The construction and installation of street lighting is an important element in the modernization of China’s cities.Besides,it also plays an important role in raising the living standards of the people.In recent year...The construction and installation of street lighting is an important element in the modernization of China’s cities.Besides,it also plays an important role in raising the living standards of the people.In recent years,with the technological and economic development,smart street lighting has gradually emerged.Key functions of smart street lighting include road illumination,cultural promotion,meteorological monitoring,public broadcasting,and 5G micro-base stations.The overall quality of smart street lighting construction directly impacts the effectiveness of urban development and the city’s comprehensive growth.This paper analyzes the concept of smart street lighting,its advantages and disadvantages,the functionalities of smart street light systems,and the application of smart street lighting in urban road illumination.展开更多
At present,the number of road engineering projects is increasing,and the corresponding street lighting work is receiving much more attention.In order to improve the lighting,operation,convenience,and energy-saving eff...At present,the number of road engineering projects is increasing,and the corresponding street lighting work is receiving much more attention.In order to improve the lighting,operation,convenience,and energy-saving effect of urban streets,the concept of“smart lighting”needs to be implemented.This includes the planning of an urban street lighting design scheme and the use of appropriate software as well as components to realize significant optimization of the lighting work in urban streets.Therefore,this paper discusses the application measures of smart lighting in urban street lighting to provide reference.展开更多
Comparing the city-size distribution at the urban agglomeration（UA） scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China＇s thre...Comparing the city-size distribution at the urban agglomeration（UA） scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China＇s three largest UAs, the Beijing-Tianjin-Hebei agglomeration（BTHA）, the Yangtze River Delta agglomeration（YRDA）, and the Pearl River Delta agglomeration（PRDA）, remain inadequate due to the limitation of data availability. Therefore, using urban data derived from time-series nighttime light data, the common characteristics and distinctive features of city-size distribution among the three UAs from 1992 to 2015 were compared by the Pareto regression and the rank clock method. We identified two common features. First, the city-size distribution became more even. The Pareto exponents increased by 0.17, 0.12, and 0.01 in the YRDA, BTHA, and PRDA, respectively. Second, the average ranks of small cities ascended, being 0.55, 0.08 and 0.04 in the three UAs, respectively. However, the average ranks of large and medium cities in the three UAs experienced different trajectories, which are closely related to the similarities and differences in the driving forces for the development of UAs. Place-based measures are encouraged to promote a coordinated development among cities of differing sizes in the three UAs.展开更多
Real-time and accurate traffic light status recognition can provide reliable data support for autonomous vehicle decision-making and control systems.To address potential problems such as the minor component of traffic...Real-time and accurate traffic light status recognition can provide reliable data support for autonomous vehicle decision-making and control systems.To address potential problems such as the minor component of traffic lights in the perceptual domain of visual sensors and the complexity of recognition scenarios,we propose an end-to-end traffic light status recognition method,ResNeSt50-CBAM-DINO(RC-DINO).First,we performed data cleaning on the Tsinghua-Tencent traffic lights(TTTL)and fused it with the Shanghai Jiao Tong University’s traffic light dataset(S2TLD)to form a Chinese urban traffic light dataset(CUTLD).Second,we combined residual network with split-attention module-50(ResNeSt50)and the convolutional block attention module(CBAM)to extract more significant traffic light features.Finally,the proposed RC-DINO and mainstream recognition algorithms were trained and analyzed using CUTLD.The experimental results show that,compared to the original DINO,RC-DINO improved the average precision(AP),AP at intersection over union(IOU)=0.5(AP50),AP for small objects(APs),average recall(AR),and balanced F score(F1-Score)by 3.1%,1.6%,3.4%,0.9%,and 0.9%,respectively,and had a certain capability to recognize the partially covered traffic light status.The above results indicate that the proposed RC-DINO improved recognition performance and robustness,making it more suitable for traffic light status recognition tasks.展开更多
文摘The construction and installation of street lighting is an important element in the modernization of China’s cities.Besides,it also plays an important role in raising the living standards of the people.In recent years,with the technological and economic development,smart street lighting has gradually emerged.Key functions of smart street lighting include road illumination,cultural promotion,meteorological monitoring,public broadcasting,and 5G micro-base stations.The overall quality of smart street lighting construction directly impacts the effectiveness of urban development and the city’s comprehensive growth.This paper analyzes the concept of smart street lighting,its advantages and disadvantages,the functionalities of smart street light systems,and the application of smart street lighting in urban road illumination.
文摘At present,the number of road engineering projects is increasing,and the corresponding street lighting work is receiving much more attention.In order to improve the lighting,operation,convenience,and energy-saving effect of urban streets,the concept of“smart lighting”needs to be implemented.This includes the planning of an urban street lighting design scheme and the use of appropriate software as well as components to realize significant optimization of the lighting work in urban streets.Therefore,this paper discusses the application measures of smart lighting in urban street lighting to provide reference.
基金National Natural Science Foundation of China,No.41621061,No.41501092 Talents Training Program from the Beijing Municipal Commission of Education No.201500002012G058
文摘Comparing the city-size distribution at the urban agglomeration（UA） scale is important for understanding the processes of urban development. However, comparative studies of city-size distribution among China＇s three largest UAs, the Beijing-Tianjin-Hebei agglomeration（BTHA）, the Yangtze River Delta agglomeration（YRDA）, and the Pearl River Delta agglomeration（PRDA）, remain inadequate due to the limitation of data availability. Therefore, using urban data derived from time-series nighttime light data, the common characteristics and distinctive features of city-size distribution among the three UAs from 1992 to 2015 were compared by the Pareto regression and the rank clock method. We identified two common features. First, the city-size distribution became more even. The Pareto exponents increased by 0.17, 0.12, and 0.01 in the YRDA, BTHA, and PRDA, respectively. Second, the average ranks of small cities ascended, being 0.55, 0.08 and 0.04 in the three UAs, respectively. However, the average ranks of large and medium cities in the three UAs experienced different trajectories, which are closely related to the similarities and differences in the driving forces for the development of UAs. Place-based measures are encouraged to promote a coordinated development among cities of differing sizes in the three UAs.
基金supported by the National Key R&D Program of China(2021YFB2501200)the Key Program of the National Natural Science Foundation of China(52131204)the Shaanxi Province Key Research and Development Program(2022GY-300).
文摘Real-time and accurate traffic light status recognition can provide reliable data support for autonomous vehicle decision-making and control systems.To address potential problems such as the minor component of traffic lights in the perceptual domain of visual sensors and the complexity of recognition scenarios,we propose an end-to-end traffic light status recognition method,ResNeSt50-CBAM-DINO(RC-DINO).First,we performed data cleaning on the Tsinghua-Tencent traffic lights(TTTL)and fused it with the Shanghai Jiao Tong University’s traffic light dataset(S2TLD)to form a Chinese urban traffic light dataset(CUTLD).Second,we combined residual network with split-attention module-50(ResNeSt50)and the convolutional block attention module(CBAM)to extract more significant traffic light features.Finally,the proposed RC-DINO and mainstream recognition algorithms were trained and analyzed using CUTLD.The experimental results show that,compared to the original DINO,RC-DINO improved the average precision(AP),AP at intersection over union(IOU)=0.5(AP50),AP for small objects(APs),average recall(AR),and balanced F score(F1-Score)by 3.1%,1.6%,3.4%,0.9%,and 0.9%,respectively,and had a certain capability to recognize the partially covered traffic light status.The above results indicate that the proposed RC-DINO improved recognition performance and robustness,making it more suitable for traffic light status recognition tasks.
