36 results about "Road accident" patented technology

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.

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 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.

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 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.

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 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.

The invention discloses a road accident prediction method, system and device under an air-ground network based on RBF-DNN approximation. The method comprises the following steps: step 1, obtaining road data through a mobile sensor and a fixed sensor of the network and processing the road data; step 2, according to the air-ground networking system model and a possible unknown fault type model, in combination with a tracking error function and a robust adaptive fault-tolerant sliding mode function, obtaining a dynamic system model with an internal actuator unknown fault; step 3, according to the obtained dynamic system model, designing an adaptive law with projection and sigma-correction and a non-Zeno event triggering mechanism, and constructing a DNN closed-loop control air-ground networking prediction control model based on RBF; 4, after the obtained prediction control model is trained, road accident prediction is carried out on the obtained road real-time data; the problem that communication link defects still exist in an existing prediction technology in a highway sudden dangerous case scene is solved.

The invention discloses a device and method for improving road accident liability judgment based on a vehicle-mounted traveling data recorder, and belongs to the technical field of computer algorithms, the device comprises a data acquisition module, a data storage module, a data processing module and a cloud platform module, the data acquisition module is integrated in the vehicle-mounted traveling data recorder, and the data storage module is integrated in the cloud platform module. The data acquisition module can acquire key data; the data storage module and the data processing module are respectively connected with the cloud platform; and the data acquisition module is connected to a front-end interface of the cloud platform module by adopting LTE (Long Term Evolution). The method has the advantages that 1, high-efficiency accident processing: through automatic data processing and analysis, the accident condition is quickly responded, and a real-time report is provided; 2, accurate responsibility judgment: combining historical records and real-time data, improving the accuracy of responsibility judgment and reducing disputes; and 3, intelligent traffic management: data support is provided for a traffic management department, traffic management measures are optimized, and the accident rate is reduced.

Vehicle-to-Everything (V2X) safety messages are generated automatically using multi-modal environmental data from infrastructure sensors (e.g. roadside infrastructure-mounted cameras, radar and lidar)

This invention discloses a path planning method integrating edge computing and anomaly detection, comprising: constructing a road network triplet containing intersection information, edge server information, and distance weights between intersections; establishing a road accident detection model including a spatiotemporal generator and a discriminator; training the model using historical traffic data and the road network; generating a set of reachable paths based on the road network using the KSP algorithm; performing anomaly detection using the trained model combined with current real traffic data to exclude paths containing abnormal road segments, thereby obtaining a set of passable paths; extracting edge server information of passable paths using the road network triplet, evaluating the edge computing capabilities of the paths, and selecting the path with the strongest edge computing capabilities as the optimal path. This method can avoid accident or congested road segments in dynamic traffic environments, fully utilize edge computing resources, reduce task latency, and improve the accuracy and timeliness of path planning.

The invention discloses a bracelet and vehicle combined early warning method and device, a vehicle, a medium and a product. Under the condition that the vehicle is started, automatically detecting a target bracelet in a driving position association range, identifying a current driver in combination with the target bracelet, and synchronizing corresponding target vehicle account information; safety early warning related information is obtained, wherein the safety early warning related information at least comprises accident monitoring information of the vehicle and the road in front of the vehicle and driving state information of a current driver; determining a target early warning object, a target early warning mode and target early warning intensity based on the safety early warning related information and the target vehicle account information; wherein the target early warning object is a target bracelet or all bracelets bound with the vehicle; and based on the target early-warning mode and the target early-warning intensity, carrying out multi-modal early-warning notification in linkage with the target early-warning object. Multi-mode combined early warning is carried out through the vehicle and the target bracelet or all bound bracelets, so that the combined application of the bracelets and the vehicle is enriched, and the driving safety is improved.

The utility model discloses a long-distance visual remote control mobile police warning device for highway road accidents, which comprises a trolley end and a mobile phone end, and the trolley end comprises a master control trolley, a vehicle-mounted mobile phone, a network control remote control trolley module, a camera module and a warning module; the network control remote control car module is used for controlling the driving of the main control car; the camera module is connected with the network-controlled remote control car module, and the camera module is used for shooting the road condition around the master control car in real time; the warning module is used for voice and visual warning of road accidents, and the vehicle-mounted mobile phone is used for providing a wireless hotspot network. The utility model provides a long-distance visual remote-control mobile police warning device for highway road accidents, which can reduce the exposure of personnel in dangerous areas of road accidents through remote control and can provide more effective warning. Secondary accidents are reduced, and rescue efficiency and safety are improved.

The application provides a real-time road safety evaluation method based on vibration sensing of a driving vehicle, a medium and equipment, first, the road to be monitored is divided into regions according to a specified size, and the road to be monitored is divided into intervals according to region attribution and road type; then a neural network regression model is established, which is used for predicting vibration difference values according to road type, temperature data, weather conditions and road surface obstacles; finally, the vibration sensing values generated by the automobile in the driving process are compared with the historical standard vibration sensing values of the automobile after a series of standardization treatments, to help judge whether abnormal conditions such as cracks, depressions and changes in the structure below the road occur. The application can effectively reduce the cost of artificial detection, discover risks in time, take countermeasures and avoid the occurrence of road accidents.

The invention discloses a vehicle-mounted emergency power supply device of an anti-collision buffer vehicle, and belongs to the technical field of electric energy storage emergency power supply, the vehicle-mounted emergency power supply device comprises a shell, the two sides of the shell are fixedly connected with mounting pieces, and the two ends in the shell are provided with mounting mechanisms. By arranging the arc-shaped guide plate and the arc-shaped pressing plate, the battery body can be guided to be positioned during installation, the battery body is prevented from being damaged by rigid collision, the linkage structure is arranged between the supporting frame and the arc-shaped guide plate, the arc-shaped guide plate and the arc-shaped pressing plate can be turned inwards while the battery body is placed in, on one hand, the cover plate can be conveniently installed, and on the other hand, the battery body is prevented from being damaged. And on the other hand, the curved surface structures of the arc-shaped guide plate and the arc-shaped pressing plate can reserve a certain ventilation and heat dissipation space for the upper part of the battery body, and the anti-collision box body can absorb the impact force of vehicle collision, reduce the risk of battery electrolyte leakage and realize zero interruption of power supply in emergency rescue under the high-vibration working condition (such as rear vehicle impact) of a road accident site.

The invention discloses a path planning method integrating edge calculation and anomaly detection, which comprises the following steps: constructing a road network triple comprising intersection information, edge server information and an inter-intersection distance weight, and establishing a road accident detection model comprising a space-time generator and a discriminator; training a model by using historical traffic data and a road network; generating a reachable path set by adopting a KSP algorithm based on the road network; performing anomaly detection through the trained model in combination with current real traffic data, and excluding paths containing abnormal road sections to obtain a passable path set; edge server information of passable paths is extracted in combination with a road network triple, the edge computing power of the paths is evaluated, and the path with the strongest edge computing power is selected as the optimal path. According to the method, accidents or congested road sections can be avoided in a dynamic traffic environment, edge computing resources are fully utilized, task delay is reduced, and the accuracy and timeliness of path planning are improved.

The present disclosure relates to methods and systems for automated road incident detection using vehicle sensor data to detect road incidents in real time. The vehicle sensor data is provided from sensors on vehicles on the road segment. The methods and systems update a map with the detected road incidents in real time of detecting the road incident, resulting in updated maps with the road incident information and updated traffic flow information on the maps.

The invention discloses an emergency early warning light control system based on deep learning, and the system comprises a data sensing module which is used for collecting visual features, radar features and thermal image features and carrying out the preprocessing; the deep learning analysis module is used for generating an anomaly score based on a feature adaptive weight LOF, and outputting an accident probability and an accident position through feature channel attention and improved DeepFM; the intelligent decision and control module is used for generating an early warning light control instruction according to the accident probability and the accident position; the communication and coordination module is used for transmitting the control instruction to roadside early warning light equipment; the early warning light execution module is used for switching a red early warning mode, a yellow warning mode or a normal light mode according to the control instruction; and the monitoring and operation and maintenance module is used for collecting the light operation state and abnormal information and executing maintenance processing. According to the invention, efficient cooperation of road accident real-time identification and light linkage early warning is realized, and the accident response speed and the driving safety level are improved.

The invention discloses a high-value traffic scene image screening method and device based on null-space features. The method comprises the following steps: mining a null space of a marked traffic scene image feature matrix, depicting unlearned feature dimensions of a model, quantifying the innovation of an unmarked sample in an unlearned feature space, and selecting a key image set capable of most effectively improving the model performance in combination with a coverage index. The method can explicitly describe the learned space and the unlearned space of the model, breaks through the limitation that traditional active learning depends on prediction uncertainty or sample surface difference, and enables the sample selection process to better fit the real learning state of the model. The method can be used for efficiently excavating images of key events such as rain and fog weather, road accidents, obstacle falling and low visibility at night.

The application discloses a kind of expressway confusing event discrimination method based on radar trajectory data, collect the driving trajectory of each car and the position information of real-time vehicle on current road surface, judge whether vehicle is stopped driving, stop driving vehicle is stored in set, there is vehicle stop driving, the number of vehicle around stop driving vehicle is counted, if it meets car many constraint condition, then continue to judge the average speed of surrounding vehicle, whether it is congestion state is judged according to speed, enter step 4;If it does not meet car many constraint condition, enter step 5;Using the way of deceleration grading, improve the distinction of each event;Multi-dimensional analysis and discrimination mode is used to each event, such as traffic flow, deceleration, distance, parking time, deceleration time, heading angle, pedestrian and other factors, using hierarchical analysis method, more comprehensive and meticulous discrimination congestion, car accident, car road accident, illegal parking, realize the purpose of low cost, high reliability, high precision, all-weather, full coverage discrimination confusing event.

The utility model provides a highway accident temporary warning device which comprises a base and a temporary warning indicator, the temporary warning indicator is detachably connected with the base, and the base is fixed to a set position beside a highway. The temporary warning indicator comprises a warning indicator shell and an active warning unit arranged in the warning indicator shell; the active warning unit comprises a warning lamp LED, a lithium battery, a lithium battery charging circuit and a lithium battery power supply control circuit, the input end of the warning lamp LED is connected to the output end of the lithium battery power supply control circuit, and the input end of the lithium battery power supply control circuit is connected to the positive electrode of the lithium battery; the lithium battery charging circuit is used for managing charging of the lithium battery; the warning indicator shell is provided with a light-transmitting window, and the light-transmitting window is sealed by a transparent material; a reflective tape is arranged on the outer side wall of the warning indicator shell.