16 results about "Traffic bottleneck" patented technology

A ramp confluence area mixed traffic flow cooperative control method based on space-time network reinforcement learning comprises the steps that firstly, a historical state sequence with a fixed length is constructed through a sliding window mechanism, and time sequence information is introduced to capture the dynamic evolution process of traffic flow; secondly, designing a spatial-temporal feature extraction structure combining multi-head space attention and mask time attention, respectively modeling the correlation of the vehicle in space and time dimensions, and enhancing the state expression ability; on this basis, a deep reinforcement learning strategy network based on Actor-Critic is constructed, and optimization of vehicle decision is realized; in order to guarantee the decision safety, a minimum safety distance constraint and action safety mask mechanism is further introduced, and action selections with collision risks are screened out. And finally, the learning efficiency and stability of the multi-agent system are improved in combination with a local reward mechanism. According to the method, the cooperative control performance of the mixed traffic flow in the ramp confluence traffic bottleneck area can be improved, the collision rate is reduced, and the safety and passing efficiency of a traffic system are enhanced.

The application belongs to the technical field of expressway, and particularly relates to an expressway traffic congestion prediction method and system based on deep learning. The method comprises the following steps: acquiring traffic flow characteristic information, identifying a traffic bottleneck node based on the traffic flow characteristic information, summarizing reference characteristic values of the traffic bottleneck node to form an overall traffic flow characteristic data set, performing discrete degree analysis on the data set to obtain a characteristic index, extracting a traffic congestion concentrated interval according to the characteristic index, identifying a risk time point in the interval, and outputting a predicted expressway congestion period and a corresponding congestion area according to the risk time point and the traffic congestion concentrated interval. The application can improve the accuracy of congestion root identification by identifying a traffic bottleneck node and quantitatively analyzing the evolution trend of the bottleneck state, and can output a region to be regulated and a regulation period, thereby providing decision support for traffic relief.

The invention discloses a compliance automatic transportation and monitoring system which comprises an algorithm fusion module and an excitation module. The algorithm fusion module is used for calculating the path length in an AGV dynamic scheduling algorithm according to a cost map updated in real time, and ensuring that each planned path is physically shortest and optimal in compliance; the algorithm fusion module comprises a fusion type AGV dynamic scheduling module, an intelligent elevator cooperative control module and a compliance path planning module. According to the invention, the information barriers among the AGV scheduling subsystem, the elevator control subsystem and the indoor path planning subsystem are thoroughly broken through the central compliance decision algorithm, and cross-system global resource optimization and cooperative command are realized. The system ensures absolute compliance of whole-process transportation and material safety. Meanwhile, the system achieves active and reserved cooperation of the AGV and the elevator, the waiting time is greatly shortened, and the traffic bottleneck of the building is eliminated.

The application discloses an inner-cross type tire crane instruction scheduling method based on multi-dimensional dynamic priority and predictive scheduling, which comprises the following steps: step S1, candidate instruction set generation and hard constraint filtering; step S2, opportunity overtaking window evaluation; step S3, nonlinear dynamic sorting of regular instructions; and step S4, instruction issuing and rescheduling. The application quantifies and decides whether to execute the overtaking instruction which can bring higher net benefit through the opportunity overtaking window evaluation, so as to improve the work efficiency. The application introduces the instruction waiting time factor and the maximum tolerance threshold with exponential growth characteristics, so as to ensure that the priority of the instruction waiting for a long time can be systematically improved, and the scheduling fairness can be ensured. In addition, the local congestion factor is used to reduce the priority of the instruction in the congestion area, so as to relieve the traffic bottleneck.

This invention discloses a method for estimating road capacity and bottleneck status considering the influence of longitudinal slope. The steps include: 1. Collecting longitudinal slope data of the target road; 2. Identifying longitudinal slope regions using wavelet transform; 3. Collecting traffic flow information under free-flow conditions of the target road; 4. Identifying macroscopic traffic flow velocity regions using wavelet transform; 5. Constructing a capacity model considering the influence of longitudinal slope; 6. Predicting traffic bottlenecks of the target road based on the current state and inflow traffic volume. This invention achieves accurate matching of road capacity under different road longitudinal slopes and free-flow velocities. By using initial state and real-time inflow statistics, it enables the prediction of bottleneck road segment status, providing important data for traffic management.

The invention relates to a multi-mode traffic network modeling and capability evaluation method and system, and the method comprises the steps: constructing a topological structure of a multi-level road and railway network based on road and railway data in combination with remote sensing images, surveying and mapping data and the like; constructing a three-section task path which simultaneously comprises a railway section, a transfer node and a road section; dynamic updating and seasonal model switching are carried out, and traffic state change is controlled based on time, weather and manual input; performing multi-target path evaluation, and performing path generation and visual display and interaction according to multiple target functions; and data persistence and interface service. According to the method, the path connection efficiency of different modes is improved, the attribute expression is multidimensional and fine, the dynamic capability is prominent, the path evaluation precision is high, the system integration degree is high, the guarantee capability is remarkably improved, traffic bottlenecks, key paths and sensitive areas are effectively identified through system modeling, and the method has a remarkable supporting effect on rapid deployment, area sealing and control, special vehicle action and the like; and the overall guarantee capability under the emergency condition is improved.

Disclosed herein are systems and methods for identifying and ranking traffic bottlenecks. An example of such methods may include operating at least one processor to: receive traffic data associated with a road network comprising a plurality of road segments, the traffic data comprising vehicle speed data collected from a plurality of vehicles operating within the road network; determine a benchmark speed for each of the plurality of road segments; determine, for each of the plurality of road segments, whether a traffic disruption is present by comparing the benchmark speed thereof to vehicle speed data collected from at least one vehicle operating therealong; determine, for each of the plurality of road segments having the traffic disruption therealong, one or more road segment metrics associated therewith; identify a traffic bottleneck by aggregating a plurality of adjacent road segments having traffic disruptions therealong and the one or more road segment metrics associated therewith; and rank each traffic bottleneck based on one or more aggregated road segment metrics associated therewith.

Disclosed are systems and methods that provide a computerized framework for accurately and efficiently estimating the backhaul bandwidth and core capacity, which can be utilized to automatically and dynamically configure and / or curate network configurations and topologies to handle network loads and traffic. The framework can utilize and / or operate RF system simulators to perform the estimation of each sector's delivered UL / DL throughputs, as well as user inputs related to the traffic model, the dedicated network's topology and product specifications related to the processing limits of BBUs and private cores in order to determine network bottlenecks. Such determinations and / or predictions can be leveraged to ensure the allocation of backhaul bandwidth and core capacity, among other network features and / or characteristics, are optimized to achieve overall high throughput and remove traffic bottlenecks.

The utility model discloses a motorized multi-mode expressway toll station structure, which relates to the technical field of expressway toll station structures, and comprises a toll queue area which is divided by depending on the interior of a single lane and is used for accommodating a plurality of vehicles to be transacted to form a transaction queue; a mobile and / or fixed charging terminal is adopted, is arranged on the side surface of the charging queue area, and carries out charging transaction corresponding to the vehicles in the transaction queue; the entrance and / or exit of the charging queue area is provided with a fee-display integrated handrail to control vehicles to go in and out. According to the utility model, the toll queue areas are divided in the single lane to accommodate multiple vehicles, and the toll terminal is matched to carry out parallel toll collection, so that the traditional single-point serial toll collection is changed into multi-point multi-vehicle parallel toll collection, the traffic bottleneck problem of insufficient toll points in peak hours is solved, and the traffic efficiency and throughput of the toll station are improved.

The application discloses a dynamic traffic bottleneck identification method based on a space-time graph attention network and belongs to the field of intelligent traffic, and the method comprises the following steps: acquiring road network data and trajectory data, pre-processing the trajectory data based on the road network data to obtain pre-processed trajectory data; constructing a space-time graph attention network, inputting the road network data and the pre-processed trajectory data into the space-time graph attention network model to obtain node representation with time sequence dynamics; and processing the node representation with time sequence dynamics by using a dynamic traffic bottleneck identification algorithm to identify a dynamic traffic bottleneck. The application can effectively extract the spatial proximity of road network nodes, accurately capture the space-time dynamics of traffic flow propagation, and the identification algorithm has a high running speed and meets the real-time requirement.

The invention relates to the technical field of traffic avoidance, in particular to a traffic conflict point active collision avoidance control method and system, and the method comprises the steps: carrying out the dynamic conflict point recognition of a road intersection, and obtaining a real-time traffic conflict point distribution diagram; performing behavior feature extraction on the traffic participants according to the real-time traffic conflict point distribution map to obtain dynamic state data of the traffic participants; inputting the dynamic state data of the traffic participants into a traffic conflict risk assessment network for risk quantification processing to obtain a traffic conflict risk assessment result; and performing conflict development trend prediction processing on the traffic conflict risk assessment result to obtain a traffic conflict evolution prediction result. Through cooperative control with infrastructures such as a traffic signal control system and a traffic guidance system, the traffic light time length, lane distribution and the like can be intelligently optimized, the efficiency of a traffic management system is improved, and the problems of traffic bottleneck and congestion are avoided.

The application discloses a kind of urban traffic bottleneck area flexible boundary robust control method and equipment, belong to intelligent transportation technical field, for solving the technical problem that the interference rejection capability of urban traffic bottleneck area boundary control method of static boundary constraint is poor, robustness is insufficient.Method includes: real-time acquisition urban traffic bottleneck area's dynamic static traffic information;According to dynamic static traffic information, determine the comprehensive traffic correlation degree of each boundary section;According to the comprehensive traffic correlation degree of each boundary section, determine the all dynamic threshold control intersections of urban traffic bottleneck area;The connection of all dynamic threshold control intersections is dynamic control boundary;Through MFD model, estimate the best vehicle accumulation in dynamic control boundary range, and determine the traffic control distribution of each boundary section;According to traffic control distribution, calculate the traffic signal lamp duration of each dynamic threshold control intersection, obtain bottleneck area traffic signal flexible boundary control scheme.

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.

Road traffic is monitored in a road network 315 leading to a selected destination 303 to obtain from live and historical data an estimate of the rate of arrival of vehicles at the destination, which may be a traffic bottleneck. If the estimated rate exceeds a desired rate, preferably selected to avoid a slow or static queue, vehicles are instructed to diverge from their intended route and may be directed to a waiting area 305. Diverted vehicles are assigned to a virtual queue and are given permission to proceed to destination 303 or elsewhere 304 in accordance with their places in the virtual queue.

The invention discloses a traffic bottleneck identification method based on urban road network base and bayonet data, and relates to the technical field of traffic monitoring. Accurate association of data and road sections is realized by building an urban road network base and configuring and binding bayonet equipment; acquiring long-term historical checkpoint data, and counting vehicle passing data volume and the proportion of large vehicles to small vehicles; based on the historical checkpoint data, calculating road section traffic capacity and theoretical traffic time by adopting a preset formula, and jointly taking the road section traffic capacity and theoretical traffic time as road section design capacity data; counting vehicle intersection average queuing time, road section average passing time and road section vehicle occupancy at preset time intervals, and completing traffic bottleneck monitoring index counting; based on road section design capability data and traffic bottleneck monitoring indexes, potential, short-term and long-term traffic bottlenecks are judged, congestion chains are tracked through a road network topological relation to identify cascade propagation attributes, and traffic bottleneck generation reasons are analyzed. According to the method, the traffic bottleneck can be quickly and accurately identified, and the cause of the traffic bottleneck is analyzed from multiple dimensions.