16 results about "Urban bus" patented technology

The application relates to the technical field of urban bus line network and timetable integration optimization, and particularly discloses a bus line network and timetable integration optimization method and device based on graph reinforcement learning. The method is used for generating a bus line network structure and a timetable in a multi-mode public transport network containing BRT, subway and shared bicycles. Firstly, a multi-mode public transport road network is constructed, and passenger flow demand data is obtained; a bus line network design and a synchronous timetable compilation process are modeled as a Markov decision process; according to a current bus line network state, the road network is reconstructed into a heterogeneous graph containing time sequence evolution arcs and spatial topology arcs, and a double attention graph neural network is used to extract candidate node features; according to the node features, an action is selected through an action network, and the bus line network state is updated; the node feature extraction, the action selection are repeated until a termination condition is met, and the bus line network structure and the line timetable are output. The application can generate a bus line network and timetable which are more coordinated with other public transport modes, and reduce the operation cost of bus enterprises and the travel and transfer time of passengers.

This application relates to the field of vehicle control technology, and provides a method and system for tracking the trajectory of urban buses based on BeiDou positioning. The method includes: acquiring vehicle driving motion information, vehicle BeiDou positioning information, and vehicle IMU positioning information; identifying multiple candidate road segments from preset map data based on the vehicle's BeiDou positioning information and IMU positioning information, and acquiring road geometric feature information for each candidate road segment; determining the vehicle's expected road segment from the multiple candidate road segments based on the vehicle's driving motion information and the road geometric feature information of the multiple candidate road segments, and determining the vehicle's drive control command based on the road geometric feature information of the expected road segment. This solution can improve the accuracy of vehicle control.

The invention discloses an optimal touring path optimization selection method for an urban landmark group based on behavior preference, and the method comprises the steps: obtaining urban landmark positions and urban road network data, calculating the shortest touring path in all touring sequences, and taking the shortest touring path as an alternative path; the selection identification degree of the alternative paths is calculated, and sightseeing visual angle attraction evaluation is carried out; acquiring urban bus station data, and carrying out bus connection accessibility evaluation on alternative paths; urban street building distribution and function attribute data are obtained, and interface function richness evaluation of alternative paths is carried out; acquiring point density data of the urban population, and evaluating the visit space vitality of the alternative paths; and finally, on the basis of user behavior preference requirements, comprehensive weighted evaluation is carried out from four dimensions, and the path with the highest comprehensive score is determined as the optimal recommended path. According to the invention, a more comprehensive and personalized urban landmark group touring path can be generated.

The invention provides an urban bus health degree evaluation system based on big data, which constructs a data-driven health degree evaluation model by extracting bus operation multi-source data, and realizes model calculation and evaluation. The method specifically comprises three cores of bus big data extraction and preprocessing, health degree evaluation model construction and model calculation and comprehensive evaluation. In order to solve the problems that an existing vehicle health degree evaluation method is high in theorization and insufficient in practicability, a health degree evaluation model which is close to actual business and can be expanded is constructed on the basis of big data analysis. The model can efficiently process mass data of a city-level public transportation system, realizes dynamic quantitative evaluation of the vehicle health state, and is beneficial to providing scientific vehicle operation and maintenance decision support for enterprise managers.

The application discloses a kind of urban public transport corridor design methods based on multi-objective optimization model, this method can fuse city land use POI (Point of Interest, point of interest) data, resident trip OD (Origin-Destination, origin-destination) data and corridor construction cost, to realize the line selection and level planning of multi-angle consideration city public transport corridor.The present application is based on multi-objective optimization theory, forms the mathematical model of public transport corridor design, compared with the experience judgment method and two-step clustering method widely used at present, the method can be based on existing traffic demand and future development trend, obtain more accurate and reasonable public transport corridor design result, greatly improve the efficiency of urban public transport corridor planning, reduce the time and cost of artificial design.

The application discloses a kind of urban public transport network optimization method considering scheduling, comprising: processing bus card data, vehicle shift data, line site data, analyze the influencing factors in the process of passenger line;For the influence factor analysis of passenger riding habit, vehicle shift, analyze the influence relationship of the selection of each type of passenger line and riding habit, respectively with the same bus station OD inter-route selection proportion and Person correlation coefficient define its correlation degree, obtain the Pearson correlation coefficient of the selection of different types of passengers and shift;Through the actual-virtual bus network construction mode, construct line and scheduling synchronous optimization model, optimize the output optimization result by the line site layout and vehicle scheduling synchronous optimization by the constructed model.The application considers the influence of vehicle scheduling in the process of public transport network optimization, optimizes the layout of public transport network and vehicle scheduling simultaneously;It is convenient for passenger travel, reduces travel cost.

The invention relates to a hybrid electric vehicle charging scheduling system and method based on multi-agent near-end strategy optimization, and belongs to the field of intelligent traffic systems and electric vehicle charging scheduling. The method comprises the following steps: firstly, constructing a hybrid charging framework integrating a fixed charging station and a mobile energy distributor; secondly, establishing a refined traffic and energy consumption model considering vehicle following behaviors, road congestion and urban bus type MED operation conditions; then, a multi-agent near-end strategy optimization algorithm is adopted, a central controller serves as a global coordinator to be responsible for task scheduling and load balancing, and multi-agent combined optimization of electric vehicle charging mode selection and a driving path is achieved; and finally, converting an original complex mixed integer nonlinear optimization problem into an intelligent decision problem which can be solved online through a multi-agent reinforcement learning framework which is trained in a centralized manner and executed in a decentralized manner. According to the invention, the charging time, the driving energy consumption, the driving distance and the charging cost of the electric vehicle in the hybrid charging system can be effectively reduced.

The invention relates to an urban bus priority active management and control method and system based on vehicle and road cloud integration. The method comprises the following steps: acquiring road network data in a research area; dividing a core area boundary and a core area of the research area; dividing a peripheral traffic control sub-area and a peripheral critical line; constructing a three-dimensional macroscopic fundamental diagram model, and determining a traffic flow control threshold value of social vehicles adjacent to the intersection; predicting the traffic flow of social vehicles and public traffic vehicles at the upstream intersection; and comparing the social vehicle flow predicted value with a traffic flow control threshold value, and formulating a management and control strategy including an optimal vehicle route according to a comparison result, the public transport vehicle flow predicted value and the road network data. According to the invention, social vehicles can be actively guided to enter a core area with an optimal route, regional management is realized with less data processing amount, traffic congestion of a large area is avoided, the problems of urban road congestion and space-time resource waste are solved, and the efficiency of urban bus operation is improved.

The application discloses a kind of bus departure timetable optimization method considering multiple bus lines transfer in charging station, first input and electric bus charging transfer various parameters, with cost-related various parameters;Second, the charging demand of each vehicle and the passenger transfer demand between each line are calculated, and the selection constraint of electric bus charging station and the charging transfer constraint in charging station are established;Finally, with the minimum bus operation cost and the maximum transfer passenger number as objective function, with bus scheduling scheme and the departure timetable of each line bus as decision variable, the bus scheduling model of multiple bus lines transfer in charging station is established.The application can meet the charging demand of bus and the passenger transfer demand in charging station simultaneously by reasonably scheduling the bus needing charging according to certain departure time, can increase the attraction of bus charging to transfer passengers, and promote the electrification process of urban bus.

This application relates to the field of vehicle control technology, and provides a method and system for tracking the trajectory of urban buses based on BeiDou positioning. The method includes: acquiring vehicle driving motion information, vehicle BeiDou positioning information, and vehicle IMU positioning information; identifying multiple candidate road segments from preset map data based on the vehicle's BeiDou positioning information and IMU positioning information, and acquiring road geometric feature information for each candidate road segment; determining the vehicle's expected road segment from the multiple candidate road segments based on the vehicle's driving motion information and the road geometric feature information of the multiple candidate road segments, and determining the vehicle's drive control command based on the road geometric feature information of the expected road segment. This solution can improve the accuracy of vehicle control.

Embodiments of the present application provide a bus scheduling method based on reinforcement learning, comprising the following steps: S110, initializing road network data, and performing regional grid division on the road network; S120, dividing trajectory data according to time periods, and calculating traffic flow of different regions in different time periods; S130, combining real-time ride request data, calculating and updating the traffic flow; S140, when a bus arrives at a route endpoint, obtaining a current road network state from multiple dimensions; S150, based on a reinforcement learning neural network, combining the updated traffic flow obtained in step S130 and the road network state obtained in step S140, calculating feedback data of the bus driving to different routes; and S160, repeating steps S130-S150, obtaining reinforcement learning model parameters, and performing bus scheduling based on the trained reinforcement learning model. Through this method, the current road network state and traffic flow can be fully considered, urban bus resources can be effectively utilized, bus operation efficiency can be improved, and urban traffic congestion can be alleviated.

The utility model provides a multifunctional stop board for urban buses, which relates to the technical field of stop boards and comprises a stop board frame, glass is arranged on one side of the stop board frame, and a mounting mechanism is arranged on the other side of the stop board frame. According to the utility model, the mounting mechanism and the fixing mechanism are arranged, a reel of roll paper is sleeved on a rotating rod, a support frame is inserted into a positioning block and is fixed by a clamping block, that is, the roll paper is fixed through the support frame and the positioning block, the support frame, the roll paper and the positioning block are inserted into the stop board frame, and a side disc is rotated to fix a threaded sleeve and the stop board frame in a threaded manner; roll paper is placed in the stop board frame, the stop board frame is provided with glass and a paper outlet hole, the remaining condition of the roll paper is observed through the glass, and the roll paper can be drawn out through the paper outlet hole for use, so that the stop board frame has good paper supply measures, and the situation that passengers suddenly need paper towels when waiting for buses is reduced; the situation that service measures are affected due to the fact that the bus stop board singly provides advertising is avoided, and convenience of the bus stop board is improved.

The utility model belongs to the technical field of urban bus folding slope plates, and particularly relates to an urban bus folding slope plate device which comprises a bottom plate, a rotating shaft rotationally installed in the bottom plate, a top plate fixedly installed on the rotating shaft, a plurality of anti-slip strips fixedly installed on the top of the top plate, a second groove formed in the bottom plate, and a supporting plate rotationally arranged in the second groove. A third groove is formed in the bottom of the top plate, the top end of the supporting plate extends into the third groove, a through groove is formed in the supporting plate, a limiting rod is slidably installed in the through groove, and the two ends of the limiting rod penetrate through the two sides of the third groove correspondingly and extend to the outside; the limiting assembly is located in the limiting rod and used for limiting the position of the limiting rod; when the whole device is used, it is ensured that the whole device can be folded, so that the whole device can occupy a small space during transportation, the whole device is convenient to transport, and meanwhile, the whole device can be conveniently held by a worker after being folded, and the whole device is convenient to carry.

The invention provides a stepless speed change, constant power and power converging and shunting hybrid power device, and belongs to the technical field of gearboxes. The device structurally comprises a high-low speed planetary structure, a forward gear planetary structure and a reverse gear planetary structure which are sequentially arranged from front to back, a variable pump is connected with a sun gear in the planetary structure, and a variable motor is connected with a sun gear in the high-low speed planetary structure; the high-low speed planet carrier is connected with the forward gear clutch and the reverse gear clutch, the forward gear clutch is connected with the forward gear ring through a friction plate, and the reverse gear clutch is connected with the reverse gear ring through a friction plate. Full-automatic transmission is achieved, safety and maneuverability are remarkably improved, meanwhile, a transmission system is protected, and performance is optimized. Compared with the prior art, the invention has the best driving comfort, and can be widely applied to engineering machinery, agricultural machinery, forestry machinery, vehicle engineering, urban buses and other machines capable of walking.

1. The name of the design product: city bus model (SW6128). 2. The use of the design product: for city bus model. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.