61 results about "Transit bus" patented technology

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.

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 application discloses a bus service gap identification method based on mobile phone signaling and bus data coupling and belongs to the technical field of traffic supply condition supervision. The method specifically comprises the following steps: S1, data collection; S2, data processing; S3, identification of job and residence locations; S4, construction of a commuting OD matrix; S5, construction of a commuting demand index; S6, construction of a bus supply level index; and S7, analysis of a demand-supply matching degree index. First, job and residence locations of residents are identified by using mobile phone signaling data, and a commuting OD matrix is established; then, commuting demand intensity and bus supply level are quantified; finally, a demand-supply matching degree index model is constructed, and a bus service gap area is identified by using GIS spatial coupling analysis.

This invention discloses a MaaS dynamic bus route and station planning method and a trip optimization method based on spatiotemporal clustering. The MaaS algorithm based on spatiotemporal clustering, within a defined boundary area of ​​no more than 25 square kilometers, determines bus routes and stops based on existing public transport demand where both origin and destination are within this area, according to established spatiotemporal clustering rules. It then returns the determined bus routes, stops, and estimated arrival times to passengers using the planned bus routes and stops. The application of this invention maximizes the convenience of public transport, reduces unnecessary waiting time and connection distances, increases bus occupancy rates, reduces the probability of empty bus runs, and minimizes stops at unnecessary stops, thereby improving operational efficiency.

The application discloses a PCB bottom plate pluggable bus electronic station board centralized controller; comprising a CB total bottom plate, and a plurality of function modules plugged on the PCB total bottom plate; the plurality of function modules at least comprise a power module, a communication DTU module, an Android master control module, a clock module, a power amplifier module and a solar controller module; the application adopts a commercially available general standard module and a pluggable structure, completely gets rid of the dependence on special customized accessories, realizes supply chain opening and controllable cost. The module is directly connected with the PCB bottom plate through a pin, internal wires are cancelled, clear printing marks are matched, assembly and operation and maintenance are greatly simplified, production can be outsourced, and only the corresponding module needs to be replaced when a fault occurs, without on-site wiring maintenance.

The application relates to a bus visualization scheduling method and system based on bus passenger flow and turnover time, which comprises the following steps: S1, checking the rationality and feasibility of relevant parameters, and taking the parameters passing the check as input parameters; S2, generating a timetable based on a space-time network optimization algorithm or a non-standardized file analysis of a regular expression; S3, obtaining basic information data of the timetable, and displaying the departure time, travel time and route sign number of all shifts in the timetable, namely Gantt chart visualization; S4, calculating the route sign and shift evaluation indexes of the timetable and comprehensively evaluating the generated timetable, and if the actual demand is met, the process is ended; if the actual demand is not met, step S5 is executed; S5, changing the input parameters in the timetable or selecting a scene to automatically optimize, adjusting the timetable and repeating steps S3 and S4. Compared with the prior art, the application improves the bus timetable scheduling efficiency and reduces the bus operation cost.

This invention provides a method, device, terminal, and storage medium for bus priority control at multiple intersections. The method includes: acquiring the approach lane status of each approach lane at each intersection within a target area at the current time, and the traffic light prediction model for each intersection; determining the target bus closest to its current intersection on each approach lane, and acquiring the bus status and bus prediction model for the target bus at the current time; predicting the traffic light phase status of each intersection at the next time based on the approach lane status, bus status, and traffic light prediction model; and predicting the bus acceleration corresponding to each target bus at the next time based on the approach lane status, bus status, and bus prediction model. This application can adjust the traffic light phase status and bus acceleration using traffic light prediction models and bus prediction models in a multi-intersection environment, thereby improving bus traffic efficiency.

The utility model belongs to the technical field of bus seat, especially involve a support apron, including two support main part, four crosspieces are fixedly connected between two support main part, two sliding slots, two sliding slots are respectively set up in the top of two support main part, two sliding slots are respectively penetrated to the outside of two support main part, first fixed subassembly, fixed subassembly sets up in the outside of connecting plate, and is used for fixing connecting plate on two support main part, two groups of second fixed subassembly, two groups of second fixed subassembly set up in the outside of two support main part respectively, and be used for fixing the slider in the inside of sliding slot, through setting above structure, can apron main body install on two support main body, and installation operation is relatively simple, and time -consuming is shorter, avoids the disadvantage that traditional use screw fixed, dismounts relatively complicated, reduces the unnecessary workload of staff, and then facilitates staff use.

The present application relates to the technical field of smart grid demand response, in particular to a power grid demand response method and system based on dynamic optimization of automatic driving bus driving strategy, vehicle state is collected to determine the station adjustment interval and screen the response trajectory, combined with load monitoring and demand instruction to determine the power grid load limiting period, according to the relationship between the predicted station and the limiting period, the trajectory is classified and labeled as access type, and then the vehicle driving and parking rhythm is adjusted to generate charging time sequence sorting, combined with real-time load verification, the actual access sequence of the vehicle is generated and the execution record is generated. The present application generates the station adjustment range based on the driving state and the electric quantity, arranges the charging sequence combined with the power grid load fluctuation, charges in advance or delays in the limited period, sorts the charging behavior and identifies the abnormality, realizes the accurate matching of charging and load constraint, reduces the peak pressure and improves the electric energy efficiency, guarantees the task completion and reduces the conflict, forms the adaptive mechanism, realizes the dynamic matching optimization of charging and power grid.

This invention discloses a method for implementing priority for multiple bus routes under coordinated control. The method first establishes a bus priority request list, starting with the time a bus approaches the intersection and ending with the time it leaves the stop line. Then, it calculates the expected adjustment value and adjustment stage number for all requesting buses. Next, without disrupting coordination, it calculates the adjustable range for each bus before it reaches the stop line. Finally, with the goal of minimizing the waiting time for all buses at the intersection, and based on the first-come, first-served principle, it adjusts the duration output of the current stage to reduce bus waiting time. This method improves bus operating efficiency while considering the start time and release time of the coordination stage.

This invention discloses a collaborative operation optimization method for an integrated bus and metro network, comprising the following steps: S1, collecting and standardizing topology data, train timetable data, and passenger travel demand data; S2, constructing a multi-layer coupled spatiotemporal network; S3, performing K-shortest path search to generate a set of passenger reachable paths; S4, verifying the reachability of the passenger path selection set under train operation rules; S5, constructing a scheduling scheme based on the allocation probabilities output by the Logit model; S6, inputting the time-series operation data into an improved Mamba network to constrain and correct the number of train departure pairs and the first station departure time, forming an evaluation index for the optimization objective function. This invention achieves collaborative optimization of train operation sequence and passenger travel demand in an integrated bus and metro network, and is applicable to intelligent scheduling and dynamic passenger flow control scenarios in large-scale urban rail transit systems.

The application discloses a bus speed prediction method and device based on space-time interaction, a terminal and a medium, and belongs to the technical field of bus big data processing. The method comprises the following steps: acquiring speed observation data and prediction characteristic data of each road section in a target region in multiple past time periods, and performing preprocessing to obtain a road section-time period speed observation matrix and the preprocessed prediction characteristic data; a multilayer Bayesian bus speed prediction model with a space-time interaction random effect term is constructed; the road section-time period speed observation matrix and the preprocessed prediction characteristic data are input into the multilayer Bayesian bus speed prediction model for training, so as to obtain a trained multilayer Bayesian bus speed prediction model; and the trained multilayer Bayesian bus speed prediction model is used to predict the bus speed of a to-be-predicted road section in a target time period, so as to obtain a speed prediction result. The application fully considers the space-time interaction characteristics, and improves the accuracy of bus speed prediction.

To increase user satisfaction with transit information services. [Solution] The display control device according to the present invention includes a control unit. When the control unit acquires transfer information, which is information relating to the transfer from the original route to the transfer destination route, it displays a playback icon on the terminal device for playing a transfer video, which is a video related to the transfer guidance. When it acquires operation information for the playback icon, it displays the transfer video relating to the acquired transfer information on the terminal device. As a result, the information processing device provides the user with information about the travel route from the original route to the transfer destination route in video format.

This application relates to a bus route and stop registration method, system, storage medium, and intelligent terminal, belonging to the field of computer analysis of public transport networks. It includes acquiring bus route and road network data from different sources; identifying missing parts of the road network based on the bus route data to obtain complete road network data; using a preset spatial clustering algorithm to cluster and merge bus stops with the same station but different coordinates to obtain real bus stops; drawing perpendiculars from the real bus stops to the roads corresponding to the complete road network data to obtain the actual nodes of the bus stops in the road network; and obtaining the bus route nodes and stops located within the complete road network data based on the bus route data, and outputting them as registration points. This application has the effect of clustering and merging bus stops from different data, and then drawing perpendiculars to the real bus stops, so that the registered bus stops can restore the actual situation as much as possible, ensuring the accuracy of the data.

The application discloses a bus starting and ending point passenger flow data processing method, device and equipment, and relates to the technical field of bus passenger flow data processing. The method comprises the following steps: according to the trip information in the electronic route sheet data, splitting the starting and ending point pairing data, and based on the passenger body state and dressing features collected in the same trip operation period, re-matching the features of the starting and ending point pairing data; for each trip, according to the opening and closing door time information and the vehicle positioning data in the station passenger getting-on and getting-off data, judging whether there is vehicle positioning data matched with the opening and closing door time information in the preset time window, and according to the positioning validity result, correcting and processing the getting-on and getting-off station information in the station passenger getting-on and getting-off data. The above scheme re-matches the features of the starting and ending point pairing data of the same trip, corrects the getting-on and getting-off station information according to the positioning validity result, and improves the accuracy, availability and consistency of the bus starting and ending point passenger flow data.

The utility model relates to the technical field of bus shelter, and a stainless steel bus shelter technical scheme for smart city, which comprises a bus shelter body and two vertical rods, two vertical rods are symmetrically installed on the bus shelter body, a horizontal rod is horizontally installed between the two vertical rods, a baffle is horizontally installed between the two vertical rods through a connecting assembly, a plurality of fixing assemblies are arranged at the bottom ends of the vertical rods respectively. The baffle is arranged to close a part of the bus shelter, and when it rains, the user stands behind the baffle. The baffle can hinder rainwater, reducing the splashing of rainwater on the user's body.

The application relates to a bus schedule synchronization and cross-line scheduling method for a hybrid electric vehicle fleet, comprising the following steps: constructing a data set according to bus network information, including lines, transfer stations, passenger arrival rates, travel times and power consumption; constructing a multi-objective integer programming model for minimizing the operating cost of a bus company and passenger waiting time and maximizing the number of convenient transfers; designing an NSGAII-SA-PSO nested heuristic algorithm to assign the most suitable algorithm to different characteristic decision variables, thereby improving the quality of the solution. Through schedule synchronization and vehicle cross-line coordination, the application can significantly improve the operating efficiency of the bus and effectively improve the travel experience of passengers.

The application discloses a center city demand response type bus operation area site selection method, relates to the technical field of traffic planning, and comprises the following steps: acquiring traffic demand data and traffic supply data of each period in the center city; matching the traffic demand data and the traffic supply data of each period to geographical grids of the center city; determining a commuting tidal region and a traffic supply and demand imbalance region as a candidate site selection range of the demand response type bus operation area according to the geographical grids; and removing an unoperable region in the center city in the candidate site selection range as a target site selection range of the demand response type bus operation area. The application accurately identifies a high demand region, fully considers actual operation conditions of the center city, removes the unoperable region, quantifies peak period capacity waste and peak connection demand, provides space site selection support for a differentiated operation mode, and improves bus resource utilization.

The application discloses a traffic transportation driving safety data supervision analysis method. The method comprises the following steps: determining a target vehicle triggering an alarm and an alarm type, wherein the alarm type comprises a departure alarm of not departing from a departure station at a scheduled departure time and an arrival alarm of not arriving at a terminal station at a scheduled arrival time. Next, reference point information is selected from periodic reported positioning point information of the target vehicle according to the alarm type, and then driving time of the target vehicle is calculated according to a reporting time of the reference point information. Finally, whether the target vehicle has driving abnormal behavior is determined according to the driving time, so that the identification precision of driving abnormal behavior of a bus is improved.

The application discloses a bus passenger alighting station inference method based on a travel chain and an integrated learning, and comprises the following steps: collecting bus multi-source data; performing data cleaning and preprocessing on the multi-source data; fusing the multi-source data and judging a passenger boarding station according to a station arrival time window; performing preliminary inference on the alighting station based on a deterministic algorithm; establishing a deterministic algorithm to infer the passenger alighting station according to a travel chain assumption and passenger travel history; performing supplementary inference on the alighting station based on the integrated learning; introducing built environment and bus line external information for a journey that cannot be inferred by the deterministic algorithm; and establishing a multi-classification model based on an integrated learning two-layer stacking framework to further infer the passenger alighting station. The application realizes non-aggregated, station-level single-ticket bus passenger alighting station inference based on bus multi-source big data, can obtain accurate bus passenger flow space-time distribution characteristics, and provides a reference for bus operation organization optimization.

The present invention discloses a method for determining the charging and swapping strategy of electric buses considering battery degradation effects, which relates to the technical fields of urban public transportation and electric vehicle energy management. According to the information of the electric bus system, the working processes of electric buses passing through the starting station, swapping station, and terminal station are designed. Further, a charging and swapping decision-making model including an objective function and constraint conditions is constructed, and a battery degradation cost function is introduced. By discretizing the decision-making model and using a standard solver for solution, the optimal strategies of the charging amounts of each electric bus vehicle at different travel stages and whether to perform swapping operations are determined. The present invention can reduce the degree of battery degradation and the daily operating cost of the system on the premise of meeting the constraints of continuous vehicle operation and facility capabilities, and is applicable to the operation decision-making and management of electric bus systems with in-transit swapping conditions.

This invention discloses a dynamic scheduling method for the entire lifecycle of a bus fleet based on hierarchical reinforcement learning, belonging to the field of dynamic intelligent scheduling technology for urban public transport systems. The method first constructs a bus information collection module to acquire real-time operational data throughout the entire lifecycle, building a virtual scheduling environment that matches actual operational rules. Then, the entire bus operation cycle is decomposed into three levels: upper-level departure timetable scheduling, middle-level joint scheduling of stops and operating speeds, and lower-level joint scheduling of intersection signal priority and traffic speeds, constructing independent Markov decision processes for each level. Next, through a hierarchical progressive training framework, the strategies of each level are trained sequentially, first the lower level, then the middle level, and finally the upper level, to obtain a full-cycle collaborative scheduling model. Finally, based on the model, a real-time scheduling strategy is output, achieving closed-loop optimization of the entire bus lifecycle. This invention can effectively suppress bus queueing and delay propagation, significantly improve bus punctuality, reduce passenger waiting time, and has strong engineering applicability.

This invention relates to the field of collaborative transportation using public transport and drones, and discloses an optimized method for express delivery allocation in urban public transport and drone collaborative transportation. The steps are as follows: collecting urban traffic flow information data; extracting clustered bus trajectory data features, constructing a multiple linear regression equation to predict road segment travel time, and continuously optimizing the equation based on actual results to reduce prediction errors; obtaining the operating time of public transport in each city, the Euclidean distance from each POI point to the integrated transfer point, and constructing a two-layer optimization framework using a three-way optimization algorithm on the outer layer and a genetic algorithm on the inner layer to realize the express delivery allocation scheme; loading express deliveries according to the allocation scheme for each batch, and determining whether to perform transfer based on real-time traffic data. This further improves the overall efficiency and intelligence level of urban last-mile logistics.

1. The name of the design product: wisdom post (vacuum). 2. The use of the design product: for the construction of urban wisdom bus. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

This invention discloses a low-floor all-aluminum vehicle chassis, consisting of a front axle, a central battery compartment, and a rear axle module connected sequentially. The central section is low, while the sides are higher, with a height difference of 240–250 mm. The load-bearing frame of the central battery compartment connects the crossbeams and longitudinal beams via mortise and tenon joints, forming a grid-like inner frame and three battery compartments, upon which the floor is mounted. The front and rear axle modules are connected to the frame and crossbeams via mortise and tenon joints, supplemented by mechanical reinforcement. This invention employs a three-segment all-aluminum height-difference structure, achieving lightweight, high rigidity, and high battery capacity synergistically for a 6-meter-class Class I low-floor minibus. The grid-like inner frame formed by the central grid-like mortise and tenon joints enhances rigidity and optimizes force transmission, while also forming three battery compartments, increasing battery capacity from 71 kWh to 105 kWh, significantly extending range. The all-aluminum design reduces weight by over 1 / 3, lowering energy consumption. The modular design improves assembly precision and efficiency, overcoming the technical bottleneck of adapting all-aluminum structures to Class I low-floor designs, providing an accessible, low-carbon, and highly reliable microbus chassis solution.

The present disclosure provides a travel time prediction method, a travel time prediction model training method, equipment and a medium, relates to the technical field of artificial intelligence, and in particular to the technical field of intelligent traffic, deep learning and map navigation. The specific implementation scheme is: constructing a bus line map and a bus station map according to road network data, bus network data and traffic condition data; obtaining a query bus route between a starting point and a terminal point, station heat information of stations in the query bus route and current time information; and predicting a bus travel time of the query bus route by using the bus line map, the bus station map, the query bus route, the station heat information and the current time information. Through the above technical scheme, the prediction accuracy of the bus travel time can be improved.

The application discloses a subway-bus network cascade fault prediction method and related device, including the following steps: constructing a subway-bus double-layer network model with transfer points; determining the importance of each node in the subway-bus double-layer network model with transfer points; obtaining the load of each node, and calculating the capacity of each node according to the load of each node; according to the capacity and importance of each node, judging whether the node with importance greater than a preset threshold value has an accident type overload, and when the node with importance greater than the preset threshold value has the accident type overload, the node is taken as an overload node; and according to the type of the overload node, the method and related device can associate different node states with load abandonment and load transfer of node passenger flow, and realize load adjustment of the node.

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.