Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportatio...Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic lights amidst complex backgrounds. The integration of dilated convolutions, Region of Interest (ROI) alignment, and Soft Non-Maximum Suppression (Soft-NMS) further improves detection accuracy and reduces false positives. By optimizing computational efficiency and parameter complexity, the framework is designed to operate seamlessly on embedded systems, ensuring robust performance in real-world applications. Extensive experiments using real-world datasets demonstrate that our model significantly outperforms existing methods, providing a scalable solution for ITS and ADAS applications. This research contributes to the advancement of Artificial Intelligence-driven (AI-driven) pattern recognition in transportation systems and offers a mathematical approach to improving efficiency and safety in logistics and transportation networks.展开更多
The occurrence time and magnitude of injection-induced seismicity are influenced by engineering factors,such as wellhead pressure,injection location,injection volume,and injection rate.Understanding the relationship b...The occurrence time and magnitude of injection-induced seismicity are influenced by engineering factors,such as wellhead pressure,injection location,injection volume,and injection rate.Understanding the relationship between injection operations and seismic magnitude is of great significance for optimizing industrial production and reducing earthquake disasters.Numerical simulation of hydromechanical coupling is a crucial method for studying injection-induced seismicity.However,few studies have explored the risk management measures for injection-induced seismicity from the perspective of engineering.How seismic magnitudes can be reduced through reasonable adjustments to injection operations in engineering remains unclear.Therefore,in this study,a 3D hydro-mechanical coupling model involving multiple faults and injection wells was established based on the geological background and well location of Fox Creek,Canada.Different injection schemes under multi-well and multi-fault conditions were studied,and a traffic light system was used to simulate and control the magnitudes under a multi-well injection scheme.Specifically,we simulated injection scenarios involving up to three wells and analyzed the response of five faults.We compared the maximum moment magnitude of different scenarios by controlling the same injection volume.The results revealed the effect and advantage of the multi-well scheme in reducing seismic magnitude.To reduce the risk of induced seismicity,utilizing far-fault operational wells to compensate for the effects of near-fault operational wells proves to be an efficient and cost-effective method,with potential for wide practical applications.展开更多
This paper comprehensively analyzes the evolution of traffic light systems in Shanghai,highlighting the technological advancements and their impact on traffic management and safety.Starting from the historical context...This paper comprehensively analyzes the evolution of traffic light systems in Shanghai,highlighting the technological advancements and their impact on traffic management and safety.Starting from the historical context of the first traffic light in London in 1868 to the modern automated systems,the study explores the complexity and adaptability of traffic lights in Shanghai.Through field surveys and interviews with traffic engineers,the paper debunks common misconceptions about traffic light operation,revealing a sophisticated network that responds to real-time traffic dynamics using software like the Sydney Coordinated Adaptive Traffic System(SCATS)6.The study also discusses the importance of pedestrian safety,suggesting future enhancements such as Global Positioning System(GPS)based emergency systems and accommodations for color-blind individuals.The paper further delves into the potential of Artificial Intelligence(AI)and Vehicle-to-Infrastructure(V21)technology in revolutionizing traffic light systems,emphasizing their role in improving traffic flow and safety.The findings underscore Shanghai’s progressive approach to traffic management,showcasing the city’s commitment to optimizing traffic control solutions for the benefit of both vehicles and pedestrians.展开更多
In low-permeability geothermal reservoirs,hydro-shearing of pre-existing natural fractures plays a crucial role in improving connectivity between injection and production wells,thereby enhancing heat extraction effici...In low-permeability geothermal reservoirs,hydro-shearing of pre-existing natural fractures plays a crucial role in improving connectivity between injection and production wells,thereby enhancing heat extraction efficiency.This process increases fracture conductivity through dilation caused by injectioninduced slip;however,it also carries the risk of inducing seismic events,posing significant challenges for geothermal operations.This study employs a coupled hydro-mechanical numerical model based on the boundary element method to simulate hydro-shearing under two distinct fluid injection scenarios:(1)monotonic injection and(2)cyclic injection regulated by a traffic light system(TLS).The model assesses the effectiveness of these injection regimes in enhancing fracture conductivity while mitigating seismic hazards.Results indicate that monotonic injection frequently triggers a cascade of seismic events,disrupting pressure and stress distributions on nearby faults and resulting in complex seismic and aseismic interactions.In contrast,TLS-regulated cyclic injection,when carefully managed,promotes stable slip behavior and improves fracture conductivity.This approach proves particularly effective over extended durations during the simultaneous stimulation of two parallel faults.However,in multi-stage stimulation scenariosdwhere natural fractures are stimulated sequentiallydTLS-based cyclic injection,while more efficient at enhancing conductivity,may increase seismicity risk with prolonged application,thereby limiting its safe operational window.展开更多
To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transfo...To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.展开更多
Energy optimization management can make fuel cell truck(FCT)power system more efficient,so as to improve vehicle fuel economy.When the structure of power source system and the torque distribution strategy are determin...Energy optimization management can make fuel cell truck(FCT)power system more efficient,so as to improve vehicle fuel economy.When the structure of power source system and the torque distribution strategy are determined,the essence is to find the reasonable distribution of electric power between the fuel cell and other energy sources.The paper simulates the assistance of the intelligent transport system(ITS)and carries out the eco-velocity planning using the traffic signal light.On this basis,in order to further improve the energy efficiency of FCT,a model predictive control(MPC)-based energy source optimization management strategy is innovatively developed,which uses Dijkstra algorithm to achieve the minimization of equivalent hydrogen consumption.Under the scenarios of signalized intersections,based on the planned eco-velocity,the off-line simulation results show that the proposed MPC-based energy source management strategy(ESMS)can reduce hydrogen consumption of fuel cell up to 7%compared with the existing rule-based ESMS.Finally,the Hardware-in-the-Loop(HiL)simulation test is carried out to verify the effectiveness and real-time performance of the proposed MPC-based energy source optimization management strategy for the FCT based on eco-velocity planning with the assistance of traffic light information.展开更多
Cellular automation traffic models can include various factors in traffic systems and the corresponding computational simulations are rather simple and effective. The Biham-Middleton-Levine model (BML model) facilitat...Cellular automation traffic models can include various factors in traffic systems and the corresponding computational simulations are rather simple and effective. The Biham-Middleton-Levine model (BML model) facilitates the simulation of two-dimensional traffic flow problems via the cellular automaton models. In this paper, the BML model is improved by removing its limitation of synchronized change of traffic lights. In the new model, the traffic light at each crossing could arbitrarily change its starting time and tempo of variation, and hence the model could more realistically describe the influence of traffic lights on the performance of traffic systems. Some new effects appearing in the new model are also elucidated.展开更多
This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is appli...This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly rainfall.MADQN is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)approaches.MADQN enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in Malaysia.Investigation is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic network.Our proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.展开更多
A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is...A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is proposed for hybrid systems, and the average queue length over all queues is used as an objective function to find an optimal switching scheme for traffic light. It is illustrated that traffic light control for single intersection is a typical hybrid system, and the optimal planning-time scheme can be obtained using the optimal hybrid systems control based on the two stages method.展开更多
Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need ...Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge.Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms,sensors and cameras.However,they also face some challenges,such as high-cost installation,operation,and maintenance issues.This paper develops a new system based on the Virtual Traffic Light(VTL)technology to improve traffic flow at different intersections and reduce the encountered loss of time and vehicles’travel time.Additionally,it reduces the costs of installation,maintenance and operation over various conventional traffic light systems.Consequently,the system proposes algorithms for traffic scheduling and lane identification by using vehicle ID,priority and time of arrival.To evaluate the system,four scenarios were presented where each scenario uses a different number of vehicles consisting of three types(emergency vehicles,public buses and private vehicles),each given a different priority.The proposed system is evaluated by integrating two simulators,namely,(OMNeT++)and(SUMO),and two frameworks,namely,(VEINS)and(INET)to prepare an appropriate working environment.the results prove that an improvement in the average travel time for several vehicles reaches 44.43%–49.76%compared with conventional traffic lights.Further,it is proven from the obtained results that the average waiting time for emergency vehicles is enhanced by 96.63%–97.63%,while the average waiting time for public buses is improved by 94.81%–97.23%.On the other hand,the waiting time for private vehicles‘improved by 87.14%to 89.71%’.展开更多
Front-of-package(FOP)nutrition labelling schemes were developed to improve consumer’s comprehension about the food nutrients associated with non-communicable diseases(NCDs).Several FOPs have already been developed,an...Front-of-package(FOP)nutrition labelling schemes were developed to improve consumer’s comprehension about the food nutrients associated with non-communicable diseases(NCDs).Several FOPs have already been developed,and Brazil is in the process of evaluating a scheme to introduce in the products.The aim of this study was to investigate the impact of TLS,the scheme proposed by the food industry,on the product healthfulness perception.A study with 141 participants was carried out.A conjoint task was designed considering three categories and levels:types of dairy products(light yogurt,prato cheese,and chocolate flavoured milk),Traffic Light System(yes vs.no)and brand(well-known vs.unknown).The effect of TLS on perceived healthfulness was evaluated using a 9-point scales(1:not healthy;9:very healthy).Results showed that the inclusion of TLS did not influence the perceived healthfulness of the products by consumers,even among consumers with higher interest in healthy eating.These findings suggest that the proposal supported by the food industry does not seem to be the most appropriate,being recommended the development of further studies to compare the efficacy of TLS and other FOP schemes.展开更多
We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless network- ing between cars. One of many technologies that make road traffic safer and more eff...We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless network- ing between cars. One of many technologies that make road traffic safer and more efficient is the Virtual Traffic Light （VTL） system, which is able to coordinate the traffic flow at intersections without the need for physical lights. VTL takes a leading vehicle at an inter- section and uses it to control the traffic lights. We developed algorithms for leader election and traffic light computation in realistic ve- hicular networking scenarios. Our key contribution is the extension of this algorithm to support arbitrary intersection layouts. We in- vestigated the proposal in synthetic and realistic scenarios. The results show that, overall, VTLs use network resources efficiently and positively influences driving experience. It performs better than stationary traffic lights for a low to medium network load. We also identify potential optimizations to deal with high network load and to improve fairness.展开更多
The use of fixed-time traffic lights for road traffic control has the disadvantage of low traffic efficiency. In order to optimize the vehicle traffic at the intersection, this paper proposes a design scheme of a real...The use of fixed-time traffic lights for road traffic control has the disadvantage of low traffic efficiency. In order to optimize the vehicle traffic at the intersection, this paper proposes a design scheme of a real-time control system for road intelligent traffic lights based on FPGA. The system adopts the polling control model, the vehicle detector detects the arrival rate of vehicles, and obtains the corresponding traffic light green time length according to the traffic rules and polling model theory. Using Altera<span><span><span>’</span></span></span><span><span><span>s Cyclone IV series EP4CE15E22C8 chip as the development platform, a specific design plan is given. The circuit mainly includes program-controlled amplifier module, AD acquisition module, cross-correlation calculation module, serial port transmission and Lab-VIEW module. The system can realize the intelligent adjustment of traffic lights. Different vehicle arrival rates are detected at different times, so that the corresponding traffic light configuration time length changes accordingly. This intelligent adjustment controls road traffic and makes the main and branch roads coordinate and cooperate, thereby improving the traffic efficiency of the intersection.</span></span></span>展开更多
The problem of traffic congestion is a significant phenomenon that has had a substantial impact on the transportation system within the country. This phenomenon has given rise to numerous intricacies, particularly in ...The problem of traffic congestion is a significant phenomenon that has had a substantial impact on the transportation system within the country. This phenomenon has given rise to numerous intricacies, particularly in instances where emergency situations occur at traffic light intersections that are consistently congested with a high volume of vehicles. This implementation of a traffic light controller system is designed with the intention of addressing this problem. The purpose of the system was to facilitate the operation of a 3-way traffic control light and provide priority to emergency vehicles using a Radio Frequency Identification (RFID) sensor and Reduced Instruction Set Computing (RISC) Architecture Based Microcontroller. This research work involved designing a system to mitigate the occurrence of accidents commonly observed at traffic light intersections, where vehicles often need to maneuver in order to make way for emergency vehicles following a designated route. The research effectively achieved the analysis, simulation and implementation of wireless communication devices for traffic light control. The implemented prototype utilizes RFID transmission, operates in conjunction with the sequential mode of traffic lights to alter the traffic light sequence accordingly and reverts the traffic lights back to their normal sequence after the emergency vehicle has passed the traffic lights.展开更多
Based on the basic composition and principle of traffic control system with single-chip microcomputer, this paper formulates the hardware composition and program design ideas. The system takes AT89C51 single-chip micr...Based on the basic composition and principle of traffic control system with single-chip microcomputer, this paper formulates the hardware composition and program design ideas. The system takes AT89C51 single-chip microcomputer as the control core, designs the hardware circuit, uses the simulation software, and analyzes the circuit structure. Draw the function flow chart of the program, then write the program code, and carry out the function test on the built hardware platform, and further improve the program according to the debugging results.展开更多
Traffic flows controlled by traffic light strategies were investigated via a cellular automaton model with anticipation, which is suitable for describing urban traffic. Three kinds of strategies, i. e., synchronized, ...Traffic flows controlled by traffic light strategies were investigated via a cellular automaton model with anticipation, which is suitable for describing urban traffic. Three kinds of strategies, i. e., synchronized, green-wave and random switching lights, were designed, simulated and compared with each other. It is shown that the green-wave strategy is only valid at lower density and there is not an effective way with the three strategies to improve the efficiency of traffic flow at high density.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
Traffic light detection and recognition is essential for autonomous driving in urban environments. A camera based algorithm for real-time robust traffic light detection and recognition was proposed, and especially des...Traffic light detection and recognition is essential for autonomous driving in urban environments. A camera based algorithm for real-time robust traffic light detection and recognition was proposed, and especially designed for autonomous vehicles. Although the current reliable traffic light recognition algorithms operate well under way, most of them are mainly designed for detection at a fixed position and the effect on autonomous vehicles under real-world conditions is still limited. Some methods achieve high accuracy on autonomous vehicle, but they can＇t work normally without the aid of high-precision priori map. The authors presented a camera-based algorithm for the problem. The image processing flow can be divided into three steps, including pre-processing, detection and recognition. Firstly, red-green-blue （RGB） color space is converted to hue-saturation-value （HSV） as main content of pre-processing. In detection step, the transcendental color threshold method is used for initial filterings, meanwhile, the prior knowledge is performed to scan the scene in order to quickly establish candidate regions. For recognition, this article use histogram of oriented gradients （HOG） features and support vector machine （SVM） as well to recognize the state of traffic light. The proposed system on our autonomous vehicle was evaluated. With voting schemes, the proposed can provide a sufficient accuracy for autonomous vehicles in urban enviroment.展开更多
Visible Light Communication( VLC) based on LED is a new wireless communication technology with high response rate and good modulation characteristics in the wavelengths of 380- 780 nm. Compared with conventional metho...Visible Light Communication( VLC) based on LED is a new wireless communication technology with high response rate and good modulation characteristics in the wavelengths of 380- 780 nm. Compared with conventional methods,the waveband of VLC is harmless to human and safe to communication because of no magnetism radiation. An audio information transmission system using LED traffic lights is presented based on VLC technology. The system is consisted of transmitting terminal,receiving terminal and communication channel. Some experiments were made under real communication environment. The experimental results showed that the traffic information transmission system works steadily with good communication quality and achieves the purpose of transmitting audio information through LED traffic lights,with a data transfer rate up to 250 kbps over a distance of 5 meters.展开更多
基金funded by the Deanship of Scientific Research at Northern Border University,Arar,Saudi Arabia through research group No.(RG-NBU-2022-1234).
文摘Transportation systems are experiencing a significant transformation due to the integration of advanced technologies, including artificial intelligence and machine learning. In the context of intelligent transportation systems (ITS) and Advanced Driver Assistance Systems (ADAS), the development of efficient and reliable traffic light detection mechanisms is crucial for enhancing road safety and traffic management. This paper presents an optimized convolutional neural network (CNN) framework designed to detect traffic lights in real-time within complex urban environments. Leveraging multi-scale pyramid feature maps, the proposed model addresses key challenges such as the detection of small, occluded, and low-resolution traffic lights amidst complex backgrounds. The integration of dilated convolutions, Region of Interest (ROI) alignment, and Soft Non-Maximum Suppression (Soft-NMS) further improves detection accuracy and reduces false positives. By optimizing computational efficiency and parameter complexity, the framework is designed to operate seamlessly on embedded systems, ensuring robust performance in real-world applications. Extensive experiments using real-world datasets demonstrate that our model significantly outperforms existing methods, providing a scalable solution for ITS and ADAS applications. This research contributes to the advancement of Artificial Intelligence-driven (AI-driven) pattern recognition in transportation systems and offers a mathematical approach to improving efficiency and safety in logistics and transportation networks.
基金funded by the Joint Funds of the National Natural Science Foundation of China(U23A20671)the Major Project of Inner Mongolia Science and Technology(2021ZD0034)the Open Research Fund of State Key Laboratory of Geomechanics and Geotechnical Engineering(No.Z021003)。
文摘The occurrence time and magnitude of injection-induced seismicity are influenced by engineering factors,such as wellhead pressure,injection location,injection volume,and injection rate.Understanding the relationship between injection operations and seismic magnitude is of great significance for optimizing industrial production and reducing earthquake disasters.Numerical simulation of hydromechanical coupling is a crucial method for studying injection-induced seismicity.However,few studies have explored the risk management measures for injection-induced seismicity from the perspective of engineering.How seismic magnitudes can be reduced through reasonable adjustments to injection operations in engineering remains unclear.Therefore,in this study,a 3D hydro-mechanical coupling model involving multiple faults and injection wells was established based on the geological background and well location of Fox Creek,Canada.Different injection schemes under multi-well and multi-fault conditions were studied,and a traffic light system was used to simulate and control the magnitudes under a multi-well injection scheme.Specifically,we simulated injection scenarios involving up to three wells and analyzed the response of five faults.We compared the maximum moment magnitude of different scenarios by controlling the same injection volume.The results revealed the effect and advantage of the multi-well scheme in reducing seismic magnitude.To reduce the risk of induced seismicity,utilizing far-fault operational wells to compensate for the effects of near-fault operational wells proves to be an efficient and cost-effective method,with potential for wide practical applications.
文摘This paper comprehensively analyzes the evolution of traffic light systems in Shanghai,highlighting the technological advancements and their impact on traffic management and safety.Starting from the historical context of the first traffic light in London in 1868 to the modern automated systems,the study explores the complexity and adaptability of traffic lights in Shanghai.Through field surveys and interviews with traffic engineers,the paper debunks common misconceptions about traffic light operation,revealing a sophisticated network that responds to real-time traffic dynamics using software like the Sydney Coordinated Adaptive Traffic System(SCATS)6.The study also discusses the importance of pedestrian safety,suggesting future enhancements such as Global Positioning System(GPS)based emergency systems and accommodations for color-blind individuals.The paper further delves into the potential of Artificial Intelligence(AI)and Vehicle-to-Infrastructure(V21)technology in revolutionizing traffic light systems,emphasizing their role in improving traffic flow and safety.The findings underscore Shanghai’s progressive approach to traffic management,showcasing the city’s commitment to optimizing traffic control solutions for the benefit of both vehicles and pedestrians.
基金the financial support of the Helmholtz Association's Initiative and Networking Fund for the Helmholtz Young Investigator Group ARES(Contract number VHNG-1516).
文摘In low-permeability geothermal reservoirs,hydro-shearing of pre-existing natural fractures plays a crucial role in improving connectivity between injection and production wells,thereby enhancing heat extraction efficiency.This process increases fracture conductivity through dilation caused by injectioninduced slip;however,it also carries the risk of inducing seismic events,posing significant challenges for geothermal operations.This study employs a coupled hydro-mechanical numerical model based on the boundary element method to simulate hydro-shearing under two distinct fluid injection scenarios:(1)monotonic injection and(2)cyclic injection regulated by a traffic light system(TLS).The model assesses the effectiveness of these injection regimes in enhancing fracture conductivity while mitigating seismic hazards.Results indicate that monotonic injection frequently triggers a cascade of seismic events,disrupting pressure and stress distributions on nearby faults and resulting in complex seismic and aseismic interactions.In contrast,TLS-regulated cyclic injection,when carefully managed,promotes stable slip behavior and improves fracture conductivity.This approach proves particularly effective over extended durations during the simultaneous stimulation of two parallel faults.However,in multi-stage stimulation scenariosdwhere natural fractures are stimulated sequentiallydTLS-based cyclic injection,while more efficient at enhancing conductivity,may increase seismicity risk with prolonged application,thereby limiting its safe operational window.
基金The Cultivation Fund of the Key Scientific and Technical Innovation Project of Higher Education of Ministry of Education (No.705020)
文摘To ensure revulsive driving of intelligent vehicles at intersections, a method is presented to detect and recognize the traffic lights. First, the stabling siding at intersections is detected by applying Hough transformation. Then, the colors of traffic lights are detected with color space transformation. Finally, self-associative memory is used to recognize the countdown characters of the traffic lights. Test results at 20 real intersections show that the ratio of correct stabling siding recognition reaches up to 90%;and the ratios of recognition of traffic lights and divided characters are 85% and 97%, respectively. The research proves that the method is efficient for the detection of stabling siding and is robust enough to recognize the characters from images with noise and broken edges.
基金the National Natural Science Foundation of China(No.U1564208).
文摘Energy optimization management can make fuel cell truck(FCT)power system more efficient,so as to improve vehicle fuel economy.When the structure of power source system and the torque distribution strategy are determined,the essence is to find the reasonable distribution of electric power between the fuel cell and other energy sources.The paper simulates the assistance of the intelligent transport system(ITS)and carries out the eco-velocity planning using the traffic signal light.On this basis,in order to further improve the energy efficiency of FCT,a model predictive control(MPC)-based energy source optimization management strategy is innovatively developed,which uses Dijkstra algorithm to achieve the minimization of equivalent hydrogen consumption.Under the scenarios of signalized intersections,based on the planned eco-velocity,the off-line simulation results show that the proposed MPC-based energy source management strategy(ESMS)can reduce hydrogen consumption of fuel cell up to 7%compared with the existing rule-based ESMS.Finally,the Hardware-in-the-Loop(HiL)simulation test is carried out to verify the effectiveness and real-time performance of the proposed MPC-based energy source optimization management strategy for the FCT based on eco-velocity planning with the assistance of traffic light information.
文摘Cellular automation traffic models can include various factors in traffic systems and the corresponding computational simulations are rather simple and effective. The Biham-Middleton-Levine model (BML model) facilitates the simulation of two-dimensional traffic flow problems via the cellular automaton models. In this paper, the BML model is improved by removing its limitation of synchronized change of traffic lights. In the new model, the traffic light at each crossing could arbitrarily change its starting time and tempo of variation, and hence the model could more realistically describe the influence of traffic lights on the performance of traffic systems. Some new effects appearing in the new model are also elucidated.
文摘This paper investigates the use of multi-agent deep Q-network(MADQN)to address the curse of dimensionality issue occurred in the traditional multi-agent reinforcement learning(MARL)approach.The proposed MADQN is applied to traffic light controllers at multiple intersections with busy traffic and traffic disruptions,particularly rainfall.MADQN is based on deep Q-network(DQN),which is an integration of the traditional reinforcement learning(RL)and the newly emerging deep learning(DL)approaches.MADQN enables traffic light controllers to learn,exchange knowledge with neighboring agents,and select optimal joint actions in a collaborative manner.A case study based on a real traffic network is conducted as part of a sustainable urban city project in the Sunway City of Kuala Lumpur in Malaysia.Investigation is also performed using a grid traffic network(GTN)to understand that the proposed scheme is effective in a traditional traffic network.Our proposed scheme is evaluated using two simulation tools,namely Matlab and Simulation of Urban Mobility(SUMO).Our proposed scheme has shown that the cumulative delay of vehicles can be reduced by up to 30%in the simulations.
文摘A single intersection of two phases is selected as a model to put forward a new optimal time-planning scheme for traffic light based on the model of hybrid automata for single intersection. A method of optimization is proposed for hybrid systems, and the average queue length over all queues is used as an objective function to find an optimal switching scheme for traffic light. It is illustrated that traffic light control for single intersection is a typical hybrid system, and the optimal planning-time scheme can be obtained using the optimal hybrid systems control based on the two stages method.
文摘Large cities suffer from traffic congestion,particularly at intersections,due to a large number of vehicles,which leads to the loss of time by increasing carbon emissions,including fuel consumption.Therefore,the need for optimising the flow of vehicles at different intersections and reducing the waiting time is a critical challenge.Conventional traffic lights have been used to control traffic flow at different intersections and have been improved to become more efficient by using different algorithms,sensors and cameras.However,they also face some challenges,such as high-cost installation,operation,and maintenance issues.This paper develops a new system based on the Virtual Traffic Light(VTL)technology to improve traffic flow at different intersections and reduce the encountered loss of time and vehicles’travel time.Additionally,it reduces the costs of installation,maintenance and operation over various conventional traffic light systems.Consequently,the system proposes algorithms for traffic scheduling and lane identification by using vehicle ID,priority and time of arrival.To evaluate the system,four scenarios were presented where each scenario uses a different number of vehicles consisting of three types(emergency vehicles,public buses and private vehicles),each given a different priority.The proposed system is evaluated by integrating two simulators,namely,(OMNeT++)and(SUMO),and two frameworks,namely,(VEINS)and(INET)to prepare an appropriate working environment.the results prove that an improvement in the average travel time for several vehicles reaches 44.43%–49.76%compared with conventional traffic lights.Further,it is proven from the obtained results that the average waiting time for emergency vehicles is enhanced by 96.63%–97.63%,while the average waiting time for public buses is improved by 94.81%–97.23%.On the other hand,the waiting time for private vehicles‘improved by 87.14%to 89.71%’.
基金Coordenacao Aperfeicaoamento de Pessoal de Nível Superior(CAPES,Brazil),Fundacaode AmparoàPesquisa do Estado do Rio de Janeiro(FAPERJ,Brazil)for financial support.
文摘Front-of-package(FOP)nutrition labelling schemes were developed to improve consumer’s comprehension about the food nutrients associated with non-communicable diseases(NCDs).Several FOPs have already been developed,and Brazil is in the process of evaluating a scheme to introduce in the products.The aim of this study was to investigate the impact of TLS,the scheme proposed by the food industry,on the product healthfulness perception.A study with 141 participants was carried out.A conjoint task was designed considering three categories and levels:types of dairy products(light yogurt,prato cheese,and chocolate flavoured milk),Traffic Light System(yes vs.no)and brand(well-known vs.unknown).The effect of TLS on perceived healthfulness was evaluated using a 9-point scales(1:not healthy;9:very healthy).Results showed that the inclusion of TLS did not influence the perceived healthfulness of the products by consumers,even among consumers with higher interest in healthy eating.These findings suggest that the proposal supported by the food industry does not seem to be the most appropriate,being recommended the development of further studies to compare the efficacy of TLS and other FOP schemes.
文摘We examine the network performance of algorithms for self-organized traffic management. In particular, we focus on wireless network- ing between cars. One of many technologies that make road traffic safer and more efficient is the Virtual Traffic Light （VTL） system, which is able to coordinate the traffic flow at intersections without the need for physical lights. VTL takes a leading vehicle at an inter- section and uses it to control the traffic lights. We developed algorithms for leader election and traffic light computation in realistic ve- hicular networking scenarios. Our key contribution is the extension of this algorithm to support arbitrary intersection layouts. We in- vestigated the proposal in synthetic and realistic scenarios. The results show that, overall, VTLs use network resources efficiently and positively influences driving experience. It performs better than stationary traffic lights for a low to medium network load. We also identify potential optimizations to deal with high network load and to improve fairness.
文摘The use of fixed-time traffic lights for road traffic control has the disadvantage of low traffic efficiency. In order to optimize the vehicle traffic at the intersection, this paper proposes a design scheme of a real-time control system for road intelligent traffic lights based on FPGA. The system adopts the polling control model, the vehicle detector detects the arrival rate of vehicles, and obtains the corresponding traffic light green time length according to the traffic rules and polling model theory. Using Altera<span><span><span>’</span></span></span><span><span><span>s Cyclone IV series EP4CE15E22C8 chip as the development platform, a specific design plan is given. The circuit mainly includes program-controlled amplifier module, AD acquisition module, cross-correlation calculation module, serial port transmission and Lab-VIEW module. The system can realize the intelligent adjustment of traffic lights. Different vehicle arrival rates are detected at different times, so that the corresponding traffic light configuration time length changes accordingly. This intelligent adjustment controls road traffic and makes the main and branch roads coordinate and cooperate, thereby improving the traffic efficiency of the intersection.</span></span></span>
文摘The problem of traffic congestion is a significant phenomenon that has had a substantial impact on the transportation system within the country. This phenomenon has given rise to numerous intricacies, particularly in instances where emergency situations occur at traffic light intersections that are consistently congested with a high volume of vehicles. This implementation of a traffic light controller system is designed with the intention of addressing this problem. The purpose of the system was to facilitate the operation of a 3-way traffic control light and provide priority to emergency vehicles using a Radio Frequency Identification (RFID) sensor and Reduced Instruction Set Computing (RISC) Architecture Based Microcontroller. This research work involved designing a system to mitigate the occurrence of accidents commonly observed at traffic light intersections, where vehicles often need to maneuver in order to make way for emergency vehicles following a designated route. The research effectively achieved the analysis, simulation and implementation of wireless communication devices for traffic light control. The implemented prototype utilizes RFID transmission, operates in conjunction with the sequential mode of traffic lights to alter the traffic light sequence accordingly and reverts the traffic lights back to their normal sequence after the emergency vehicle has passed the traffic lights.
文摘Based on the basic composition and principle of traffic control system with single-chip microcomputer, this paper formulates the hardware composition and program design ideas. The system takes AT89C51 single-chip microcomputer as the control core, designs the hardware circuit, uses the simulation software, and analyzes the circuit structure. Draw the function flow chart of the program, then write the program code, and carry out the function test on the built hardware platform, and further improve the program according to the debugging results.
基金Project supported by National Natural Science Foundation of China （Grant No. 10532060）
文摘Traffic flows controlled by traffic light strategies were investigated via a cellular automaton model with anticipation, which is suitable for describing urban traffic. Three kinds of strategies, i. e., synchronized, green-wave and random switching lights, were designed, simulated and compared with each other. It is shown that the green-wave strategy is only valid at lower density and there is not an effective way with the three strategies to improve the efficiency of traffic flow at high density.
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.
基金supported by Natural Basic Research Program of China (91120306, 61203366)
文摘Traffic light detection and recognition is essential for autonomous driving in urban environments. A camera based algorithm for real-time robust traffic light detection and recognition was proposed, and especially designed for autonomous vehicles. Although the current reliable traffic light recognition algorithms operate well under way, most of them are mainly designed for detection at a fixed position and the effect on autonomous vehicles under real-world conditions is still limited. Some methods achieve high accuracy on autonomous vehicle, but they can＇t work normally without the aid of high-precision priori map. The authors presented a camera-based algorithm for the problem. The image processing flow can be divided into three steps, including pre-processing, detection and recognition. Firstly, red-green-blue （RGB） color space is converted to hue-saturation-value （HSV） as main content of pre-processing. In detection step, the transcendental color threshold method is used for initial filterings, meanwhile, the prior knowledge is performed to scan the scene in order to quickly establish candidate regions. For recognition, this article use histogram of oriented gradients （HOG） features and support vector machine （SVM） as well to recognize the state of traffic light. The proposed system on our autonomous vehicle was evaluated. With voting schemes, the proposed can provide a sufficient accuracy for autonomous vehicles in urban enviroment.
基金Sponsored by the National Science and Technology Innovation Fund for Small and Medium Enterprises(Grant No.10C26211200144)Tianjin Science and Technology Key Supporting Projects(Grant No.10ZCGYGX18300)
文摘Visible Light Communication( VLC) based on LED is a new wireless communication technology with high response rate and good modulation characteristics in the wavelengths of 380- 780 nm. Compared with conventional methods,the waveband of VLC is harmless to human and safe to communication because of no magnetism radiation. An audio information transmission system using LED traffic lights is presented based on VLC technology. The system is consisted of transmitting terminal,receiving terminal and communication channel. Some experiments were made under real communication environment. The experimental results showed that the traffic information transmission system works steadily with good communication quality and achieves the purpose of transmitting audio information through LED traffic lights,with a data transfer rate up to 250 kbps over a distance of 5 meters.
