69 results about "Single vehicle" patented technology

The application relates to a traffic capacity estimation method based on traffic basic graph parameter calibration, belongs to the technical field of intelligent traffic systems and traffic flow modeling, and particularly relates to a traffic capacity estimation method based on traffic basic graph parameter calibration. The application aims to solve the problem that the existing method cannot obtain accurate traffic basic graph parameters, resulting in low traffic capacity estimation precision. The process is as follows: step one, obtaining historical traffic flow single vehicle data samples of a road section; processing the obtained single vehicle data samples to obtain a final aggregated data set; step two, obtaining adaptive weights based on kernel density estimation based on the obtained final aggregated data set; step three, obtaining an optimal parameter set of a traffic basic graph model by adopting a particle swarm optimization algorithm based on the adaptive weights; and step four, obtaining traffic capacity based on the optimal parameter set of the traffic basic graph model.

The application discloses a kind of single vehicle control methods based on scene style migration and SAC network cooperation, including steps: S1, using SUMO tool to build simulation platform;S2, construct single vehicle longitudinal control model, SAC network is used to obtain traffic state from simulation platform, then take action control vehicle behavior, after action execution, agent receives the reward value updated agent parameter that simulation platform feedback;S3, define policy network, output the numerical value of acceleration;Define value function network, output layer represents the estimation of state value;S4, through the vehicle control experimental platform built in call SUMO to simulate different weather conditions, and build measurement model;S5, on the basis of single vehicle longitudinal control model build migration learning framework;S6, using migration learning will train convergent single vehicle longitudinal control model to be transplanted to different weather conditions and train.The application can effectively inhibit traffic stop and go wave, ensure traffic safety, reduce fuel consumption.

The utility model relates to pipeline loading and unloading arrangement technical field especially is a kind of HDPE pipeline loading and unloading car arrangement structure, including thickening felt, PE pipe, first HDPE pipeline, sleeper, second HDPE pipeline, flexible rope and loading and unloading rigging;The utility model passes through design a kind of HDPE pipeline loading and unloading car arrangement structure, 4 1.4mHDPE pipes can be loaded and unloaded by single vehicle, by using PE pipe cushion layer, the sleeper of adding baffle and flexible vehicle fastening rope, can ensure transportation safety, adopts 2 groups of hook mode when loading and unloading, and the 2 roots of each layer are lifted simultaneously, ensure the efficient convenience of unloading car, can maximum degree improve HDPE pipeline transportation and loading and unloading car efficiency, to maximum degree save transportation cost.

The application discloses an abnormal driving behavior recognition method and system based on multi-modal data fusion, and particularly relates to the technical field of multi-vehicle cooperative driving safety control, and is used for solving the problem that the existing cooperative driving system cannot convert the abnormal behavior risk of a driver into a cooperative control instruction at the vehicle fleet level; the abnormal state of the driver is recognized by collecting and fusing multi-modal sensor data of the vehicle; when the vehicle is a lead vehicle of a vehicle fleet, the comprehensive risk of the abnormal state to the safety of the vehicle fleet is evaluated based on the abnormal state through probabilistic evolution simulation; the expected effect of different vehicle fleet control strategies is simulated according to the risk evaluation result, and the best strategy is selected; vehicle fleet risk information containing the strategy is generated and sent to all following vehicles through vehicle-to-vehicle communication; the whole process from single-vehicle driver state monitoring to vehicle fleet level cooperative risk prevention and control is realized, and the overall safety of the vehicle fleet system is improved.

This invention relates to the field of artificial intelligence technology and discloses an obstacle detection method and system based on unmanned mining trucks. One obstacle detection method for unmanned mining trucks includes: collecting and preprocessing vehicle data; constructing a dust and fog evolution prediction network to obtain a defogging multispectral image; extracting the distribution information of different materials in the scene to form an enhanced scene feature representation; performing adaptive fusion and uncertainty evaluation to obtain a gating feature representation; using an obstacle detection model to detect obstacles; and constructing a multidimensional occupancy grid to output multidimensional obstacle data. This invention overcomes the performance bottleneck of traditional defogging algorithms in heavy dust and fog environments in mining areas by decoupling from the dust and fog environment through physical modeling. By constructing a multi-vehicle collaborative perception network with sparse feature sharing, it overcomes the problems of blind spots and insufficient long-distance perception capabilities in single-vehicle perception, enhancing the system's detection reliability in dynamic and complex environments and ensuring the safety of autonomous driving operations in mining areas.

The application relates to the technical field of intelligent transportation and carbon governance, in particular to a passenger car carbon emission monitoring and regulation system and method based on multi-source spatio-temporal data. The application solves the problem of scattered and inconsistent data by preprocessing and uniformly mapping multi-source spatio-temporal data. A three-dimensional carbon emission calculation model of vehicle-space unit-time period is constructed to realize accurate calculation of single-trip carbon emission of a single vehicle and positioning of high-carbon emission hotspots. A clustering algorithm is used to complete differentiated division of user groups. A dynamic early warning threshold is generated based on a warning threshold prediction model, regional carbon emission targets and historical data to reduce false positives and false negatives. A warning type-policy tool-adaptation object mapping rule library is established, and a regulation strategy is generated by combining early warning signals and real-time data to realize automatic and accurate generation of regulation strategies from problem identification. The model parameter, early warning threshold and mapping rule are optimized by using policy implementation effect data to form a monitoring, early warning, regulation, optimization closed-loop management and realize accurate regulation.

The invention obtains a controller and a control method capable of improving assistance performance for a rider. A controller for a rider-assistance system of a straddle-type vehicle (100) includes an execution section executing rider-assistance operation to assist a rider of an own vehicle (100) on the basis of positional relationship information between the own vehicle (100) and a target, and further includes an acquisition section acquiring positional information of the own vehicle (100) in a group in the case where a group travel mode as a mode in which a group formed of plural straddle-type vehicles (300), including the own vehicle (100), travel in plural vehicle lines (C1, C2) in a single lane (L) is determined to be valid. In the case where it is determined that the group travel mode is valid, the execution section executes the rider-assistance operation on the basis of the positional information acquired by the acquisition section.

The application provides an accident hidden danger road section dynamic identification method and platform based on multi-dimensional data fusion, relates to the technical field of traffic data identification, and comprises the following steps: converting a target road section area into a directed graph to determine a road network topology; generating a normal situation partition traffic trajectory through multi-dimensional road network data, judging a single vehicle trajectory and a traffic disturbance mode in combination with a real-time traffic trajectory, and generating a hidden danger identification instruction; positioning a hidden danger road section in the road network topology, performing combined inversion and state transition probability analysis based on random variables, and generating a hidden danger probability curve; performing hidden danger disturbance propagation analysis in the road network topology, determining hidden danger identification information, and performing traffic hidden danger early warning management. The application can solve the technical problem of affecting the accuracy of traffic hidden dangers in the prior art, realize dynamic hidden danger identification and prediction capability based on real-time traffic flow data and road network topology information, and achieve the technical effect of accurately identifying the space-time distribution of hidden dangers.

The disclosure relates to a system for detecting load displacement in a vehicle (100), comprising at least one image data acquisition device (102) configured to be attached to the exterior of the vehicle. The at least one image data acquisition device is configured to acquire image data of the exterior of the vehicle (100), and an electronic control unit (ECU) is configured to process the acquired image data to generate a primary plane (P1) in a static position without a load and a secondary plane (P2) in a driving position with a load. The ECU is further configured to determine a primary height (H1) of the primary plane (P1) and secondary heights (H2a, H2b, H2c, H2d) of the secondary plane (P2) from the ground and to compare the primary height (H1) of the primary plane (P1) with the secondary heights (H2a, H2b, H2c, H2d) of the secondary plane (P2) to detect load displacement.

The application discloses a green wave vehicle speed guiding method based on GA-PSO, realizes low-delay information interaction and unified queuing coordination between vehicles through a bidirectional navigation topological structure, effectively alleviates queuing oscillation under high-density traffic, and significantly improves intersection traffic throughput and queuing stability; a UV-TSA model is used to process the acceleration and deceleration process in stages, so that the speed conversion is continuous and smooth, the driving comfort is greatly improved, and the vehicle fuel consumption and exhaust emission are reduced; the GA-PSO hybrid algorithm combines the advantages of genetic operation and particle swarm optimization, enhances the population diversity, realizes efficient global optimization of the speed trajectory under multiple constraint conditions, solves the problem that traditional green wave vehicle speed guiding depends on single vehicle decision and has poor adaptability, and effectively alleviates urban intersection congestion and environmental pollution.

This invention discloses a loading operation data processing method, relating to the field of vehicle parameter measurement technology. The method includes: determining bucket movement and position based on visual detection or control signals; recording the number of digging operations based on bucket movement; determining the effective loading operations from the digging operations based on bucket movement and position, and obtaining the effective single-bucket fuel consumption corresponding to the effective loading operations; determining the effective loading rate based on the number of digging operations and the effective loading operations; determining the loading status of the vehicle to be loaded based on visual detection and / or the effective loading operations; recording a loading operation and its corresponding single-vehicle fuel consumption when the loading status meets a loading threshold; and determining the effective fuel consumption based on the single-vehicle fuel consumption and the effective single-bucket fuel consumption. The loading operation data processing method provided by this invention utilizes multi-dimensional monitoring and analysis to replicate the operation process, improve the control of effective working hours, enhance the automation and intelligence level of management, and improve the overall efficiency of loading operations in mining areas.

Embodiments of the present application disclose an information display method and device, electronic equipment and readable storage medium. After determining that the road section type of the road section where the vehicle is located is a two-way single lane, the driving action of the vehicle is detected, and after detecting that the vehicle starts to perform a U-turn action, the positioning mark of the vehicle in the map page is bound to the road according to the sequence of arc-shaped point positions until the vehicle ends the U-turn action. Embodiments of the present application can simulate the U-turn process of the vehicle on the two-way single lane based on the sequence of arc-shaped point positions to realize the binding of the positioning mark of the vehicle to the road in the map, thereby avoiding the problem of delay and lag of the positioning mark of the vehicle in the map due to the U-turn, improving the trajectory accuracy of the positioning mark in the map, making the positioning mark close to the actual vehicle motion state, improving the steering fluency of the positioning mark, and further improving the user experience.

The application discloses a method and system for vehicle path optimization in a single-vehicle channel under dynamic demand, acquires a path point request and adds the path point request to a request queue; a vehicle path optimization model is constructed, and according to a current position of the vehicle and the dynamic request queue, an optimal order of the request queue is dynamically calculated within a certain time limit after the request is sent, a next request is dynamically selected to minimize total travel time, and the next path point is determined; a priority queue is divided from the request queue according to a time when the request is sent, for the priority queue, a current target, a next target and a second next target are determined in sequence; when the vehicle reaches the next target, the next target is updated to the current target, and the second next target is updated to the next target, and the process is sequentially and circularly promoted to form a processing order until the requests in the priority queue are all responded.

The application relates to the control field and particularly discloses a logistics decomposition trolley running control method and system. The method comprises the following steps: after a server receives information sent by wireless communication devices on multiple vehicles, a vehicle cooperation relationship model is constructed; while the vehicle running track is determined, the positioning position sequence of a single vehicle and the cooperation relationship among the vehicles are considered; according to the results of station and operation behavior identification and cooperation relationship analysis, effective positioning positions are screened out as track points to generate a preliminary vehicle running track; according to road network information, the track is optimized, and the logistics decomposition trolley running control is realized based on the generated and optimized track. The server of the application dynamically updates the cooperation relationship model, predicts path intersection or regional occupation conflicts based on the cooperation relationship model, dynamically adjusts the vehicle speed or path, jointly smooths the tracks of multiple vehicles, ensures the consistency of path curvatures of adjacent vehicles, avoids sudden turns or stops, and in this way, the problem of track misjudgment is avoided.

The application discloses a kind of vehicle screen automation test control methods based on OCR technology, comprising: test initialization, import test case;Based on the test case, real-time ADB screenshot and OCR identification are executed;According to whether the OCR identification result conforms to the expectation of corresponding test case, intelligent decision and instruction execution are carried out;Test result record and determination, generate test report.The vehicle screen automation test control method based on OCR technology of the application realizes the automatic closed-loop test control of vehicle screen based on OCR technology, through the whole-process automation of ADB screenshot-OCR identification-intelligent decision-instruction execution, realizes the efficient and accurate verification of vehicle screen full-scene test, can overcome the problems such as inefficiency, low compatibility and dynamic scene loss of existing vehicle screen test;Efficiency is significantly improved: replace manual operation, single vehicle type test time is shortened from 48h to 24h or less, support multi-vehicle type test.

The embodiment of the application discloses a vehicle re-identification model construction method based on multi-image learning, comprising: acquiring a vehicle image set, each vehicle image comprising a single vehicle and being labeled with a vehicle category; according to the space-time information of each vehicle image, combining multiple vehicle images taken at the same space-time position into an image package, and taking the vehicle category with the most labels in the image package as the labeled category of the image package; and training a vehicle re-identification model based on deep learning by using each image package. The embodiment improves the accuracy of vehicle re-identification.

The application discloses a lane keeping anomaly detection method and device in a decentralized vehicle group environment, mainly aiming at the problems that the existing single-vehicle intelligent lane keeping scheme cannot distinguish between sensing anomalies and real driving deviations, the lane reference cognition of the decentralized vehicle group is not unified, and the safety redundancy is insufficient. The visual lane line parameters of the vehicle and neighbor vehicles are collected first, and after the coordinate system alignment, the vehicle group consensus lane line is generated through a decentralized distributed consistency filter. Then, the multi-dimensional lateral deviation is calculated to obtain the vehicle sensing deviation and neighbor control deviation. The threshold comparison is performed to determine the anomaly type and output the corresponding detection signal. Compared with the prior art, the application can accurately identify multiple types of anomalies without relying on a central node and a high-precision map, can guarantee the collaborative stability of the vehicle group, can improve the safety and robustness of the lane keeping system, and is suitable for commercial vehicle high-speed platoon scenes and the like.

This invention discloses a method, apparatus, device, and medium for full lifecycle management of vehicle-mounted containers. Its features include: monitoring the process status of the core process of a target vehicle-mounted container based on a monitoring process, and detecting the response status of the core process; if the monitoring process detects an abnormal response from the core process, then performing a process-level restart of the core process; verifying the response status of the core process based on the monitoring process, and if the core process is in an abnormal state, then performing a container-level restart of the target vehicle-mounted container. This invention can identify abnormal processes of vehicle-mounted containers in real time, and quickly and timely restore abnormal services of vehicle-mounted containers by restarting a single vehicle-mounted container process or restarting the entire vehicle-mounted container, thereby rapidly restoring container services, improving vehicle-mounted container recovery efficiency and resource utilization, significantly reducing service interruption time and maintenance costs, and possessing strong adaptability to cope with various extreme operating scenarios.

This utility model relates to the field of vehicle inspection technology. It provides an auxiliary structure for vehicle inspection, including a platform, a lifting plate, a winch, and a traction assembly. The traction assembly includes a first steel wire rope wound on the winch. A movable pulley is mounted on the first steel wire rope, and a plate ring tension / compression sensor is connected to the first steel wire rope after passing over the movable pulley. The other end of the plate ring tension / compression sensor is connected to a second steel wire rope fixedly connected to the lifting plate. A cable connected to the vehicle under test is attached to the movable pulley. This utility model has the following advantages: The plate ring tension / compression sensor is fixedly connected to the lifting plate via the second steel wire rope, maintaining a stable position and eliminating the need for movement during the traction process. This avoids the limitation of the test stroke caused by the sensor cable length in traditional structures, significantly increasing the effective test range, reducing the accuracy requirements for the vehicle's parking position, reducing the inconvenience of operators repeatedly adjusting the vehicle, and improving the inspection efficiency of a single vehicle.

The application discloses an industrial internet motor vehicle production collaborative scheduling method and system, the method comprises the following steps: acquiring vehicle production, material distribution, station operation and process connection state data; establishing a plan binding relationship between the vehicle and a single-vehicle material package; and establishing a passing point binding record and a field binding record when the vehicle passes through a point and the material package arrives at a line side; judging a synchronous arrival condition based on a vehicle station arrival window and a single-vehicle material package arrival window, and judging a binding consistent condition in combination with the plan binding relationship, the passing point binding record and the field binding record; when vehicle and material synchronization abnormalities occur, sequentially performing vehicle waiting disposal, material package temporary storage disposal, material package binding change disposal and replacement vehicle release disposal judgment; when the scheduling disposal cannot be completed, generating a previous flow limiting instruction, and generating an abnormal freezing instruction or a manual review prompt according to execution feedback, and updating the binding state. The method can reduce the risk of vehicle and material mismatch and local abnormal diffusion.

The present scheme relates to a gel curing tool and method for workpieces and a gel curing assembly suitable for multiple vehicle types, which are used to solve a series of problems caused by the fact that the gel curing equipment in the prior art can only be adapted to the production of a single vehicle front cover. The controller of the gel curing tool determines at least one target special component that is adapted to the vehicle type code of the workpiece to be processed from a plurality of special support mechanisms after receiving the vehicle type code of the workpiece to be processed, and controls the at least one target special component to switch to the respective preset position. After identifying that the workpiece to be processed is the workpiece of the vehicle type to be processed, the controller controls the plurality of common components and the at least one target special component to clamp and assemble the workpiece of the vehicle type to be processed. After identifying that the workpiece of the vehicle type to be processed is assembled in place, the controller controls each gel curing mechanism to extend respectively. After each gel curing mechanism extends to the position, each gel curing mechanism heats each part to be heated of the workpiece of the vehicle type to be processed.

This invention relates to a heterogeneous vehicle group cooperative consistency control method based on a collision warning mechanism, belonging to the field of intelligent transportation application technology. It includes: setting up a typical single-lane heterogeneous vehicle group traffic scenario on an urban road; acquiring and analyzing vehicle state information data through roadside sensing units, and constructing a four-level collision warning mechanism based on dual-indicator fusion, combining vehicle distance and collision time; establishing a longitudinal kinematic model of vehicles based on the kinematic characteristics of heterogeneous vehicles, combined with the vehicle information topology, and simultaneously constructing a traditional human-driven vehicle control model and a connected autonomous vehicle control model based on collision warning levels; and establishing a heterogeneous vehicle group cooperative consistency control method based on vehicle speed and spacing within the heterogeneous vehicle group. This invention enables heterogeneous vehicle groups based on a collision warning mechanism to quickly achieve state consistency and maintain stable driving.

This invention discloses a lane-changing decision-making method for intelligent connected vehicles at signalized intersections in a vehicle-road cooperative environment, belonging to the field of intelligent path decision-making. The method includes: addressing the problems of ineffective lane changing and ineffective following caused by uneven vehicle dissipation capabilities between lanes at signalized intersections; constructing a state space by real-time acquisition of traffic light status, vehicle status, and lane queuing information; processing this state space using a deep reinforcement learning model to generate a hybrid action that integrates longitudinal acceleration and lateral lane changing; and performing dual safety verification of the action based on an intelligent driving model and a vehicle interaction safety judgment method, ultimately outputting control commands. This invention enables intelligent connected vehicles to adaptively make optimal lane-changing decisions during critical periods such as the end of a red light or the beginning of a green light, effectively improving single-vehicle traffic efficiency, reducing energy consumption, and promoting the overall efficient utilization of spatiotemporal resources at intersections while ensuring safety.

Disclosed in the present invention are a dynamic power flow calculation-based traction energy saving method for rail transit, a system, an electronic device, and a readable storage medium. According to the traction energy saving method, dynamic analysis is performed on multi-dimensional coupling conditions such as power supply, vehicles, signals, and tracks by means of modules such as an ATO single vehicle energy saving + ATS operation chart planning multi-vehicle coordinated energy saving module, a passenger flow requirement-based dynamic map adjustment module, and a regenerative braking energy feed module, dynamic power flow calculation is performed from the perspective of energy flow by means of a power flow dynamic calculation and analysis module of a traction power supply system, and techniques such as ATO energy saving, ATS energy saving, and energy saving using a regenerative braking energy recovery apparatus are dynamically coordinated, to perform unified management and coordinated linkage, so that energy consumption monitoring and statistical analysis are performed for different traction energy saving measures, to track and evaluate a long-term energy saving operation effect. By means of continuous adjustment and optimization of an energy saving control policy according to analysis results by a line energy consumption-operational data variable prediction model, an enhanced energy saving effect in real sense can be achieved.

The application discloses a kind of multi-source vehicle data fusion method, medium and computer equipment, wherein the method comprises: extracting multi-source vehicle data from the vehicle data storage device of the vehicle of traffic accident;Different data processing methods are provided for single-source time period data and single-source continuous data obtained from a single vehicle data storage device, efficient integration and accurate alignment of single-source data are realized to ensure the consistency of time series and the reliability of data source in subsequent analysis;Merge multiple single-source time period data and multiple single-source continuous data onto the same time axis.The application can automatically and systematically extract data from different electronic control units of the vehicle and merge them onto the same time reference data axis with high precision and high reliability to support high-quality vehicle accident data forensics analysis.

This application relates to the field of intelligent transportation technology, and discloses a method, device, system, and storage medium for real-time collaborative optimization of traffic emissions. The method includes collecting vehicle operation data to calculate vehicle power, constructing a two-dimensional bin-structured index of the instantaneous emission rate as a baseline, and correcting it in real-time using pre-fixed rules to output single-vehicle, single-step emissions at the microscopic level; aggregating emission data according to spatial hierarchical logic and simultaneously calculating performance indicators such as average commuting time; calling templates to generate strategies when indicators exceed limits; compiling the strategies into a set of six-tuple standard actions and performing fairness and conflict checks; using an exactly-once mechanism and consistency window to ensure atomic execution across devices; and evaluating strategies based on in-loop monitoring, combined with a third-generation non-dominated sorting genetic algorithm and a conditional risk-value risk term, outputting a Pareto optimal solution set that is continuously updated. This invention balances traffic efficiency, environmental benefits, and system execution stability through a high-precision calculation model and robust optimization algorithm.