515 results about "Signal lamp" patented technology

The invention discloses a global traffic signal control method based on a regional context enhanced large language model, and the method comprises the steps: dividing a target region into K traffic signal lamp control regions according to a traffic network structure of the target region; global real-time traffic information of the target area is collected and converted into global traffic text information; and inputting the global traffic text information into the large language model after LoRA fine tuning, and outputting a global traffic signal lamp control strategy of the target area, namely a traffic signal lamp phase of each intersection. In the fine tuning process of the large language model, an optimal phase decision is generated by using a reinforcement learning agent, a decision result is converted into text data, a region-level optimal phase decision data set is constructed according to an adjacent region division strategy, fine tuning is performed on the model by using the data set, region loss is calculated, and the large language model is optimized through the loss. According to the invention, optimization of global traffic signal lamp control can be realized, the overall traffic delay is reduced, and the traffic efficiency is improved.

The embodiment of the invention provides a training method of a signal lamp control model, a signal lamp control method, a device, equipment, a medium and a product, and relates to the technical field of urban road traffic. The method comprises the following steps: acquiring a plurality of first traffic data, constructing a state characterization matrix and a reward function according to the plurality of first traffic data, and performing model training according to the plurality of first traffic data, the state characterization matrix and the reward function to obtain a signal lamp control model. According to the method, in a model training process, a state representation matrix is utilized to dynamically quantify passing priorities of buses in all directions, and meanwhile, a reward function is utilized to guide the model training process, so that a signal lamp control model obtained through training can recognize and preferentially respond to bus passing demands, and signal lamp actions are dynamically adjusted; therefore, the collaborative optimization of multi-direction bus priority requests in a complex scene is realized, and the coordination capability and response efficiency of a bus priority system in a complex urban traffic environment are improved.

The invention provides a signal lamp fault intelligent diagnosis method and system based on the Internet of Things, and relates to the technical field of data processing, and the method comprises the steps: 1, collecting the electrical parameters, environment data, working time sequence information and video image data of a signal lamp unit in real time, and constructing a multi-mode data set of the operation state of a signal lamp; step 2, transmitting the multi-modal data set to a central diagnosis platform, performing feature extraction and preliminary fault identification by using a pre-trained fault identification model, and generating fault type and fault position information; and step 3, based on the fault position information, selecting a plurality of monitoring devices in time-space association to form a diagnosis group, and performing fusion analysis and collaborative diagnosis on multi-source data of the diagnosis group to generate a fault judgment result. According to the invention, intelligent diagnosis and operation and maintenance management of the operation state of the signal lamp are realized, and the accuracy of fault identification and the processing efficiency are improved.

The invention discloses an AI algorithm-based road section violation behavior accurate identification and automatic warning system, and the system comprises an image acquisition module which is used for collecting a road monitoring image and carrying out the standardization processing; the feature extraction module is used for extracting semantic and structural information in the image based on a visual self-distillation network; the behavior modeling module is used for constructing a traffic behavior characteristic probability distribution model by using an improved multi-dimensional Gaussian modeling method; the anomaly detection module is used for comparing the current image features with the normal behavior model and outputting an anomaly score and a regional thermodynamic diagram; the warning judgment module judges whether warning is triggered or not according to the abnormal score and the state of the signal lamp; and the warning execution module is used for carrying out acousto-optic prompt, voice broadcast and image display through edge equipment. According to the method, image processing and AI identification technologies are fused, automatic identification and real-time warning of road section violation behaviors are realized, and the method has the advantages of high precision, fast response and easy deployment.

The invention discloses an inland waterway congestion dredging method and device, and relates to the field of traffic control, and the method comprises the steps: obtaining multi-source traffic data and waterway meteorological and hydrological data of each ship in a waterway; performing space-time registration and fusion processing on the multi-source traffic data, generating comprehensive traffic situation information of the whole section of the channel, and extracting traffic flow characteristic parameters and channel congestion indexes; inputting the traffic flow characteristic parameters, the channel congestion index and the channel meteorological and hydrological data into a trained traffic flow prediction model to obtain traffic prediction information of key nodes in the channel in a future preset time window; based on the comprehensive traffic situation information and the traffic prediction information, generating preventive control parameters for channel key node signal lamps; and according to the traffic prediction information and the preventive control parameters, traffic guidance information is generated and sent to the corresponding ship terminals, and the preventive control parameters are sent to the corresponding signal lamp control machines. The overall passing efficiency of the channel can be improved.

The invention provides a smart city traffic abnormity monitoring method and system based on an Internet of Things large model, and relates to the field of Internet of Things and smart city traffic management. The system comprises an abnormity judgment module and a diversion module. The abnormity judgment module is configured to perform abnormity judgment on the target area according to the multi-source data and determine a plurality of hidden danger hot areas; the diversion module is configured to determine a plurality of standby routes according to the judgment result and the regional road network topological map; determining a plurality of main routes according to the plurality of standby routes and the position information of the plurality of variable information boards, generating a diversion instruction, and sending the diversion instruction to the emergency supervision object platform; and based on the diversion instruction, controlling a plurality of variable information boards to display a sketch of a corresponding main route, and controlling traffic lights on a plurality of standby routes to perform green light signal display according to a passing period. According to the method, the main pushing route of the variable information boards can be reasonably determined and controlled, potential traffic accident hidden dangers are prevented, and traffic safety is guaranteed.

The invention provides a signal machine flashing light monitoring method and system based on full-electronic interlocking, the monitoring method is applied to a monitoring system comprising an interlocking machine and a flashing light power supply, and the monitoring method specifically comprises the steps that in response to a control demand, the interlocking machine outputs a flashing light driving signal to a signal machine, and the signal machine is driven to execute flashing light; filament current and on-off state of each lamp position of the signal machine are collected in real time, and signal machine flashing fault detection is carried out according to the filament current and on-off state of each lamp position; and when a signal machine flashing light fault is detected, the fault type is identified according to a fault detection result, and a corresponding operation and maintenance strategy is formulated. According to the invention, through real-time acquisition and linkage analysis of two parameters of filament current and on-off state, flashing lamp fault identification requirements under full-electronic interlocking are met, the problem of misjudgment caused by frequent fluctuation of current is avoided, other fault types possibly existing in the flashing lamp control process can be further covered, the fault missed judgment risk is reduced, and the working efficiency is improved. And the safety of flashing display of the signal lamp is ensured.

The invention discloses a smart city traffic planning method and system based on deep learning, and relates to the technical field of city traffic management, and the method comprises the steps: recognizing an activity region of a traffic disturbance activity, constructing a disturbance region graph Ga, collecting vehicle driving related data and lamp control cycle data, and constructing a standardized data set H; coupling modeling is carried out on path length change and direction deviation of the traffic driving path before and after the traffic disturbance activity so as to quantify the traffic state of the activity area, a path disturbance deviation coefficient Py is acquired, the traffic state of the activity area is evaluated in combination with a path disturbance threshold Pyyz, and when the traffic state is in an abnormal state, the traffic disturbance deviation coefficient Py is calculated. According to the method, signal lamp cycle rhythm analysis is carried out, a phase dislocation propagation index Xw is obtained, and coupling modeling is carried out to obtain a comprehensive rhythm adaptation index Zh, so that the risk level of a traffic signal control system is divided, a system adjustment instruction is generated, intelligent adjustment is carried out, and the intelligent, precise and real-time level of smart city traffic planning is improved.

The invention discloses an urban traffic cooperative scheduling method and system based on a large model and multiple agents. The method comprises the steps that natural language task description is converted into a task semantic graph and a structured prompt; generating a plurality of strategy candidates by using a large language model, and performing language scoring and reasoning arbitration; based on the scoring result, selecting an optimal strategy for multi-agent execution; behavior execution data are collected and evaluated and fed back, and strategy closed-loop updating is achieved through parameter optimization and Prompt fine tuning; and a distributed task embedding mechanism and a lightweight migration module are combined, so that the multi-task adaptability and the training efficiency of the system are improved. The cooperative training system constructed by the invention has the capabilities of natural language interaction, strategy interpretability, behavior controllability and task migration, and is suitable for various complex urban tasks such as traffic jam dispersion, emergency response, signal lamp linkage and the like.

The invention relates to the technical field of road traffic management, and particularly discloses a signal lamp fault monitoring and early warning method based on Internet data, which comprises the following steps: establishing a historical database, acquiring historical traffic characteristic data of an intersection, establishing a historical traffic characteristic database, and setting an early warning threshold value for each traffic characteristic data; performing data judgment and early warning, comparing the real-time traffic characteristic data of the intersection in the same time section with historical traffic characteristic data, and when any one of the real-time traffic characteristic data reaches an early warning threshold value, sending early warning information to a traffic management department; and fault processing: after the traffic management department receives the early warning information, the traffic management department sends a checker to check the fault, and if the fault check is true, the traffic management department arranges a maintainer to carry out fault maintenance processing. According to the signal lamp fault monitoring and early warning method based on the signal lamp data, the problems that signal lamp fault operation and maintenance are not timely and incomplete, cost is high and the like are effectively solved, and potential traffic safety hazards caused by signal lamp faults are reduced.

The invention discloses an urban traffic signal lamp adaptive control method based on artificial intelligence, and the method comprises the steps: firstly converting vehicle data into a fluid field matrix through employing a space grid mapping technology, calculating a virtual fluid dynamic pressure index combining kinetic energy density and acceleration divergence, so as to represent a congestion evolution direction; the system identifies a fluid infinitesimal state, generates a game weight, monitors back propagation characteristics of a dynamic pressure shock wave, sends a phase pre-wake-up request to an upstream intersection, edge computing nodes construct a game revenue function based on a node reputation value and downstream impedance, and searches an optimal timing strategy through distributed interaction. And the system triggers asynchronous signal switching according to the deviation between the optimal strategy and the current state, and executes phase difference nonlinear compensation. According to the method, through quantification of the traffic flow state and the cooperative game, potential congestion sources are effectively identified, non-cooperative behaviors of nodes are inhibited, and real-time blocking of burst shock waves and dynamic coordination of regional signals are realized.

Techniques are described herein for determining an active traffic light signal. The techniques involve, determining active signals for first and second traffic light heads of a group of traffic light heads, wherein members of the group of traffic light heads share an active signal at a point in time. A first vote is allocated for the active signal for the first traffic light head indicating a signal state of the first traffic light head and a second vote is allocated for the active signal for the second traffic light head indicating a signal state of the second traffic light head. A signal indicated by the group of traffic light heads is determined based at least in part on the first and second votes.

The embodiment of the invention relates to the technical field of traffic information, and discloses an intersection historical data playback method and device, a medium and a product. Task information input by a user is acquired, wherein the task information comprises an intersection number and a time range of historical data; generating a playback task according to the task information, and splitting the playback task into a plurality of subtasks; processing historical data according to the subtasks, wherein the historical data comprises network connection vehicle data, sensing data, signal lamp data and copy data; storing the processed historical data into a playback data table of a database; and playing and displaying the processed historical data on a page through a digital twinning technology. The technical problem of low intersection historical data playback performance can be at least solved.

According to the multifunctional traffic flow laser monitoring method and system provided by the invention, the initial traffic flow data is collected through the multi-source sensor network and is processed to obtain the standardized flow feature set, then the pressure evaluation is performed on the flow feature set, the operation state classification is determined, and the traffic flow monitoring accuracy is improved. The control parameters of the signal lamp period are adjusted through operation state classification and historical flow data, and then the signal period adjustment amplitude and the dynamic timing constraint condition are determined in combination with the influence of environmental factor data and the dynamic timing demand of the signal lamp. Then, an adjusting instruction is generated in combination with an intersection priority weight value to adjust and monitor a signal lamp controller, so that traffic management is more accurate and timely, and finally, abnormal flow monitoring, controller fault analysis and signal lamp timing parameter adjustment are performed, so that a final signal lamp control scheme better conforms to the actual traffic condition, and the traffic safety is improved. It is ensured that the adjustment scheme adapts to the real-time condition change of the current intersection, and the flexibility and efficiency of urban traffic management are improved.

The invention relates to the technical field of traffic control, in particular to an intersection signal control effect evaluation method and system based on full-amount vehicle passing data, and the method comprises the steps: obtaining and synchronizing the full-amount vehicle passing data and signal lamp state data, including at least a vehicle unique identifier, a timestamp, an intersection identifier, an in-out direction, a lane number and a passing position; the full-amount vehicle passing data is preprocessed, and event extraction and segmentation according to an evaluation window are carried out; estimating model parameters based on a preprocessing result, performing queue evolution prediction by adopting a periodic-level discrete queue model, and approximately calculating periodic-level delay; calculating and outputting control effect indexes according to the evaluation window, wherein the control effect indexes comprise average delay, parking rate, average parking times, queue length statistics, green light utilization rate, throughput and passing time; when different control schemes are compared, scheme comparison is carried out on control effect indexes according to matching samples or covariable adjustment rules, and significance and confidence intervals of effect differences of the control schemes are calculated through a statistical method.

The utility model discloses a high-voltage power supply and a high-voltage power supply circuit for an X-ray tube. The high-voltage power supply circuit comprises a high-voltage circuit, a filament circuit, a control circuit, an over-temperature protection circuit and a global protection circuit. The high-voltage circuit is connected with the anode of the X-ray tube and is used for generating a target voltage signal; the filament circuit is connected with a filament of the X-ray tube and is used for generating filament working voltage; the over-temperature protection circuit is connected with the control circuit and is used for generating an over-temperature protection signal based on the filament temperature; the control circuit is connected with the high-voltage circuit and the filament circuit and is used for generating an enable signal based on the over-temperature protection signal or an external control signal; and the global protection circuit is connected with the control circuit, the high-voltage circuit and the filament circuit and is used for turning off the high-voltage circuit and the filament circuit based on the enable signal. By arranging the global protection circuit, the high-voltage circuit and the filament circuit can be started only after active enabling of a user, accidental starting or wrong operation is avoided, and the accident risk is reduced.

The application discloses a traffic signal lamp trigger type countdown control output method, comprising the following steps: S100, configuring signal lamp fixed time countdown time length and configuring current cycle phase information; S200, reading the cycle phase information of the traffic signal lamp at the current time node and the signal lamp fixed time countdown time length, and generating a running phase chain table; S300, judging whether the time before the non-traffic light color of the current lost traffic right phase meets the configured fixed time countdown time length; S400, if the configured fixed time countdown time length is met, triggering the corresponding countdown timer; if the configured fixed time countdown time length is not met, performing countdown correction and calculating the countdown extension time; and S500, repeating steps S200-S400. The application can generate a running phase chain table under the condition that traffic intersection parameters are pre-configured, pre-add, real-time update and calculate signal control data to achieve accurate control of the time when the trigger signal triggers the countdown timer, and realize the trigger type pulse control countdown algorithm.

The utility model relates to the technical field of mounting supports, and discloses a signal lamp stable mounting support which comprises a traffic light, a clamping plate is arranged on the outer wall of the traffic light, a wedge-shaped block is fixedly connected to the lower end of the clamping plate, a sliding block is fixedly connected to the rear end of the wedge-shaped block, a supporting plate is arranged at the lower end of the traffic light, and an air cylinder is fixedly connected to the upper end of the supporting plate. The driving end of the air cylinder is fixedly connected with a sliding rod, the sliding rod is slidably connected to the inner side of the wedge-shaped block, a fixing plate is arranged at the rear end of the air cylinder, a sliding groove is formed in the inner wall of the fixing plate, the sliding block is slidably connected to the inner wall of the sliding groove, the bottom end of the supporting plate is fixedly connected with a vertical rod, and the outer wall of the vertical rod is fixedly connected with a hydraulic rod. According to the utility model, the clamping device is driven by the cylinder to replace the traditional traffic light loading and unloading mode, thereby improving the maintenance efficiency and reducing the cost. Meanwhile, the design that anti-collision rubber is combined with hydraulic current limiting is adopted, collision energy is effectively absorbed, the signal lamp is protected against vibration damage, and the service life is prolonged.

The application provides a traffic signal lamp fault emergency management system and method based on an Internet of Things large model, and relates to the field of urban traffic signal lamp supervision. The method is executed by an emergency supervision management platform of the traffic signal lamp fault emergency management system based on the Internet of Things large model, and comprises the following steps: determining a state evaluation result of a signal lamp based on first monitoring data and second monitoring data of the signal lamp; determining a target signal lamp based on the state evaluation result; cutting off the power supply of a fault signal lamp and issuing a detour suggestion to target personnel; determining a fault prediction situation of an abnormal signal lamp based on the first monitoring data, the second monitoring data and the state evaluation result of the abnormal signal lamp; and determining a maintenance parameter based on the fault prediction situation and sending the maintenance parameter to maintenance personnel. The application can accurately diagnose the state of the signal lamp, cut off the power supply and issue a detour suggestion when a fault occurs, predict a fault and determine a maintenance parameter when an abnormality occurs, realize rapid response and active intervention, and improve operation and maintenance efficiency.

The invention relates to a traffic signal lamp emergency control method and system, a terminal and a storage medium, and relates to the technical field of intelligent traffic, and the method comprises the steps: obtaining lamp bead state data of a preset traffic signal lamp; judging whether the lamp bead state data is consistent with preset lamp bead normal state data or not; if yes, continuing to obtain the lamp bead state data for cyclic judgment; if not, acquiring a lamp bead fault type; and controlling a preset traffic signal lamp adjusting device to adjust the traffic signal lamp according to the lamp bead fault type. The invention has the effect of improving the emergency capability of the traffic signal lamp.

The invention discloses a method for improving small sample signal lamp state recognition accuracy, and the method comprises the steps: constructing a source domain data set and a target domain data set, training a target detection model, and obtaining a pre-training model; performing back propagation by combining a CNN-LRP method to obtain a channel-level correlation feature map of each convolutional layer in a signal lamp identification task; performing channel dimension summation to obtain a two-dimensional correlation feature map; calculating a pixel forward correlation ratio and a correlation space focusing degree; calculating a layer depth penalty factor and a layer contribution score of each convolutional layer; scoring the average contribution degree, the variation coefficient and the layer adaptability of each convolutional layer on different input images of the target domain signal lamp; sorting the layer adaptability scores of all the layers to form a final freezing strategy; and freezing and training partial layers of the pre-training model to obtain an optimized target domain model. According to the method, the freezing decision is guided by explainable and quantifiable indexes, and the mobility and field adaptability of the signal lamp state recognition model are improved.

The invention belongs to the technical field of navigation signal lamps, and particularly relates to a navigation signal lamp for a polar region and a deicing and signal control method thereof.The navigation signal lamp comprises an outer shell, an outer insulation pad, an outer heating component, an outer lampshade and a lamp body component, the outer surface of the outer shell is conformal with a silencing layer covering a boat body, and an annular groove for containing the outer lampshade is formed; the outer lampshade is basically flush with the outer surface of the outer shell, the outer insulation pad is arranged between the outer lampshade and the outer shell, the outer heating component is in heat conduction connection with the outer lampshade, comprises a heat conduction metal piece and an embedded heating source and is filled with a heat conduction medium, and the sealing structure tolerates deep sea water pressure; the inner heating lampshade is provided with a transparent conductive heating layer, and the navigation signal lamp further comprises a control printed board component which is used for temperature monitoring, heating control and light attenuation monitoring. The problem that reliability and adaptability are insufficient under the conditions of polar region low temperature, freezing and impact is solved, and rapid deicing and demisting, deep sea pressure resistance, stable light emitting and high visibility are achieved.

The invention provides a lamp strip length detection method, a lamp strip control circuit, a lamp strip control system and a storage medium, and the method comprises the steps: enabling a lamp strip controller to transmit a length detection signal to a lamp strip according to a preset mode when the lamp strip control circuit is powered on; and the lamp strip controller obtains residual signals after the lamp strip lamp bead driver intercepts corresponding data in the length detection signals, and the length of the lamp strip is determined according to the residual signals. The method for detecting the length of the lamp strip can automatically detect the length of the lamp strip, reduces the labor cost, and is less affected by the voltage amplitude.

The utility model discloses a movable box type pressure oven. The movable box type pressure oven comprises a supporting frame, a control panel, a base, a signal lamp, an oven body and an electric control box. The oven body, the electric control box, the signal lamp and the control panel are respectively arranged on the supporting frame, the oven body, the control panel and the signal lamp are respectively and electrically connected with the electric control box, and a plurality of bases and a plurality of universal wheels with locking functions are arranged at the bottom of the supporting frame. According to the movable box type pressure oven, the control panel, the oven body, the electric control box and other assemblies are integrated through the supporting frame, free movement can be achieved in cooperation with the base and the universal wheels, and the movable box type pressure oven can be suitable for overall carrying in different scenes and has good applicability.

The utility model relates to signal lamp testing equipment which comprises a testing box body and a cleaning assembly, a placing cavity used for placing a signal lamp strip to be tested is formed in the testing box body, an observation opening is formed in one side of the placing cavity and covered with an observation baffle, the cleaning assembly comprises a driving mechanism and a wiping mechanism, and the wiping mechanism is arranged on the box body in a sliding mode. The wiping mechanism is provided with a wiping face abutting against the observation baffle, and the driving mechanism drives the wiping mechanism to move along the observation baffle so that the wiping mechanism can clean the observation baffle. According to the signal lamp testing equipment, the wiping assembly is arranged on the testing box body, the observation baffle can be automatically wiped in the testing process, the situation that water drops condensed on the observation baffle block testing personnel is avoided, and it is guaranteed that the testing personnel clearly observe the state of the signal lamp in the containing cavity. The test box body does not need to be opened during wiping, so that the stability of a test environment is ensured, and the accuracy of a test result is improved.

The utility model belongs to the technical field of Bluetooth equipment, and discloses blind person traffic signal prompting equipment based on low-power RSSI Bluetooth, which is used for being matched with a Bluetooth terminal arranged on an intersection signal lamp to carry out signal receiving and transmitting and intersection passing prompting, and comprises a shell and a circuit board arranged in the shell, the circuit board is connected with a Bluetooth module, a loudspeaker module and a battery through pin welding; the front surface of the housing is provided with a horn mouth corresponding to the internal horn module, and the horn mouth is filled with waterproof sound transmission cotton. According to the utility model, the prompting device worn on the body of the visually impaired person can be identified at the intersection provided with the corresponding Bluetooth terminal, and after the visually impaired person wearing the prompting device is captured within a certain range through the low-power-consumption Bluetooth technology, information is pushed to guide pedestrians to cross the street. Compared with existing camera recognition auxiliary equipment, the camera recognition auxiliary equipment is low in cost, and compared with existing GPS auxiliary equipment, the camera recognition auxiliary equipment is high in accuracy.

1. The name of the design product: motorcycle steering tail light (KS25-070). 2. The use of the design product: steering tail light for motorcycle. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: design 1 perspective view 1. 5. Design 1 is designated as the basic design.

To more accurately suppress erroneous detection of signal ignorance.SOLUTION: According to an aspect of the embodiments, a center device includes a controller configured to receive, from an in-vehicle device, information including position information at which the in-vehicle device has detected signal ignoring, calculate a traffic volume of vehicles in a predetermined period at a point where signal ignoring frequently occurs based on the information, calculate an occurrence probability of signal ignoring at the point from the number of occurrences of signal ignoring based on the information and the traffic volume, and determine that the point where the occurrence probability is equal to or greater than a threshold value is an abnormality detection point of signal ignoring.SELECTED DRAWING: Figure 6

The application discloses a traffic control robot system and a control method thereof, and belongs to the technical field of road traffic. The system comprises: a plurality of traffic control robots, wherein the traffic control robots are provided with data acquisition devices and signal lamp devices; a server is in communication connection with the plurality of traffic control robots, and the server is used for dynamically constructing a scene image of a target intersection based on intersection data of the target intersection collected by the plurality of traffic control robots; the server is also used for determining target arrangement information based on road information of the target intersection in the scene image; and the server is also used for determining a signal lamp control strategy based on congestion information of the target intersection in the scene image in the case that the traffic control robots are arranged at corresponding target positions, and controlling the signal lamp devices of the plurality of traffic control robots according to the signal lamp control strategy. The system can optimize intersection signal lamp control according to real-time traffic conditions.

The application provides a ramp traffic signal adaptive control method and system based on unmanned aerial vehicle cooperation, belongs to the technical field of intelligent traffic control, and comprises the following steps: collecting traffic data in real time based on an unmanned aerial vehicle cluster dynamically arranged above a ramp, constructing a global traffic state matrix, and performing preliminary processing through edge computing; generating a local optimal signal timing suggestion in real time through edge computing of the edge node on the preliminarily processed data; integrating and uniformly training the local optimal signal timing suggestions uploaded by multiple unmanned aerial vehicles on the cloud to generate a global optimal signal timing strategy; and adjusting the signal lamp parameters in real time based on the global optimal signal timing strategy, thereby enhancing the direct intervention ability on the on-site traffic through the air guidance function and providing a high-reliability solution for a smart traffic system.