines how drivers'perceived risk changes during car following under different adverse weather conditions by using driving simulation experiment.An expressway road scenario was built in a driving simulator.Eleven types of weather conditions,including clear sky,four levels of fog,four levels of rain and two levels of snow,were designed.Furthermore,to simulate the carfollowing behavior,three car-following situations were designed according to the motion of the lead car.Seven car-following indicators were extracted based on risk homeostasis theory.Then,the entropy weight method was used to integrate the selected indicators into an index to represent the drivers'perceived risk.Multiple linear regression was applied to measure the influence of adverse weather conditions on perceived risk,and the coefficients were considered as indicators.The results demonstrate that both the weather conditions and road type have significant effects on car-following behavior.Drivers'perceived risk tends to increase with the worsening weather conditions.Under conditions of extremely poor visibility,such as heavy dense fog,the measured drivers'perceived risk is low due to the difficulties in vehicle operation and limited visibility.
文摘Driving a vehicle is one of the most common daily yet hazardous tasks. One of the great interests in recent research is to characterize a driver’s behaviors through the use of a driving simulation. Virtual reality technology is now a promising alternative to the conventional driving simulations since it provides a more simple, secure and user-friendly environment for data collection. The driving simulator was used to assist novice drivers in learning how to drive in a very calm environment since the driving is not taking place on an actual road. This paper provides new insights regarding a driver’s behavior, techniques and adaptability within a driving simulation using virtual reality technology. The theoretical framework of this driving simulation has been designed using the Unity3D game engine (5.4.0f3 version) and programmed by the C# programming language. To make the driving simulation environment more realistic, the HTC Vive Virtual reality headset, powered by Steamvr, was used. 10 volunteers ranging from ages 19 - 37 participated in the virtual reality driving experiment. Matlab R2016b was used to analyze the data obtained from experiment. This research results are crucial for training drivers and obtaining insight on a driver’s behavior and characteristics. We have gathered diverse results for 10 drivers with different characteristics to be discussed in this study. Driving simulations are not easy to use for some users due to motion sickness, difficulties in adopting to a virtual environment. Furthermore, results of this study clearly show the performance of drivers is closely associated with individual’s behavior and adaptability to the driving simulator. Based on our findings, it can be said that with a VR-HMD (Virtual Reality-Head Mounted Display) Driving Simulator enables us to evaluate a driver’s “performance error”, “recognition errors” and “decision error”. All of which will allow researchers and further studies to potentially establish a method to increase driver safety or alleviate “driving errors”.
基金National Basic Research Program of China(973 Program)(No.2010CB334711)the Applied Basic Research of China National Textile and Apparel Council (Textile Vision Science and Education Fund of China in 2012)
文摘The high-speed reciprocating motion of a detaching roller limits the velocity of a cotton comber and affects the quality of comber slivers. The article has proposed a controllable time-sharing unidirectional hybrid drive mechanism after analyzing detaching roller's current numerical control drive method. The analysis focuses on the detaching roller motion required according to cotton comber's velocity and process. The double-servo motors of the mechanism consists of differential gear trains. The mechanism addresses the problem of increased servo motor power,and failure of promptly responded to the positive inversion process of mechanism driven by servo motors. A velocity calculation model of the detaching roller controllable drive mechanism will be generated by using superposition method and design of differential gear trains. The accuracy of the model will be verified using the test platform. This study has presented a reliable and practical high-speed drive mechanism and can be a reference to future studies on high-speed reciprocating motion drive.
文摘In recent years, the number of traffic accidents caused by elderly drivers has increased in Japan. However, a car is an important mode of transportation for the elderly. Therefore, to ensure safe driving, a system that can assist elderly drivers is required. In this study, we propose a driver-agent system that provides support to elderly drivers during and after driving and encourages them to improve their driving. This paper describes the prototype system based on the analysis of the teaching records of a human instructor, and the subjective evaluation of driving support to elderly and non-elderly driver from three different agent forms, a voice, visual, and robot. The result revealed that the robot form is more noticeable, familiar, and acceptable to the elderly and non-elderly than other forms.
基金This work was supported by the National Natural Science Foundation of China under Grant 51677169 and Grant 51637009.
文摘This paper presents parametric analysis of driving range of electric vehicles driven by V-type interior permanent magnet motors aiming at maximum driving range,i.e.,minimal total energy consumption of the motors over a driving cycle.Influence of design parameters including tooth width,slot depth,split ratio(the ratio of inner diameter to outer diameter of the stator),and V-type magnet angle on the energy consumption of the motors and driving range of electric vehicles over a driving cycle is investigated in detail.The investigation is carried out for two typical driving cycles with different characteristics to represent different conditions:One is high-speed,low-torque cycle-Highway Fuel Economy Test and the other is low-speed,high-torque cycle-Artemis Urban Driving Cycle.It shows that for both driving cycles,the same parameters may have different influence on the energy consumption of the motors,as well as driving range of electric vehicles.
文摘Real-time drive cycles and driving trends have a vital impact on fuel consumption and emissions in a vehicle. To address this issue, an original and alternative approach which incorporates the knowledge about real-time drive cycles and driving trends into fuzzy logic control strategy was proposed. A machine learning framework called MC_FRAME was established, which includes two neural networks for self-learning and making predictions. An intelligent fuzzy logic control strategy based on the MC_FRAME was then developed in a hybrid electric vehicle system, which is called FLCS_MODEL. Simulations were conducted to evaluate the FLCS_MODEL using ADVISOR. The simulation results indicated that comparing with the default controller on the drive cycle NEDC, the FLCS_MODEL saves 12.25% fuel per hundred kilometers, with the HC emissions increasing by 22.7%, the CO emissions reducing by 16.5%, the NOx emissions reducing by 37.5% and with the PM emissions reducing by 12.9%. A conclusion can be drawn that the proposed approach realizes fewer fuel consumption and less emissions.
基金Project(20102304120007) supported by the Research Fund for the Doctoral Program of Higher Education of ChinaProject(QC2010009)supported by the Natural Science Foundation of Heilongjiang Province, China+1 种基金Projects(20110491030, LBH-Z10219) supported by China Postdoctoral Science FoundationProject(HEUCF120706) supported by the Fundamental Research Funds for the Central Universities of China
文摘A three-DOF (degree of freedom) planar robot completely restrained and positioned parallel pulled by four wires was studied. The wire driving properties were analyzed through experiments. The restrained three-DOF planar platform was established based on slippery course and bearing, and dSPACE real-time control system was used to perform the platform's motion control experiment on robot. Based on the kinematic equation and mechanical balance equation of moving platform, the stiffness of the robot system was analyzed and the calibration scheme of the system considering wire tension was put forward. Position servo control experiments were carried out, position servo tracking precision was analyzed, and real-time wire tension was detected. The results show that the moving error of the moving platform tracking is small (the maximum difference is about 3%), and the rotation error is large (the maximum difference is about 12%). The wire tension has wave properties (the wire tension fluctuation is about 10 N).
文摘An experiment was conducted to find the variability of driver eye movement according to different driving experience. An eye tracking system was used to study the regularity of driver eye movements, such as fixation duration, variations of fixation points, and the distribution of glance zone. It was found that driving experience had a significant effect on driver eye movement behavior. The percentage of fixation duration to total glance time for inexperienced drivers was 61.5%, while the percentage for experienced drivers was 50.2%. Moreover, the majority of drivers paid attention to the left region of the field of view more frequently than the central and the right regions. This study indicates that it takes inexperienced drivers more time to recognize traffic signs. The findings from this study will assist traffic engineers in designing and installing the traffic signs in an optimal way.
文摘This article provides new insights regarding driver behavior, techniques and adaptability. This study has been done because: 1) driving a vehicle is critical and one of the most common daily tasks;2) simulators are used for the purpose of training and researching driver behavior and characteristics;3) the article addresses driver experience by involving new virtual reality technologies. A simulator has been used to assist novice drivers to learn how to drive in a very safe environment, and researching and collecting data for researchers has become easier due to this secure and user-friendly environment. The theoretical framework of this driving simulation has been designed by using the Unity3D game engine (5.4.f3 version) and was programmed with the C# programming language. To make the driving environment more realistic we, in addition, utilized the HTC Vive Virtual reality headset which is powered by Steamvr. We used Unity Game Engine to design our scenarios and maps because by doing this we are able to be more flexible with designing. In this study, we asked 10 people ranging from ages 19 - 37 to participate in this experiment. Four Japanese divers and six non-Japanese drivers engaged in this study, some of which do not have a driver’s license in Japan. A few Japanese drivers have a license and car, while others have a license but no car. In order to analyze the results of this experiment we are used MatlabR2016b to analyze the gathered data. The result of this research indicates that individual’s behavior and characteristics such as controlling the speed, remaining calm and relaxed when driving, driving at appropriate speeds depending on changes in road structures and etc. can affect their driving performance.
文摘in this paper, an electromechanically coupled mathematic model of multi-roller driving system for belt conveyor is set up, and the computing equations for dynamic displacement and dynamic tension of the conveyor are also formulated when the hoister is used for straining. Based on the belt conveyor of main inclined shaft in Chengzhuang coal mine, the driving torque, driving power and starting-speed characteristic of each electric motor are studied and measured when multi-roller variable-frequency drive (power distribution 2∶1) is used. The optimal control and the optimal starting-acceleration of the multi-roller variable-frequency drive are determined by a large number of industrial experiments and theoretical calculations.
基金the Natural Science Foundation of Shandong Province(No.ZR2020MG021)the Key Research and Development Project of Shandong Province(No.2018GGX105009)+1 种基金the Humanities and Social Sciences Research Planning Foundation of Chinese Ministry of Education(No.18YJAZH067)the National Natural Science Foundation of China(No.62003182)。
文摘To examine the variation law of the driving psychological load in subsea tunnels under different illumination and longitudinal slope conditions,22 drivers were recruited to participate in a real vehicle test in off peak hours under similar traffic conditions,and the skin electric signals of the drivers in the free flow state were collected.Considering the skin conductance level(SCL)as the load characteristic index,the influence of the different illuminance and slope conditions on the drivers’skin electrical signals was analyzed,and a measurement model of the relationship between the uphill and downhill slopes,illuminance and driver’s SCL value was constructed.The results indicate that the illuminance change rate and driver’s SCL are positively correlated.A larger illuminance change rate leads to an increase in the SCL and psychological workload of the driver.The influence of the uphill and downhill slopes on the driver’s SCL value in different areas of the subsea tunnel is considerably different.With the increase in the degree of the uphill and downhill slopes,the driver’s SCL value increases,and the maximum SCL appears in a slope range of 3.5%–4%.Moreover,the SCL of the drivers in the downhill section is higher than that in the uphill section,corresponding to a larger driving psychological load.
文摘125 automobile drivers, including 85 drivers with accidents (Accident Group, AG) and 40 drivers without accidents (Nonaccident Group, NAG), and 51 controls (Control Group. CG )were tested with WHO Neurobehavioral Core Test Battery (WHO NCTB). The results showed that there were obvious negative mood states such as tension-anxiety and fatigue in AG and drivers with accidents had more poor neurobehavioral performances, especially attention, response speed and perceptual-motor speed than drivers without accidents and controls. We also found that automobile drivers' neurobehavioral functions got weakened with the increase of their age and got strengthened with the elevation of their educational level. And the functions were inversely correlative to the accidents they cuased. The results of our study suggest that WHO NCTB can be an index of researches on driving accidents that automobile drivers caused and can be used in occupational selection and training of drivers.
文摘Japan has become a more aged society and there are more drivers, 65 years of age and above. Cars represent an important mode of transportation for the elderly;however, in recent years, the number of traffic accidents caused by elderly drivers has been on the rise, and this has become a social issue. Thus, for the elderly drivers to encourage them to improve their driving, we study a driver agent system which consists of smartphone, communication robot and cloud service and provides the driving support by attention awakening and the feedback support based on driving behavior evaluation. In this paper, we presented a summary of the proposed agent and reported on a set of preliminary experiments using our agent in an actual car environment. From the analysis of subjective evaluations and fixation points during driving, the results revealed the possibility that the drivers accept the agent and supports from the agent during driving and that the agent in an actual car environment did not distract the driver.
