A high-precision map(HPM)is the key infrastructure to realizing the function of automated driving(AD)and ensuring its safety.However,the current laws and regulations on HPMs in China can lead to serious legal complian...A high-precision map(HPM)is the key infrastructure to realizing the function of automated driving(AD)and ensuring its safety.However,the current laws and regulations on HPMs in China can lead to serious legal compliance problems.Thus,proper measures should be taken to remove these barriers.Starting with a complete view of the current legal obstacles to HPMs in China,this study first explains why these legal obstacles exist and the types of legal interests they are trying to protect.It then analyzes whether new technology could be used as an alternative to resolve these concerns.Factors such as national security,AD industry needs,and personal data protection,as well as the flexibility of applying technology,are discussed and analyzed hierarchically for this purpose.This study proposes that China should adhere to national security and AD industry development,pass new technical regulations that redefine the scope of national security regarding geographic information in the field of HPMs,and establish a national platform under the guidance and monitoring of the government to integrate scattered resources and promote the development of HPMs via crowdsourcing.Regarding the legal obstacles with higher technical plasticity,priority should be given to technical solutions such as“available but invisible”technology.Compared with the previous research,this study reveals the current legal barriers in China that have different levels of relevance to national security and different technical plasticity.It also proposes original measures to remove them,such as coordinating national security with the development of the AD industry,reshaping the boundary of national security and industrial interests,and giving priority to technical solutions for legal barriers that have strong technical plasticity.展开更多
Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time p...Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time perception of traffic resources in the entire space-time range,and the criterion for the operation and control of the whole process of the vehicle.As a new form of map,it has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps.Thus,it is necessary to analyze and discuss its key features and problems to promote the development of research and application of intelligent high-precision map.Accordingly,we propose an information transmission model based on the cartography theory and combine the wheeled robot’s control flow in practical application.Next,we put forward the data logic structure of intelligent high-precision map,and analyze its application in autonomous driving.Then,we summarize the computing mode of“Crowdsourcing+Edge-Cloud Collaborative Computing”,and carry out key technical analysis on how to improve the quality of crowdsourced data.We also analyze the effective application scenarios of intelligent high-precision map in the future.Finally,we present some thoughts and suggestions for the future development of this field.展开更多
With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,spec...With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,specialized,and innovative enterprises.As a representative of such enterprises,JL Technology has faced challenges to its R&D efficiency due to talent loss in recent years.This study takes this enterprise as a case to explore feasible paths to reduce turnover rates through optimizing training and career development systems.The research designs a method combining learning maps and talent maps,utilizes a competency model to clarify the direction for engineers’skill improvement,implements talent classification management using a nine-grid model,and achieves personalized training through Individual Development Plans(IDPs).Analysis of the enterprise’s historical data reveals that the main reasons for turnover are unclear career development paths and insufficient resources for skill improvement.After pilot implementation,the turnover rate in core departments decreased by 12%,and employee satisfaction with training increased by 24%.The results indicate that matching systematic talent reviews with dynamic learning resources can effectively enhance engineers’sense of belonging.This study provides a set of highly operational management tools for small and medium-sized high-precision,specialized,and innovative technology enterprises,verifies their applicability in such enterprises,and offers replicable experiences for similar enterprises to optimize their talent strategies[1].展开更多
China has made some remarkable achievements in sustainable development,but the constant deterioration of the overall trend of the environment has not yet been effectively curbed.To achieve the goal of sustainable deve...China has made some remarkable achievements in sustainable development,but the constant deterioration of the overall trend of the environment has not yet been effectively curbed.To achieve the goal of sustainable development,we must first ensure coordination and coherence of national development goals in different areas and adhere to green development road.To achieve the objectives related to green development,and to clarify the direction of green development in the next 20years,a road map is needed to guide and coordinate the process.This paper describes the concept of the green development road map,introduces a green development road map for the western region,and further elaborates it The road map clarifies the objectives and guiding principles of green development in the western region,points the areas that deserve more concern and institutional innovation,and builds a green development monitoring and evaluation(M&E)framework.Finally,the paper provides corresponding policy recommendations based on the established road map.展开更多
This article describes a biologically inspired node generator for the path planning of serially connected hyper-redundant manipulators using probabilistic roadmap planners. The generator searches the configuration spa...This article describes a biologically inspired node generator for the path planning of serially connected hyper-redundant manipulators using probabilistic roadmap planners. The generator searches the configuration space surrounding existing nodes in the roadmap and uses a combination of random and deterministic search methods that emulate the behaviour of octopus limbs. The strategy consists of randomly mutating the states of the links near the end-effector, and mutating the states of the links near the base of the robot toward the states of the goal configuration. When combined with the small tree probabilistic roadmap planner, the method was successfully used to solve the narrow passage motion planning problem of a 17 degree-of-freedom manipulator.展开更多
The essential requirement for precise localization of a self-driving car is a lane-level map which includes road markings(RMs).Obviously,we can build the lane-level map by running a mobile mapping system(MMS)which is ...The essential requirement for precise localization of a self-driving car is a lane-level map which includes road markings(RMs).Obviously,we can build the lane-level map by running a mobile mapping system(MMS)which is equipped with a high-end 3D LiDAR and a number of high-cost sensors.This approach,however,is highly expensive and ineffective since a single high-end MMS must visit every place for mapping.In this paper,a lane-level RM mapping system using a monocular camera is developed.The developed system can be considered as an alternative to expensive high-end MMS.The developed RM map includes the information of road lanes(RLs)and symbolic road markings(SRMs).First,to build a lane-level RM map,the RMs are segmented at pixel level through the deep learning network.The network is named RMNet.The segmented RMs are then gathered to build a lane-level RM map.Second,the lane-level map is improved through loop-closure detection and graph optimization.To train the RMNet and build a lane-level RM map,a new dataset named SeRM set is developed.The set is a large dataset for lane-level RM mapping and it includes a total of 25157 pixel-wise annotated images and 21000 position labeled images.Finally,the proposed lane-level map building method is applied to SeRM set and its validity is demonstrated through experimentation.展开更多
Renewable energy (RE) has been attached high attention around the world due to its carbon-free and indigenous production in a sustainable way. China enjoys plenty of renewable energy resources, particularly the wind, ...Renewable energy (RE) has been attached high attention around the world due to its carbon-free and indigenous production in a sustainable way. China enjoys plenty of renewable energy resources, particularly the wind, solar, hydro- and biomass energy, which could be a sound basis for a large-scale exploitation. This report examines the current status of RE technology and industry, analyzes the challenges of promoting RE in China. In order to pave the way for a long-term development of RE, this paper outlines the basic principles and priorities for individual RE technology. In line with these, the paper puts forward the RE targets and further describes the RE road map by 2020, 2030 and extend to 2050, taking consideration of China’s RE resources, industrial basis and energy demand etc. At last, this paper provides some recommendations to ensure the achievements of the RE targets.展开更多
Landslide susceptibility mapping of mountain roads is frequently confronted by insufficient historical landslide sample data,multicollinearity of existing evaluation index factors,and inconsistency of evaluation facto...Landslide susceptibility mapping of mountain roads is frequently confronted by insufficient historical landslide sample data,multicollinearity of existing evaluation index factors,and inconsistency of evaluation factors due to regional environmental variations.Then,a single machine learning model can easily become overfitting,thus reducing the accuracy and robustness of the evaluation model.This paper proposes a combined machine-learning model to address the issues.The landslide susceptibility in mountain roads were mapped by using factor analysis to normalize and reduce the dimensionality of the initial condition factor and generating six new combination factors as evaluation indexes.The mountain roads in the Youxi County,Fujian Province,China were used for the landslide susceptibility mapping.Three most frequently used machine learning techniques,support vector machine(SVM),random forest(RF),and artificial neural network(ANN)models,were used to model the landslide susceptibility of the study area and validate the accuracy of this evaluation index system.The global minimum variance portfolio was utilized to construct a machine learning combined model.5-fold cross-validation,statistical indexes,and AUC(Area Under Curve)values were implemented to evaluate the predictive accuracy of the landslide susceptibility model.The mean AUC values for the SVM,RF,and ANN models in the training stage were 89.2%,88.5%,and 87.9%,respectively,and 78.0%,73.7%,and 76.7%,respectively,in the validating stage.In the training and validation stages,the mean AUC values of the combined model were 92.4% and 87.1%,respectively.The combined model provides greater prediction accuracy and model robustness than one single model.展开更多
In order to realize an optimal balance between the efficiency and reliability requirements ofroad models,a road modeling method for digital maps based on cardinal spline is studied.First,the cardinal spline is chosen ...In order to realize an optimal balance between the efficiency and reliability requirements ofroad models,a road modeling method for digital maps based on cardinal spline is studied.First,the cardinal spline is chosen to establish an initial road model,which is specified by a series of control points and tension parameters.Then,in view of the initial road model,a gradual optimization algorithm,which can determine the reasonable control points and optimal tension parameters according to the degree of the change of road curvature,is proposed to determine the final road model.Finally,the proposed road modeling method is verified a d evaluated through experiments,and it is compared with the conventional method for digital maps based on the B-spline.The results show that the proposed method can resize a neaoptimal balance between the efficiency and reliability requirements.Compared with the conventional method based on the B-spline,this method occupies less data storage and achieves higher accuracy.展开更多
As a disaster prevention measure based on self-assistance and mutual assistance,disaster prevention maps are being created with citizen participation throughout Japan.The process of creating disaster prevention maps i...As a disaster prevention measure based on self-assistance and mutual assistance,disaster prevention maps are being created with citizen participation throughout Japan.The process of creating disaster prevention maps is itself a disaster prevention measure that contributes to raising awareness of disaster prevention by promoting exchange and cooperation within the region.By focusing on relations between road networks and hazardous elements,we developed a system to support disaster prevention map creation that visualizes roads at high risk during a disaster and facilitates the study of evacuation simulations.This system leads to a completed disaster prevention map in three phases.In the first phase,we use a device with GPS logging functions to collect information related to hazardous elements.In the second phase,we use Google Maps(“online map,”below)to visualize roads with high evacuation risk.In the final phase,we perform a regional evaluation through simulations of disaster-time evacuations.In experimental verifications,by conducting usability tests after creating a disaster prevention map in the target area,we evaluated the system in terms of simple operability and visibility.We found that by implementing this series of processes,even users lacking specialized knowledge regarding disaster prevention can intuitively discover evacuation routes while considering the relations between visualized road networks and hazardous elements.These results show that compared with disaster prevention maps having simple site notations using existing WebGIS systems,disaster prevention maps created by residents while inspecting the target area raise awareness of risks present in the immediate vicinity even in normal times and are an effective support system for prompt disaster prevention measures and evacuation drills.展开更多
A method for road boundary detection and tracking using laser ladar with respect to a vehicle＇ s local coordinates is proposed. It can be applied to different types of road conditions, such as roads with or without c...A method for road boundary detection and tracking using laser ladar with respect to a vehicle＇ s local coordinates is proposed. It can be applied to different types of road conditions, such as roads with or without curbs, having relatively rough road surface and with obstacles on road surface. In the method, some line segments are extracted after a series of preprocessing on range data. The extracted line segments are combined and further selected. They are then united to match the road models and generate the road boundary points which are tracked by Kalman filter. Then the obtained road boundary points are transformed to build a precise vector map by least squares fitting algorithm. These fitted line segments represent road boundary vectors. The vector map is precise enough to provide ample road information such as the orientation of road, the road width and the passable road region. Finally, extensive experiments conducted in urban and semi-urban environment demonstrate the robustness, effectiveness and viability of the proposed method.展开更多
Sfax is one of the Tunisian governorates with a large number of road accidents, injuries and fatalities every year. This study aimed to analyze and map traffic accidents in this governorate. We analyzed the spatial di...Sfax is one of the Tunisian governorates with a large number of road accidents, injuries and fatalities every year. This study aimed to analyze and map traffic accidents in this governorate. We analyzed the spatial distribution of accidents, their distribution by cause, by type of road, by size of traffic, by months of the year and days of the week. Accidents were correlated with several variables such as population numbers and densities, motorization rate, length and structure of the road network, and the amount of traffic. On the cartographic level, we have built a database, through which we have produced a series of thematic maps to argue this analysis. Through cartographic production, we also aimed to help road users, decision-makers and researchers in <span>this area and in the field of transport. This work showed that Sfax occupies, among the other Tunisian governorates, an advanced position in gravity. Various human, climatic and technical factors explained this situation, of which human factors were the most important, and contributed </span></span><span style="font-family:"">to</span><span style="font-family:""> almost</span><span style="font-family:""> 90% of accidents. The current situation of accidents in Sfax requires a series of measures and actions to alleviate and mitigate the gravity of this phenomenon.展开更多
There is a problem of real-time detection difficulty in road surface damage detection. This paper proposes an improved lightweight model based on you only look once version 5(YOLOv5). Firstly, this paper fully utilize...There is a problem of real-time detection difficulty in road surface damage detection. This paper proposes an improved lightweight model based on you only look once version 5(YOLOv5). Firstly, this paper fully utilized the convolutional neural network(CNN) + ghosting bottleneck(G_bneck) architecture to reduce redundant feature maps. Afterwards, we upgraded the original upsampling algorithm to content-aware reassembly of features(CARAFE) and increased the receptive field. Finally, we replaced the spatial pyramid pooling fast(SPPF) module with the basic receptive field block(Basic RFB) pooling module and added dilated convolution. After comparative experiments, we can see that the number of parameters and model size of the improved algorithm in this paper have been reduced by nearly half compared to the YOLOv5s. The frame rate per second(FPS) has been increased by 3.25 times. The mean average precision(m AP@0.5: 0.95) has increased by 8%—17% compared to other lightweight algorithms.展开更多
A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional an...A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.展开更多
基金the Research on Governing Princi-ples and Mechanism of Autonomous Driving Supported by the Shanghai Science and Technology Committee(No.20511101703)the Research on Key Applicable Techniques and Legal Social Problem about Autonomous Driving Electronic Vehicles Sup-ported by the Ministry of Science and Technology(No.2018YFB0105202-05)。
文摘A high-precision map(HPM)is the key infrastructure to realizing the function of automated driving(AD)and ensuring its safety.However,the current laws and regulations on HPMs in China can lead to serious legal compliance problems.Thus,proper measures should be taken to remove these barriers.Starting with a complete view of the current legal obstacles to HPMs in China,this study first explains why these legal obstacles exist and the types of legal interests they are trying to protect.It then analyzes whether new technology could be used as an alternative to resolve these concerns.Factors such as national security,AD industry needs,and personal data protection,as well as the flexibility of applying technology,are discussed and analyzed hierarchically for this purpose.This study proposes that China should adhere to national security and AD industry development,pass new technical regulations that redefine the scope of national security regarding geographic information in the field of HPMs,and establish a national platform under the guidance and monitoring of the government to integrate scattered resources and promote the development of HPMs via crowdsourcing.Regarding the legal obstacles with higher technical plasticity,priority should be given to technical solutions such as“available but invisible”technology.Compared with the previous research,this study reveals the current legal barriers in China that have different levels of relevance to national security and different technical plasticity.It also proposes original measures to remove them,such as coordinating national security with the development of the AD industry,reshaping the boundary of national security and industrial interests,and giving priority to technical solutions for legal barriers that have strong technical plasticity.
基金National Key Research and Development Program(No.2018YFB1305001)Major Consulting and Research Project of Chinese Academy of Engineering(No.2018-ZD-02-07)。
文摘Taking autonomous driving and driverless as the research object,we discuss and define intelligent high-precision map.Intelligent high-precision map is considered as a key link of future travel,a carrier of real-time perception of traffic resources in the entire space-time range,and the criterion for the operation and control of the whole process of the vehicle.As a new form of map,it has distinctive features in terms of cartography theory and application requirements compared with traditional navigation electronic maps.Thus,it is necessary to analyze and discuss its key features and problems to promote the development of research and application of intelligent high-precision map.Accordingly,we propose an information transmission model based on the cartography theory and combine the wheeled robot’s control flow in practical application.Next,we put forward the data logic structure of intelligent high-precision map,and analyze its application in autonomous driving.Then,we summarize the computing mode of“Crowdsourcing+Edge-Cloud Collaborative Computing”,and carry out key technical analysis on how to improve the quality of crowdsourced data.We also analyze the effective application scenarios of intelligent high-precision map in the future.Finally,we present some thoughts and suggestions for the future development of this field.
文摘With the intensifying competition in the integrated circuit(IC)industry,the high turnover rate of integrated circuit engineers has become a prominent issue affecting the technological continuity of high-precision,specialized,and innovative enterprises.As a representative of such enterprises,JL Technology has faced challenges to its R&D efficiency due to talent loss in recent years.This study takes this enterprise as a case to explore feasible paths to reduce turnover rates through optimizing training and career development systems.The research designs a method combining learning maps and talent maps,utilizes a competency model to clarify the direction for engineers’skill improvement,implements talent classification management using a nine-grid model,and achieves personalized training through Individual Development Plans(IDPs).Analysis of the enterprise’s historical data reveals that the main reasons for turnover are unclear career development paths and insufficient resources for skill improvement.After pilot implementation,the turnover rate in core departments decreased by 12%,and employee satisfaction with training increased by 24%.The results indicate that matching systematic talent reviews with dynamic learning resources can effectively enhance engineers’sense of belonging.This study provides a set of highly operational management tools for small and medium-sized high-precision,specialized,and innovative technology enterprises,verifies their applicability in such enterprises,and offers replicable experiences for similar enterprises to optimize their talent strategies[1].
基金financially supported by the "Strategy and Policies on Environment and Development in Western China" project of "China Council for International Cooperation onEnvironment and Development(CCICED)."
文摘China has made some remarkable achievements in sustainable development,but the constant deterioration of the overall trend of the environment has not yet been effectively curbed.To achieve the goal of sustainable development,we must first ensure coordination and coherence of national development goals in different areas and adhere to green development road.To achieve the objectives related to green development,and to clarify the direction of green development in the next 20years,a road map is needed to guide and coordinate the process.This paper describes the concept of the green development road map,introduces a green development road map for the western region,and further elaborates it The road map clarifies the objectives and guiding principles of green development in the western region,points the areas that deserve more concern and institutional innovation,and builds a green development monitoring and evaluation(M&E)framework.Finally,the paper provides corresponding policy recommendations based on the established road map.
文摘This article describes a biologically inspired node generator for the path planning of serially connected hyper-redundant manipulators using probabilistic roadmap planners. The generator searches the configuration space surrounding existing nodes in the roadmap and uses a combination of random and deterministic search methods that emulate the behaviour of octopus limbs. The strategy consists of randomly mutating the states of the links near the end-effector, and mutating the states of the links near the base of the robot toward the states of the goal configuration. When combined with the small tree probabilistic roadmap planner, the method was successfully used to solve the narrow passage motion planning problem of a 17 degree-of-freedom manipulator.
基金This work was supported by the Industry Core Technology Development Project,20005062Development of Artificial Intelligence Robot Autonomous Navigation Technology for Agile Movement in Crowded Space,funded by the Ministry of Trade,industry&Energy(MOTIE,Republic of Korea).
文摘The essential requirement for precise localization of a self-driving car is a lane-level map which includes road markings(RMs).Obviously,we can build the lane-level map by running a mobile mapping system(MMS)which is equipped with a high-end 3D LiDAR and a number of high-cost sensors.This approach,however,is highly expensive and ineffective since a single high-end MMS must visit every place for mapping.In this paper,a lane-level RM mapping system using a monocular camera is developed.The developed system can be considered as an alternative to expensive high-end MMS.The developed RM map includes the information of road lanes(RLs)and symbolic road markings(SRMs).First,to build a lane-level RM map,the RMs are segmented at pixel level through the deep learning network.The network is named RMNet.The segmented RMs are then gathered to build a lane-level RM map.Second,the lane-level map is improved through loop-closure detection and graph optimization.To train the RMNet and build a lane-level RM map,a new dataset named SeRM set is developed.The set is a large dataset for lane-level RM mapping and it includes a total of 25157 pixel-wise annotated images and 21000 position labeled images.Finally,the proposed lane-level map building method is applied to SeRM set and its validity is demonstrated through experimentation.
文摘Renewable energy (RE) has been attached high attention around the world due to its carbon-free and indigenous production in a sustainable way. China enjoys plenty of renewable energy resources, particularly the wind, solar, hydro- and biomass energy, which could be a sound basis for a large-scale exploitation. This report examines the current status of RE technology and industry, analyzes the challenges of promoting RE in China. In order to pave the way for a long-term development of RE, this paper outlines the basic principles and priorities for individual RE technology. In line with these, the paper puts forward the RE targets and further describes the RE road map by 2020, 2030 and extend to 2050, taking consideration of China’s RE resources, industrial basis and energy demand etc. At last, this paper provides some recommendations to ensure the achievements of the RE targets.
基金the financial support from the National Natural Science Foundation of China(No.U2005205,No.42007235,No.41972268)the Science and Technology Innovation Platform Project of Fuzhou Science and Technology Bureau(No.2021-P-032)。
文摘Landslide susceptibility mapping of mountain roads is frequently confronted by insufficient historical landslide sample data,multicollinearity of existing evaluation index factors,and inconsistency of evaluation factors due to regional environmental variations.Then,a single machine learning model can easily become overfitting,thus reducing the accuracy and robustness of the evaluation model.This paper proposes a combined machine-learning model to address the issues.The landslide susceptibility in mountain roads were mapped by using factor analysis to normalize and reduce the dimensionality of the initial condition factor and generating six new combination factors as evaluation indexes.The mountain roads in the Youxi County,Fujian Province,China were used for the landslide susceptibility mapping.Three most frequently used machine learning techniques,support vector machine(SVM),random forest(RF),and artificial neural network(ANN)models,were used to model the landslide susceptibility of the study area and validate the accuracy of this evaluation index system.The global minimum variance portfolio was utilized to construct a machine learning combined model.5-fold cross-validation,statistical indexes,and AUC(Area Under Curve)values were implemented to evaluate the predictive accuracy of the landslide susceptibility model.The mean AUC values for the SVM,RF,and ANN models in the training stage were 89.2%,88.5%,and 87.9%,respectively,and 78.0%,73.7%,and 76.7%,respectively,in the validating stage.In the training and validation stages,the mean AUC values of the combined model were 92.4% and 87.1%,respectively.The combined model provides greater prediction accuracy and model robustness than one single model.
基金The National Natural Science Foundation of China(No.61273236)the National Key Research and Development Plan of China(No.2016YFC0802706,2017YFC0804804)+1 种基金the Program for Special Talents in Six Major Fields of Jiangsu Province(No.2017JXQC-003)the Project of Beijing Municipal Science and Technology Commission(No.Z161100001416001)
文摘In order to realize an optimal balance between the efficiency and reliability requirements ofroad models,a road modeling method for digital maps based on cardinal spline is studied.First,the cardinal spline is chosen to establish an initial road model,which is specified by a series of control points and tension parameters.Then,in view of the initial road model,a gradual optimization algorithm,which can determine the reasonable control points and optimal tension parameters according to the degree of the change of road curvature,is proposed to determine the final road model.Finally,the proposed road modeling method is verified a d evaluated through experiments,and it is compared with the conventional method for digital maps based on the B-spline.The results show that the proposed method can resize a neaoptimal balance between the efficiency and reliability requirements.Compared with the conventional method based on the B-spline,this method occupies less data storage and achieves higher accuracy.
基金This work was supported by JSPS KAKENHI Grant Number JP20K20122.
文摘As a disaster prevention measure based on self-assistance and mutual assistance,disaster prevention maps are being created with citizen participation throughout Japan.The process of creating disaster prevention maps is itself a disaster prevention measure that contributes to raising awareness of disaster prevention by promoting exchange and cooperation within the region.By focusing on relations between road networks and hazardous elements,we developed a system to support disaster prevention map creation that visualizes roads at high risk during a disaster and facilitates the study of evacuation simulations.This system leads to a completed disaster prevention map in three phases.In the first phase,we use a device with GPS logging functions to collect information related to hazardous elements.In the second phase,we use Google Maps(“online map,”below)to visualize roads with high evacuation risk.In the final phase,we perform a regional evaluation through simulations of disaster-time evacuations.In experimental verifications,by conducting usability tests after creating a disaster prevention map in the target area,we evaluated the system in terms of simple operability and visibility.We found that by implementing this series of processes,even users lacking specialized knowledge regarding disaster prevention can intuitively discover evacuation routes while considering the relations between visualized road networks and hazardous elements.These results show that compared with disaster prevention maps having simple site notations using existing WebGIS systems,disaster prevention maps created by residents while inspecting the target area raise awareness of risks present in the immediate vicinity even in normal times and are an effective support system for prompt disaster prevention measures and evacuation drills.
基金Supported by the National Natural Science Foundation of China (61174178)
文摘A method for road boundary detection and tracking using laser ladar with respect to a vehicle＇ s local coordinates is proposed. It can be applied to different types of road conditions, such as roads with or without curbs, having relatively rough road surface and with obstacles on road surface. In the method, some line segments are extracted after a series of preprocessing on range data. The extracted line segments are combined and further selected. They are then united to match the road models and generate the road boundary points which are tracked by Kalman filter. Then the obtained road boundary points are transformed to build a precise vector map by least squares fitting algorithm. These fitted line segments represent road boundary vectors. The vector map is precise enough to provide ample road information such as the orientation of road, the road width and the passable road region. Finally, extensive experiments conducted in urban and semi-urban environment demonstrate the robustness, effectiveness and viability of the proposed method.
文摘Sfax is one of the Tunisian governorates with a large number of road accidents, injuries and fatalities every year. This study aimed to analyze and map traffic accidents in this governorate. We analyzed the spatial distribution of accidents, their distribution by cause, by type of road, by size of traffic, by months of the year and days of the week. Accidents were correlated with several variables such as population numbers and densities, motorization rate, length and structure of the road network, and the amount of traffic. On the cartographic level, we have built a database, through which we have produced a series of thematic maps to argue this analysis. Through cartographic production, we also aimed to help road users, decision-makers and researchers in <span>this area and in the field of transport. This work showed that Sfax occupies, among the other Tunisian governorates, an advanced position in gravity. Various human, climatic and technical factors explained this situation, of which human factors were the most important, and contributed </span></span><span style="font-family:"">to</span><span style="font-family:""> almost</span><span style="font-family:""> 90% of accidents. The current situation of accidents in Sfax requires a series of measures and actions to alleviate and mitigate the gravity of this phenomenon.
基金supported by the Shanghai Sailing Program,China (No.20YF1447600)the Research Start-Up Project of Shanghai Institute of Technology (No.YJ2021-60)+1 种基金the Collaborative Innovation Project of Shanghai Institute of Technology (No.XTCX2020-12)the Science and Technology Talent Development Fund for Young and Middle-Aged Teachers at Shanghai Institute of Technology (No.ZQ2022-6)。
文摘There is a problem of real-time detection difficulty in road surface damage detection. This paper proposes an improved lightweight model based on you only look once version 5(YOLOv5). Firstly, this paper fully utilized the convolutional neural network(CNN) + ghosting bottleneck(G_bneck) architecture to reduce redundant feature maps. Afterwards, we upgraded the original upsampling algorithm to content-aware reassembly of features(CARAFE) and increased the receptive field. Finally, we replaced the spatial pyramid pooling fast(SPPF) module with the basic receptive field block(Basic RFB) pooling module and added dilated convolution. After comparative experiments, we can see that the number of parameters and model size of the improved algorithm in this paper have been reduced by nearly half compared to the YOLOv5s. The frame rate per second(FPS) has been increased by 3.25 times. The mean average precision(m AP@0.5: 0.95) has increased by 8%—17% compared to other lightweight algorithms.
基金The National Key Technology R&D Program of China during the 11th Five Year Plan Period(No.2008BAJ11B01)
文摘A solution to compute the optimal path based on a single-line-single-directional（SLSD）road network model is proposed.Unlike the traditional road network model,in the SLSD conceptual model,being single-directional and single-line style,a road is no longer a linkage of road nodes but abstracted as a network node.Similarly,a road node is abstracted as the linkage of two ordered single-directional roads.This model can describe turn restrictions,circular roads,and other real scenarios usually described using a super-graph.Then a computing framework for optimal path finding（OPF）is presented.It is proved that classical Dijkstra and A algorithms can be directly used for OPF computing of any real-world road networks by transferring a super-graph to an SLSD network.Finally,using Singapore road network data,the proposed conceptual model and its corresponding optimal path finding algorithms are validated using a two-step optimal path finding algorithm with a pre-computing strategy based on the SLSD road network.
