19 results about "Traffic violation" patented technology

Disclosed are systems and methods for detecting traffic violations using one or more mobile detection devices. Videos captured by one or more mobile detection devices can be processed on the mobile detection devices to extract data and information concerning a potential traffic violation involving a vehicle and a restricted road area. The mobile detection devices can transmit such data and information to a server configured to make a determination as to whether a traffic violation has occurred by comparing the data and information received from the mobile detection devices.

The application discloses a kind of man-machine collaborative traffic violation intelligent detection identification method, system.The method includes: through vehicle terminal continuous caching with space-time information video stream;Through voice recognition, driver instruction is received and event reference point T0 is marked;Based on T0, extract the historical video segment and metadata of preset time length and upload to cloud end by backtracking;Cloud end carries out analysis to video segment by multi-task deep neural network model, executes vehicle tracking, lane line and sign identification based on vision, violation behavior determination and license plate recognition, generates structured report;Report is returned to vehicle terminal, after driver confirmation or correction, in local, generate and store with legal force violation event archives with digital signature and trusted time stamp in combination.This application realizes the efficient cooperation of active trigger of driver and intelligent analysis of machine, evidence solidification, improves the convenience, accuracy and evidence credibility of traffic violation evidence.

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.

This system provides a vehicle driving safety comparison system that allows for a compelling comparison of the driving safety of elderly drivers and others. [Solution] In the vehicle driving safety comparison system 1, the first determination unit 4 determines whether there is a violation of traffic rules on a registered road X based on driving information, road location information, and traffic rules, and the calculation unit 5 calculates the first violation frequency of traffic rule violations determined on a single registered road X during a predetermined period for multiple sample vehicles Z driven by drivers within a predetermined age range, and the second violation frequency of traffic rule violations determined on the same registered road during the same predetermined period for target vehicles Y driven by drivers older than the predetermined age range. A vehicle driving safety comparison system characterized by having the following features.

The application belongs to the technical field of intelligent traffic, vehicle-road cooperation and traffic monitoring, and discloses a monitoring and cooperative management system based on intelligent identification of traffic violations, which comprises a multi-modal heterogeneous perception layer, an edge and cloud cooperative transmission layer, a dynamic game decision layer, a cross-domain cooperative disposal layer connected in sequence in communication, and an intelligent traceability and optimization layer in bidirectional communication with the dynamic game decision layer. By constructing the four-modal heterogeneous perception layer of space base, road base, vehicle-mounted and human base, multi-dimensional data cross verification is realized, solving the problem of single or binary perception blind area and high misjudgment rate in the prior art. By designing a dynamic game decision algorithm linked in real time with multi-modal fusion data, introducing a dynamic weight adjustment, scene correction and illegal hazard level coefficient calibration mechanism, the illegal level can be accurately distinguished, and different traffic scenes can be adapted, solving the problem that the existing algorithm cannot adapt to complex scenes and has low accuracy.

The present disclosure provides an AI-powered traffic control system (102) mounted on a vehicle (301) for autonomous monitoring and management of traffic violations and conditions. The system includes at least one AI-powered camera (201) to capture images or video, detect traffic violations, conditions, and unsafe driving behaviours using image recognition and machine learning algorithms; a speed detection device (202) to measure vehicle speed; and an adaptive light system (203) to deliver real-time visual feedback to surrounding drivers. A processor (501) analyses data from the camera (201) and speed detection device (202), controlling the adaptive light system (203) and communicating with external systems. Memory (502) stores data for reporting and post-incident analysis. A method for implementing the system includes initializing components, capturing data, analysing violations, providing feedback, and ensuring privacy protection. This system (102) enables decentralized traffic management, enhancing road safety and regulatory compliance in varied traffic environments.

This invention discloses an AI-powered BeiDou vehicle-road-cloud system and method for source control of vehicle violations, relating to the fields of traffic safety and vehicle-road-cloud integration technology. Currently, most traffic violations are handled post-incidentally, resulting in shortcomings such as insufficient source control (e.g., drunk driving, unlicensed driving, fatigued driving, inadequate screening of hazardous and prohibited items), data gaps across departments, and delayed early warnings. The nation's vigorous promotion of the strategies of a safe China, a strong transportation nation, national security governance, and vehicle-road-cloud integration urgently requires proactive and preemptive safety control technologies. This invention relies on AI large-scale models and BeiDou high-precision positioning, with hardware integrated and deployed in key areas of the vehicle. It enables driver facial recognition verification, identity verification, intelligent alcohol control, fatigue driving intervention, in-vehicle status perception, detection of drugs, dangerous goods, and explosives, multilingual sensitive word monitoring, biometric comparison of rear-seat occupants, and multi-dimensional risk assessment. Combined with vehicle-road-cloud collaborative interaction and black box full-process evidence storage, it connects with the public security system, enabling silent and unobtrusive reporting of abnormal risks and tiered, humane handling. It blocks traffic violations and public safety hazards at the source, deeply aligning with national security governance strategic needs, balancing road traffic management and national security prevention and control requirements, and is suitable for large-scale deployment and application of various commercial and social vehicles.

This invention discloses an AI-powered intelligent identification method for traffic violations based on big data analysis, comprising the following steps: acquiring historical behavior datasets, merging and performing data preprocessing to generate a sequence of violation events as input; constructing an event generation and judgment framework by calling a neural time-point process hybrid model to generate a set of mechanistic event intensities; constructing a dynamic responsibility allocation mechanism, performing weighted modulation processing to obtain modulated event intensities; performing state recursive updates to generate a violation risk state representation and performing state coupling updates; constructing a judgment-driven event generation mechanism, performing judgment-driven reweighting processing to generate judgment event generation results; performing a joint inference process to generate intelligent identification results for traffic violations; and performing feedback update processing on the event generation and judgment framework based on the intelligent identification results for traffic violations. This invention improves the stability, consistency, and interpretability of traffic violation identification.

1. Name of the product in this design: Traffic supplementary lighting. 2. Purpose of this design: For supplementary lighting in traffic violation detection. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key points: the front view.

This system provides a vehicle driving safety comparison system that allows for a compelling comparison of the driving safety of elderly drivers and others. [Solution] In the vehicle driving safety comparison system 1, the first determination unit 4 determines whether there is a violation of traffic rules on a registered road X based on driving information, road location information, and traffic rules, and the calculation unit 5 calculates the first violation frequency of traffic rule violations determined on a single registered road X during a predetermined period for multiple sample vehicles Z driven by drivers within a predetermined age range, and the second violation frequency of traffic rule violations determined on the same registered road during the same predetermined period for target vehicles Y driven by drivers older than the predetermined age range. A vehicle driving safety comparison system characterized by having the following features.

A driving assistance device according to an embodiment of the present disclosure is capable of: predicting whether a second vehicle traveling ahead of a first vehicle will commit a traffic violation, on the basis of travel information of the second vehicle and traffic-related information ahead of the second vehicle; if the second vehicle is predicted to commit a traffic violation, predicting the action of the second vehicle to avoid the traffic violation once the driver of the second vehicle notices the traffic violation; and performing travel control or notification control to prevent the first vehicle from colliding with the second vehicle, on the basis of travel information of the first vehicle, the travel information of the second vehicle, and the predicted action of the second vehicle.

The application provides a horn function triggering method, which comprises the following steps: detecting, via a touch detection device, a touch of an object on a first area and obtaining a touch detection result; judging whether the object touches the first area based on the touch detection result; detecting, via a first pressing detection device and a second pressing detection device, a pressing of the object on a panel and obtaining a first pressing detection result and a second pressing detection result; judging whether the object presses a second area based on the first pressing detection result and the second pressing detection result; and triggering a horn function if it is determined that the object does not touch the first area and presses the second area. The application can accurately prevent the horn function on the steering wheel control panel from being triggered by mistake without increasing hardware cost, thereby improving the control performance of the steering wheel control panel, avoiding potential traffic violation behaviors and driving safety hazards, improving the driving experience of users, and leaving more design space for the appearance modeling of the panel.

A system for the automated detection and management of traffic violations, comprising: a surveillance camera network with a multitude of cameras, each camera configured to record continuous video streams for monitoring vehicle movements and potential traffic violations, and processing the recorded video streams for license plate and traffic violation recognition; a license plate recognition module communicatively connected to the surveillance camera network and configured to receive the continuous video streams, the license plate recognition module further configured to extract and process license plate images from the video stream to accurately identify offending vehicles and to determine the vehicle registration data from the extracted license plate images;a machine learning processing unit communicatively connected to the surveillance camera network, configured to receive the continuous video streams, wherein the machine learning processing unit is further configured to analyze the video streams using computer vision algorithms and detect traffic violations such as speeding, running red lights, illegal parking and accidents; a real-time data processing module configured to: receive violation data from the machine learning processing unit and vehicle identification data from the license plate recognition module, correlate the received data with learned violation patterns, generate violation records containing timestamps, location and vehicle details, and transmit the violation records to law enforcement agencies and users;a user notification and resolution interface configured to send automated notifications of violations to vehicle owners via SMS, email, or mobile application, the user notification and resolution interface further configured to provide an interface for reviewing evidence of violations, contesting violations, and settling penalties; an emergency services integration module configured to detect accidents and, upon detection, automatically notify nearby hospitals and police stations; and a traffic management integration interface that interacts with existing traffic infrastructure and APIs to provide parking advice, manage violation workflows, and support community-reported incidents.

This application provides a method and apparatus for obtaining traffic violation information. The method includes: obtaining a first input from a user, the first input being used to instruct a vehicle to obtain traffic violation information; in response to obtaining the first input, obtaining first data collected by a camera device outside the vehicle's cabin and second data collected by at least one radar; generating a traffic violation report text based on the first and second data, the traffic violation report text including multiple pieces of traffic violation information, the multiple pieces of traffic violation information including at least one of the following: violation time, violation location, license plate number, license plate color, and violation type; and controlling a prompting device of the vehicle to prompt the user with the traffic violation report text. The method for obtaining traffic violation information provided by this application can improve the accuracy of obtaining traffic violation information and improve the efficiency of reporting traffic violations, which is beneficial to improving the user experience.

The application provides a public security work system based on real person authentication technology and an implementation method, and belongs to the field of internet information technology.The system specifically comprises three function support modules: a background management research and judgment module, a real person authentication module and a data interface module;three business handling modules: a traffic violation handling module, a population flow management module and a real name clue reporting module;the background management research and judgment module serves as the core of the system, performs data interaction and scheduling with the three business handling modules through the data interface module, and is responsible for data statistical analysis and task distribution;the user real person authentication module provides identity verification services for the business handling module, and ensures that the identity information of the operator is reliable;the system and the implementation method can solve the problems existing in current public security work, such as traffic violation behavior deduction, untimely population information update and online reporting uncertainty.

This disclosure provides an intelligent integrated panoramic monitoring terminal and data processing method for combating violations, belonging to the field of power system technology. The method includes: acquiring multi-source heterogeneous violation alarm data and preprocessing it; evaluating the credibility of the preprocessed alarm data based on multi-dimensional feature extraction results; dynamically allocating credibility weights for each violation event based on the credibility evaluation results; and prioritizing and filtering the violation events according to the credibility weights. The solution of this disclosure can dynamically allocate credibility weights for violation events based on multi-source heterogeneous violation alarm data in the power industry to solve the problem of alarm overload caused by high low-confidence false alarm rates.

This invention discloses a method and system for correlation analysis of traffic violation behavior by rail transit drivers based on LLM (Local Language Model), belonging to the field of traffic violation analysis technology. The method includes: inputting the original text containing driver violation content into a large language model; analyzing and standardizing it using preset prompt words to obtain standardized text; converting it into a high-dimensional vector; calculating the cosine similarity between the standardized text and the standard clause vector; selecting a candidate set and judging it; if the candidate set is not empty, proceeding to the next step; if the candidate set is empty, setting an adaptive degradation and recall strategy; concatenating the original text, candidate set, zero-sample examples, and task instructions, inputting them into the large language model, and outputting the analysis results. If the relevance score is higher than a preset score, returning the matching violation standard; otherwise, returning the fallback standard. This application, through rewriting and rearranging, enables even non-standard descriptions to accurately find corresponding regulatory clauses, with an accuracy rate far exceeding traditional keyword search.