37 results about "Traffic reduction" patented technology

The embodiment of the invention provides an auxiliary driving control method and device, electronic equipment and a vehicle, and relates to the technical field of intelligent driving, environmental perception information of the advancing direction of a target vehicle in the driving process is obtained, and if it is determined that multiple continuous fixed obstacles exist in the advancing direction of the target vehicle based on the environmental perception information, the target vehicle is driven to move. According to the method and the device, if the traffic warning objects are identified, a plurality of continuous fixed obstacles are virtualized into virtual edges, and then auxiliary driving control is carried out based on the virtual edges, so that the plurality of continuous fixed obstacles are virtualized into the virtual edges, and then the auxiliary driving control is carried out by utilizing the virtual edges, so that missing identification of the traffic warning objects can be reduced; in this way, the effect of auxiliary driving control can be improved in a scene facing a plurality of continuous fixed obstacles, and the risk of collision is reduced.

A processor-implemented method for managing bus traffic of a system-on-chip (SoC) includes receiving a mixed signal in a computing device including the SoC. One or more polarity changes in a slope of a waveform corresponding to the mixed signal are detected. One or more of an analog-to-digital converter (ADC) or a portion of SoC bus traffic associated with ADC operation is selectively disabled between one or more polarity changes in a slope of a waveform.

This invention relates to the field of road management, specifically to a data-driven road traffic risk control system and method, comprising: a road monitoring module, a vehicle management module, an accident analysis module, a traffic focusing module, and a dispatching and allocation module. The road monitoring module is used to establish a road network model; the vehicle management module is used to plan the optimal driving route; the accident analysis module is used to determine the type of accident; the traffic focusing module is used to optimize patrol routes; and the dispatching and allocation module is used to build an exchange service platform for command and dispatch. This invention can improve traffic operation efficiency, reduce accident risks, build an intelligent traffic management system, enhance the perception and management level of urban traffic, improve the accuracy of traffic accident target detection, improve traffic infrastructure construction, enhance road network safety, optimize the allocation of human and material resources, and reduce traffic management costs.

The invention discloses a port ship traffic organization optimization and regulation and control method, which belongs to the technical field of waterway traffic optimization and intelligent management and control, and comprises the following steps: collecting port data, constructing an information physical system framework, and dynamically managing a port by using the port data through the information physical system framework. The method comprises the following steps of: extracting and quantizing, performing uniform feature fusion, obtaining a judgment result by utilizing an event triggering mechanism, updating a system state, predicting the updated system state by utilizing a model prediction control algorithm to obtain a system step length, predicting the system step length in real time by utilizing a self-adaptive vision field mechanism to obtain a real-time step length, and calculating the real-time step length according to the real-time step length. And solving by utilizing a multiplier alternating direction method according to the judgment result and the real-time step length to obtain a port ship traffic scheduling control strategy. According to the invention, high-efficiency ship traffic scheduling and resource optimization can be realized in a complex and changeable port environment, the port transportation efficiency is obviously improved, traffic congestion is reduced, and the self-adaptive capability of the system is enhanced.

The application discloses a port ship traffic organization optimization and regulation method, and belongs to the technical field of waterway traffic optimization and intelligent management and control. The method comprises the following steps: collecting port data, constructing an information physical system framework, using the information physical system framework to realize dynamic management of the port, uniformly fusing features after extraction and quantization, using an event triggering mechanism to obtain a judgment result, updating a system state, using a model prediction control algorithm to predict the system step length, using an adaptive horizon mechanism to obtain a real-time step length, using a multiplier alternating direction method to solve according to the judgment result and the real-time step length, and obtaining a port ship traffic scheduling control strategy. The application can realize efficient ship traffic scheduling and resource optimization in a complex and changeable port environment, significantly improve port transportation efficiency, reduce traffic congestion, and enhance the adaptive ability of the system.

In order to improve passenger satisfaction with a transportation service and to provide an operation plan creation means capable of reducing operating costs for a transportation service provider, an operation plan creation device comprises: a transportation leg network generation unit that generates transportation leg network information that defines each transportation leg of the transportation service; a cancellation determination unit that generates transportation leg cancellation possibility information that indicates whether or not cancellation of each transportation leg of the transportation service is possible; a travel route candidate determination unit that generates travel route candidate information that indicates a travel route candidate for each travel plan in passenger travel plan information; a people flow prediction unit that generates people flow prediction information that indicates a predicted people flow in the transportation service; and an operation plan generation unit that generates new operation plan information in which certain transportation legs of the transportation service are eliminated.

This invention relates to the field of vehicle control technology, and more specifically to a multi-vehicle system model for non-signal-controlled intersections. Through third-order linear transformation, the nonlinear system model can be converted into a third-order linear state-space model. This simplifies the model while meeting the requirements of vehicle motion control. Considering parameter mismatch and bounded acceleration, it more realistically reflects the longitudinal dynamics data of vehicles during actual driving, making it suitable for more realistic vehicle and traffic conditions. This provides more accurate data for vehicle control systems to control vehicles. By analyzing the vehicle terminal dynamics data through a multi-vehicle control system, it is possible to better control the current vehicle to maintain a certain and appropriate distance from surrounding vehicles to ensure safe driving. Simultaneously, it can alleviate traffic congestion, reduce traffic accidents, and increase traffic capacity.

A system, a method and a computer program product are provided to determine a left turn decision for a user or autonomous vehicle attempting to turn at an intersection of a road. For example, the system obtains contextual features and / or sensor data related to the intersection of the road. An optimal location on the road is determined for the user or autonomous vehicle to position the vehicle to make the left turn decision, based on the contextual features and / or the sensor data. A left turn risk factor is determined based on the location on the road for the user or autonomous vehicle to position the vehicle to make a left turn. An alert is presented to the user or autonomous vehicle regarding the left turn risk factor with a left turn advisory message.

The invention discloses a multi-source traffic data driven signal lamp accurate control method and system, and the method comprises the following steps: S1, collecting multi-source traffic data, and carrying out the data preprocessing, and forming a multi-source traffic original data set; s2, according to a flow conservation relationship, performing unification processing on the original data, and outputting calibrated traffic state data; s3, utilizing a shock wave neural operator module to predict motorcade wavefront arrival time and queuing emptying time of each entrance lane; s4, constructing a sequential logic constraint set and an uncertainty scene set; s5, through distributed robust optimization solution, generating a signal control scheme satisfying constraints, and generating a plan time axis; and S6, a control scheme is issued to a signal controller, adaptive phase switching is implemented, and after execution, recovery data are updated online. According to the accurate signal lamp control method driven by the multi-source traffic data, signal lamp scheduling is optimized in real time, the traffic flow management efficiency is improved, and traffic congestion is reduced.

The application discloses a traffic flow prediction fused traffic light adaptive control method and system, and relates to the technical field of intelligent traffic, comprising: obtaining real-time traffic flow data of a target intersection; obtaining a current traffic light control strategy of the target intersection; obtaining a traffic flow prediction result; performing change degree evaluation according to the real-time traffic flow data and the traffic flow prediction result, obtaining a traffic flow change coefficient, and whether it is greater than or equal to a traffic flow change threshold; if the traffic flow change coefficient is greater than or equal to the traffic flow change threshold, generating a traffic light adjustment instruction, adjusting the current traffic light control strategy according to the traffic flow prediction result, generating a future traffic light control strategy, and performing traffic light adaptive control of the target intersection. The application solves the technical problems of inaccurate traffic flow prediction and inflexible traffic light control strategy in the prior art, and achieves the technical effects of improving traffic efficiency, reducing traffic congestion and optimizing traffic light control.

The utility model belongs to the technical field of barrier gates, and relates to a barrier gate rod offset damage early warning device for a barrier gate, which comprises a mounting plate, one end of the mounting plate is provided with a data processing main body, the middle part of the mounting plate is provided with an interrupting type microwave sensor, and the interrupting type microwave sensor is electrically connected with the data processing main body. A rotating groove is formed in the end, away from the data processing body, of the mounting plate, a driving shaft is rotationally connected into the rotating groove, and a barrier gate rod is mounted on the driving shaft. Under the condition that the barrier gate rod is damaged, the device can timely inform background customer service to report and repair through the data processing main body, meanwhile, the standby barrier gate rod of the device is started to intercept charging, normal operation of the parking lot charging barrier gate can be ensured, and especially in the peak period, traffic jam can be reduced, and the service life of the parking lot charging barrier gate is prolonged. The passing efficiency of the parking lot is improved, and meanwhile management disorder and income loss caused by barrier gate damage are reduced.

The application discloses a kind of multi-source data interaction's traffic light control optimization method and system, it is related to intelligent transportation technology field, including: obtaining the real-time traffic information dataset of target section;Based on real-time traffic information dataset, construct real-time traffic twin model, and embed traffic prediction model, carry out traffic jam prediction, obtain congestion result;Dynamically determine vehicle traffic priority, generate traffic light control target based on congestion result and vehicle traffic priority;Different signal timing schemes are simulated randomly by real-time traffic twin model, determine traffic efficiency index evaluation result set, select optimal control strategy according to traffic efficiency index evaluation result set;Based on optimal control strategy, adjust the traffic light signal of target section.The application solves the technical problems that traffic light signal timing is not flexible and cannot adapt to traffic flow changes in real time in the prior art, achieves the technical effects of improving traffic flow efficiency, reducing traffic congestion and improving the priority passing capacity of emergency vehicles.

The invention discloses a traffic control method and a traffic control system, and relates to the technical field of traffic control, and the method comprises the steps: collecting all-time video data in all directions through an intersection camera device, carrying out the standardization, training a flow prediction model with a vehicle arrival rate as a target through a neural network algorithm, and carrying out the optimization of the traffic prediction model; the traffic light cycle suitability is analyzed in combination with historical videos, and the queuing length in each direction of the next cycle is predicted by fusing a model prediction value and lane saturation traffic rate multi-dimensional data; and triggering a hierarchical control instruction according to a comparison result of the actually measured queuing length and a preset threshold value, and finally linking multiple devices to execute the instruction to execute a feedback optimization model and a threshold value parameter so as to realize accurate and efficient traffic control. According to the scheme, the predicted value of the queuing length is output by training the flow prediction model, and the traffic jam and the adjustment hysteresis are reduced by combining dynamically associated traffic light timing and hierarchical control instructions and matching with a multi-module cooperative execution and closed-loop feedback optimization mechanism.

The application discloses a traffic accident prediction method, comprising: acquiring a vehicle-mounted video and preprocessing to obtain continuous image frames, extracting time features and space features from the continuous image frames, and performing mid-term fusion on the time-space features; performing position weighting on the object-level features based on a graph structure; performing spatial attention on the weighted object-level features; splicing the object-level features and full-frame features, and performing frame-level aggregation and time period-level aggregation to sufficiently learn traffic scene context information; performing space-time relationship reasoning on the obtained double-layer aggregated information to obtain a hidden state representation of a current time step; inputting the hidden state representation of the current time step into a full connection network to obtain an accident score, and giving a warning signal when the accident score exceeds a predetermined threshold. The method can successfully predict the occurrence of a traffic accident 2-4 seconds in advance, thereby giving a driving system or a driver sufficient reaction time, and thus greatly reducing the possibility of traffic accidents.

Embodiments of the present application provide a radar communication method, system, device, equipment and storage medium, relating to the technical field of radar communication, and applied to a slave radar in radar communication networking, which further comprises a master radar. The method comprises detecting a command action of a user of the master radar, and sending the command action to other slave radars in the radar communication networking, so as to remind the user of the slave radar to control a vehicle according to the command action. The present application detects and transmits the command action of the user of the master radar in real time, so that the user of the slave radar behind can obtain the intention of the user of the master radar in time, and thus can take corresponding measures in advance, reduce the probability of traffic accidents, and further improve the safety and user experience of travel. In addition, the automatic radar detection and information transmission reduce the dependence on visual observation or language communication, so that the radar user can more focusedly control the vehicle, and further enhance the safety and user experience of travel.

The present application relates to a kind of riding risk perception test methods based on immersive virtual reality interactive platform, the method is by constructing virtual reality traffic scene, simulation builds immersive virtual reality interactive test platform, let rider simulate real riding behavior in virtual scene, by recording the speed, acceleration and other riding data of rider, jointly use the objective data of riding behavior in virtual reality and risk perception subjective data to carry out risk assessment, construct dynamic risk assessment model applicable to immersive virtual reality interactive platform, and study the reaction behavior of rider under traffic conflict scene, test the perception and response ability of rider to riding risk.The present application can provide theoretical basis for slow traffic safety analysis, and the test results can be targeted to propose safety suggestions, so as to improve the traffic safety consciousness of rider and reduce the occurrence of traffic accident.

The application discloses a traffic prediction method, device and equipment and a computer readable storage medium. The traffic prediction method comprises the following steps: acquiring a plurality of model parameters sent by a plurality of clients, performing similarity analysis on the plurality of model parameters, dividing the plurality of model parameters into corresponding clusters, optimizing the model parameters in the clusters, determining the optimized model parameters in the clusters, sending the optimized model parameters to a server, receiving a traffic prediction model established by the server according to the optimized model parameters, acquiring traffic data to be analyzed, and substituting the traffic data to be analyzed into the traffic prediction model to obtain a traffic prediction result. The application can reduce the communication overhead of traffic prediction model update transmission by acquiring and analyzing the optimized model parameters.

The invention discloses an expressway multi-ramp cooperative traffic control method and system in the technical field of intelligent traffic control, and the method comprises the steps: carrying out the cooperative control of variable speed limit and ramp metering based on a multi-agent reinforcement learning framework, collecting the average speed, lane occupancy rate, ramp queuing length and upstream and downstream traffic flow data of a confluence region, and carrying out the cooperative control of the variable speed limit and ramp metering. And constructing a multi-dimensional state vector. According to the method, through demonstration-guidance training and multi-agent cooperative control, the traffic control performance in a multi-ramp scene is effectively improved, the method has high practicability and popularization value, and in practical application, the method can dynamically adjust ramp control and speed limiting strategies according to real-time traffic flow data, and traffic congestion and queuing length are remarkably reduced. Through collaborative decision-making among multiple agents, quick response and accurate control of a complex traffic environment are realized, and the scheme also has relatively good robustness and can adapt to control requirements under different traffic conditions.

The application relates to a highway high-level auxiliary driving system based on a true value system, which comprises an ADAS domain controller, wherein a perception module is used for receiving point cloud data information of a driving road of a vehicle, image data information of the driving road of the vehicle, data information of a position and an attitude of the vehicle, and outputting data information of a perception result of vehicle auxiliary driving; and a rule control module is connected with the perception module, used for receiving the data information of the perception result of the vehicle auxiliary driving, adopting a rule control algorithm to represent vehicle auxiliary driving decision, and obtaining data information of a decision of the vehicle auxiliary driving. The application not only reduces high vehicle high-level auxiliary driving cost, improves high-level auxiliary driving system use efficiency, but also relieves driver fatigue caused by long-distance highway driving and reduces traffic accident sending.

The invention relates to a signal joint debugging control method and system based on Internet multi-source data, and belongs to the technical field of traffic control, and the method comprises the steps: obtaining the Internet multi-source data representing the traffic state of a target road section and road condition monitoring verification data in real time, and determining the traffic state of the target road section based on the road condition monitoring verification data; carrying out confidence evaluation on the Internet multi-source data, and constructing a traffic state data set conforming to a reliability standard; based on the traffic scene of the target road section, calling a corresponding basic timing scheme from a pre-constructed scenarized basic scheme library; and based on the traffic state data set, predicting a traffic state association relationship of a regional intersection associated with the target road section through a space-time diagram convolutional network model, and by taking the basic timing scheme and the traffic state association relationship as a reference, performing optimization solution by adopting a multi-target genetic algorithm to generate a regional signal collaborative optimization scheme. Therefore, the real-time performance of traffic regulation and control is improved, and traffic congestion is reduced.

The invention relates to a method for operating a broadband access network of a telecommunications network, the broadband access network comprising at least one network domain, wherein the network domain comprises, or is assigned to or has access to a control plane comprising a policy decision and enforcement entity or functionality, wherein a specific network node of the network domain is connected such as to provide communication services to customers of the telecommunications network and receives traffic from at least one of a plurality of traffic sources as part of the broadband access network, especially as part of the network domain, wherein, in order to realize a reliable accounting functionality despite a potential overload situation, the method comprises the following steps: -- in a first step, the specific network node detects an overload situation and transmits an overload indication to the policy decision and enforcement entity or functionality, -- in a second step, the policy decision and enforcement entity or functionality transmits a traffic reduction control message to the at least one of the plurality of traffic sources, the traffic reduction control message indicating to reduce traffic, or mark counting invalid, due to an overload situation.

The application provides a cooperative path planning method and system of an intelligent connected vehicle, relates to the technical field of traffic optimization, determines a plurality of groups of initial planning paths of a plurality of intelligent connected vehicles in a preset area, identifies a first connected vehicle set located at a first intersection at a first prediction time, performs a traditional vehicle shunting feature prediction at the first intersection, performs intersection connected vehicle shunting optimization in combination with a first shunting prediction information, a driving purpose certainty label, and an initial planning path corresponding to the first connected vehicle set, returns an optimization result to a corresponding intelligent connected vehicle control terminal, solves the problem that intelligent connected vehicles and traditional vehicles form a decision conflict, cause path conflict and low shunting efficiency, and cause traffic hazards and congestion, and achieves the effects of improving the traffic flow and overall traffic efficiency of the intersection, reducing traffic congestion and conflict, and improving traffic safety and efficiency.

This disclosure provides a status indication method, device, autonomous vehicle, and storage medium, belonging to the field of autonomous driving. The method includes: real-time detection of the current status information of the autonomous vehicle, determining the status type of the status information, and outputting indication information corresponding to the status type through the autonomous vehicle's output device. This enables other intelligent agents to accurately and fully understand the current status of the autonomous vehicle and perform operations based on the current status, minimizing conflicts between the operations of other intelligent agents and the driving operations of the autonomous vehicle, thereby reducing the probability of traffic accidents and improving safety. Furthermore, by actively interacting with other intelligent agents, the autonomous vehicle can eliminate misunderstandings, reduce risks, improve traffic safety, and reduce traffic accidents.

The invention discloses an intelligent traffic management system based on a block chain and the Internet of Things, and relates to the technical field of intelligent traffic, and the intelligent traffic management system comprises an Internet of Things sensing module, a core block chain module, a data processing and analysis module and a user interaction interface module. The core block chain module is used for guaranteeing the authenticity, reliability and storage safety of data, the data processing and analysis module is used for collecting multi-source traffic data information and carrying out processing analysis and modeling, and the user interaction interface module can enable the public to easily obtain required traffic information and participate in management and feedback, so that the user experience is improved. The public participation sense and travel experience are improved, the whole intelligent traffic management system can operate efficiently through effective cooperation among the modules, the management efficiency and the intelligent level of the traffic system are improved, the transparency and the safety of the traffic management system are enhanced, and traffic congestion can be reduced.

This invention discloses a land-use-intensive roundabout topology design method based on adaptive traffic volume, comprising: acquiring the physical structure and current traffic flow parameters of the target intersection; calculating the theoretical capacity based on the gap acceptance theory using the yield rule for entering the roundabout; inputting the traffic flow parameters into a micro-traffic simulation model, and obtaining the slow traffic reduction coefficient and left-turn ratio reduction coefficient of motor vehicle capacity by changing the slow traffic flow and left-turn ratio variables, respectively; correcting the theoretical capacity using the above two reduction coefficients to obtain the adaptive traffic volume of the target intersection; and finally matching the corresponding center island radius and number of roundabout lanes in a preset intersection selection library according to the adaptive traffic volume, and outputting the final physical topology modification scheme. This invention accurately quantifies the interference degree of mixed traffic flow and turning ratio, avoids the subjective blindness of manual selection, and significantly improves the scientificity and land-use efficiency of intersection design.

The invention relates to a traffic signal optimization system applied to roads in a steel enterprise plant, and belongs to the technical field of traffic signal control. The system comprises a database, a data reading module, a prediction module, a genetic algorithm processing module and a user interface. The database is used for storing traffic signals, road intersection traffic flow and stay time data; the data reading module is used for cleaning data in a database to remove noise and error data and then standardizing the cleaned data; the prediction model module is used for predicting future traffic conditions, and the genetic algorithm processing module is used for optimizing a traffic signal timing scheme and finally displaying the traffic signal timing scheme through a user interface. Real-time traffic conditions are responded by dynamically adjusting the time sequence of the traffic signal lamps, so that the road use efficiency is improved, traffic congestion is reduced, and vehicle exhaust emission is reduced.

The invention discloses a lane speed monitoring method and system based on a base station. The method comprises the steps of 1, vehicle data collection, wherein GPS positioning information and speed data of a vehicle and signal strength parameters of the base station are collected through communication signals of a communication base station; step 2, lane identification: according to the position data of the vehicle and the coverage area of the base station, calculating a specific lane where the vehicle is located through a preset road network model and lane distribution information; step 3, vehicle speed monitoring; 4, lane departure early warning is carried out; step 5, cloud computing and data storage; and step 6, displaying at a user side. According to the invention, real-time monitoring of vehicles is realized through the base station, the large-range coverage capability is realized, large-scale road monitoring can be realized, and the limitation of traditional monitoring equipment such as ground induction coils and radars is overcome. The road monitoring efficiency can be remarkably improved, traffic accidents are reduced, and the traffic management level is improved.

The invention discloses a wheel ferry vehicle and passenger intelligent dispersion method and system, and relates to the field of traffic intelligent planning, and the method comprises the following steps: S1, obtaining current wheel ferry ticket selling information, and classifying vehicle drivers and passengers in the same shift; s2, according to the ticket buying time and the set batch interval time, an improved column generation algorithm is adopted to intelligently plan boarding batches and time nodes of vehicle drivers and passengers, and identification pass codes are generated according to the boarding batches and the time nodes and sent to the user side; s3, scanning the identification pass code in real time at a boarding gate and carrying out statistics, and if boarding does not exist in a corresponding boarding batch time window, automatically rearranging to a next boarding batch; s4, calculating the predicted off-ship time of the vehicle and the on-board passengers, and intelligently planning off-ship batches by adopting a space-time synchronous clustering algorithm; pushing the off-ship batch information to the user side; effective dispersion of boarding and leaving is achieved, the experience feeling of passengers is improved, and meanwhile traffic jam is reduced.

The invention discloses a method and a device for realizing mixed loading of heterogeneous traffic monitoring processors based on TCAS (Traffic Collision Avoidance System) amplitude-phase compatibility. The device is characterized in that a traffic monitoring processor of an amplitude system is respectively connected with a traffic monitoring antenna and a traffic monitoring processor of a phase system through an antenna interface unit and a traffic monitoring change-over switch in sequence; a traffic monitoring processor of an amplitude system or a traffic monitoring processor of a phase system is selected through an airborne control panel, and the selected traffic monitoring processor is communicated with a traffic monitoring antenna through a traffic monitoring change-over switch. The traffic monitoring processor of the amplitude system and the traffic monitoring processor of the phase system share the same traffic monitoring antenna in a time-sharing manner. The number of traffic monitoring antennas can be reduced, radio frequency cables between the traffic monitoring antennas and the traffic monitoring processor can be reduced, and the total weight of the system can be reduced.

The invention relates to a road width-limited area safety passage control system, which comprises a signal capturing mechanism arranged at a road width-limited area and used for executing field image signal capturing operation on an automobile which is about to pass to the road width-limited area; the signal detection mechanism is used for intelligently identifying an entity width value of a vehicle which is about to enter the road width limiting area; and the state identification mechanism is used for sending a width limiting reminding command when the received entity width value is greater than the maximum passing width corresponding to the road width limiting area. The safe traffic control system for the road width-limited area is compact in design, safe and reliable. On the basis of customized visual data intelligent analysis, when the entity width value of the vehicle which is about to enter the width-limited road surface area is greater than the maximum passing width corresponding to the road width-limited area through intelligent analysis, the width-limited reminding command is sent out, so that the number of traffic road surface accidents is reduced.