8 results about "Traffic law enforcement" patented technology

The invention discloses a traffic law enforcement virtual simulation training method based on a dynamic scene and cognitive evaluation, and the method comprises the steps: generating an initialization parameter according to a trainee portrait and a training target, and driving an emergence type scene generation engine to synthesize a dynamic three-dimensional virtual training scene containing composite illegal elements; in scene operation, multi-modal interaction behaviors and physiological response data of the trainees are synchronously collected to form a data stream; through real-time analysis of the data flow, a cognitive behavior analysis report for evaluating attention, cognitive load and decision intention is generated; constructing a space-time knowledge graph based on the student operation sequence, performing automatic reasoning and contradiction detection in combination with formalized legal rules, and outputting an evidence chain logic verification result; and fusing the report and the result to carry out multi-dimensional weighted evaluation, and generating a comprehensive score and personalized feedback. According to the method, normal form transformation from preset process training to open cognitive evaluation is realized, and the authenticity, pertinence and evaluation depth of training are improved.

The application discloses a traffic law enforcement resource scheduling method and system based on multi-source real-time data, which comprises the following steps: acquiring multi-source real-time data, wherein the multi-source real-time data at least comprises law enforcement task data, law enforcement resource data and environmental support data; pre-processing and fusing the multi-source real-time data to construct a standardized scheduling data resource pool; based on the scheduling data resource pool, structurally analyzing the law enforcement task and determining a task priority sequence; based on the scheduling data resource pool, constructing a dynamic portrait of law enforcement resources; inputting the task priority sequence and the dynamic portrait into a preset intelligent scheduling decision model, and performing multi-objective optimization calculation combined with law enforcement compliance constraint conditions to generate a target scheduling scheme; and outputting the target scheduling scheme to perform dynamic scheduling of law enforcement resources. The traffic law enforcement resource is accurately matched, quickly responded and compliantly scheduled in a dynamic scene, and the law enforcement disposal efficiency and resource utilization rate are significantly improved.

The invention discloses an off-site comprehensive risk assessment method and system for an overloaded vehicle and a storage medium thereof, and relates to the field of intelligent traffic law enforcement. The method comprises the following steps: firstly, collecting multi-source data when a vehicle passes through a monitoring area, wherein the multi-source data comprises weight data of at least two weighing sensors, vehicle running speed and transverse offset; performing weighted fusion on the weight data based on the confidence coefficient weight of each sensor to obtain an actually measured weight and an overload weight; respectively calculating a speed penalty factor and an offset penalty factor according to the vehicle speed and the offset; and substituting the overload weight and the two penalty factors into the comprehensive scoring model to obtain a quantitative comprehensive risk score S. And S is compared with a preset risk threshold value, whether the vehicle has a high-risk overload behavior or not is judged, and off-site electronic evidence containing complete data is automatically generated. According to the method, single overload judgment is converted into multi-dimensional risk assessment fusing weight, speed and attitude, and quantification and refinement of law enforcement basis are achieved.

The invention discloses an urban road high-risk rider and pedestrian illegal behavior identification and early warning method and system, and belongs to the technical field of intelligent traffic management. The method comprises the following steps: collecting multi-modal data of a road intersection in real time; identifying illegal behaviors based on the data, and carrying out identity identification on illegal individuals or groups; and generating an early warning strategy based on the identification result and the identity label and executing directional early warning. The system comprises a sensing module, an analysis decision module and an early warning execution module. According to the method, the problems of response lag, inaccurate early warning, data island and lack of pre-judgment ability in the prior art are solved, the conversion from post-event evidence obtaining to pre-event prevention is realized, the timeliness and effectiveness of traffic violation intervention are remarkably improved through accurate identification and collaborative early warning, and meanwhile, data support is provided for traffic management decision making. The method is suitable for wide popularization and application in traffic management.

The present application relates to the technical field of intelligent transportation, in particular to a method and system for intelligent judgment of low-altitude parking violation target based on deep learning. It includes: traffic flow field anomaly diagnosis step, unmanned aerial vehicle collects road video data, generates vehicle motion vector field, and autonomously determines traffic obstruction area; obstruction root space-time backtracking step, through the attention network of stop state propagation graph and reverse propagation graph, the initial stationary vehicle as the obstruction root is locked; parking violation influence quantification and comprehensive judgment step, the additional traffic delay quantification index is calculated and whether parking violation is judged comprehensively according to the spatial relationship; dynamic causal evidence chain generation step, encapsulating the structured evidence file containing traffic flow evolution process, space-time backtracking path and quantification index. The present application realizes the paradigm upgrade from "passive single-point detection" to "active obstruction source tracing", greatly improves the intelligent level and disposal efficiency of low-altitude traffic law enforcement.

This application relates to the field of intelligent transportation technology and discloses an intelligent identification and evidence collection system for traffic violations based on multimodal fusion perception. The system includes an edge sensing terminal, which uses a synchronous control module to achieve hardware synchronous acquisition of multimodal sensors. A data processing module performs spatiotemporal alignment of the acquired data and performs cross-modal correlation and fusion tracking of the target to generate a high-precision fused motion trajectory. Finally, the trajectory is compared with a digital road traffic rule model to determine the violation. This invention solves the technical problems of low accuracy and susceptibility to false alarms and missed detections caused by single sensors in complex scenarios such as adverse weather and target occlusion. It can generate highly credible multi-dimensional structured evidence, significantly improving the automation level and credibility of traffic law enforcement.

The utility model provides a portable multifunctional traffic transportation law enforcement detection box, and relates to the field of traffic transportation law enforcement. The portable multifunctional traffic transportation law enforcement detection box comprises a detection box body and a plurality of clamps, the detection box body comprises two double box bodies, the two double box bodies are connected through a connecting assembly, an integrated isolation belt is installed between the two double box bodies, and the two ends of the isolation belt make contact with the two clamps respectively; according to the portable multifunctional traffic transportation law enforcement detection box, the detection box body is compact in structure, under the condition that the loading capacity is increased, space can be saved, the isolation belt can isolate the clamp, the protection effect is achieved, the probability that a detection instrument in the clamp is damaged is reduced, and when the detection box body is used, the detection box body can be separated from the ground and prevented from being polluted; and the isolation belt can be separated from the clamp and cooperates with the detection box main body to form a stable structure, so that the stability of taking the instrument is improved.

The application discloses a kind of off-site comprehensive risk assessment method, system and its storage medium of overloaded vehicle, it is related to intelligent traffic law enforcement field.The method first collects the multi-source data of vehicle when passing through monitoring area, including the weight data of at least two weighing sensors, vehicle speed and lateral offset.According to the confidence weight of each sensor, the weight data is weighted and fused to obtain the measured weight and overload weight;According to the speed and offset, the speed penalty factor and offset penalty factor are calculated respectively.The overload weight and two penalty factors are substituted into the comprehensive score model to obtain the quantitative comprehensive risk score S.By comparing S with the preset risk threshold, it is determined whether the vehicle has high-risk overload behavior, and the off-site electronic evidence containing complete data is automatically generated.The application changes the single "overload or not" judgment into a multi-dimensional risk assessment that integrates weight, speed and attitude, and realizes the quantification and refinement of law enforcement basis.