60 results about "Road accident" patented technology

The invention discloses a smart city traffic resource optimal configuration method, a platform and a storage medium, and relates to the technical field of traffic optimization. When a road accident is detected, accident information is collected, and a traffic accident position and traffic accident characteristics are obtained; time consumption prediction is carried out according to the traffic accident characteristics, and traffic control duration is obtained; calling real-time traffic data from an intelligent traffic system to obtain associated road data; executing multi-thread traffic flow back-stepping analysis to obtain associated traffic flow prediction information; carrying out shunting performance evaluation; and dynamically updating the signal lamp configuration of the plurality of shunting candidate roads by taking the associated traffic flow prediction information as a constraint. According to the invention, the technical problems of aggravation of traffic jam and low emergency management efficiency caused by lack of scientificity and dynamic adaptability of shunting planning and lagging of signal lamp regulation in a traffic accident scene in the prior art are solved, and the technical effects of optimizing traffic resource configuration, relieving traffic jam and improving traffic emergency management efficiency are achieved.

The invention discloses a mountain road traffic accident high-risk point space-time evolution analysis method based on improved kernel density estimation, and the method comprises the steps: constructing a kernel density estimation model considering the accident severity based on a conventional kernel density estimation formula in combination with a Gaussian kernel function and a bandwidth parameter, and enabling the kernel density estimation model to be used for discriminating an accident high-risk region; then, through a Getis-Ord Gi * hotspot analysis method, an accident space distribution rule and an aggregation effect are quantified; on the basis, the time-space evolution rule of the high-risk area of the mountainous area accident is analyzed by using hotspot clustering and rasterization. The method can deeply analyze heterogeneity characteristics of high-risk road sections of mountain road accidents, reveal distribution characteristics and dynamic change rules of traffic accidents in time and space, and provide decision basis for formulating differentiated mountain road accident prevention and control strategies.

The invention relates to a vehicle control method, a controller and a vehicle, and relates to the technical field of vehicles, and the method comprises the steps that it is determined that a transverse stability fault of the vehicle occurs, and the transverse stability fault comprises tire burst and / or wheel control failure; acquiring driving state information of the vehicle; and according to the driving state information, steering control is at least carried out on rear wheels of the vehicle so as to avoid transverse deviation of the vehicle. By using the vehicle control method provided by the invention, the transverse stability and the path following capability of the vehicle can be improved when the wheels break down, so that the driving safety of the vehicle is improved, and the possibility of road accidents is reduced.

This utility model is applicable to a device for preventing vehicle accidents when an external object enters the space under the pedal unit, more specifically the gap between the pedal lever and the floor while the vehicle is moving, thereby preventing fatal road accidents. The device comprises at least one cutting element created to pierce a large external object and is in the form of a shaped cover plate, which is a semicircle with an outer and inner edge, the outer edge of which is in the form of the said at least one cutting element, and the inner edge is made for mounting to the pedal lever of the vehicle. The device has a simple design, is effective for piercing / cutting an external object that has entered the space under the control pedal unit, is easy to install on the pedal lever and prevents accidents.

The invention discloses a road accident and illegal parking identification early warning method and system based on intelligent traffic, and relates to the technical field of intelligent traffic, and the method comprises the steps: analyzing a preprocessed road monitoring video stream in real time, and sensing multi-dimensional accident features and multi-modal vehicle state features; constructing a parallel accident identification model and an illegal parking detection model, constructing an adaptive threshold value based on camera parameters and environment features, and identifying an accident scene and an illegal parking scene by using multi-dimensional accident features and multi-modal vehicle state features in combination with the adaptive threshold value; the influence range of the accident scene and the illegal parking scene is estimated, and a multi-level early warning response mechanism is combined to be linked with a sound-light alarm, navigation pushing and rescue platform. According to the invention, through combination of intelligent accident and illegal parking identification and a multistage early warning linkage mechanism, a more efficient and more accurate highway accident prevention and control system is constructed, and travel safety is guaranteed.

The invention belongs to the technical field of road traffic, and particularly relates to a road traffic accident intelligent reproduction method based on automatic Pc-Crash simulation and an MLP algorithm. Comprising the following steps: 1, establishing a simulation model template in Pc-Crash simulation software according to road traffic accident scene information; 2, a simulation test is designed for unconfirmed parameters on the road accident site, and a simulation data set is obtained; 3, constructing, optimizing and training a multi-layer perceptron neural network model; 4, taking the stopping position of an accident participant of the road traffic accident or the tire friction trace deviation minimization as a core, constructing a target function, predicting an accident result by adopting an MLP neural network model, and obtaining an optimal solution of an unconfirmed parameter by using a multi-starting-point search global optimization algorithm; a simulation result is compared with actual exploration data, and the accuracy of the optimal solution is verified; intelligent reproduction of the whole process of a road traffic accident is realized, and important technical support is provided for responsibility determination and compensation processing during traffic accident processing.

This invention belongs to the field of on-street parking within intelligent parking systems and relates to an on-street parking reservation management system based on orderliness. The system comprises an information acquisition module, a parking reservation module, and an information feedback module. First, a parking orderliness model is designed and its feasibility verified. Second, the parking orderliness model is incorporated into the parking reservation module. The information acquisition module then acquires on-street parking system information, which is then used to determine the optimal parking space through the parking reservation module. Finally, the information feedback module provides feedback to departing vehicles. The technical solution employed in this invention can reduce on-street cruising time spent searching for parking spaces, improve parking space utilization, and, to a certain extent, reduce traffic congestion and road accidents caused by searching for parking spaces.

The invention relates to an accident identification model training method of an intelligent traffic monitoring system, multifunctional intelligent sensing equipment in the intelligent traffic monitoring system adopts a three-axis acceleration sensor to monitor expressway vibration information, and the collected data is uploaded to a cloud data server for road accident identification model training. Through data enhancement, the problems of insufficient training sample data and non-representativeness of the sample data when a road accident identification model is trained due to the fact that data sets of accidents are few and collected data sets are concentrated are solved, and accident sample data enhancement is performed by adopting a variational auto-encoder, so that the accuracy of road accident identification is improved. And the purpose of rapidly training an iterative traffic monitoring system accident identification model is achieved.

The application discloses a CAV speed guiding system based on deep reinforcement learning, which comprises the following steps: a vehicle-mounted system detects vehicle driving data and vehicle state information data; a roadside monitoring system detects driving environment, vehicle information data on different roads and pedestrian information data, matches the pedestrian and vehicle information data with a lane-level road link to obtain a data packet; a vehicle-road cooperation cloud computing center processes and stores the received data, and sends the processed data to a mobile edge computing center; the mobile edge computing center comprehensively evaluates road accident risks, constructs a Markov decision process and a speed guiding model of a multi-target additional reward function, calculates an optimal guiding speed of a CAV by using the multi-target additional reward function, and sends the optimal guiding speed of the CAV to the vehicle-mounted system. The communication delay problem is solved; a multi-target environment reward mechanism is comprehensively integrated, and the guiding speed of the CAV is improved in terms of traffic safety, stability and passing efficiency.

The utility model discloses an equipment fire fighting truck for handling various dangerous chemical tanker road accidents, which comprises a fire fighting truck body, a movable carriage is arranged on the fire fighting truck body, a pull arm hook is arranged between the fire fighting truck body and the movable carriage, and a plurality of placing bins are arranged in the movable carriage. The movable carriage is moved to the ground through the pull arm hook, the movable carriage can incline in the moving process, the limiting assembly in the movable carriage can limit the bearing frame in the containing bin, and the device is prevented from moving and inclining; the electric carrying vehicle can be taken out from the interior of the containing bin by moving the getting-off slope plate on the side edge of the compartment, and devices and instruments in the corresponding containing bin can be taken out through the electric carrying vehicle according to dangerous case requirements, so that other functional vehicles can be quickly, effectively and independently handled or assisted in handling various dangerous chemical tank truck road accidents.

The present invention relates to the technical field of traffic control systems. Specifically, it relates to a road traffic safety control system and a control method. It includes a camera device, a first reminder device, and a second reminder device; the camera device is used to take pictures of vehicles on the road to obtain the speed of the vehicles; when the speed of the vehicle is greater than a preset value, the first reminder device projects an overspeed warning reminder onto the windshield of the corresponding vehicle, or projects it at a preset distance in front of the vehicle and moves with the vehicle; in the case that the vehicle still does not decelerate, the second reminder device projects a red guiding line to guide the vehicle into an automatic deceleration lane, and an auxiliary deceleration device is arranged on the automatic deceleration lane. It can automatically guide the vehicle to the automatic deceleration lane, reducing the incidence of road accidents and improving the safety of drivers.

This application provides a vehicle detection method for foggy road accident scenes using a fusion backbone and hypergraph computing approach, relating to the field of image processing technology. The method acquires target traffic accident images from traffic accident video data on foggy roads according to a set image sampling frequency. Then, a backbone network extracts original features, eliminates fog interference, and extracts semantic features from the target traffic accident images to obtain original features, fog-dissipated features, and multiple semantic features. Next, a neck network performs cross-level feature fusion on the original features, fog-dissipated features, and multiple semantic features to obtain a first fused feature. The first fused feature is then enhanced and subjected to multi-scale feature fusion to obtain multiple second fused features. Finally, the multiple second fused features are input into a prediction network to obtain multiple vehicle detection results for the foggy road accident scene. This improves the accuracy and real-time performance of vehicle detection in foggy road accident scenes.

The invention provides a big data analysis-based dynamic speed limit control system for a road section with high occurrence of road accidents, and belongs to the technical field of road control. According to the invention, the video camera is used for collecting the vehicle flow data, the vehicle flow data of the two sections of the road section are compared and analyzed, the emergency in the road section area can be judged at low cost, and the situation of the emergency can be quickly judged in time in combination with the tracking processing of the data acquisition module. The cloud computing control platform is overlapped with the ramp control system to dynamically adjust the speed limit in the road section area, and the vehicle flow entering the high-incidence road section is synchronously limited, so that the vehicle flow pressure of the high-incidence road section is relieved from the source, the secondary accident phenomenon is reduced in an auxiliary manner, the active defense for the road traffic accident is enhanced, and the safety of the road traffic accident is improved. The dynamic adjustment effect of the system in the using process is effectively improved, and the road safety is greatly improved.

Systems and methods are provided for determining a start time and severity value associated with the roadway incident to provide traffic management instructions. The system may, for example, receive sensor data from a vehicle at a location associated with a roadway incident. The system can determine a traffic flow profile for the location, where the traffic flow profile identifies characteristics of the roadway incident that match characteristics of the traffic flow profile. Based on the traffic flow profile, the system may determine a severity value for the roadway incident and calculate a start time of the roadway incident. The start time may correspond with the traffic flow profile for the location in view of the severity value.

Provided are a method and apparatus for generating a safety control signal of a road. The method includes inputting road state information for a first time point, including a safety control signal for the first time point and dynamic information for the first time point obtained from a video of a road, to a prediction model, inferring dangerous situation prediction information for a second time point after the first time point, by using the prediction model, and generating a safety control signal notifying a risk of accident on the road for the second time point, based on the inferred dangerous situation prediction information, wherein the prediction model is trained by using a loss function configured by dangerous situation prediction information inferred for a specific time point from road state information before the specific time point, and dangerous situation measurement information calculated from road state information for the specific time point.

The invention is suitable for the technical field of road traffic safety and intelligent control, and provides a UWB positioning-based road accident automatic defense organizing system and a UWB positioning-based road accident automatic defense organizing method. In the embodiment, for an area where a road accident occurs, the position of the equipment is determined through a UWB label on the defense organizing equipment and UWB base stations installed around the defense organizing equipment, then the defense organizing final position is determined based on the position and the occurrence position of the road accident, and then the defense organizing final position is determined according to the position of the defense organizing equipment. The method comprises the following steps: determining an action path of a defense organizing device according to a defense organizing target position and a barrier position between the defense organizing target position and the defense organizing target position, determining a defense organizing point on the action path according to the number of the defense organizing devices participating in defense organizing, finally controlling each defense organizing device to organize defense at the defense organizing point, and finally indicating the defense organizing devices to carry out early warning. According to the embodiment of the invention, centimeter-level positioning precision can be realized through UWB technology deployment, the problem of insufficient positioning precision in the prior art is solved, and rapid, safe and accurate deployment of an accident site is realized, so that the risk of a secondary accident is reduced.

The invention belongs to the field of intelligent traffic, and provides a highway accident detection method, system, medium and equipment, and the method comprises the steps: carrying out the feature extraction of 4D millimeter wave radar point cloud data and image data, and obtaining a multi-scale image feature and a multi-scale local point cloud feature; performing Ro I feature extraction on the multi-scale local point cloud features and the multi-scale image features by adopting a hierarchical Ro I query strategy and a cross attention mechanism to obtain Ro I image features of each scale; performing feature fusion and global feature extraction on the multi-scale local point cloud features and all-scale Ro I image features to obtain a 3D target detection frame containing speed information; according to the method provided by the invention, the robustness of the system in all weather is enhanced by using the 4D radar, the accident detection accuracy of the system on the high-speed lane in extreme weather is improved, and the real-time efficiency of the system can also be ensured.

The utility model relates to the field of road emergency equipment, in particular to a wrecker for cleaning road accident residual parts, which comprises a vehicle body, a swing arm unit and a wrecker box unit, the swing arm unit is provided with a long shaft rotatably connected to the bottom of the vehicle body and two groups of support arms of the swing arm unit fixedly connected to two ends of the long shaft, and the swing arm unit is provided with a swing arm. The supporting arm can swing on the periphery of the vehicle body; the obstacle clearing box unit is provided with an open box hopper, a door plate capable of being opened and closed is arranged on the open box hopper, an extrusion assembly is arranged at the other end away from the open box hopper, the box hopper is further provided with an overturning driving assembly, and the box hopper is connected to the suspension ends of the supporting arms of the two sets of swing arm units, can swing along with the supporting arms and can automatically overturn. According to the wrecker designed by the utility model, the supporting arm swings back and forth and the box hopper turns over, so that the wrecker can be used for collecting residual parts and automatically unloading the residual parts into the bucket, and the extrusion component can be used for compacting the light and loose residual parts, so that the wrecker efficiency can be improved, and the wrecker time can be shortened.

To provide a dangerous area identification device, map data, and a dangerous area identification method and program for effectively identifying dangerous areas.SOLUTION: In a navigation device 10, a dangerous area identification unit 34 identifies dangerous areas of popping out based on past information showing situations of the past pop-out accidents acquired by a past information acquisition unit 24 and surrounding information showing situations around vehicles acquired by a surrounding information acquisition unit 32. Here, the past information is configured to include information on surrounding facility identification information (information relating to identified feature) used for identifying dangerous areas of popping out and information relating to pop-out target objects. Therefore, a pop-out dangerous area identification unit 34 can identify the pop-out dangerous areas caused by the feature (facility) in a pop-out accident. Therefore, the navigation device 10 can effectively identify the pop-out dangerous areas.SELECTED DRAWING: Figure 4

A road accident management system (100) and method are disclosed that detects accidents or burglary events and provides emergency assistance. A detection module (202) detects incidents occurring on the road. A sensing module (204) senses the impact of the detected incident and generates an activation signal. A capturing module (206) captures one or more images of the incident based on the activation signal and a reset instruction provided by a user. A location identification module (208) identifies the location of the incident based on the position of the capturing module (206). A switching module (210) activates the lighting devices (103) based on the sensed impact of the incident and the identified location of the incident. A communication module transmits the identified location of the incident to a service station (108). The service station (108) instantly transmits emergency assistance to the identified location of the incident.

The invention relates to the technical field of data processing, and discloses a guardrail state monitoring system and method based on multimode communication, and the system comprises the steps: receiving a guardrail node state sent by each guardrail state monitoring terminal through a guardrail state monitoring gateway, generating road accident information, and evaluating the grade of a road accident; the road accident level and the endurance electric quantity value in the guardrail state information are sent to a guardrail state monitoring cloud, and the road accident level and the endurance electric quantity value in the guardrail state information are converged into the topological graph according to the road historical traffic flow of the target area and the maintenance time of the current guardrail maintenance period; and controlling the corresponding guardrail state monitoring terminal to execute the display of road traffic warning information on the basis of the principle of meeting the traffic flow descending proportion, the guardrail maintenance cycle endurance requirement and the residual endurance electric quantity value uniformity. Therefore, by ensuring that the endurance of the guardrail state monitoring terminal meets the maintenance period requirement, the self-relieving capability of urban roads facing traffic accidents is improved, and the contradiction between the traffic guidance function operation and the endurance guarantee is solved.

The application provides an automatic driving accident prevention simulation scene generation technology based on swarm intelligence, which can realize random sampling in a road accident area, design an algorithm for splitting a lane to establish a KD tree, effectively reduce the time for searching a nearest neighbor lane, quickly determine the direction of a generated accident vehicle, and greatly reduce the search time compared with a method without optimization. Then, the constraint relationship of participants in the automatic driving accident prevention simulation scene is analyzed, an evaluation function is designed, a lane trajectory and a normal direction are searched along a lane in the road accident area based on a firework algorithm, and a suitable vehicle generation area is gradually approached. A sensor object is created through an interface provided by a Carla simulator, and an accident image is generated according to simulation data received by the sensor object. Compared with an existing scheme, the application can effectively improve the speed of automatic driving accident prevention simulation scene generation.

1. Name of the Design Product: Accident Prompt Area of the Navigation Graphical User Interface of an Electronic Device. 2. Use of the Design Product: An electronic device. 3. Design Key Points of the Design Product: Lies in the partial graphical user interface in the electronic device for which protection is requested. 4. Picture or Photograph that Best Illustrates the Design Key Points: The front view of Design 1. 5. Design 1 is designated as the basic design. 6. Use of the Graphical User Interface: The graphical user interface is used for navigation. The partial graphical user interface for which protection is requested is used to display road accidents and related information. In response to detecting that the distance between the vehicle and the accident occurrence point is less than a preset distance, the graphical user interface changes from the front view of Design 1 to the first change state diagram of Design 1 to prominently display accident prompt information; in response to the user touching or clicking the "View Details" button, the graphical user interface changes from the first change state diagram of Design 1 to the second change state diagram of Design 1 to display the content of the details page of the accident. In response to the user touching or clicking the "View Details" button, the graphical user interface changes from the front view of Design 2 to the change state diagram of Design 2 to display the content of the details page of the accident. In response to the user touching or clicking the "View Details" button, the graphical user interface changes from the front view of Design 3 to the change state diagram of Design 3 to display the content of the details page of the accident. In response to detecting that the distance between the vehicle and the accident occurrence point is less than a preset distance, the graphical user interface changes from the front view of Design 4 to the first change state diagram of Design 4 to prominently display accident prompt information; in response to the user touching or clicking the "View Details" button, the graphical user interface changes from the first change state diagram of Design 4 to the second change state diagram of Design 4 to display the content of the details page of the accident. In response to the user touching or clicking the "View Details" button, the graphical user interface changes from the front view of Design 5 to the change state diagram of Design 5 to display the content of the details page of the accident. In response to the user touching or clicking the "View Details" button, the graphical user interface changes from the front view of Design 6 to the change state diagram of Design 6 to display the content of the details page of the accident. 7. Other Circumstances Requiring Explanation: Other Explanation: The parts of the graphical user interface shown by dashed lines in the views of Design 1 to Design 6 do not constitute the parts protected by this design.

The invention provides a road accident key cause identification method based on high-dimensional small sample data, and solves the problems of low prediction precision, insufficient generalization ability and inaccurate key cause identification when an existing accident analysis model processes the high-dimensional small sample data. The method mainly comprises the following steps: 1) providing a feature combination algorithm based on logic addition and logic subtraction aiming at small sample data features so as to enhance the interpretability of data; 2) a key accident cause identification algorithm is developed by combining a LightGBM method and a Shapley value method; and 3) integrating a feature combination algorithm and an accident cause recognition algorithm into a unified framework, and constructing a key cause recognition system suitable for high-dimensional small sample data. Through actual accident data verification, the explanatory power and model prediction performance of high-dimensional small sample accident data are remarkably improved, the accident key causes can be effectively identified, and a scientific basis is provided for road accident analysis.

Techniques are disclosed to determine driver scoring that consider road accident proneness scores in driver score computations. The road accident proneness scores may be based on one or more alerts. Further, road types of roads may be determined based on alerts. The determination of the road type may use a machine learning model. In contrast to the conventional approaches, the use of road accident proneness scores in the computation of driver scores allows for the consideration of accident proneness of the road to improve upon conventional scoring techniques. Further, map data and generated maps may be improved based on determined road types.

The invention belongs to the technical field of intelligent network connection automobile driving control, and discloses an intelligent network connection automobile formation driving control method, which comprises the following steps: acquiring position information, passing point information and terminal point information of each automobile; obtaining a vehicle formation according to the position information, the passing point information and the terminal point information of each vehicle; the vehicle formation is processed according to the vehicle formation logic, the vehicle logic, the position information, the passing point information and the terminal point information, and an updated driving route is obtained; obtaining a route completion action instruction according to the updated driving route and sending the route completion action instruction to each vehicle; and each vehicle receives and executes the route completion action instruction to complete vehicle formation driving. According to the invention, each intelligent network connection vehicle can orderly run on the road, so that the accident rate of the road is reduced, and the traffic efficiency of the road is improved.

The application discloses a road accident and illegal parking identification and early warning method and system based on intelligent traffic, relates to the technical field of intelligent traffic, and comprises the following steps: analyzing a preprocessed road monitoring video stream in real time, perceiving multi-dimensional accident features and multi-modal vehicle state features; constructing a parallel accident identification model and an illegal parking detection model, constructing an adaptive threshold based on camera parameters and environmental features, identifying accident scenes and illegal parking scenes by using the multi-dimensional accident features and the multi-modal vehicle state features in combination with the adaptive threshold; estimating the influence range of the accident scenes and the illegal parking scenes, and combining a multi-level early warning response mechanism to link sound and light alarms, navigation push and a rescue platform. The application constructs a more efficient and more accurate expressway accident prevention and control system by combining intelligent accident and illegal parking identification with a multi-level early warning linkage mechanism, and guarantees travel safety.

The invention provides a road accident risk black spot generation method, equipment, a device and electronic equipment, and the method comprises the steps: obtaining a plurality of pieces of historical accident data, and determining time-space parameters in each piece of historical accident data, the time-space parameters comprising accident coordinates; taking each piece of historical accident data as a reference point, performing clustering with other historical accident data according to a set aggregation distance, and determining a successfully clustered core reference point according to a set minimum aggregation number; based on the clustering result of each core reference point, determining a clustering result belonging to the accident black spots; and determining the area range of the accident black spots based on the accident coordinates in the historical accident data in the accident black spots. According to the method, detailed distribution and statistics of accident risks are finally obtained through multi-dimension statistical analysis of accident black spot generation, region splicing, high-incidence time periods and the like, and prediction and basis are provided for subsequent command decision and post deployment.

The application provides a highway maintenance equipment vehicle anti-collision system, belonging to the anti-collision technical field, which comprises a vehicle-mounted end, a vehicle position detection end and a highway maintenance equipment vehicle end, the vehicle-mounted end is wirelessly connected with the vehicle position detection end, the vehicle position detection end is wirelessly connected with the highway maintenance equipment vehicle end, and the vehicle-mounted end is used for sending an addressing signal in real time for the vehicle position detection end to detect.The application can effectively avoid the collision of the vehicle with the cone barrel or the highway maintenance equipment vehicle, reduce the occurrence of road accidents, and effectively avoid the personnel injury caused by the accident, while the staff on the highway maintenance equipment vehicle can be informed to make an avoidance notification in time when the vehicle information is not avoided in time, and the real-time detection of the traffic flow information at the rear can timely make an adjustment when congestion or preparation for congestion occurs, so as to avoid the influence of the highway maintenance equipment vehicle on the road traffic.