18 results about "Taxis" patented technology

The invention discloses a transportation hub transport capacity scheduling system based on big data, and particularly relates to the technical field of traffic scheduling, which comprises a data aggregation and sensing module, an early warning and triggering module, a scheduling scheme simulation and decision module and an instruction distribution and execution monitoring module. The system collects subway, bus, taxi, online car-hailing and passenger flow data in real time through a multi-source interface and a sensor, and a unified transport capacity diagram is generated after cleaning and anomaly detection; carrying out transport capacity gap identification and early warning based on a multi-index coupling risk analysis model; a plurality of scheduling schemes are generated and evaluated through a microscopic simulation model integrated with passenger behavior prediction, and an optimal scheme is recommended; finally, the scheme is converted into a specific instruction to be distributed and executed, and real-time monitoring and feedback are performed to form closed-loop management. According to the invention, the transformation from passive response to active intervention and from experience decision to scientific scheduling is realized, and the transport capacity cooperation efficiency and passenger evacuation capability of the transportation hub are significantly improved.

A drive unit for air vehicle, which allows building the vertical take-off and landing vehicles, intended for use, for instance, in the production of flying taxis, as well as in the model-making branch and in the toy industry.The drive unit is composed of the air channel, in the form of a straight segment of a tube with circular section, which has fans with engines fixed on its both ends. The vertical draft force outlet-inlet nozzle opening is located between fixed fans of the drive unit.

An integrated intelligent safety and surveillance system for vehicles combining multiple cameras (internal fisheye, front, rear), radar collision sensor, high-precision GPS unit, environmental sensors (temperature, humidity, air quality), and ambient LED lighting within a single embedded unit with internal battery and optional solar power. Features protocol-agnostic communication architecture (GSM / 3G / 4G / 5G, Wi-Fi, Bluetooth, satellite, CAN bus) and supports multiple platforms (Android, Arduino, ESP, Raspberry Pi, STM32). Provides collision warning, 360-degree monitoring, real-time GPS tracking, geofencing, stolen vehicle recovery, driving behavior analysis, and risk heat maps. Targets commercial vehicles, taxis, ride-sharing, and fleet management. Core innovation: integrating all systems into one flexible platform with comprehensive spatial-temporal analytics.

1. Name of the product in this design: Display screen. 2. Purpose of this design: To display vehicle status and advertising information on the roof of taxis. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the design's key features: the front view.

This utility model discloses a car rubber floor mat with a drainage structure, comprising a rubber floor mat body, an internal drainage mechanism, and limiting plates on the front and rear sides of the top left side of the rubber floor mat body. The drainage mechanism includes absorbent cotton, a rubber sheet, several drainage grooves, and limiting grooves. The bottom of the absorbent cotton is fixedly connected to the top of the rubber sheet. The drainage grooves are located on the top of the rubber floor mat body, and the limiting grooves are located on the left side of the top of the rubber floor mat body. This invention solves the problem that some existing car rubber floor mats lack a drainage structure, which, especially in rainy seasons and in vehicles such as taxis and ride-hailing vehicles where passengers frequently get in and out, can easily bring rainwater into the surface of the car rubber floor mat, causing water to accumulate on the surface and become slippery, affecting riding comfort and safety when getting in and out of the vehicle.

This invention belongs to the field of intelligent transportation and low-carbon technology, specifically disclosing a hub taxi intelligent dispatching method and system based on dynamic zoning. The method includes: classifying passengers into three levels: short-distance, medium-distance, and long-distance; performing status detection and coding management on taxis entering the hub area to construct a vehicle attribute set; dividing the lanes in the hub waiting area into three types: dedicated short-distance lanes, dedicated long-distance lanes, and flexible adjustment lanes, and periodically adjusting the number of each type of lane based on real-time collected passenger type distribution data and taxi queuing data; and achieving optimal matching between passengers and taxis through a multi-factor weighted matching algorithm based on passenger level, identification number, and vehicle attribute set, and planning the optimal driving route for the order. This invention solves the problem that existing technologies lack a systematic solution for demand perception, dynamic adjustment, precise matching, and effect feedback, and cannot simultaneously meet the needs of drivers, passengers, and the environment.

The application relates to the field of traffic communication transmission control, in particular to a car-to-car communication data transmission control method and equipment for taxis. The method obtains the congestion degree of each taxi at the current moment by analyzing the distance distribution between each vehicle in the local area of each taxi and the speed difference, obtains the trajectory disorder index of each vehicle in the local area at the current moment according to the position point change of each vehicle in the local area at each moment in a preset time period before the current moment of each taxi, and obtains the communication transmission weight of each taxi at the current moment in combination with the congestion degree of each taxi at the current moment. The communication transmission of each taxi is carried out with different priorities based on the communication transmission weight. The application can make the taxis with greater congestion or collision risk transmit communication data in time, and ensure the timeliness of taxi communication.

This invention discloses a charging guidance method and system for two-shift electric taxis based on Q-learning. The method first constructs an electric taxi operation process model to simulate the vehicle's route selection and state of charge changes under different states. Second, it establishes a charging behavior model based on the Q-learning algorithm. By defining discretized time, region, and state of charge spaces, it sets passenger-finding and charging actions and designs a sum-of-benefits penalty function that includes state of charge threshold constraints at shift change times, training to obtain the optimal charging decision strategy. Finally, the guidance effect is evaluated from three dimensions: charging cost, satisfaction of residents' travel needs, and grid power supply balance. This invention effectively reduces unnecessary charging times through intelligent guidance, smooths the charging load during shift change times, lowers operating costs, and simultaneously improves grid stability and residents' travel security.

This invention relates to the field of vehicle management technology, specifically to a management system for managing unauthorized substitute drivers. The system includes a management settings module, a non-driving fare meter unlocking / locking module, an information data management module, an anti-fraud electronic service supervision module, and a hardware interaction module. The management settings module manages the activation and deactivation of non-driving detection, automatically locking the fare meter upon detection failure, and sets the detection interval, detection frequency, and facial recognition matching threshold. The non-driving fare meter unlocking / locking module is used for locking and unlocking the fare meter. The information data management and query module stores information on officially hired drivers. The anti-fraud electronic service supervision module obtains driver information. The hardware interaction module enables two-way data communication between the dynamic monitoring platform and the taxi. This system controls driver qualifications from the source, manages the entire process, completely eradicates industry management loopholes related to unauthorized substitute drivers in taxis, and reduces operational risks for businesses.

The application discloses a short-distance order intelligent matching and load balancing scheduling system for cruising taxis, and particularly relates to the technical field of intelligent traffic management, and the system comprises a topology evidence module, a queue gating module, a batch matching module and a closed-loop processing module; wherein the topology evidence module is used for unified access, time benchmark alignment and site topology modeling of multi-source data of key sites and surrounding roads to generate a sequence evidence chain of vehicles; the queue gating module is used for reconstructing real-time sequences of vehicle queue areas, forming a queue sequence list, and generating a sequence evidence credibility and a load gating quantity of each vehicle; the batch matching module is used for completing short-distance order identification, release batch generation, sequence layer range determination, vehicle and order matching and passenger pickup window allocation within a rolling scheduling window; and the closed-loop processing module is used for executing issuing, process monitoring, abnormality processing, rollback adjustment and audit solidification.

At the very least, it provides a taxi navigation method that eliminates the need for communication between the user and the driver of the vehicle (including taxis) regarding the destination address. [Solution] A method for navigating a taxi comprises the steps of: a user terminal transmitting destination information relating to the destination address; and a navigation device installed in the taxi receiving the destination information.

An object of the system according to the embodiment is to instantaneously compare various elements of a plurality of vehicle types.SOLUTION: A system according to an embodiment includes a price comparator, a fuel economy comparator, a quietness comparator, an acceleration feeling comparator, a tax comparator, an insurance comparator, and a travel fee comparator. The price comparison unit uses the generated AI to compare the prices of the plurality of vehicle types that the user is considering. The fuel efficiency comparison unit compares the fuel efficiencies of a plurality of vehicle types that the user is considering. The quietness comparator compares quietness of a plurality of vehicle types that the user is considering. The acceleration feeling comparison unit compares acceleration feelings of a plurality of vehicle types that the user is considering. The tax comparison unit compares taxes of a plurality of vehicle types that the user is considering. The insurance comparison unit compares insurances of a plurality of vehicle types that the user is considering. The travel fee comparator compares the travel fees of the plurality of vehicle types that the user is considering.SELECTED DRAWING: Figure 1

The present application relates to the technical field of automatic driving and intelligent traffic management, in particular to a method and device for joint scheduling and charging of an unmanned taxi fleet. The method comprises: obtaining current state information of the system, and establishing a decision target with the goal of maximizing platform revenue; converting the decision target into a Markov decision process, and establishing a composite reward function for multi-objective optimization; constructing a bipartite graph for joint scheduling and charging, and using a reinforcement learning model to obtain dynamic weights of the composite reward function to calculate the comprehensive weights of each edge in the bipartite graph, matching the bipartite graph to obtain the current optimal matching decision and executing it. The present application solves the problems of vehicle supply and demand imbalance, charging station congestion and low long-term system revenue caused by the separation of order scheduling and vehicle charging decision in the prior art.

The system according to the embodiment aims to efficiently detect items left behind on buses and taxis and notify their owners. [Solution] A system according to an embodiment includes a recognition unit, a detection unit, a notification unit, and a guidance unit. The recognition unit uses a camera to recognize people and their belongings. The detection unit detects whether the belongings have been left on the seat based on the information recognized by the recognition unit. The notification unit notifies the owner of the information detected by the detection unit. The guidance unit guides the person to the location of the belongings based on the information notified by the notification unit.

This invention discloses a multi-agent simulation method for air taxis combining a Double-DQN network. The method includes constructing a low-to-high-level composite urban air taxi traffic network model based on urban geographic information data; then building a fixed-time-step multi-agent simulation system based on the constructed air taxi agent model and station passenger behavior model; constructing an air taxi scheduling model; training the air taxi scheduling model within the multi-agent simulation system; deploying the trained air taxi scheduling model into the multi-agent simulation system; running the simulation based on the low-to-high-level composite urban air taxi traffic network model; and outputting the simulation results of air taxi operation. This invention constructs a two-layer urban air traffic network, employs multiple air taxi agents to finely simulate the entire process behavior, and combines optimized scheduling strategies to achieve realistic simulation and efficiency improvement of air taxi operation.

The image shown is for displaying the results of operational data analysis for vehicles such as taxis and other commercial vehicles. Clicking on a target area on the map located on the left side of the image will display data such as sales figures, average fare, or number of trips for a specific period (e.g., day of the week, time of day) for that area in a table located on the right side of the map. A list of buttons for selecting a driver is displayed within a vertical rectangular frame on the far right of the image.

The invention, which relates to the technical field of the smart power grid, discloses an artificial intelligence-based fine prediction method for load and power supply spatial-temporal distribution, and the method comprises the steps: S1, building a multi-source spatial-temporal information hierarchical correlation model; s2, according to the multi-source data in the correlation model, carrying out public charging station candidate point distribution position optimization to obtain public charging station candidate point distribution positions; s3, obtaining a better public charging station configuration scheme by using a multi-target optimization model configured by the public charging station within the range of the public charging station candidate distribution position; and S4, taking the public charging station configuration scheme as input, simulating the electric taxi charging load spatial-temporal distribution by using a multi-agent system, and obtaining an electric taxi charging load spatial-temporal distribution prediction result under the fixed condition of the public charging station. The mutual influence of charging station configuration and charging load space-time distribution is fully considered.