With the advent of deep learning,self-driving schemes based on deep learning are becoming more and more popular.Robust perception-action models should learn from data with different scenarios and real behaviors,while ...With the advent of deep learning,self-driving schemes based on deep learning are becoming more and more popular.Robust perception-action models should learn from data with different scenarios and real behaviors,while current end-to-end model learning is generally limited to training of massive data,innovation of deep network architecture,and learning in-situ model in a simulation environment.Therefore,we introduce a new image style transfer method into data augmentation,and improve the diversity of limited data by changing the texture,contrast ratio and color of the image,and then it is extended to the scenarios that the model has been unobserved before.Inspired by rapid style transfer and artistic style neural algorithms,we propose an arbitrary style generation network architecture,including style transfer network,style learning network,style loss network and multivariate Gaussian distribution function.The style embedding vector is randomly sampled from the multivariate Gaussian distribution and linearly interpolated with the embedded vector predicted by the input image on the style learning network,which provides a set of normalization constants for the style transfer network,and finally realizes the diversity of the image style.In order to verify the effectiveness of the method,image classification and simulation experiments were performed separately.Finally,we built a small-sized smart car experiment platform,and apply the data augmentation technology based on image style transfer drive to the experiment of automatic driving for the first time.The experimental results show that:(1)The proposed scheme can improve the prediction accuracy of the end-to-end model and reduce the model’s error accumulation;(2)the method based on image style transfer provides a new scheme for data augmentation technology,and also provides a solution for the high cost that many deep models rely heavily on a large number of label data.展开更多
An integrated system has been provided with a-Si/H solar cells as energy conversion device,NiCo2O4 battery-supercapacitor hybrid(BSH)as energy storage device,and light emitting diodes(LEDs)as energy utilization device...An integrated system has been provided with a-Si/H solar cells as energy conversion device,NiCo2O4 battery-supercapacitor hybrid(BSH)as energy storage device,and light emitting diodes(LEDs)as energy utilization device.By designing three-dimensional hierarchical NiCo2O4 arrays as faradic electrode,with capacitive electrode of active carbon(AC),BSHs were assembled with energy density of 16.6 Wh kg-1,power density of 7285 W kg-1,long-term stability with 100% retention after 15,000 cycles,and rather low self-discharge.The NiCo2O4//AC BSH was charged to 1.6 V in 1 s by solar cells and acted as reliable sources for powering LEDs.The integrated system is rational for operation,having an overall efficiency of 8.1% with storage efficiency of 74.24%.The integrated system demonstrates a stable solar power conversion,outstanding energy storage behavior,and reliable light emitting.Our study offers a precious strategy to design a self-driven integrated system for highly efficient energy utilization.展开更多
Self-driving and semi-self-driving cars play an important role in our daily lives.The effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital information.Howev...Self-driving and semi-self-driving cars play an important role in our daily lives.The effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital information.However,external infrastructures also play significant roles in the transmission and reception of control data,cooperative awareness messages,and caution notifications.In this case,roadside units are considered one of themost important communication peripherals.Random distribution of these infrastructures will overburden the spread of self-driving vehicles in terms of cost,bandwidth,connectivity,and radio coverage area.In this paper,a new distributed roadside unit is proposed to enhance the performance and connectivity of these cars.Therefore,this approach is based primarily on k-means to find the optimal location of each roadside unit.In addition,this approach supports dynamicmobility with a long period of connectivity for each car.Further,this system can adapt to various locations(e.g.,highways,rural areas,urban environments).The simulation results of the proposed system are reflected in its efficiency and effectively.Thus,the system can achieve a high connectivity rate with a low error rate while reducing costs.展开更多
The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas, Inspired by human driving behaviors, we propose a novel method of drivable area detection ...The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas, Inspired by human driving behaviors, we propose a novel method of drivable area detection for self-driving cars based on fusing pixel information from a monocular camera with spatial information from a light detection and ranging (LIDAR) scanner, Similar to the bijection of collineation, a new concept called co-point mapping, which is a bijection that maps points from the LIDAR scanner to points on the edge of the image segmentation, is introduced in the proposed method, Our method posi- tions candidate drivable areas through self-learning models based on the initial drivable areas that are obtained by fusing obstacle information with superpixels, In addition, a fusion of four features is applied in order to achieve a more robust performance, In particular, a feature called drivable degree (DD) is pro- posed to characterize the drivable degree of the LIDAR points, After the initial drivable area is characterized by the features obtained through self-learning, a Bayesian framework is utilized to calculate the final probability map of the drivable area, Our approach introduces no common hypothesis and requires no training steps; yet it yields a state-of-art performance when tested on the ROAD-KITTI benchmark, Experimental results demonstrate that the proposed method is a general and efficient approach for detecting drivable area,展开更多
Based on the idea of infinitesimal analysis, we establish the basic model of relation between speed and flow. Since putting a certain amount of self-driving car will affect the average speed of mixed traffic flow, we ...Based on the idea of infinitesimal analysis, we establish the basic model of relation between speed and flow. Since putting a certain amount of self-driving car will affect the average speed of mixed traffic flow, we choose the proportion of self-driving car to be a variable, denoted by k. Based on the least square method, we find two critical values of k that are 38.63% and 68.26%. When k 38.63%, the self-driving cars have a negative influence to the traffic. When 38.63% < k < 68.26%, they have a positive influence to the traffic. When k > 68.26%, they have significant improvement to the traffic capacity of the road.展开更多
The self-driving cars are highly developed and about to meet the market, but the driving strategies and corresponding behaviors with others still need to be tested. In this paper, based on its characteristics and beha...The self-driving cars are highly developed and about to meet the market, but the driving strategies and corresponding behaviors with others still need to be tested. In this paper, based on its characteristics and behaviors of manual-driving vehicles, we propose the driving strategies of manual-driving cars as well as self-driving cars. And we use the cellular automaton to simulate the traffic reality under different conditions, and to evaluate the efficiency of a road when self-driving cars are put into use. This research can be a reference by traffic planning and vehicles performance test, and further research can be designed in a model which can calculate the efficiency of a road when the percentage of self-driving cars are different.展开更多
Self-diiviiig tour is one of the most important wajrs for people to travel, and network travel notes actually reflect the traveling information of self-driving tourists. In this paper, witii the network travel notes o...Self-diiviiig tour is one of the most important wajrs for people to travel, and network travel notes actually reflect the traveling information of self-driving tourists. In this paper, witii the network travel notes of self-driving tourists as the tesearch object^ methods such as text analysis and visualization were adopted to study behavior patterns of self-driving tourists, tourism experience, time-space migration, and distribution of tourism resources in Inner Mongolia, fi:om the multiple dimensions of mobile drivers, perceived, dimensions, and spatial migration. The results showed tiiat ①self-cidviiig tourists had a variety of motivations for traveling, in which love for nature dominated; ②self-driving tour destinations were mainly Hulunbuir, Ordos, and Alxa League; ③spatial migration was characterized by obvious seasonal fluctuations. The fesearch on the behavior of self-driving tourists in Inner Mongolia is an important part of the study of the connection between tourism resources and market connection in Inner Mongolia, and is of significance for guiding the theory, practice and poliqr foimuktion of self-doving tours in Inner Mongolia.展开更多
Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoe networks is crucial to the reliable exchange of information and control data. In this paper, we propos...Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoe networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS) to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DOS) and black hole attacks on vehicular ad hoe networks (VANETs). The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA) and Quadratic Diseriminant Analysis (QDA) which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.展开更多
Countries have invested considerable sums of human capital and material resources in the practical application of self-driving cars demonstrating the impressive market opportunity.In light of this trend,Taiwan does no...Countries have invested considerable sums of human capital and material resources in the practical application of self-driving cars demonstrating the impressive market opportunity.In light of this trend,Taiwan does not want to fall behind either.As on-road testing and technological development for self-driving cars continue to develop in different countries,the controversial issues of safety,ethics,liability,and the invasion of privacy continue to emerge.In order to resolve these issues,the government of Taiwan seeks to provide a good environment for AI(artificial intelligence)innovation and applications.This article summarizes and highlights relevant content and key points of Unmanned Vehicles Technology Innovative Experimentation Act,which was legislated in Taiwan in 2018.In addition,it points out the fundamental ethics regulation of AI,which has influenced Taiwan legal policy.展开更多
Late this March.China's Internet giant Baidu became the first self-driving car developer to obtain temporary license plates to carry out self driving tests on public roads in Beijing.
Stainless steels are used in a wide range of complex environments due to their excellent corrosion resistance.Multiphase stainless steels can offer an excellent combination of strength,toughness and corrosion resistan...Stainless steels are used in a wide range of complex environments due to their excellent corrosion resistance.Multiphase stainless steels can offer an excellent combination of strength,toughness and corrosion resistance due to the coexistence of different microstructures.The microstructure and mechanical properties of a novel cast multiphase stainless steel,composed of martensite,ferrite,and austenite,were investigated following appropriate heat treatment processes:solution treatment at 1,050℃ for 0.5 h followed by water quenching to room temperature,and aging treatment at 500℃ for 4 h followed by water quenching to room temperature.Results show reversed austenite is formed by diffusion of Ni element during aging process,and the enrichment of Ni atoms directly determines the mechanical stability of austenite.The austenite with a lower Ni content undergoes a martensitic transformation during plastic deformation.The tensile strength of the specimen exceeds 1,100 MPa and the elongation exceeds 24%after solid solution,and further increases to 1,247 MPa and 25%after aging treatment.This enhancement is due to the TRIP effect of austenite and the precipitation of the nanoscale G-phase pinning dislocations in ferrite and martensite.展开更多
Foreign tourists'trips to China recently reached a new height,both online and offline.Travel agents around the world also made trips to China,generating more thoughts for the development of new routes and the desi...Foreign tourists'trips to China recently reached a new height,both online and offline.Travel agents around the world also made trips to China,generating more thoughts for the development of new routes and the design of innovative tourist products,and contributing to the development of China's inbound tourism.展开更多
基金the National Natural Science Foundation of China(51965008)Science and Technology projects of Guizhou[2018]2168Excellent Young Researcher Project of Guizhou[2017]5630.
文摘With the advent of deep learning,self-driving schemes based on deep learning are becoming more and more popular.Robust perception-action models should learn from data with different scenarios and real behaviors,while current end-to-end model learning is generally limited to training of massive data,innovation of deep network architecture,and learning in-situ model in a simulation environment.Therefore,we introduce a new image style transfer method into data augmentation,and improve the diversity of limited data by changing the texture,contrast ratio and color of the image,and then it is extended to the scenarios that the model has been unobserved before.Inspired by rapid style transfer and artistic style neural algorithms,we propose an arbitrary style generation network architecture,including style transfer network,style learning network,style loss network and multivariate Gaussian distribution function.The style embedding vector is randomly sampled from the multivariate Gaussian distribution and linearly interpolated with the embedded vector predicted by the input image on the style learning network,which provides a set of normalization constants for the style transfer network,and finally realizes the diversity of the image style.In order to verify the effectiveness of the method,image classification and simulation experiments were performed separately.Finally,we built a small-sized smart car experiment platform,and apply the data augmentation technology based on image style transfer drive to the experiment of automatic driving for the first time.The experimental results show that:(1)The proposed scheme can improve the prediction accuracy of the end-to-end model and reduce the model’s error accumulation;(2)the method based on image style transfer provides a new scheme for data augmentation technology,and also provides a solution for the high cost that many deep models rely heavily on a large number of label data.
基金the support of National Natural Science Foundation of China (Nos. 51702284 and 21878270)Zhejiang Provincial Natural Science Foundation of China (LR19B060002)+5 种基金the Startup Foundation for Hundred-Talent Program of Zhejiang University(112100-193820101/001/022)the support of Shenzhen Science and Technology Project of China (JCYJ20170412105400428)the support of Zhejiang Provincial Natural Science Foundation of China (LR16F040001)Open Project of Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang Universitythe support of Innovation Platform of Energy Storage Engineering and New Material in Zhejiang University (K19-534202-002)Provincial Innovation Team on Hydrogen Electric Hybrid Power Systems in Zhejiang Province
文摘An integrated system has been provided with a-Si/H solar cells as energy conversion device,NiCo2O4 battery-supercapacitor hybrid(BSH)as energy storage device,and light emitting diodes(LEDs)as energy utilization device.By designing three-dimensional hierarchical NiCo2O4 arrays as faradic electrode,with capacitive electrode of active carbon(AC),BSHs were assembled with energy density of 16.6 Wh kg-1,power density of 7285 W kg-1,long-term stability with 100% retention after 15,000 cycles,and rather low self-discharge.The NiCo2O4//AC BSH was charged to 1.6 V in 1 s by solar cells and acted as reliable sources for powering LEDs.The integrated system is rational for operation,having an overall efficiency of 8.1% with storage efficiency of 74.24%.The integrated system demonstrates a stable solar power conversion,outstanding energy storage behavior,and reliable light emitting.Our study offers a precious strategy to design a self-driven integrated system for highly efficient energy utilization.
文摘Self-driving and semi-self-driving cars play an important role in our daily lives.The effectiveness of these cars is based heavily on the use of their surrounding areas to collect sensitive and vital information.However,external infrastructures also play significant roles in the transmission and reception of control data,cooperative awareness messages,and caution notifications.In this case,roadside units are considered one of themost important communication peripherals.Random distribution of these infrastructures will overburden the spread of self-driving vehicles in terms of cost,bandwidth,connectivity,and radio coverage area.In this paper,a new distributed roadside unit is proposed to enhance the performance and connectivity of these cars.Therefore,this approach is based primarily on k-means to find the optimal location of each roadside unit.In addition,this approach supports dynamicmobility with a long period of connectivity for each car.Further,this system can adapt to various locations(e.g.,highways,rural areas,urban environments).The simulation results of the proposed system are reflected in its efficiency and effectively.Thus,the system can achieve a high connectivity rate with a low error rate while reducing costs.
基金This research was partially supported by the National Natural Science Foundation of China (61773312), the National Key Research and Development Plan (2017YFC0803905), and the Program of Introducing Talents of Discipline to University (B13043).
文摘The randomness and complexity of urban traffic scenes make it a difficult task for self-driving cars to detect drivable areas, Inspired by human driving behaviors, we propose a novel method of drivable area detection for self-driving cars based on fusing pixel information from a monocular camera with spatial information from a light detection and ranging (LIDAR) scanner, Similar to the bijection of collineation, a new concept called co-point mapping, which is a bijection that maps points from the LIDAR scanner to points on the edge of the image segmentation, is introduced in the proposed method, Our method posi- tions candidate drivable areas through self-learning models based on the initial drivable areas that are obtained by fusing obstacle information with superpixels, In addition, a fusion of four features is applied in order to achieve a more robust performance, In particular, a feature called drivable degree (DD) is pro- posed to characterize the drivable degree of the LIDAR points, After the initial drivable area is characterized by the features obtained through self-learning, a Bayesian framework is utilized to calculate the final probability map of the drivable area, Our approach introduces no common hypothesis and requires no training steps; yet it yields a state-of-art performance when tested on the ROAD-KITTI benchmark, Experimental results demonstrate that the proposed method is a general and efficient approach for detecting drivable area,
文摘Based on the idea of infinitesimal analysis, we establish the basic model of relation between speed and flow. Since putting a certain amount of self-driving car will affect the average speed of mixed traffic flow, we choose the proportion of self-driving car to be a variable, denoted by k. Based on the least square method, we find two critical values of k that are 38.63% and 68.26%. When k 38.63%, the self-driving cars have a negative influence to the traffic. When 38.63% < k < 68.26%, they have a positive influence to the traffic. When k > 68.26%, they have significant improvement to the traffic capacity of the road.
文摘The self-driving cars are highly developed and about to meet the market, but the driving strategies and corresponding behaviors with others still need to be tested. In this paper, based on its characteristics and behaviors of manual-driving vehicles, we propose the driving strategies of manual-driving cars as well as self-driving cars. And we use the cellular automaton to simulate the traffic reality under different conditions, and to evaluate the efficiency of a road when self-driving cars are put into use. This research can be a reference by traffic planning and vehicles performance test, and further research can be designed in a model which can calculate the efficiency of a road when the percentage of self-driving cars are different.
基金Sponsored by Scientific Research Projects of Colleges and Universities in the Inner Mongolia Autonomous Region(NJSY018)
文摘Self-diiviiig tour is one of the most important wajrs for people to travel, and network travel notes actually reflect the traveling information of self-driving tourists. In this paper, witii the network travel notes of self-driving tourists as the tesearch object^ methods such as text analysis and visualization were adopted to study behavior patterns of self-driving tourists, tourism experience, time-space migration, and distribution of tourism resources in Inner Mongolia, fi:om the multiple dimensions of mobile drivers, perceived, dimensions, and spatial migration. The results showed tiiat ①self-cidviiig tourists had a variety of motivations for traveling, in which love for nature dominated; ②self-driving tour destinations were mainly Hulunbuir, Ordos, and Alxa League; ③spatial migration was characterized by obvious seasonal fluctuations. The fesearch on the behavior of self-driving tourists in Inner Mongolia is an important part of the study of the connection between tourism resources and market connection in Inner Mongolia, and is of significance for guiding the theory, practice and poliqr foimuktion of self-doving tours in Inner Mongolia.
文摘Security systems are a necessity for the deployment of smart vehicles in our society. Security in vehicular ad hoe networks is crucial to the reliable exchange of information and control data. In this paper, we propose an intelligent Intrusion Detection System (IDS) to protect the external communication of self-driving and semi self-driving vehicles. This technology has the ability to detect Denial of Service (DOS) and black hole attacks on vehicular ad hoe networks (VANETs). The advantage of the proposed IDS over existing security systems is that it detects attacks before they causes significant damage. The intrusion prediction technique is based on Linear Discriminant Analysis (LDA) and Quadratic Diseriminant Analysis (QDA) which are used to predict attacks based on observed vehicle behavior. We perform simulations using Network Simulator 2 to demonstrate that the IDS achieves a low rate of false alarms and high accuracy in detection.
文摘Countries have invested considerable sums of human capital and material resources in the practical application of self-driving cars demonstrating the impressive market opportunity.In light of this trend,Taiwan does not want to fall behind either.As on-road testing and technological development for self-driving cars continue to develop in different countries,the controversial issues of safety,ethics,liability,and the invasion of privacy continue to emerge.In order to resolve these issues,the government of Taiwan seeks to provide a good environment for AI(artificial intelligence)innovation and applications.This article summarizes and highlights relevant content and key points of Unmanned Vehicles Technology Innovative Experimentation Act,which was legislated in Taiwan in 2018.In addition,it points out the fundamental ethics regulation of AI,which has influenced Taiwan legal policy.
文摘Late this March.China's Internet giant Baidu became the first self-driving car developer to obtain temporary license plates to carry out self driving tests on public roads in Beijing.
基金supported by the Inner Mongolia Autonomous Region Science and Technology Major Special Project(Grant No.2021SZD0082).
文摘Stainless steels are used in a wide range of complex environments due to their excellent corrosion resistance.Multiphase stainless steels can offer an excellent combination of strength,toughness and corrosion resistance due to the coexistence of different microstructures.The microstructure and mechanical properties of a novel cast multiphase stainless steel,composed of martensite,ferrite,and austenite,were investigated following appropriate heat treatment processes:solution treatment at 1,050℃ for 0.5 h followed by water quenching to room temperature,and aging treatment at 500℃ for 4 h followed by water quenching to room temperature.Results show reversed austenite is formed by diffusion of Ni element during aging process,and the enrichment of Ni atoms directly determines the mechanical stability of austenite.The austenite with a lower Ni content undergoes a martensitic transformation during plastic deformation.The tensile strength of the specimen exceeds 1,100 MPa and the elongation exceeds 24%after solid solution,and further increases to 1,247 MPa and 25%after aging treatment.This enhancement is due to the TRIP effect of austenite and the precipitation of the nanoscale G-phase pinning dislocations in ferrite and martensite.
文摘Foreign tourists'trips to China recently reached a new height,both online and offline.Travel agents around the world also made trips to China,generating more thoughts for the development of new routes and the design of innovative tourist products,and contributing to the development of China's inbound tourism.