20 results about "Traffic capacity" patented technology

The application relates to a traffic capacity estimation method based on traffic basic graph parameter calibration, belongs to the technical field of intelligent traffic systems and traffic flow modeling, and particularly relates to a traffic capacity estimation method based on traffic basic graph parameter calibration. The application aims to solve the problem that the existing method cannot obtain accurate traffic basic graph parameters, resulting in low traffic capacity estimation precision. The process is as follows: step one, obtaining historical traffic flow single vehicle data samples of a road section; processing the obtained single vehicle data samples to obtain a final aggregated data set; step two, obtaining adaptive weights based on kernel density estimation based on the obtained final aggregated data set; step three, obtaining an optimal parameter set of a traffic basic graph model by adopting a particle swarm optimization algorithm based on the adaptive weights; and step four, obtaining traffic capacity based on the optimal parameter set of the traffic basic graph model.

This invention belongs to the field of intelligent unmanned systems and path planning technology. It discloses a dynamic evaluation method for the path mobility of unmanned vehicles applicable to complex environments. This method constructs a mapping relationship between traffic influencing factors and traffic coefficients; and builds a closed-loop learning system of "perception-decision-verification-update" using a convolutional neural network (ResNet) and a graph attention network (GAT). Compared to traditional mobility evaluation methods with their single evaluation conditions and the high computational complexity and lack of adaptability of traditional overlay analysis methods, this invention effectively improves the accuracy and adaptability of mobility evaluation by introducing multi-source environmental factor modeling and machine learning mechanisms, providing scientific and efficient decision support for unmanned vehicle path planning.

The application discloses a kind of vehicle flow path planning method based on logistics park and surrounding road network double constraint, by constructing mathematical model, simultaneously consider the processing capacity limit of internal service node of logistics park and the traffic capacity limit of surrounding road network section and node, accurately present the interaction mechanism of both, solve the problem that prior art cannot accurately depict its complex relationship;Second, based on the solution algorithm, the model is solved, in the double-constrained environment of comprehensive and accurate, fully excavate path combination, quickly find the vehicle flow path scheme that meets the conditions and makes the optimal solution of transportation efficiency, cost and other targets, overcome the problem that optimal solution is difficult to obtain;In addition, the influence of different constraint conditions is analyzed in depth, the action mechanism of vehicle flow path is mastered, and the model and algorithm are optimized accordingly, and the planning scheme can be adjusted in real time according to the actual situation, so that the planning can follow the changes of actual demand, effectively make up for the defects that the prior art is difficult to dynamically optimize and adjust.

Techniques disclosed herein include receiving a request to perform an upgrade. The upgrade can comprise changes to firmware or software of the network interface card. Input / Output (I / O) traffic can be monitored on one or more paths between the network interface card and a storage device. The paths can have a path capacity comprising a bandwidth of Input / Output traffic. The spare Input / Output traffic capacity can be calculated based at least in part on the Input / Output traffic and the path capacity. Whether to remove a path can be determined based at least in part on the spare Input / Output traffic capacity. The upgrade can be performed with the path halted in accordance with a determination to remove the path. The upgrade can be performed with the path included in accordance with a determination to not remove the path.

The application provides a VISSIM microcosmic traffic flow simulation method and system, which firstly introduces the road use characteristics (flatness, skid resistance) of solid waste pavement into the VISSIM simulation parameter system; the length optimization is realized by hierarchical constraint + dynamic iteration instead of static single simulation; the quantitative correlation of'material characteristics-traffic parameters-operation zone length' is established by using the traffic capacity attenuation coefficient, so that the decision is changed from 'empirical type' to 'quantitative type', and specifically, through the process, the most economical operation zone length can be found under the premise that the service level of the operation zone is greater than or equal to three, which not only avoids the problems of 'cost waste caused by too long' or 'traffic congestion caused by too short' in the traditional method, but also adapts to the special pavement conditions of the solid waste utilization reconstruction and expansion project.

The application discloses a kind of based on multi-objective optimization's river-sea intermodal ship collaborative scheduling method and system, the method includes: the dynamic data of river ship and sea ship, static data, scheduling application data and channel environment data are collected and fused, and fusion multi-source heterogeneous data are obtained;Channel digital model is constructed, and the dynamic traffic capacity of each channel is calculated according to fusion multi-source heterogeneous data;With the minimum of all ship total scheduling time and total waiting time as the goal to build multi-objective optimization model;Multi-objective optimization model is solved based on improved DE-NSGA-II algorithm, and the pareto optimal solution set is obtained;Final scheduling scheme is selected from the pareto optimal solution set and executed.The application significantly reduces ship operating cost, reduces carbon emissions, and helps green port construction.The reduction of ship waiting time and total voyage directly reduces fuel consumption and ship operating cost.

The application provides a kind of intersection traffic adaptive control optimization decision method and system based on electric police data, it is related to intersection traffic signal optimization field.First, based on electric police data, the influencing factors such as cycle flow, vehicle type, signal cycle and driving behavior are obtained by data integration.Second, the adaptive control effect expressed by traffic capacity is the dependent variable, and the above four traffic influencing factors are the independent variables to construct a multiple linear regression model for key factor analysis.Finally, according to the decision criteria and analysis results, the decision suggestions are given.The application introduces the evaluation method based on data analysis to evaluate the adaptive control effect to support the corresponding decision, and this data analysis and optimization method based on electric police data can help optimization personnel make different decisions for intersections with different characteristics, find out the key influencing factors of intersection congestion, and make targeted optimization, so as to improve the adaptive control effect of intersection.

The application provides a waterway traffic capacity prediction and ship navigation guidance method and system, and relates to the technical field of intelligent transportation and water traffic safety management. The guidance method specifically comprises the following steps: collecting on-site images of an accident water area and calculating a three-dimensional posture of an accident ship; generating a time-varying residual waterway width function representing the available width of a future waterway; constructing a space-time state matrix of a to-be-passing ship; constructing a space geometric constraint based on the time-varying residual waterway width function, and constructing a wave effect constraint for determining the maximum critical navigation speed of each to-be-passing ship based on on-site observation of the wave generated by the passing ship; and based on the space-time state matrix, the space geometric constraint and the wave effect constraint, performing global optimization solving of multi-objective navigation scheduling to generate and issue a navigation timetable containing the optimal passing navigation speed of each to-be-passing ship.

Embodiments of the present application relate to a kind of road traffic capacity measurement method, device and electronic equipment for automatic driving, comprising: obtaining the lane type of each lane in the road section to be measured;According to lane type, determine at least one vehicle type allowed to pass in each lane;The headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate corresponding to each of at least one vehicle type and the probability of each vehicle type selecting the lane type of the m-th lane are obtained;According to the market penetration rate corresponding to each of each vehicle type in the m-th lane, the probability of each vehicle type selecting the lane type of the m-th lane, and the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the average headway of the m-th lane is obtained;Based on the average headway corresponding to each of each lane in all lanes, the total traffic capacity of the road section to be measured is determined.

The application provides a traffic signal control method, device and electronic equipment. The method obtains multi-scale traffic state data, including the import flow of each import in each intersection, the vehicle flow turning ratio of each turning in each intersection and the turning traffic capacity. The turning flow of each turning in each intersection is obtained by calculation according to the import flow and the vehicle flow turning ratio. The real-time saturation of each turning in each intersection is obtained by calculation based on the turning flow and the turning traffic capacity. The network average saturation is obtained by calculation according to the real-time saturation. The target control model is determined based on the comparison result of the network average saturation and the preset saturation. The signal timing scheme is generated according to the control strategy corresponding to the target control model. The traffic signal is controlled based on the signal timing scheme. The above method provides a more practical and accurate traffic signal control method.

The invention provides a bus signal priority compensation control method and system based on green wave band protection. The method comprises the steps that trunk line green wave coordination parameters are acquired; collecting road traffic information, traffic signal state information and vehicle running state information; judging whether a bus priority triggering condition is met or not according to the collected information; when the trigger condition is met, executing a bus priority strategy, and determining additional phase time increased by the strategy in the current signal period; executing a phase compensation mechanism which specifically comprises the following steps: judging whether a non-coordinated phase has enough compensation capability in a current period; if there is enough compensation capability, compensation of the additional phase time is completed in the current period; and if the compensation capability is not enough, performing partial compensation by using the available compensation time of the non-coordinated phase in the current period, and distributing the residual disturbance time to the subsequent one or more periods to gradually complete compensation. According to the invention, the operation efficiency of buses and the overall traffic capacity of urban traffic are improved.

The application discloses a kind of power distribution network mobile emergency resource pre-configuration method considering the influence of extreme weather, which comprises the following steps: based on power grid topology, traffic network node and power grid node are sequentially coupled corresponding, collect power grid information and traffic network information, obtain power and traffic coupling network;Mobile emergency resource driving path analysis is carried out based on Dijkstra algorithm;Based on blind number theory, construct the power distribution network fault scene under extreme weather;Construct the integrated failure rate model of line under single weather;Construct the integrated failure probability model of line under multiple weather factors;Construct the mobile emergency resource pre-configuration model considering power and traffic coupling network under extreme weather;Resource pre-configuration is carried out based on mobile emergency resource pre-configuration model.The application comprehensively considers the power distribution network fault recovery demand under extreme weather and the influence of extreme weather on traffic network traffic capacity, so that path decision is more matched actual working condition.

The application discloses an entrance ramp mixed traffic simulation method and a signal scheme evaluation method, which comprises the following steps: establishing an entrance ramp traffic flow simulation based on a cellular automaton model; adding competition and cooperation strategies to the model; adding observation points to investigate the degree of vehicle fleet dispersion phenomenon; setting road condition simulation parameters and signal lamp initial conditions; simulating traffic flow driving process under a given traffic light control scheme; analyzing traffic flow state and the influence of large vehicles on ramp traffic capacity, and generating charts; and iteratively evaluating traffic light control schemes multiple times and performing scoring and sorting. The application studies lane changing and following rules of mixed traffic flow of autonomous vehicles and manually driven vehicles at an entrance ramp bottleneck, simulates possible traffic phenomena and corresponding traffic flow parameters, tests comprehensive performance of a signal lamp scheme under specific road conditions, and obtains real-time evaluation results of the signal lamp scheme through a scoring system.

The application discloses a kind of intersection signal control methods based on real-time overflow detection, it is related to intelligent transportation technology field, according to intersection real-time detection data, the overflow state of each flow direction of intersection is determined, and the mapping relationship between overflow state and passable traffic flow is established;Real-time light state of downstream intersection is obtained, the time required for overflow dissipation of current intersection is calculated;Based on the real-time queuing length of each direction of current intersection and signal light state, the expected traffic benefit under different signal control strategies is calculated, and a penalty mechanism for overflow deterioration is introduced;Combined with the business constraints of signal control, an optimization model is constructed to maximize the traffic capacity without worsening the overflow;Optimal control strategy is executed, and the optimal control strategy and optimal extension time are obtained by solving the optimization model, and are converted into signal machine control instructions to issue and execute.

The application discloses a kind of traffic AI scheduling decision-making methods based on multi-source geographic big data, it is related to intelligent transportation technology field, including, collection multi-source traffic data and pre-processing, generate after processing traffic dataset;Using trained long short-term memory network, the multi-scale time series analysis is carried out to after processing traffic dataset, generates traffic flow prediction result;Using particle swarm optimization algorithm, traffic flow prediction result is adjusted, generates candidate traffic scheduling scheme;Candidate traffic scheduling scheme is dynamically optimized, generates after optimization traffic flow control scheme;Optimization after traffic flow control scheme is compared and analyzed with newly collected multi-source traffic data, generates adjusted traffic flow control scheme, and based on real-time traffic flow feedback, adjusted traffic flow control scheme is dynamically adjusted, forms continuous feedback cycle.The application improves the traffic capacity of road and resource use efficiency.

The application provides a judgment method and device for a highway maintenance construction organization mode, relates to the technical field of traffic organization, and comprises the following steps: constructing a construction road section traffic bottleneck analysis model according to core parameters; solving the construction road section traffic bottleneck analysis model through a genetic algorithm to obtain single-lane traffic capacity; calculating a first ratio and a second ratio according to a road occupation construction period, a closed construction period, a target single-lane number, a target maintenance road occupation number, daily traffic volume and the single-lane traffic capacity; determining a construction organization mode type, a first ratio threshold and a per-kilometer daily traffic fee threshold according to the second ratio and a second ratio threshold; constructing a construction organization mode comparison table according to the target single-lane number, the target maintenance road occupation number, the per-kilometer daily traffic fee threshold, the first ratio threshold and the construction organization mode type; and selecting a final construction organization mode in the construction organization mode comparison table according to to-be-measured road section traffic data.

This invention discloses a method and system for allocating vertical transportation capacity resources based on urban area pedestrian flow heat maps. The method includes: constructing a standardized basic data set by collecting urban public transportation operation data, regional pedestrian flow heat map data, and basic operation data of vertical transportation facilities in the target building. Based on this data set, a macro-level pedestrian flow prediction method is used to calculate the scale and distribution characteristics of people arriving in the target area in the future, and the demand for elevators on each floor is accurately predicted by combining the pedestrian flow heat map. Based on the demand prediction results and the vertical transportation capacity supply conditions, a pre-allocation plan for transportation resources is generated, and the elevator parking planning and operation mode are dynamically adjusted. After the plan is issued and implemented, actual pedestrian flow data and elevator operation feedback information are collected in real time, and the allocation plan is continuously corrected based on data deviations, realizing adaptive and refined control of vertical transportation capacity resources.

The technology is generally directed to the continued use of a link between nodes of a network in which at least one of the lanes in the link has failed. Rather than identify the link as a failure in response to a lane failure, the traffic may be redistributed amongst the remaining lanes in the link. The redistribution of traffic may result in the link operating in a degraded mode. To mitigate the reduced traffic capacity of the degraded mode, the remaining links may be overclocked, such that the bandwidth of each link is increased to return the link to a traffic capacity corresponding to the initial capacity. In some examples, the traffic may be diverted to a redundant, otherwise inactive lane, thereby allowing for the traffic to be transmitted and received via the link, without any degradation in the performance of the link.

The application discloses a kind of based on underwater map improves the method of channel traffic volume, belong to water transport technical field, including the following steps: S1 constructs underwater high-precision map, deploys unmanned ship, underwater robot, utilizes multibeam sounding technology to collect underwater topographic data to construct high-precision underwater map;S2 dynamic channel planning model is established, using big data analysis and machine learning algorithm, collect the hydrological data of channel different time and place and ship traffic data, generate dynamic channel use scheme;S3 integration ship navigation and management system, develop ship navigation terminal equipment, integrate dynamic channel planning model with the monitoring system of channel management department.This application optimizes channel resource utilization, realizes intelligent dynamic planning, improves ship traffic efficiency, navigation autonomy, navigation safety and system stability, reliability, enhances the scientific nature of channel management, strengthens the coordination of ship and management department.

The technology is generally directed to the continued use of a link between nodes of a network in which at least one of the lanes in the link has failed. Rather than identify the link as a failure in response to a lane failure, the traffic may be redistributed amongst the remaining lanes in the link. The redistribution of traffic may result in the link operating in a degraded mode. To mitigate the reduced traffic capacity of the degraded mode, the remaining links may be overclocked, such that the bandwidth of each link is increased to return the link to a traffic capacity corresponding to the initial capacity. In some examples, the traffic may be diverted to a redundant, otherwise inactive lane, thereby allowing for the traffic to be transmitted and received via the link, without any degradation in the performance of the link.