352 results about "Transit bus" patented technology

The invention discloses a bus and station interactive scheduling method and system based on V2X and deep reinforcement learning decision, a medium and equipment, and the method comprises the steps: collecting bus operation dynamic data, station passenger flow and environment data in real time, and combining V2X network interaction information to construct a full-dimension perception system; a deep reinforcement learning model is adopted for dynamic decision making, intelligent closed-loop control of vehicle scheduling, station service and traffic signal cooperation is achieved, the bus punctuality rate is remarkably increased, the waiting time of passengers is shortened, operation safety is guaranteed through active early warning of abnormal conditions, and intelligent upgrading of a bus system from passive response to active prevention is achieved.

The invention discloses an automatic driving bus collaborative formation dynamic scheduling method, which comprises the following steps of: after introducing a vehicle formation operation, constructing a vehicle energy consumption model based on vehicle specific power, and measuring the vehicle operation energy consumption of an automatic driving bus formation in any formation mode; in an intelligent network connection environment, based on a rolling time domain optimization framework, a Markov decision process model is constructed, and an automatic driving bus collaborative formation dynamic scheduling problem is explained; defining a state variable and a decision variable of the Markov decision process model, and determining constraint conditions of related variables and a target function of the Markov decision process model; the decision space of the Markov decision process model is reduced, and an approximate dynamic programming algorithm is used to solve the automatic driving bus collaborative formation scheduling problem; a multi-step look-ahead strategy based on dynamic planning is provided, the convergence efficiency of an approximate dynamic planning algorithm is improved, and an automatic driving bus collaborative formation optimization scheduling scheme is obtained. And the automatic driving bus capacity utilization rate is improved.

The embodiment of the invention provides a training method of a signal lamp control model, a signal lamp control method, a device, equipment, a medium and a product, and relates to the technical field of urban road traffic. The method comprises the following steps: acquiring a plurality of first traffic data, constructing a state characterization matrix and a reward function according to the plurality of first traffic data, and performing model training according to the plurality of first traffic data, the state characterization matrix and the reward function to obtain a signal lamp control model. According to the method, in a model training process, a state representation matrix is utilized to dynamically quantify passing priorities of buses in all directions, and meanwhile, a reward function is utilized to guide the model training process, so that a signal lamp control model obtained through training can recognize and preferentially respond to bus passing demands, and signal lamp actions are dynamically adjusted; therefore, the collaborative optimization of multi-direction bus priority requests in a complex scene is realized, and the coordination capability and response efficiency of a bus priority system in a complex urban traffic environment are improved.

The invention relates to the technical field of urban traffic management and carbon emission reduction accounting, and provides a bus travel carbon emission reduction accounting method fused with Beidou spatio-temporal data, which comprises the following steps: acquiring spatio-temporal trajectory data based on a Beidou satellite navigation system, and constructing a passenger-trajectory-station three-dimensional correlation model for passenger flow analysis; constructing a passenger transfer analysis system based on the passenger flow analysis result; constructing a dynamic'perception-prediction-optimization 'dynamic scheduling optimization system for passenger flow detail analysis on the basis of space-time trajectory data and a reinforcement learning algorithm; and constructing a mileage-frequency distribution model and a station efficiency evaluation model based on the spatio-temporal trajectory data, respectively generating a trajectory matching optimization strategy and a differentiated station optimization scheme, and realizing adaptive optimization of the public transportation system under dynamic demand change. Compared with a traditional static data dependence method, the method achieves the dynamic and fine-grained monitoring of the operation process of the public transportation system, and effectively improves the timeliness and integrity of data.

The invention relates to the technical field of intelligent monitoring, in particular to an intelligent bus kiosk monitoring method and system with an abnormal behavior intelligent monitoring function. The method comprises the following steps: acquiring multi-source monitoring data of a target bus kiosk, and based on the multi-source monitoring data, performing character and article linkage behavior analysis on the multi-source monitoring data to generate an entity interaction feature set; extracting a timestamp sequence and a space coordinate sequence based on the entity interaction feature set, and generating a space-time parameter set based on the timestamp sequence and the space coordinate sequence; based on the entity interaction feature set, according to the space-time parameter set, analyzing whether the current entity interaction feature has an abnormal behavior in the corresponding bus kiosk space-time scene, and if yes, extracting abnormal behavior information; and according to the abnormal behavior information, determining and outputting an abnormal early warning signal. According to the method, the abnormal characteristics of the behaviors under the bus kiosk are analyzed in a multi-dimensional mode, safety early warning is achieved, and the public traffic order is guaranteed.

The invention relates to the technical field of image or video recognition or understanding, and discloses a bus driver driving state evaluation method, which comprises the following steps: acquiring a face image, an electrocardiosignal and voice audio data of a bus driver, performing timestamp alignment and preprocessing, and constructing a multi-mode driving state data set; extracting multi-modal features of the collected data, and mapping the multi-modal features to a unified feature space; fusing multi-modal features through a cross-modal attention mechanism, dynamically adjusting attention weight based on an emotional change difficulty index, and extracting emotional change key features; and predicting a two-dimensional continuous emotion value of the driver by using the fusion features, calculating a long-time-sequence emotion driving risk score based on an emotion stimulation dynamic model, and performing evaluation and early warning of a driving state. The problems of single-mode analysis, lack of long-period early warning and driving state static recognition in the prior art are solved, and the purposes of accurate evaluation, high safety, multi-mode fusion and long-time-sequence prediction are achieved.

The invention discloses a subway passenger flow prediction method, system and device considering subway-bus transfer, and a medium, and the method comprises the following steps: obtaining the historical passenger flow of a subway station in a certain region within a period of time and the historical passenger flow of a corresponding bus station around each subway station, and forming a data set; dividing the data set into a training set and a test set according to a time sequence; constructing a dynamic space-time decomposition and fusion network, wherein the dynamic space-time decomposition and fusion network comprises a time sequence decomposition module, a dynamic graph convolution module, a gated cross-modal attention fusion module and a dual-path space-time adaptive fusion module; and training the dynamic space-time decomposition and fusion network by using the training set and the test set, and predicting the subway passenger flow volume by using the optimized dynamic space-time decomposition and fusion network by using a mean absolute error, a root-mean-square error and a weighted mean absolute error percentage as performance evaluation indexes. The prediction precision is improved, and the practicability and generalization ability of the model are enhanced.

The invention belongs to the technical field of urban public transport management, and particularly relates to an electric public transport scheduling and charging scheduling method considering source-load double-side fluctuation. The objective of the invention is to solve the problems that a public transportation system has source-load double-side fluctuation due to the intermittency of existing source-side photovoltaic power generation and the randomness of load-side public transportation operation energy consumption, so that the charging demand and the power supply capacity in part of time periods are not matched, the operation task cannot be completed in time, and the energy storage utilization efficiency is low. The invention provides an electric bus scheduling and charging scheduling method considering source-load double-side fluctuation. The method comprises the steps of calculating bus battery remaining capacity based on an optimization time period; calculating the remaining capacity of the energy storage battery based on the remaining capacity of the bus battery; based on the bus battery remaining capacity and the energy storage battery remaining capacity, constructing a chance constraint planning model; and solving the opportunity constraint planning model to obtain an optimal feasible solution which comprises an electric bus scheduling and charging scheduling scheme.

The invention relates to an intelligent scheduling decision support method and system for a community bus special line, and solves the problems of unreasonable transport capacity distribution and insufficient key travel demand guarantee caused by incapability of distinguishing travel purposes in an existing scheduling method, and the method comprises the steps: firstly, integrating card swiping, reservation and static data to construct a travel demand data set; secondly, through a clustering algorithm, identifying travel destination modes and extracting multi-modal features, generating a prediction report containing a passenger flow thermodynamic diagram and a space-time probability matrix through prediction of an adaptive multi-head attention model, and further calculating service priorities of the modes; then, a decision framework coordinated by route planning and station jump decision intelligent agents is constructed, a global reward function is endowed with differentiated weights according to priorities, and a dynamic scheduling scheme is jointly generated; the method has the following effects: community bus accurate scheduling based on travel purpose identification and priority guarantee is realized, and transport capacity sharing is upgraded to on-demand intelligent distribution.

The invention discloses a bus shift extraction optimization method based on multi-dimensional score driving, and relates to the field of urban public traffic scheduling management, and the method comprises the following steps: initializing shift extraction parameters, determining a shift extraction target, defining time period features, and setting a score weight and a penalty coefficient; constructing a shift extraction optimization mathematical model, including defining decision variables and establishing an objective function and constraint conditions thereof; respectively constructing a multi-dimensional scoring system and a constraint verification strategy by utilizing the objective function and the constraint conditions thereof; generating candidate shift drawing schemes, calculating a comprehensive score and selecting an optimal shift drawing scheme; performing iteration processing on the optimal shift extraction scheme in combination with loop control and a scheme rollback strategy to obtain a final shift extraction scheme; and verifying and counting the final shift drawing scheme, and generating a corresponding shift drawing report. On the premise that operation balance and service integrity are ensured, global optimal selection of the shift drawing scheme is achieved, and the intelligent level and operation efficiency of bus dispatching are remarkably improved.

The invention discloses a collaborative operation optimization method for a bus and subway integrated network. The method comprises the following steps: S1, carrying out collection and standardization processing on topological structure data, train operation timetable data and passenger travel demand data; s2, completing the construction of a multi-layer coupling space-time network; s3, K short path searching is executed, and a passenger reachable path set is generated; s4, carrying out reachability verification on the passenger path selection set under a train operation rule; s5, a scheduling scheme is formed based on the distribution probability output by the Logit model; and S6, inputting the time sequence operation data into the improved Mamba network, performing constraint check and correction on the line departure logarithm and the departure moment of the first station, and forming an evaluation index for optimizing the objective function. According to the method, collaborative optimization of the train operation time sequence and the passenger travel demand under the bus and subway integrated line network is achieved, and the method is suitable for intelligent scheduling and dynamic passenger flow regulation and control scenes of a large-scale urban rail transit system.

The express cabinet comprises an unmanned aerial vehicle intelligent connection express cabinet body arranged at a bus station, an unmanned aerial vehicle take-off and landing platform is arranged on the unmanned aerial vehicle intelligent connection express cabinet body, an intelligent express delivery unmanned aerial vehicle is arranged at the top of the unmanned aerial vehicle take-off and landing platform, and a parcel distribution mechanism is arranged in the unmanned aerial vehicle intelligent connection express cabinet body. The unmanned aerial vehicle take-off and landing platform is connected to the top of the unmanned aerial vehicle intelligent connection express delivery cabinet through a connecting piece and used for allowing an unmanned aerial vehicle to stay and work, and the unmanned aerial vehicle intelligent connection express delivery cabinet is arranged at the position of a bus station. The surface of the unmanned aerial vehicle intelligent connection express cabinet is provided with the bus information electronic display board, so that a bus station is formed, and the mode of combining the unmanned aerial vehicle intelligent connection express cabinet and the bus station is integrated, so that public resources are integrated and utilized.

The invention relates to the technical field of intelligent bus prediction, in particular to an intelligent bus kiosk real-time bus prediction method and system. The method comprises the following steps: acquiring a bus route vector data set, and determining a bus operation chain topology table according to the bus route vector data set based on a bus network spatio-temporal topology coupling strategy; acquiring a real-time severe weather influence data set, and constructing a bus station pressure propagation network based on a traffic node load distribution strategy according to the real-time severe weather influence data set and the bus operation chain topology table; on the basis, predicting dynamic pressure influence on each bus station and each bus route caused by negative influence caused by real-time severe weather and a networked conduction path of the dynamic pressure influence, and determining a dynamic coupling disturbance conduction network; and according to the dynamic coupling disturbance conduction network, carrying out real-time prediction on the bus condition in the bus operation chain topology table, and outputting and pushing prediction information. According to the invention, the operation state of the bus in the dynamic scene is accurately predicted.

The invention relates to the technical field of intelligent traffic system (ITS) and urban public traffic scheduling control, in particular to an intelligent bus scheduling method based on multi-source data fusion, which comprises the following steps: S1, a central scheduling platform receives and stores multi-source data; s2, obtaining a fusion feature sequence; s3, sending to a calibrated demand prediction model to obtain a point prediction and demand interval; s4, constructing a transport capacity interval with an upper bound and a lower bound based on the vehicle availability, the driver shift, the maximum passenger capacity of the single vehicle and the road section speed distribution; s5, calculating overlapping ratio = intersection / prediction interval length; when the vehicle number is lower than the threshold value, distributed robust multi-target scheduling optimization of an ambiguity set defined by the Wasserstein radius is solved, the departure interval and the vehicle distribution number are updated, and the target is that the vehicle waiting time condition is weighted in a risk value and an empty driving rate, and the vehicle number, the employees, the departure interval and the insertable control point constraint are met; and S6, issuing an instruction and executing according to a vehicle positioning and control point arrival event. And unified modeling and robust triggering in the same space-time key interval are realized.

The invention provides a bus signal priority control method considering coordination of a phase deviation state, and belongs to the technical field of vehicle-road cooperation. The method comprises the following steps: constructing an end-side-cloud architecture system for an intersection implementing bus signal priority control, acquiring basic data of the intersection and buses, establishing a signal priority control method considering coordination phase deviation state constraint, and calculating the maximum bus signal priority time of the intersection. And signal timing schemes under different priorities are generated in advance according to the priority time, so that the accuracy and the real-time performance of bus priority execution are ensured. According to the invention, a reliable control means for passing without stopping is provided for buses, interference to social vehicle passing benefits is reduced, the coordination offset time is fully utilized, the success rate of bus signal priority control is increased, the riding experience of passengers can be improved, the energy consumption of the buses can be reduced, and the cost is reduced. The method is of great significance to further development of an urban public transport system.

The invention discloses an intelligent bus operation and maintenance task scheduling method based on an edge intelligent prediction model, and belongs to the field of vehicle operation and maintenance scheduling, and the method comprises the following steps: carrying out the segment division of a continuous sampling sequence according to a preset time window, extracting derived feature parameters used for operation and maintenance risk discrimination and prediction inference in each segment, and carrying out the prediction of the operation and maintenance risk; and packaging the derived feature parameters and data quality information corresponding to the derived feature parameters to generate a feature certificate, performing comparable correction on the derived feature parameters based on the data quality information in the feature certificate, and obtaining a certificate-driven operation and maintenance risk judgment result based on a derived feature drift index. And generating a model input sequence and inputting an edge intelligent prediction model to obtain a model-driven operation and maintenance risk judgment result, thereby solving the problems of risk judgment fluctuation and operation and maintenance scheduling jitter caused by the fact that different report strategy gears are easy to introduce derived feature offset in the prior art.

The invention relates to a vehicle-road collaborative non-blind area sensing system for intelligent network connection buses, which belongs to the technical field of intelligent traffic and vehicle-road collaborative sensing, and is characterized in that based on multi-dimensional data of vehicle side and road side sensors, a vehicle sensor sensing range, a fixed bus route and real-time pose information are combined; a blind area target is sensed and predicted in real time, the potential risk of the blind area target to a bus is dynamically evaluated, high-risk information is transmitted back to a bus end, non-blind area global environment sensing and early warning are achieved, a reliable sensing basis is provided for follow-up functions such as intelligent scheduling, safety early warning and automatic driving, and the system is suitable for popularization and application. And the sensing safety and the risk early warning capability of the bus in the complex urban road section are obviously improved.

We provide a traffic management system, traffic management method, and traffic management program suitable for bus operations. [Solution] The operation management system includes: a setting unit that sets multiple location areas surrounded by multiple location information points in a continuous sequence in the direction of travel of the bus at the entrance and exit of a traffic facility where the bus is parked; an acquisition unit that acquires bus location information relating to the position of the bus running with a positioning sensor and bus time information relating to the time when the position is measured; a determination unit that determines whether the bus has passed through a location area based on the travel trajectory consisting of multiple bus positions recorded in the bus location information; and a recording unit that, if the determination unit determines that the bus has passed through a location area, records the bus's travel time based on the time recorded in the corresponding bus time information when the bus's position was measured.

The invention discloses a bus shelter plate laser cutting device, and particularly relates to the technical field of cutting devices.The bus shelter plate laser cutting device comprises a cutting chamber, a mounting frame is arranged in the cutting chamber, a first cutting assembly and an air blowing assembly are sequentially mounted at the top of an inner cavity of the cutting chamber, and two symmetrical auxiliary assemblies are arranged at the top of the inner cavity of the cutting chamber; a second cutting assembly is arranged below the mounting frame. The rotating plate and the sliding roller move along the limiting groove, and guide constraint of the straight guide rail, the sliding block and the sliding rod is matched, so that the first laser cutting structure accurately completes U-shaped seam cutting; through cooperation of a push rod, a vertical baffle and the like, left-right position adjustment of a first laser cutting structure is achieved, the two cutting ranges are overlapped, then a U-shaped groove meeting the assembly requirement is formed through cutting, through cooperation of an air blowing assembly and a rack, a first air bag is extruded to spray out nitrogen during cutting, an inert environment is formed around a cutting head, and oxidation of the cut position of a plate is avoided; during resetting, the second air bag blows dry air to form a positive pressure area, and pollutants are prevented from flowing backwards.

The invention belongs to the technical field of smart city infrastructure, and discloses a bus station smart cabin device integrated with a low-altitude aircraft multifunctional use scenario, which comprises a smart cabin, a low-altitude aircraft support system, a smart logistics system, a smart traffic management system and a power supply system, and is characterized in that the smart cabin comprises a passenger service area and a functional area; a parking platform is arranged in the functional area; the low-altitude aircraft support system comprises a navigation module, an obstacle avoidance module, a communication module and an energy management module; the intelligent logistics system comprises an intelligent sorting module, a distribution module and a data management platform. The intelligent traffic management system comprises a traffic monitoring module and a data analysis module. The system has the beneficial effects that multiple functions are creatively integrated into a whole, and the system adapts to the intelligent construction requirements of infrastructures of different cities; good economic benefits, social benefits and environmental benefits can be generated, and the method has a wide application prospect.

The invention discloses a public transport vehicle and driver joint scheduling method based on safety consideration, and the method comprises the following steps: S1, building a vehicle scheduling network flow model related to the travel of public transport vehicles based on a space-time network framework, and considering the constraint condition of a multi-parking-lot public transport vehicle scheduling problem; s2, based on survival analysis, according to historical bus travel information and driver driving risk early warning information, establishing driver survival functions under different driving characteristics; s3, designing a driving section cutting strategy and a driving section connection strategy for a vehicle task chain in the vehicle scheduling network flow model, and generating a feasible driver shift plan; s4, matching the driver survival function with the driver shift plan, and establishing a vehicle and driver joint scheduling model by considering the constraint condition of the driver scheduling problem; and S5, performing rolling solution on the vehicle and driver combined dispatching model by using a heuristic algorithm to obtain a vehicle and driver combined dispatching scheme based on safety consideration.

This invention discloses an intelligent terminal system that changes the interface skin according to environmental changes, relating to the field of communication technology. The system includes the following steps: acquiring the driver's gender information and determining the main color scheme of the interface based on the gender information; collecting the driver's facial emotions and generating a face recognition result; collecting the brightness value inside the bus and comparing the brightness value with a set threshold to obtain the current brightness level; acquiring the current location information of the bus and connecting to a server to obtain the current weather conditions based on the location information; comprehensively analyzing the obtained data and searching and configuring it with an interface database, outputting the configured result, and changing the current interface skin to the updated interface skin to complete the skin change; judging the driver's emotional state based on the skin change result and providing reminders to the driver accordingly. This invention not only changes the traditional impression left by in-vehicle terminal devices on customers but also improves vehicle driving safety and enhances user satisfaction.

The invention relates to a collaborative optimization method for charging station facility configuration and electric bus charging scheduling. The method comprises the following steps: step 1, collecting data; 2, calculating the carbon emission cost and the charging cost of the vehicle charged from the power grid; 3, calculating the photovoltaic power generation carbon emission cost and the charging cost of the charging station; step 4, calculating photovoltaic internet surfing income of the charging station; 5, photovoltaic panels and energy storage capacity configuration limits of all stations are calculated; step 6, constructing a joint optimization model of multi-station photovoltaic energy storage charging station facility configuration and electric bus charging scheduling; and 7, solving the joint optimization model established in the step 6, and obtaining the optimal number of photovoltaic panels configured at different stations, the optimal energy storage battery capacity configuration configured at different stations and different vehicle charging scheduling plans. Compared with the prior art, the method has the advantages that the utilization rate of the stations is improved, local stations are prevented from being overloaded, resources of other stations are prevented from being idle, and the photovoltaic power generation consumption condition is improved.

This application discloses a vehicle regulation method and related equipment, belonging to the field of traffic safety technology. The method includes: acquiring first road information of a non-bus lane and second road information of a bus lane within a target road segment; predicting a first driving speed of a non-bus in the non-bus lane based on the first road information; predicting a second driving speed of a non-bus in the bus lane based on the second road information; generating a regulation strategy based on the first and second driving speeds and sending a regulation command to a target vehicle, wherein the target vehicle is any non-bus within the target road segment. This method considers the impact of different road conditions on vehicle driving, making the generated regulation strategy more reasonable and improving road utilization.

The invention discloses a bus resource dynamic scheduling method, device and system, and a storage medium, a bus scheduling problem is modeled as an optimization problem covering a plurality of travels, stations, vehicles and drivers, and based on a two-stage decoupling heuristic scheduling algorithm, through the cooperation of two stages of global resource allocation and local resource scheduling, the dynamic scheduling of bus resources is realized. And efficient configuration of resources is realized. By adopting the technical scheme of the invention, the operation cost is reduced, and the riding experience is improved.

The invention provides a bus operation method and system based on a modularized automatic driving vehicle, and relates to the technical field of intelligent traffic management, and the method comprises the steps: obtaining the historical riding data of a passenger; a bus operation model is constructed based on preset modularized automatic driving vehicle information, the bus operation model comprises a vehicle and a station, and the vehicle is composed of a power unit and a plurality of cabins; constructing an average total cost function of bus operation based on the historical riding data of the passengers and a preset cost calculation formula; by taking the minimization of the average total cost function as an expected target, carrying out optimization solution on the bus operation model to obtain the optimal cabin density, the optimal station spacing and the optimal marshalling cabin number; and carrying out bus operation based on the optimal cabin density, the optimal station spacing and the optimal marshalling cabin number. According to the invention, the problem that the existing method cannot obtain the optimal bus operation planning scheme under intelligent traffic is solved.

The invention discloses a liftable barrier-free ramp system for an island-type bus station and a control method, the liftable barrier-free ramp system is arranged on a non-motorized vehicle lane between the island-type bus station and a sidewalk, and the liftable barrier-free ramp system comprises a foundation frame, a passage flat slope surface, an uphill slope surface and a downhill slope surface; a plurality of vertical lifting devices are arranged between the passing flat slope surface and the foundation frame; one end of the upslope slope surface and one end of the downslope slope surface are connected with the two ends of the passing flat slope surface respectively in a hinge connection mode, and the other ends are connected with the corresponding ends of the foundation frame through telescopic supporting sleeves; wheelchair and vehicle waiting areas are arranged at the positions, corresponding to the two sides of the flat passing slope, of the island type bus station and the sidewalk. The positions, close to the uphill slope face and the downhill slope face, of the non-motorized vehicle lane are each provided with a plurality of flickering warning lamps evenly distributed in the width direction. The problem of curb height difference from a sidewalk to a platform is solved, a barrier-free path for passing through the platform is created, and the experience of height difference sensitive passengers on the island type platform is improved.

The application discloses a kind of ticket box detection method and system, it is related to bus ticket box detection processing technical field, the method includes: through the vehicle-mounted machine on vehicle, the empty box card data of empty box is collected;Through the vehicle-mounted machine, the heavy box card data of heavy box is collected;The vehicle-mounted machine sends the empty box card data, heavy box card data and vehicle data to the background server;The background server carries out data processing according to the data processing rule received data, to obtain the result data of box collection.This application can automatically collect and record the card data of empty box and heavy box, without manual record processing, and can automatically count and process the result of box collection of corresponding vehicle, improve the efficiency of box collection data processing, conducive to the development of box collection statistical work.

This application relates to the technical field of parking garages, improving upon the complex structure of existing multi-level bus parking garages. It discloses a multi-level bus parking garage, including a vehicle platform and multiple vertically arranged lifting columns. Connecting mechanisms and driving mechanisms that drive the connecting mechanisms to slide vertically along the lifting columns are connected to the lifting columns. The driving mechanism includes a driving rod connected to the connecting mechanisms and a linear drive component that drives the driving rod to move linearly. All connecting mechanisms are connected to the vehicle platform. A fall prevention mechanism is provided between the connecting mechanisms and the vehicle platform to prevent the vehicle platform from falling after detaching from the connecting mechanisms. This application allows for vehicle parking and retrieval simply by moving the vehicle platform up and down. The entire multi-level parking garage has a simple structure, low cost, and convenient and quick parking and retrieval processes. Furthermore, the fall prevention mechanism reduces the possibility of the vehicle platform being subjected to excessive external force, causing it to detach from the connecting mechanisms and resulting in a vehicle falling and colliding with a vehicle below, thus ensuring high parking garage safety.

The application provides a bus priority method based on a game coordination mechanism, comprising the following steps: constructing a traffic game model between a bus and other vehicles, considering a strategy space and an utility function of each bus at an intersection, and the utility function in the model can reflect a traffic efficiency of the bus; according to traffic states of the bus and the other vehicles, an optimization algorithm is used to solve the game model, and an optimal strategy of the bus is obtained; according to the optimal strategy of the bus, a traffic signal timing is dynamically adjusted, and a bus priority strategy is provided; in addition, a special situation that different phases of the intersection have buses arriving at the same time can be handled, and the bus can realize priority passing at the intersection, while reducing the influence on the other vehicles. The method of the application not only considers the priority of the bus, but also takes into account the traffic demand of the other vehicles, and realizes the target of traffic coordination.