712results about How to "Improve transportation efficiency" patented technology

The invention discloses an elevator control system based on artificial intelligence, which belongs to the technical field of elevator control, and comprises a plurality of layers of architectures such as data acquisition, transmission, processing, intelligent decision, execution control and the like. The data acquisition layer collects multi-source data through a car inside and outside and operation state sensor group; the data processing layer provides support for intelligent decision-making through preprocessing, analysis mining and model training optimization. An elevator dispatching module of the intelligent decision-making layer carries out peak dynamic zoning and flat peak energy-saving dispatching according to information such as passenger flow; the safety protection module monitors and processes hidden dangers in real time; the personalized service module provides customized services based on passenger behaviors and demands. And driving of the control layer, a door machine and a car environment control system are executed, and stable lifting of the car, safe operation of a door and intelligent environment adjustment are achieved correspondingly. Experiments show that the system can remarkably improve the elevator operation efficiency, safety and passenger satisfaction and reduce energy consumption, and has important application value.

The invention discloses a container tracking management system and method. The method comprises the following steps: S1, carrying out dynamic encryption binding and multi-dimensional data acquisition on an RFID chip; s2, realizing real-time position data acquisition of the container under different environmental conditions through a multi-source signal fusion and error correction algorithm; s3, various sensor modules are installed inside and outside the container, and data processing is carried out through distributed edge nodes; s4, performing on-chain storage on total data generated in the transportation process through a Hash encryption algorithm, and realizing automatic data verification, state tracking and abnormity alarm in combination with an intelligent contract; s5, carrying out real-time dynamic modeling analysis on the transportation path and resource allocation, and dynamically adjusting the transportation plan by using a distributed scheduling strategy; and S6, integrating the real-time state data, the path optimization model and the transportation scheduling decision, and providing a report for a user. The method has the advantages of high positioning precision, high data security, high transportation efficiency and good real-time performance.

The invention relates to the technical field of path planning, in particular to an intelligent transportation path planning method based on deep learning, which comprises the following steps: constructing a joint network model based on a convolutional neural network and a long short-term memory network, and training the joint network model by using historical traffic data; in the current transportation task, the real-time traffic data of the non-driving road sections in the current path are analyzed based on the joint network model, and the traffic change trend of each non-driving road section at the next moment is predicted; if the undriven road section of the current path has the sudden traffic event, or one or more undriven road sections in the current path are predicted to have traffic jam at the next moment, re-planning the path; and when the path is re-planned, dynamically optimizing the current path through the reinforcement learning model under the constraint of the multi-objective optimization function. According to the method, the accuracy of the future traffic condition can be improved, and the adaptive optimization of the transportation path can be realized.

The invention, which relates to the technical field of coal mine transportation scheduling, discloses a coal mine intelligent transportation scheduling optimization system comprising a map construction module, a data acquisition module, a communication module, a monitoring module, an intelligent scheduling module, an emergency processing module and a man-machine interaction module. The system has the advantages that the operation states of coal mine collection equipment and transportation equipment are monitored in real time through the equipment monitoring unit and the environment monitoring unit, the environment state of a mining area is comprehensively monitored, equipment abnormity and environment risks can be found and early warned in time, safety accidents are prevented, and the system is safe and reliable. The service life prediction unit can predict the residual service life of the equipment by monitoring and analyzing the operation time and the accumulated workload of the equipment, and gives out early warning when the equipment is close to the end point of the service life, so that potential safety hazards caused by equipment aging are avoided, and the safety of coal mine transportation is improved.

The invention relates to the technical field of solid waste sorting scheduling, in particular to a real-time monitoring optimization method and device for a solid waste collection, transportation and sorting ERP system. The method comprises the following steps: obtaining a real-time solid waste sorting log based on a solid waste collection, transportation and sorting ERP system; solid waste carrying vehicle tracking is carried out on the real-time solid waste sorting log, and a carrying track distribution visual view is constructed; acquiring an omnibearing monitoring image of a real-time sorting site; equipment sorting behavior visual identification is carried out on the real-time sorting site omnibearing monitoring image, dynamic sorting evolution is carried out, and a dynamic sorting twinborn model is constructed; carrying out multi-time-point solid waste sorting simulation on the dynamic sorting twinborn model, carrying out sorting load demand prediction, and generating a sorting load demand prediction value; and carrying out vehicle load calculation on the sorting load demand prediction value one by one, and then carrying out dynamic vehicle scheduling decision making to obtain a dynamic vehicle scheduling strategy. According to the invention, efficient and real-time solid waste sorting scheduling optimization is realized.

The invention provides a conveying platform for internal parts of a compact fusion reactor and a using method of the conveying platform, and belongs to the field of transportation of the internal parts of the fusion reactor. Vacuum outdoor transportation parts of the conveying platform comprise a supporting steel frame assembly, a transportation track assembly, a transportation trolley assembly and a mobile crane assembly, and the supporting steel frame assembly comprises a cage-shaped steel frame; one section of the transportation track assembly is straightly installed in the building channel, the other sections of the transportation track assembly are straightly located in the cage-shaped steel frame and extend to a window in the vacuum chamber, and the movable crane assembly and the transportation trolley are sequentially located on the transportation track assembly. The cable-stayed hanger rail component comprises cable-stayed rods, a bearing steel beam and an annular hanger rail, the cable-stayed rods are installed at the upper end of the regular polygon-shaped frame in an annular array mode, one end of each cable-stayed rod is connected with the upper window collar of the vacuum chamber, and the other end of each cable-stayed rod is connected with the bearing steel beam of the frame. According to the invention, after internal parts on the equatorial plane of the vacuum chamber are quickly conveyed, the internal parts can be conveyed through simple adjustment.

The invention relates to the technical field of inter-city cargo splicing and loading, in particular to an inter-city cargo splicing and loading transportation path optimization algorithm based on large model optimization, and solves the problems that in the prior art, an optimization algorithm based on a large model generally relates to a complex calculation process and needs a large amount of calculation resources and time, and especially in a real-time path planning scene, the calculation process is complicated. And the calculation delay can influence the transportation efficiency. The invention discloses an inter-city cargo splicing transportation path optimization algorithm based on large model optimization. The algorithm comprises data collection and preprocessing, model construction and training, algorithm optimization and verification, path optimization calculation, result evaluation and feedback, and algorithm deployment and application. According to the method, various possible transportation paths are analyzed and compared through an algorithm, the optimal path is selected, unnecessary detour and waiting time is reduced, so that the transportation efficiency is improved, and the algorithm can perform intelligent scheduling and reasonable arrangement of transportation vehicles and routes according to real-time traffic conditions, cargo demands, vehicle states and other information.

The invention discloses a multi-locomotive path planning method and system based on a Q-learning algorithm, and relates to the technical field of iron-steel interface locomotive path planning, and the method comprises the steps: obtaining environment data, building a transportation system environment model, and defining states and actions; performing path optimization on the vehicle path through a Q-learning algorithm to obtain an initial path plan; and the central control system receives the key information in real time, and dynamically adjusts vehicle path planning in real time through a Q-learning algorithm. According to the method, through learning and optimization of the Q-learning algorithm, the central control system can find the shortest path, the transportation time and distance are reduced, and the transportation efficiency is improved; the path planning is dynamically adjusted through the central control system, so that the congestion and conflicts of track routes are avoided, and the smoothness of the transportation process is ensured; by using the Q-learning algorithm, the method can adapt to a dynamically changing environment, and normal operation of the system can be ensured even if an accident occurs.

The invention relates to a scraper conveyor with a coal quantity monitoring function, and relates to the technical field of coal mining machinery, the scraper conveyor comprises a rack, a driving assembly, a monitoring assembly and a flattening assembly, the rack is rotatably connected with a plurality of rotating rollers, the plurality of rotating rollers are uniformly arranged in the conveying direction of the rack, and the plurality of rotating rollers are jointly sleeved with a conveying belt; the driving assembly is arranged on the rack and used for driving the conveying belt to rotate. The monitoring assembly is arranged on the rack and used for monitoring the height and gradient of a coal pile. The flattening assembly is arranged on the rack, located on the side, away from the input end of the rack, of the monitoring assembly and used for reducing the height of the coal pile. The method has the effect of improving the transportation efficiency.

The invention belongs to the technical field of lithium ion batteries, and discloses an amidated polyacrylic acid water-based polymer binder for a silicon-based negative electrode of a lithium ion battery and a preparation method and application of the amidated polyacrylic acid water-based polymer binder for the silicon-based negative electrode of the lithium ion battery. The preparation method comprises the following steps: under a protective atmosphere, sequentially adding 1-ethyl-(3-dimethylaminopropyl) carbodiimide hydrochloride, N-hydroxysuccinimide and levodopa, stirring to fully react, carrying out dialysis freeze-drying treatment to obtain a primary product PL, and uniformly mixing the PL with glycerol to obtain the product. According to the binder, a dynamic bond is successfully introduced, the transportation efficiency of lithium ions is improved, a three-dimensional network structure is constructed, adverse stress generated by volume expansion of a SiOx negative electrode material in the charging and discharging process of an electrode can be effectively inhibited, and the SiOx negative electrode shows good cycling stability.

The invention relates to the technical field of medicine cold chains, in particular to a medicine cold chain aging optimization method and system based on a neural network, and the method comprises the steps: collecting and recording historical temperature data of medicine in a transportation process, collecting historical data of a medicine state, a transportation route and a traffic condition, and building a cold chain data set in combination with the historical temperature data; preprocessing the data in the cold chain data set, establishing a neural network model, and training the neural network model by using the preprocessed training set data; according to the method, related data of cold-chain logistics are collected, the related data comprise historical temperature data, medicine states, transportation routes, traffic conditions and the like, a neural network model is established by using historical data, the neural network model is trained, a real-time monitoring system is established, and the cold-chain logistics process is monitored in real time. And monitoring data is fed back to the neural network model, and a transportation plan and a transportation route are adjusted in time through real-time monitoring and feedback so as to deal with emergencies and optimize logistics timeliness.

The invention relates to the technical field of logistics management and control of cloud computing, and particularly discloses a remote logistics management method and system based on cloud big data management and control, and the method comprises the steps: obtaining multi-source data in a logistics transportation process in real time through a data collection module, including the information of road conditions, weather, warehouse states and the like; the real-time data and historical data are compared and analyzed through a data comparison and analysis module, and the optimal logistics transportation path is determined; monitoring the real-time data based on the selected path through a path risk assessment module, assessing the risk existing in the current logistics transportation, and dividing the risk into a high risk or a low risk according to the assessment result; different countermeasures are taken according to the risk levels, that is, the current transportation process continues to be executed for low-risk paths, and for high-risk paths, risk factors are analyzed, and alternative schemes are implemented; according to the invention, functions of real-time data acquisition, intelligent path planning and dynamic risk assessment are integrated, and efficient management of logistics transportation is realized.

The invention relates to the technical field of battery management, in particular to an unmanned aerial vehicle carrying platform battery management method and system, and the method comprises the steps: adjusting the charging power of a battery pack through a dynamic power adjustment type charging management algorithm; determining the charging demand and strategy of the battery according to the demand of the flight task; by implementing a quick charging technology, the charging time is shortened, and the flight efficiency of the unmanned aerial vehicle is improved; excessive charging and discharging are avoided by setting proper charging and discharging cut-off voltage. The vehicle-mounted unmanned aerial vehicle cluster system has the beneficial effects that through a vehicle-mounted unmanned aerial vehicle cluster scheme, the transportation efficiency of electric power materials in remote mountain regions is effectively improved, and meanwhile, comprehensive life guarantee and work support are provided for working field personnel. In addition, according to the technology, the energy supply process is optimized, and through a dynamic power regulation type charging management algorithm and a rapid charging technology, the charging efficiency of the battery is remarkably improved, and the service life of the battery is remarkably prolonged. And meanwhile, through advanced data acquisition and remote control capabilities, the accuracy and safety of operation are enhanced.

The invention discloses an operation method and system for distributed organic solid waste centralized treatment and quality improvement and application, and relates to the field of chemical engineering, the operation method comprises the following steps: respectively carrying out pyrolysis treatment on organic solid waste distributed in different areas to obtain combustible gas and solid combustible materials and / or pyrolysis oil, using the combustible gas as fuel for pyrolysis treatment, and using the solid combustible materials and / or pyrolysis oil for pyrolysis treatment; the solid combustible comprises carbon powder and / or pyrolysis residues; concentrating and gasifying the solid combustibles and / or pyrolytic oil obtained in different areas to obtain mixed gas, dedusting the mixed gas, and converting the dedusted mixed gas by using water vapor to obtain a hydrogen crude product; purifying the hydrogen crude product to obtain a hydrogen product; packaging, storing or conveying the hydrogen product; the method solves the problem that large-scale industrial treatment and economic benefit improvement are difficult to realize due to the fact that the organic solid waste in a distributed area or a remote area has the characteristics of multiple types, small quantity, dispersive distribution, high transportation, recovery and treatment cost and the like.

The invention relates to a multi-task allocation method and device for unmanned transportation equipment, equipment and a medium, and the method comprises the steps: constructing a multi-task combination model, and setting related constraint conditions; obtaining an initial population through chaotic mapping; performing rapid non-dominated sorting on the initial population, and based on a dynamic congestion degree sorting strategy, selecting and determining a plurality of parent populations through a champion; for each parent population, generating a new individual through adaptive crossover operation, and then performing mutation operation through Gaussian mutation to obtain a filial population; combining the parent population and the child population, performing rapid non-dominated sorting operation, and screening excellent individuals through a probability distribution function to obtain a new parent population; performing iterative computation based on the new parent population, and gradually optimizing a result to obtain an optimal multi-task allocation scheme; and performing multi-task allocation on the unmanned transportation equipment through the optimal multi-task allocation scheme. The method can improve the transportation efficiency, and balance the task scheduling complexity and the utilization rate of unmanned transportation equipment.

The invention discloses a logistics remote control method and system based on virtual reality, relates to the technical field of logistics transportation management, and reduces the possibility of human errors through automatic encasement scheme generation and path planning. The system automatically calculates and generates a boxing scheme according to goods characteristics and loading constraints, and the risk of manual operation errors is avoided. And if the efficiency evaluation index is higher than 0.8, the system confirms that the current scheme is the optimal scheme. The trajectory planning module combines the anchoring position of the target ship and the container yard position, generates a plurality of paths by using a dynamic path planning method, and calculates a trajectory coefficient and transportation time. The path planning method based on real-time data can flexibly cope with sudden changes in the transportation process, the transportation time is shortened, and it is ensured that tasks are completed in time. The dynamic path planning module can adjust the path and the position of a hoisting point in real time, and collision or other potential safety hazards possibly occurring in the operation process are avoided.

The invention provides a gallium oxide ultraviolet detector based on a difunctional self-assembly passivation layer and a preparation method thereof, the gallium oxide ultraviolet detector comprises a substrate layer, an oxidant layer and the difunctional self-assembly passivation layer which are arranged from bottom to top, and two sides of the difunctional self-assembly passivation layer are provided with metal electrodes in contact with a gallium oxide layer. Wherein the bifunctional self-assembly passivation layer comprises a first passivation layer and a second passivation layer which are arranged from bottom to top, the passivation material of the first passivation layer is a material for reducing surface defects of the gallium oxide layer, and the passivation material of the second passivation layer is a material for enhancing the ultraviolet photon absorption rate. Passivation materials with different functions are combined to form the dual-function self-assembly passivation layer, and the dual-function self-assembly passivation layer is adopted to perform passivation treatment on the gallium oxide ultraviolet detector, so that the performance of the gallium oxide ultraviolet detector is jointly improved from two aspects of reducing surface defects of gallium oxide and enhancing ultraviolet photon absorption.

The invention relates to the technical field of cold-chain logistics. The invention discloses a medical cold chain transport capacity planning system and method, and the system comprises a plurality of refrigerated transport units, each refrigerated transport unit comprises a refrigerated container which can maintain a plurality of different preset temperature intervals, and a transport task management module which is used for receiving and processing the drug information and transport requests of a plurality of drugs, the system comprises a transport task management module used for managing drug information and carrying out priority grading on the drug information and transport requests, a transport capacity demand prediction module used for predicting future transport capacity demands according to historical data, and a path optimization module used for carrying out transport arrangement according to the information provided by the transport task management module in combination with various comprehensive data. According to the medical cold-chain transportation capacity planning system provided by the invention, efficient, safe and reliable medical cold-chain transportation is realized by integrating a plurality of modules such as task management, capacity demand prediction, path optimization, real-time monitoring, alarm and user interface, and the high requirement of the modern medical industry on cold-chain logistics is met.

The utility model provides a dung cleaning truck capable of adjusting the posture of a dung scraping hopper, which comprises a collecting end and a feeding assembly, and the dung scraping assembly comprises a dung scraping shaft and the dung scraping hopper for carrying dung; the transmission shaft is connected to a shell of the manure cleaning vehicle, and the manure scraping shaft is connected with the transmission component. The sliding assembly is arranged at the end of the manure scraping shaft, a first sliding part of the sliding assembly always moves along the guide groove, a second sliding part alternately moves along the guide groove and the auxiliary guide groove, and the sliding assembly plays a role in guiding and limiting in the cyclic operation process of the manure scraping hopper; the turning groove in the guide groove protrudes towards the side, away from the auxiliary guide groove, of the guide groove, and when the first sliding part moves to the turning groove, the second sliding part rotates relative to the first sliding part, so that the centrifugal force of the excrement scraping hopper is improved, and rotation of the excrement scraping hopper is accelerated. The excrement cleaning truck capable of adjusting the posture of the excrement scraping hopper solves the technical problems that in the related technology, the posture of the excrement scraping hopper cannot be adjusted in the excrement conveying process, excrement dumping is not thorough, and the excrement cleaning efficiency is affected.

The invention relates to a folding house with an aluminum alloy frame structure, and belongs to the technical field of buildings. The invention relates to a multi-functional greenhouse which comprises a supporting mechanism, a bottom mechanism, a roof mechanism, a side face mechanism, a gable mechanism and a connecting mechanism, the supporting mechanism comprises a bottom supporting piece, a stand column piece and a top supporting piece, the lower end of the stand column piece is connected with the bottom supporting piece, and the upper end of the stand column piece is connected with the top supporting piece; the upper end of the side face mechanism is slidably connected with the roof mechanism, the lower end of the side face mechanism is slidably connected with the bottom mechanism, the two gable wall mechanisms are connected and hinged to the two ends of the stand column piece respectively, and the bottom mechanism and the bottom supporting piece, the roof mechanism and the top supporting piece and the gable wall mechanisms and the stand column piece are hinged through connecting mechanisms. The container house has the effect that the problems that a container house is heavy and not easy to disassemble and assemble are solved.

The invention provides a turnout snow melting system and a control method thereof. The system is characterized in that a monitoring center is connected with a cloud server; the cloud server is connected with the meteorological station and the Internet of Things; the turnout snow melting equipment is used for melting accumulated snow and / or an ice layer on a turnout steel rail in response to the control instruction sent by the monitoring center; the rail temperature monitoring sensor is installed on a turnout steel rail and used for monitoring the first real-time temperature of the turnout steel rail in real time; the meteorological station is mounted beside a station corresponding to the turnout steel rail and used for monitoring meteorological information of the station; the Internet of Things is used for acquiring weather forecast information; the monitoring center is used for determining a control instruction according to the weather forecast information, the weather information and the first real-time temperature; the control instruction is used for controlling at least one turnout snow melting device in the snow melting area. Therefore, the turnout working efficiency of the turnout snow melting equipment is improved, and the railway transportation efficiency is further improved.

The invention relates to the technical field of unmanned driving, automatic driving and unmanned vehicles, and discloses a speed control method and device of an unmanned vehicle and the unmanned vehicle. The method comprises the following steps: acquiring current position information of the unmanned vehicle, and acquiring a corresponding theoretical speed limit value according to the current position information; calculating an empirical speed value corresponding to the current position of the unmanned vehicle according to a predetermined empirical speed function; wherein the empirical speed function is determined based on driving data when the manned vehicle is driven to different positions; and generating a speed control strategy according to the theoretical speed limit value and the experience speed value, and controlling the driving speed of the unmanned vehicle based on the speed control strategy. According to the invention, by fusing static map speed limiting and driving experience data, more intelligent and efficient unmanned mine car speed control is realized.

The utility model provides a self-locking support for an unmanned aerial vehicle to transport a photovoltaic assembly, and particularly relates to the technical field of new energy assembly transportation. A self-locking support for an unmanned aerial vehicle to transport photovoltaic modules comprises a frame, a plurality of gear shafts are arranged on the frame, a telescopic spring is arranged at the top of the frame, the bottom end of the telescopic spring is connected with a lifting rod, a lifting rack is arranged on the lifting rod and meshed with teeth on the inner sides of the gear shafts, and a groove is formed in the frame. A sliding block is arranged on the groove and fixedly connected with the moving rod. The photovoltaic assembly self-locking support has the advantages that the design of the self-locking device is newly added, the photovoltaic assembly is placed on the self-locking support, binding is not needed, the photovoltaic assembly is directly fixed, the assembly binding time can be shortened, the device is a four-side contact assembly, the assembly can be evenly stressed in the transportation process, damage is reduced, and the service life of the photovoltaic assembly is prolonged. The unmanned aerial vehicle is used as a carrier for transportation, the unmanned aerial vehicle body can fly autonomously, and the transportation efficiency is improved.

The present invention relates to the technical field of packaging circulation box management, and in particular to a packaging circulation box management system and management method, in which a colored light strip is arranged on the outer edge of the packaging circulation box, and a storage unit, a Bluetooth unit and a box control unit are embedded in the box body, so as to realize real-time data collection and storage of the circulation box. The circulation box positioning module includes positioning communication devices on the site and the transport vehicle, which interact with the packaging circulation box data and transmit it to the intelligent cloud management module, so as to realize real-time tracking and monitoring of the circulation box and ensure the accuracy and timely update of the data. The intelligent cloud management module determines the use status of the circulation box according to the real-time data and makes dynamic adjustments and reasonable allocations. The circulation box is scheduled by a reinforcement learning algorithm, and a scheduling plan is generated based on the site demand, the current position of the circulation box and the real-time traffic conditions to improve the rationality of the site distribution of the circulation box. The abnormal alarm module detects the loss of the circulation box and issues an alarm to reduce losses and improve safety.

The invention provides a vehicle navigation path planning method and related equipment, and is applied to the technical field of data processing. The method comprises the following steps: processing target user information to generate navigation preference information and target logistics attribute information of a target user; processing the navigation preference information of the target user and the target logistics attribute information to generate a vehicle dynamic influence factor; processing the target road information to generate attribute information of the target road and traffic information matched with the target road information; processing the attribute information of the target road and the traffic information matched with the target road information to generate a target road dynamic influence factor; processing a preset vehicle navigation path generation model based on the training sample set to generate a target vehicle navigation path generation model; and processing the vehicle dynamic influence factor and the target road dynamic influence factor based on a target vehicle navigation path generation model to generate target navigation route information.

The invention discloses an intelligent warehousing operation auxiliary system and method based on mixed reality, and relates to the technical field of warehousing management, and the system comprises a storage stack point pre-screening module, an intelligent task planning module, a task execution monitoring module, an abnormal task execution adjustment module, and an optimal carrying equipment screening module. According to the method, the optimal storage stack point can be screened, the utilization rate of the storage space is improved, cargo extrusion or space waste caused by space mismatching is avoided, the transportation efficiency is improved, the energy consumption is reduced, abnormal conditions can be found in time, and the reliability of task execution is guaranteed. When abnormity occurs, early warning can be triggered quickly, the replacement mode of the carrying equipment can be judged reasonably, continuity and high efficiency of warehousing operation are ensured, and the overall operation efficiency of the intelligent warehousing system, the goods storage quality and the scientificity of management decision are improved.

The invention provides a vehicle transportation route hydrogen consumption simulation system and method based on multiple models. The method belongs to the technical field of new energy and simulation, and comprises the steps of based on a basic power demand model and a hydrogen consumption calculation model, collecting multi-source data in real time through a multi-source data collection network, combining the multi-source data with historical data, optimizing an existing model through a machine learning algorithm, and updating the hydrogen consumption calculation model. By collecting multi-source data in real time and optimizing an existing model in combination with historical data and a machine learning algorithm, the hydrogen consumption condition can be predicted more accurately. Meanwhile, by collecting new data of external environmental factors in real time, the environmental influence model is optimized, the hydrogen consumption calculation result is further corrected, and the simulation precision is improved.

The present invention provides a vehicle-road cooperative control method, device, equipment and readable storage medium, including: when the distance from a bus to a target station is less than a preset distance, if the number of passengers getting off the bus at the target station is zero, obtaining the number of passengers getting on the bus at the target station; determining the theoretical time for the bus to enter and exit the target station according to road condition information; determining the theoretical number of passengers getting on the bus according to the theoretical time; detecting whether the number of passengers getting on the bus at the target station is less than the theoretical number of passengers; if the number of passengers getting on the bus at the target station is less than the theoretical number of passengers, outputting a prompt that the bus does not stop at the target station; if the number of passengers getting on the bus at the target station is not less than the theoretical number of passengers, outputting a prompt that the bus stops at the target station. Through the present invention, the selectivity of passengers is increased, thereby improving the transportation efficiency of bus lines.

The invention relates to the technical field of transportation management systems, and discloses an underground auxiliary transportation system based on vehicle-road cooperative localization, which comprises a data acquisition unit, a data processing unit, a data analysis unit, a data transmission unit, a barrier gate control unit and a vehicle-mounted control unit. Corresponding control signals are generated according to different conditions, safe driving of vehicles and orderly passing of roadways are effectively guaranteed, traffic signal lamps and vehicle-mounted warning lamps are controlled through the barrier gate control unit and the vehicle-mounted control unit respectively, intuitive and clear instructions are provided for drivers, the risk of accidents is reduced, and the traffic safety is improved. For a narrow one-way roadway, a reasonable locking function and a priority entry analysis mechanism are set, conflicts and congestion of vehicles in a narrow space are avoided, transportation safety and high efficiency under special conditions are ensured, and adaptability and flexibility of the system are improved.

The invention belongs to the field of electrochemical sensors, and relates to an electrochemical sensor for high-sensitivity detection of carbendazim and a preparation method of the electrochemical sensor. The surface of a glassy carbon electrode (GCE) is modified with an LDMS-CCN-GCT nanocomposite material prepared from dendritic large-aperture mesoporous silica, conductive carbon black nanoparticles and graphitized carbon nanotubes, and a CCN-GCT-LDMS / GCE working electrode is formed. The preparation method comprises the following steps: firstly, uniformly dispersing CCN and GCT in an N, N-dimethylformamide solution through magnetic stirring in an ultrasonic environment, wherein the CCN and the GCT are equal in mass; then, adding LDMS into the solution, and carrying out ultrasonic dispersion to obtain a uniformly mixed CCN (at) GCT (at) LDMS suspension; and finally, dispensing the uniform suspension onto the surface of GCE, and drying under an infrared lamp to prepare the working electrode CCN (at) GCT (at) LDMS / GCE modified by the CCN (at) GCT (at) LDMS nano composite material. Based on the synergistic effect generated by LDMS and CCN-coated GCT, the CCN-coated GCT-coated LDMS / GCE sensor is high in sensitivity, the detection limit can reach 7.36 nM, and the CCN-coated GCT-coated LDMS / GCE sensor has excellent carbendazim sensing detection performance.