2132 results about "Vehicle (Transportation)" patented technology

The invention relates to the technical field of logistics management, in particular to a logistics transportation management method and system based on multi-source data fusion, and the method comprises the following steps: monitoring the vehicle transportation duration in real time, calculating a congestion point, judging a coincidence time period in combination with predicted replenishment time, and generating a rhythm window; and matching the storage delivery time and sorting to generate a path segment code, fitting a path to screen a vehicle binding label, sending an instruction to monitor the path consistency, and generating a scheduling result. According to the invention, transportation time is monitored in real time, congestion points are generated, a rhythm window is dynamically generated in combination with replenishment task time, path segment coding is carried out on a picking sequence, channel use and shipping time, vehicle resources are screened based on path fitting and a path label is bound, and distribution consistency is monitored in real time to generate a scheduling instruction. Multi-dimensional data are analyzed in a unified mode and driven in a time sequence mode, intervention is reduced, efficiency is improved, path coding matching tracks are combined with congestion adjustment to avoid conflicts and redundancy, and the response period is shortened.

The invention relates to the technical field of logistics transportation management, and discloses a vehicle transportation management method based on a digital technology, and the method comprises the following steps: collecting the energy state data of a vehicle in real time through a vehicle monitoring module; transmitting the collected vehicle data to a big data platform by using an Internet of Things technology, analyzing the data, and generating an early warning signal of an energy state; when the early warning signal is triggered, determining an optimal supply path according to the current position of the vehicle and traffic information, and arranging an energy supply service in advance; and through an intelligent scheduling module, according to real-time traffic information, vehicle load and destination distance factors, a transportation route and task distribution of the vehicle are dynamically adjusted. Through real-time monitoring and analysis, the system can automatically trigger a supply early warning signal when the energy state is lower than a safety threshold value, so that non-planned parking caused by energy exhaustion is avoided, and the accuracy of energy management and the operation reliability are remarkably improved.

The invention relates to a traffic engineering BIM (Building Information Modeling) and VR (Virtual Reality) technology combined interactive design and simulation system, which relates to the field of traffic engineering and comprises an interactive configuration module used for selecting simulation configuration to obtain user feedback information; the route mining module is used for performing networking frequent mining to obtain a mobile route case set; the virtual driving module is used for starting simulated driving and obtaining a three-dimensional dynamic time sequence diagram of a vehicle and heart rate monitoring time sequence information of a user; the safety scoring module is used for receiving a user driving safety score through the user side; the risk evaluation module is used for obtaining a driving risk evaluation value set; and the safety identification module is used for performing safety identification and then sending the information to the traffic engineering design end. Through combination of BIM and VR technologies, virtual simulation acquisition and analysis of user driving behaviors are realized, so that the driving risk of a design scheme is evaluated in a targeted manner, traffic engineering optimization design is guided, and the safety of traffic engineering design is improved.

The embodiment of the invention provides a lens, a display module, a vehicle lamp device, electronic equipment and a vehicle. The lens comprises at least five lenses arranged from the image side to the object side in the optical axis direction. At least three lenses in the at least five lenses have positive focal power, at least one lens has negative focal power, and when the number of the lenses with the negative focal power in the lens is one, the lens with the negative focal power in the lens is arranged between the lens closest to the image side in the lens and the lens closest to the object side in the lens in the optical axis direction. The lens provided by the embodiment of the invention can have the characteristics of a large aperture and a large field angle at the same time, so as to meet the use requirements.

The invention provides an Apple cold-chain logistics path optimization system and method considering vibration loss, and the method comprises the following steps: collecting data required by cold-chain logistics distribution, including client point information, real-time road condition information, vehicle vibration acceleration and vehicle driving information; establishing an apple vibration loss calculation model in the transportation process according to the characteristics of the apples; according to the vehicle transportation cost, the goods damage cost, the refrigeration cost, the time window constraint violation cost and the carbon emission cost, an Apple cold-chain logistics distribution path optimization model with the minimum total cost as the target is established; solving the apple cold-chain logistics distribution path optimization model by using an improved ant colony algorithm; according to the detected CO2 concentration, temperature and vibration loss, the method is used for monitoring the apple quality condition in real time, establishing a feedback adjustment mechanism, and giving loss reduction measures according to the apple quality condition. The optimal distribution path is selected in combination with an algorithm, and cost reduction and benefit increase of apple cold-chain logistics transportation are achieved.

The invention discloses a CVaR-based highway hazardous chemical vehicle accident rescue and evacuation path planning method, and belongs to the technical field of traffic safety and emergency. The path planning method comprises the following steps: acquiring dangerous chemical vehicle transportation accident occurrence points, rescue vehicle rescue points, accident vehicle placement points (evacuation destinations) and road network related parameters; the rescue stage is a path from a rescue exit point to an accident occurrence point of a rescue vehicle, comprehensively considers that the response time of the rescue vehicle is shortest, the efficiency is highest and an upper-layer rescue vehicle travel time shortest model is established, considers that a secondary accident is extremely easy to occur in a dangerous chemical vehicle transportation accident on a highway, and constructs a lower-layer model with the minimum secondary accident risk based on CvaR; a highway dangerous chemical vehicle accident rescue double-layer game planning model is formed; in the evacuation stage, a dangerous chemical substance accident vehicle is a path from an accident occurrence point to a vehicle placement point, the possibility of pollution caused by dangerous chemical substance leakage in the evacuation stage is considered, and an accident vehicle evacuation path planning model based on the CVaR dangerous chemical substance leakage risk is established. According to the highway hazardous chemical vehicle accident rescue and evacuation path planning method provided by the invention, the road traffic safety level and the emergency rescue efficiency can be improved, and smooth and orderly operation of highway traffic is ensured.

The invention discloses a logistics freight vehicle transportation supervision system and method based on the Internet of Things, and relates to the technical field of vehicle transportation supervision, the supervision system is constructed based on multi-source data fusion and hierarchical anomaly detection, and the problems of false data and signal interference which are difficult to identify in traditional supervision can be effectively solved; through multi-level comparison and block chain evidence storage, supervision blind areas caused by manual tampering or equipment faults are greatly reduced; meanwhile, the self-learning analysis module dynamically recognizes repeated or regular pseudo data, and by iteratively updating a threshold value and improving an early warning level, false alarms can be remarkably reduced, and accurate positioning of potential anomalies can be enhanced; the real-time performance and traceability of freight vehicle transportation supervision are improved, and the method has significant improvement value for the traditional mode which depends on a single data source and lacks a rapid verification mechanism.

Intelligent eco mode optimization in a battery electric vehicle (BEV) includes collecting data from one or more systems of a vehicle in which the vehicle includes a battery. A predicted route is generated based on the collected data. The collected data includes a navigation map for a portion of a vehicle transportation network. A state of the vehicle is determined based on the collected data and the predicted route. A drive mode is determined, using a decision-making model, for the vehicle based on the state of the vehicle and the predicted route. The drive mode is either a first drive mode having a first acceleration curve or a second drive mode have a second acceleration curve and the second drive mode reduces a rate of discharge of the battery as compared to the first drive mode. The vehicle is set to use the drive mode.

The invention provides a multi-center hybrid fleet joint scheduling method based on an improved genetic variable neighborhood algorithm, and the method comprises the steps: building a joint scheduling model with the minimization of vehicle transportation cost, charging cost and overtime penalty cost as a target, and building constraint conditions; a genetic algorithm is adopted for optimization, and a joint scheduling scheme with the lowest total cost under the constraint condition is obtained; performing variable neighborhood local search on each generation of optimal individuals after genetic manipulation; executing a dynamic disturbance operation; and judging whether the maximum number of iterations is reached or not, if so, ending the process, and obtaining a multi-center hybrid fleet joint scheduling scheme, otherwise, repeating the previous steps. According to the invention, a joint scheduling mechanism is introduced to realize transportation resource sharing, and the overall resource configuration is optimized; a joint scheduling model is constructed based on a hybrid motorcade, an electric vehicle charging strategy is optimally designed, an improved genetic algorithm and a variable neighborhood algorithm are used for optimization solution, and customer service satisfaction experience can be improved.

The invention relates to the technical field of ice bridges, and discloses an ice bridge for river-crossing transportation in a cold region and a construction method. The pine rods perpendicular to the water flow direction are placed perpendicular to the water flow direction and used for enhancing the ice bridge structure; the pine rods parallel to the water flow direction are placed parallel to the water flow direction and are alternately matched with the pine rods perpendicular to the water flow direction to form a stiffened framework of the ice bridge; the natural ice surface serves as a foundation of the ice bridge and bears transportation loads. The designed width of the ice bridge is 6-8 m, and the snow cleaning width of the ice surface at the ice channel is 20-25 m. The bearing capacity and stability of the ice bridge can be greatly improved through a reasonable construction method such as multi-layer ice layer reinforcement and wooden pole framework supporting. The basic layer of the ice bridge adopts the basic ice layer with the thickness of 50cm, and the strength of the second reinforcing ice layer is further enhanced, so that the bearing capacity of the ice surface is enhanced, and heavy vehicles and mechanical equipment can be supported.

The invention discloses a multi-vehicle cooperative intelligent marshalling speed regulation method for railway transportation of power batteries. The method comprises the following steps: establishing state characteristics of each transportation truck, and constructing a position sensitive damage cost function for evaluating the risk cost of each truck at different marshalling positions according to the state characteristics; in the railway vehicle transportation process, an event-driven time pane dynamic optimization method is adopted, a vehicle marshalling and train speed control curve is dynamically updated according to state parameters collected in real time, and in the optimization process, a variable damping distribution strategy of a coupler and a cooperative vehicle speed curve generation algorithm are adopted, so that the train speed control curve is dynamically updated. Meanwhile, time dispersion is carried out on coupling impact events through an impact time peak shifting strategy; and when the comprehensive risk index of any transport truck exceeds a preset threshold value, an emergency re-marshalling strategy based on the energy absorption remaining amount of the battery packaging unit and the coupler health degree is executed. The method can comprehensively consider the thermal characteristics of the power lithium battery, the dynamic response of the vehicle and the risk evolution.

The invention discloses a vehicle transportation management system based on Beidou positioning, which belongs to the technical field of vehicle transportation and comprises a Beidou positioning module, a data processing module, a multi-source heterogeneous data fusion module, a vehicle state monitoring module, a data analysis module, a transportation route planning module, a transportation route optimization module and a data report generation module. Through the high-precision positioning function of the Beidou positioning module and in combination with the error correction technology, more accurate vehicle position information can be provided, the accuracy and reliability of transportation are improved, the received data including satellite orbit errors, atmospheric delay errors and the like are processed, the positioning accuracy is further improved, and the positioning accuracy is improved. A comprehensive vehicle running state view is formed by combining Beidou positioning information with a vehicle sensor and an external data source, so that information from different data sources can be compared and analyzed on a common time axis, and the accuracy and effectiveness of data analysis are improved.

A system is provided.SOLUTION: A system including means for a user to input a destination, a departure point, a departure date, a period of stay, a desired transportation means, a condition of an accommodation facility, and a necessity of a rental car, means for collecting information on an optimum transportation means, an accommodation facility, and a rental car based on the condition of the travel from the Internet by using a generated AI, means for analyzing the collected data and generating a cost-effective travel plan, means for displaying the generated travel plan and time sale information of an airline company to a user, and means for communicating with a corresponding transportation means, accommodation facility, and rental car according to the travel plan selected by the user to make a reservation.SELECTED DRAWING: Figure 1

The invention belongs to the technical field of garbage collection and transportation, and particularly relates to a hook arm garbage collection and transportation vehicle transportation route dynamic optimization system and method, the loading state of a garbage can is monitored through a sensor, and a collection and transportation instruction is automatically triggered when a preset threshold value is reached, so that garbage overflow is avoided, and meanwhile invalid scheduling is reduced. The intelligent scheduling system combines reinforcement learning and a Transform architecture, can comprehensively analyze real-time road condition information, dynamically calculates an optimal driving path, and timely adjusts the path according to traffic changes. Meanwhile, the system achieves cooperative scheduling of full-load vehicles and empty-box vehicles, ensures efficient connection of all links, effectively improves the response speed and execution efficiency of the clearance task, reduces the vehicle empty driving rate and energy consumption, achieves intelligent and fine management of the garbage clearance process, and improves the efficiency of the clearance task. The problem of low efficiency caused by information lag and fixed path in a traditional scheduling mode is solved.

The invention provides a logistics distribution vehicle intelligent scheduling method, system and device based on a space-time attention mechanism, and a medium, belongs to the technical field of artificial intelligence and logistics transportation, and specifically relates to collection of an express order set and construction of an express vehicle transportation network diagram; constructing an express vehicle scheduling model, and setting constraint conditions; designing a deep reinforcement learning algorithm based on a space-time attention mechanism, and carrying out order distribution and vehicle route planning; constructing a reinforcement learning algorithm based on actors and commentators, and training a target parameter network; and generating a vehicle route, calculating a reward value of the route and a state value of the valuation network, and completing training of a preset round based on updating parameters of the actor strategy network and the commentator network to obtain a target parameter network. According to the invention, the total path length of vehicle driving is reduced, the intersection and repetition of the paths are avoided, and the load factor and the driving speed of the vehicle are improved, so that the transportation efficiency of the express vehicle is improved, and the express delivery time is shortened.

The invention relates to the field of intelligent logistics optimization, and discloses an unmanned aerial vehicle transportation route distribution method for logistics multi-point transportation, which comprises the following steps: carrying out coordinate-weight joint standardization on a distribution point set to generate a three-dimensional feature vector; constructing a topological complex based on the standardized data, and extracting a key ring structure through continuous coherence; encoding the ring structure into a topological constraint term of a quantum model, and constructing Hamiltonian containing distance, load and topological constraint; dividing quantum sub-blocks according to the topological ring, and executing block annealing solution through chain coupling constraint; and carrying out topology-guided privacy fine tuning under a federated learning framework by using gradient information of a quantum solution. According to the method, a complex path optimization problem is decomposed into sub-problems capable of being processed in parallel through a quantum topological coding and block annealing strategy, quantum bit grouping is guided through a topological ring structure, the calculation complexity is reduced, efficient solving of a large-scale logistics network is achieved, and the calculation speed is increased compared with a traditional optimization method.

The invention provides a mountain leaf transfer vehicle anti-rollover early warning method and system based on data driving, and relates to the technical field of vehicle anti-rollover risk early warning, and the method comprises the following steps: S1, carrying out the joint simulation to generate a neural network training data set; s2, constructing RBF neural network training as a vehicle sprung load parameter estimation model; s3, optimizing parameters of the RBF neural network by using an improved grey wolf optimization algorithm; s4, optimizing the RBF neural network, and performing sprung load prediction based on the optimized RBF neural network; s5, state information in the vehicle driving process is obtained through a vehicle-mounted sensor, the sprung load distribution condition of the vehicle is obtained, and an early warning signal is generated; and S6, building an ROS-based wind power blade mountain transfer vehicle anti-rollover visual platform, and carrying out anti-rollover early warning. According to the method, real-time vehicle rollover prevention early warning is carried out according to the parameters in the vehicle driving process, and the safety in the vehicle transportation process is improved.

The embodiment of the invention provides a travel state detection method, wearable equipment and a storage medium, and relates to the technical field of state detection. The method is applied to the wearable device, the wearable device comprises a motion sensor and an image sensor, and the motion sensor comprises an IMU: obtaining an image sequence collected by the image sensor in response to the fact that the accuracy of a first travel state detection result is lower than a preset threshold; inputting the image sequence into a pre-trained feature extraction model, and extracting spatial features and time sequence features of the image sequence; obtaining a second travel state detection result by using a pre-trained multi-layer perception model based on the spatial features, the time sequence features and a corresponding relation learned in the training process of the multi-layer perception model; and determining a target travel state detection result based on the probability that the user takes the vehicle. Therefore, the travel state detection is performed twice by using the data and the image sequence acquired by the IMU, and the travel state detection accuracy is improved.

The present invention belongs to the technical field of transportation vehicles, and particularly relates to a self-learning prediction method for road noise of an automotive suspension structure. The present invention provides a self-learning prediction method for road noise of an automotive suspension structure, aiming to enhance the robustness and interpretability of the automotive road noise prediction method. Based on a knowledge-driven model for suspension road noise and a data-driven model built using LSTM, the present invention iteratively fuses knowledge and data, aiming to enhance the robustness and interpretability of the automotive road noise prediction method, and can realize the self-learning of the knowledge-driven model and the data-driven model as the data samples are expanded, thereby providing effective guidance for automotive NVH engineers and improving the efficiency of automotive road noise prediction and analysis.

An apparatus of a first vehicle includes a processor configured to detect a fault associated with a second vehicle. The processor is configured to obtain sensor data associated with a sensing region of the second vehicle. The processor is configured to provide an output, based on the sensor data, for controlling the second vehicle to traverse a vehicle transportation network

The invention discloses a module vehicle transportation anti-collision monitoring system and method. The system comprises an environment sensing module, a data preprocessing module, a coordinate and time processing module, a data fusion and association module, a target tracking and prediction module, an anti-collision decision module, a collision early warning and safe distance module and an early warning and interaction module. The method comprises; the method comprises the following steps: 1, environment perception and data acquisition; step 2, data preprocessing and coordinate time synchronization; step 3, target association and data fusion; step 4, target tracking and prediction; 5, performing anti-collision decision and path planning; step 6, collision early warning and safe distance management; according to the method, factors such as driver response time, vehicle braking performance and road adhesion conditions are comprehensively considered, a corrected safety distance threshold formula is established, and the accuracy of collision early warning is remarkably improved by combining TrickSim and Simulink joint simulation verification.

The invention discloses a vehicle charging control method and device, a vehicle and a computer readable storage medium, and the method comprises the steps: judging whether a primary vehicle and a secondary vehicle meet a first preset condition or not when a received instruction used for indicating the vehicle to enter a preset charging mode is valid, the first preset condition comprises that neither the primary vehicle nor the secondary vehicle has a fault, and if yes, the primary vehicle and the secondary vehicle enter the preset charging mode; the power battery of the primary vehicle and the power battery of the secondary vehicle are connected with the voltage converter; if yes, the vehicle is controlled to enter a preset charging mode, and the power battery of the child vehicle is controlled to charge the power battery of the mother vehicle through the voltage converter. In the vehicle transportation process, the mother vehicle is charged through the son vehicle, the endurance mileage of the mother vehicle can be prolonged, the requirement for parking and charging in the midway is avoided, the transportation time cost is reduced, the transportation efficiency is improved, meanwhile, the number of vehicles running in the vehicle transportation process can be reduced, and therefore the passing cost of the vehicles is reduced, and the purpose of saving the cost is achieved.

Aspects of the disclosure relate to arranging trips for an autonomous vehicle transportation service. In one instance, a request for a first trip from a user is received. The trip may include a pickup location and a destination location. Whether the user has previously completed the first trip may be determined by comparing the pickup location and the destination location to a trip history for the user. Based on the determination, a notification suggesting that the user establish a routine may be provided for display to the user. Confirmation that the user wants to establish a routine based on the pickup location and the destination location may be received. The routine may be stored in memory for later use.

Aspects of the technology relate to providing service area maps for an autonomous vehicle transportation service having a fleet of vehicles. For instance, each vehicle of the fleet is associated with a polygon corresponding to a service area for that vehicle. A first location may be received from a client computing device, and a set of vehicles of the fleet of vehicles that are currently available to provide transportation services may be identified based on the first location. The polygons associated with each of the set of vehicles may be used to determine a first polygon having a geographic area. A first portion of map information corresponding to the geographic area of the first polygon may be identified, and the first portion may be provided to the client computing device for display to a user such that the portion represents a currently available service area for the user.

Collective action by multiple vehicles traversing a vehicle transportation network is used to improve operation of vehicles and utilization of the vehicle transportation network. Sensor data for multiple monitored vehicles traveling in a common direction along a road in a vehicle transportation network is received and used as input to a traffic estimation model to determine an estimated congestion for the road in the common direction. A cruise control setting for each of several controlled vehicles, at least some of the controlled vehicles traveling behind the monitored vehicles in the common direction, is determined from the estimated congestion. The cruise control setting is transmitted to the controlled vehicles to modify operation of the controlled vehicles using respective cruise control systems of the controlled vehicles.

The invention provides a vehicle transportation control method and device based on a throwing box and electronic equipment, and relates to the technical field of throwing box control, a box body of the throwing box is connected with a vehicle through a 360-degree track, and the box body is correspondingly provided with a box body displacement control device; the method comprises the following steps: in response to a direction control operation for a driving direction control operation device, transmitting a direction control instruction corresponding to the direction control operation to a box body displacement control device; based on the direction control instruction, the specified vehicle body weight corresponding to the vehicle and a front road condition image of the vehicle acquired by an image acquisition device, analyzing and predicting the to-be-driven angle of the vehicle and the to-be-moved intensity of the vehicle through an AI system; and according to the to-be-driven angle and the to-be-driven moving intensity, the box body is controlled to move and / or rotate on the track through a box body displacement control device, so that the inertia force caused by the to-be-driven moving intensity and the to-be-driven angle to the box body is counteracted in advance through second displacement of the box body relative to the vehicle.

The invention provides a glass assembly, a display method applied to the glass assembly, a display system applying the glass assembly and a vehicle. The glass assembly includes: a glass body including a first glass body and a second glass body stacked and attached to each other by an adhesive layer; the shielding layer is arranged between the first glass body and the second glass body; the reflecting layer is arranged on the surface, away from the second glass body, of the first glass body, or arranged on the surface, away from the first glass body, of the second glass body, or arranged between the first glass body and the second glass body so as to display patterns and / or images through reflection, and at least part of the reflecting layer is located in the shielding layer in the section direction of the glass body; and a light emitting layer disposed between the shielding layer and the reflective layer between the first glass body and the second glass body, and located within the shielding layer in a cross-sectional direction of the glass bodies. According to the glass assembly, through combination of the shielding layer and the reflecting layer, the immersive display effect of patterns and / or images for enhancing the contrast ratio is provided, meanwhile, through the light-emitting layer hidden between the shielding layer and the reflecting layer, a seamless display interaction interface can be provided according to different application occasions and user requirements, and the user experience is improved. A diversified display effect is provided, and the use atmosphere and the experience comfort level of the user are improved.

The invention relates to the technical field of path planning, in particular to an AGV intelligent yarn carrier transport path planning method and system, and the method comprises the steps: determining a common path segment based on the initial transport path of each AGV intelligent yarn carrier, and determining the transport path of each AGV intelligent yarn carrier according to the relation between the time for any two AGV intelligent yarn carriers to reach the common path segment; the method comprises the following steps: determining whether any two AGV intelligent yarn carriers have a path conflict or not, if the path conflict occurs, determining the waiting cost generated by any two AGV intelligent yarn carriers waiting to give way and the bypassing cost generated by bypassing, and selecting the minimum cost in the waiting cost and the bypassing cost and the scheduling scheme corresponding to the minimum cost. In this way, even if the number of the AGV intelligent yarn transporting vehicles is large, the AGV intelligent yarn transporting vehicle dispatching scheme with the minimum cost can be determined under the condition that path conflicts occur, and therefore the situation that the AGV intelligent yarn transporting vehicles are mutually blocked is avoided, and the transporting efficiency of the AGV intelligent yarn transporting vehicles is improved.

The invention relates to the technical field of vehicles, and discloses a foldable wing for a hybrid carrier and the hybrid carrier. The foldable wings comprise two sets of wing assemblies which are installed on the two sides of the aircraft body respectively and comprise primary wings and secondary wings, the primary wings are installed on the top of the aircraft body, and the secondary wings are installed on the primary wings in a telescopic mode; the two mother wings can rotate in the horizontal direction, and at least one mother wing can swing in the vertical direction; the driving assembly drives the wing assembly to be switched between an unfolded state and a folded state; in the unfolding state, the son wings extend to the outer sides of the mother wings, the mother wings are unfolded to the outer side of the aircraft body, and the two mother wings in the two sets of wing assemblies are located in the same plane; in the folding state, the son wings retract into the mother wings, the mother wings are folded to the inner side of the aircraft body, and at least parts of the two mother wings are mutually stacked. Through double-shaft movement (horizontal rotation and vertical swing) of the mother wing and nested extension and retraction of the son wing, breakthrough design of the wing width and minimization of the folding size are achieved.