Control method of unmanned vehicle, vehicle and storage medium

Abstract

The embodiment of the application provides a control method of an unmanned vehicle, a vehicle and a storage medium, the method comprises the following steps: obtaining order state information of the unmanned vehicle; in response to the order state information representing that the unmanned vehicle has an order, determining a space occupation state of the unmanned vehicle, wherein the space occupation state comprises a non-occupation state and a passenger occupation state; in response to the space occupation state being the non-occupation state, controlling the unmanned vehicle to perform a temperature adjustment operation; and in response to the space occupation state being the passenger occupation state, controlling the unmanned vehicle to perform an environment detection operation, and controlling the unmanned vehicle to perform a safety response operation based on the environment detection result. The application solves the technical problem that the existing technology cannot dynamically respond to the change of the vehicle mode, thereby causing the riding safety and comfort of the unmanned vehicle to be low.

Description

Technical Field

[0001] This application relates to the field of automation control technology, and more specifically, to a control method for an unmanned vehicle, the vehicle itself, and a storage medium. Background Technology

[0002] Against the backdrop of the rapid development of intelligent connected vehicles and autonomous driving technologies, driverless cars, as an important component of future urban transportation, are receiving increasing attention for their in-vehicle environment safety and passenger experience. Especially in autonomous vehicles, the elimination of the traditional driver role necessitates higher levels of autonomous perception, decision-making, and execution capabilities to ensure passenger safety under various operating conditions. Accurate identification and response to vehicle operating modes (such as standby, order taking, passenger transport, empty driving, charging, or maintenance) are fundamental to achieving dynamic control of the intelligent cockpit environment.

[0003] In practical applications, autonomous vehicles often face complex and ever-changing service scenarios, such as rapid switching between consecutive orders, sudden air quality incidents, or potential leaks of harmful gases. These scenarios place clear demands on vehicles: the system should be able to automatically adjust environmental parameters such as air conditioning, ventilation, air purification, and door and window control according to the current operating mode of the vehicle, ensuring the health and comfort of passengers while prioritizing safety.

[0004] However, most existing environmental control systems for autonomous vehicles follow the static control logic of traditional automobiles, relying solely on fixed sensor thresholds for localized feedback adjustments and lacking a global perception of the vehicle's overall operating status. The system cannot identify the vehicle's current operating mode, nor can it dynamically adjust control strategy priorities accordingly. When a vehicle switches from an empty or charging state to a passenger-carrying state, the environmental control still uses the settings from the previous stage, potentially leading to the accumulation of harmful gases, energy waste, or delayed emergency response. More seriously, in scenarios involving safety risks, the system's failure to promptly link vehicle mode information prevents the triggering of corresponding safety protection mechanisms, significantly reducing passenger safety in actual operation of autonomous vehicles.

[0005] There is currently no good solution to the above problems. Summary of the Invention

[0006] This application provides a control method for unmanned vehicles to at least solve the technical problem in the prior art where the unmanned vehicle's inability to dynamically respond to changes in vehicle mode results in low passenger safety and comfort.

[0007] According to one aspect of the embodiments of this application, a control method for an unmanned vehicle is provided, comprising: acquiring order status information of the unmanned vehicle; determining the space occupancy status of the unmanned vehicle in response to the order status information indicating that the unmanned vehicle has an order, wherein the space occupancy status includes an unoccupied status and a passenger-occupied status; controlling the unmanned vehicle to perform a temperature adjustment operation in response to the space occupancy status being an unoccupied status; and controlling the unmanned vehicle to perform an environmental detection operation in response to the space occupancy status being a passenger-occupied status, and controlling the unmanned vehicle to perform a safety response operation based on the environmental detection results.

[0008] Furthermore, in response to the order status information indicating that the unmanned vehicle has no orders, the idle time of the unmanned vehicle without orders is obtained; the idle time is compared with a preset time to obtain a first comparison result; in response to the first comparison result indicating that the idle time is greater than the preset time, the unmanned vehicle is determined to be in a stopped order-accepting state; in response to the unmanned vehicle being in a stopped order-accepting state, the unmanned vehicle is controlled to perform cleaning operations.

[0009] Furthermore, in response to the autonomous vehicle completing the cleaning operation, the current battery level of the autonomous vehicle is detected; the current battery level is compared with the preset battery level to obtain a second comparison result; in response to the second comparison result indicating that the current battery level is less than the preset battery level, the autonomous vehicle is controlled to perform a charging operation.

[0010] Furthermore, in response to the space occupancy status being non-occupancy, the number of passengers is determined based on the order status information; the suitable temperature for the autonomous vehicle is determined based on the number of passengers; the current interior temperature of the autonomous vehicle is obtained; in response to the inconsistency between the current interior temperature and the suitable temperature for the order, the autonomous vehicle is controlled to adjust the current interior temperature to the suitable temperature for the order.

[0011] Furthermore, in response to the space occupancy status being passenger occupancy, multiple environmental parameters of the autonomous vehicle are detected in real time, including carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration; multiple preset concentration thresholds corresponding to the multiple environmental parameters are obtained, wherein each environmental parameter corresponds to a preset concentration threshold; the multiple environmental parameters are compared with the multiple preset concentration thresholds in real time to obtain a third comparison result; in response to the third comparison result indicating that any one of the multiple environmental parameters is greater than the corresponding preset concentration threshold, the autonomous vehicle is controlled to perform a safety warning operation.

[0012] Furthermore, in response to any environmental parameter exceeding the corresponding preset concentration threshold, the driver controls the unmanned vehicle to open its windows and sends a warning message to the passengers; obtains the current location information of the unmanned vehicle; determines a safe area based on the location information, and controls the unmanned vehicle to drive to the safe area to perform a parking operation.

[0013] Furthermore, in response to the order status information indicating that the unmanned vehicle has an order, the current battery level of the unmanned vehicle is monitored in real time; the current battery level is compared with the preset battery level to obtain a fourth comparison result; in response to the fourth comparison result indicating that the current battery level is less than the preset battery level, the power supply status of the unmanned vehicle is determined; and the unmanned vehicle is controlled to perform energy-saving operations based on the power supply status.

[0014] Furthermore, in response to the autonomous vehicle's power supply status meeting the solar power supply conditions, the autonomous vehicle's power supply status is adjusted to solar power supply; in response to the autonomous vehicle's power supply status not meeting the solar power supply conditions, the output power of the autonomous vehicle's environmental control equipment is reduced.

[0015] According to another aspect of the embodiments of this application, a vehicle is also provided, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods in various embodiments of this application when it runs.

[0016] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, the computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0017] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0018] According to another aspect of the embodiments of this application, a computer program product is also provided, including a non-volatile computer-readable storage medium storing a computer program, which, when executed by a processor, implements the methods in various embodiments of this application.

[0019] According to another aspect of the embodiments of this application, a computer program is also provided, which, when executed by a processor, implements the methods of the various embodiments of this application.

[0020] In this embodiment of the application, the order status information of the unmanned vehicle is obtained. By determining that the unmanned vehicle has an order in the above order status information, the space occupancy status of the unmanned vehicle is further determined. This achieves the purpose of controlling the unmanned vehicle to perform corresponding operations through the space occupancy status of the unmanned vehicle, thereby realizing the technical effect of improving the riding safety and comfort of the unmanned vehicle. This solves the technical problem in the prior art that the unmanned vehicle cannot dynamically respond to changes in vehicle mode, resulting in low riding safety and comfort. Attached Figure Description

[0021] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments of this application and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings:

[0022] Figure 1 This is a flowchart of an optional unmanned vehicle control method according to an embodiment of this application. Figure 1 ;

[0023] Figure 2 This is a flowchart of an optional unmanned vehicle control method according to an embodiment of this application. Figure 2 ;

[0024] Figure 3 This is a schematic diagram of an optional control system architecture for an unmanned vehicle according to an embodiment of this application;

[0025] Figure 4 This is a system flowchart of an optional control method for an unmanned vehicle according to an embodiment of this application;

[0026] Figure 5 This is a structural block diagram of an optional control device for an unmanned vehicle according to an embodiment of this application. Detailed Implementation

[0027] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0028] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0029] According to an embodiment of this application, a control method for an unmanned vehicle is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0030] This embodiment provides a control method for an unmanned vehicle. Figure 1 This is a flowchart of a control method for an unmanned vehicle according to an embodiment of this application, such as... Figure 1 As shown, the process includes the following steps:

[0031] Step S101: Obtain the order status information of the unmanned vehicle.

[0032] Optionally, the execution subject in this embodiment is the unmanned vehicle control system. It should be noted that other electronic devices and processors can also be used as the execution subject, and no further limitations are made here.

[0033] In the technical solution provided in step S101 of the present invention, the unmanned vehicle control system can collect status data related to the current vehicle service task in real time from the on-board task management module connected to the unmanned vehicle, so as to determine whether the vehicle is in a specific business stage such as standby, accepting orders, going to pick up passengers, carrying passengers, or the end of the trip.

[0034] As an optional implementation, in this approach, the autonomous vehicle establishes a secure connection with a cloud-based dispatch platform via an onboard communication unit (such as a 4G / 5G module). The dispatch platform, acting as an order management center, maintains the real-time task status of each autonomous vehicle. Periodically or when a status change event is triggered, the vehicle sends a status query request to the platform, which returns structured data including the order number, order status, and estimated pick-up time.

[0035] As an alternative implementation, in this method, the onboard computing unit of the autonomous vehicle runs a task scheduling agent. After receiving an order instruction from the cloud, this agent caches the order status information in a local database or memory variable and continuously updates it. The system can obtain the current order status by reading this locally stored status variable.

[0036] It is worth noting that by acquiring the order status information of the autonomous vehicle, the system can accurately identify the vehicle's current business mode, providing a foundation for subsequent pattern-based dynamic decision-making. This technical step itself ensures that the system can reliably and in real time grasp the service stage the vehicle is in, thereby supporting adjustments to vehicle behavior or system control strategies.

[0037] Step S102: In response to the order status information indicating that the unmanned vehicle has an order, determine the space occupancy status of the unmanned vehicle, wherein the space occupancy status includes the non-occupancy status and the passenger occupancy status.

[0038] In the technical solution provided by step S102 of the present invention, when the unmanned vehicle is connected to the vehicle task management module and it is confirmed that the unmanned vehicle has received a valid order, it is further determined whether there are passengers actually entering the vehicle, thereby distinguishing between the two states of "the vehicle has an order but the passenger has not yet boarded" (non-occupied state) and "the passenger has boarded and is on the journey" (passenger occupied state).

[0039] As an optional implementation, once the order status information indicates that the vehicle is in the "heading to pick up passengers" or "arrived at the pick-up point" stage, the system continuously monitors the opening and closing status of the doors (via door lock sensors or CAN bus signals) and the presence signals of occupants in the cabin (such as seat pressure sensors, infrared pyroelectric sensors, or millimeter-wave radar). If a door is detected to have opened and then closed, and at least one seat's occupant sensor outputs a valid signal, it is determined to be in a "passenger occupied state." Furthermore, if the door is not opened, or opens and then closes without an occupant signal, it is still considered to be in a "non-occupied state."

[0040] As an alternative implementation, in driverless vehicles equipped with in-cabin cameras, the system activates the image acquisition module after an order is activated and analyzes the cabin footage in real time using a lightweight human detection algorithm deployed on the onboard computing unit. If a passenger is detected entering and taking a seat within a preset time window (e.g., 30 seconds) after the door opens, the system determines the current space occupancy status as "passenger occupied." Furthermore, if no human target is detected within the time limit, the system maintains an "unoccupied" status.

[0041] It is worth noting that through this technical step, given the existence of an order, it is possible to accurately distinguish whether the driverless vehicle is currently in a state of "waiting for passengers to board" or "already having passengers inside," thereby achieving a refined identification of the actual usage of the vehicle's space.

[0042] In step S103, in response to the space occupancy status changing to an unoccupied state, the driverless vehicle is controlled to perform a temperature adjustment operation.

[0043] In the technical solution provided by step S103 of the present invention, when the unmanned vehicle control system confirms that there are no passengers in the vehicle (i.e., it is in an "unoccupied state") but there is a valid order (such as the vehicle has accepted the order and is heading to the pick-up point), it actively adjusts the temperature inside the vehicle to make the vehicle a suitable riding environment before the passengers get on.

[0044] As an optional implementation, when the system determines that the current space occupancy status of the autonomous vehicle is "unoccupied," it reads the preset target cabin temperature (e.g., 24℃ in summer, 22℃ in winter) from the cloud or local configuration and starts the air conditioning system. The onboard temperature and humidity sensor collects the current temperature inside the cabin in real time, and the controller can calculate the output power of the compressor, blower, or PTC heater according to the PID algorithm, and dynamically adjust the air supply temperature and air volume until the cabin temperature approaches the target temperature (i.e., the comfortable temperature for passengers).

[0045] As an alternative implementation, while acquiring an order, the system analyzes the estimated pick-up time and external environmental data (such as temperature and sunlight intensity). If the remaining arrival time is greater than a preset threshold (such as 5 minutes), a low-power temperature control mode is activated in advance during the journey (such as only turning on the internal circulation ventilation or intermittent cooling / heating). This can avoid the autonomous vehicle from experiencing a surge in energy consumption or excessive battery burden due to high-power temperature adjustment when approaching the pick-up point.

[0046] It's worth noting that triggering temperature adjustment when the space is not occupied ensures that the cabin temperature is adjusted to a comfortable range before passengers board, improving the riding experience. This technical step allows for the start / stop and parameter setting of the air conditioning system, avoiding problems such as ineffective operation when there are no passengers or unsuitable cabin temperature when passengers board.

[0047] In step S104, in response to the space occupancy status being passenger occupancy, the driverless vehicle is controlled to perform an environmental detection operation, and based on the environmental detection results, the driverless vehicle is controlled to perform a safety response operation.

[0048] In the technical solution provided by step S104 of the present invention, under the premise that it is confirmed that there are passengers in the vehicle (i.e., "passenger occupancy status"), the unmanned vehicle control system needs to immediately start detecting the environmental parameters inside the cabin and trigger corresponding safety measures based on the detection results.

[0049] As an optional implementation, when the system determines that the space is occupied as "passenger occupied," it immediately activates a multimodal environmental sensor array deployed in the cabin, including sensors for CO (carbon monoxide), CO2 (carbon dioxide), VOCs (volatile organic compounds), and combustible gases (such as methane). These sensors continuously collect air quality data and compare the collected values ​​with preset safety thresholds in real time. Furthermore, if any indicator exceeds the standard (e.g., CO concentration > 35 ppm), the system will trigger a "safety response operation," such as automatically activating external ventilation, shutting off internal ventilation, increasing blower speed, or, in severe cases, sending an alarm to a remote monitoring platform.

[0050] As an alternative implementation, in driverless vehicles equipped with in-cabin cameras and gas sensors, the system simultaneously runs visual anomaly detection algorithms (such as smoke / open flame recognition) and gas concentration monitoring while passengers are present. If the visual module detects suspected smoking or fire behavior, and the VOC or CO sensor readings rise abnormally, it is determined to be a high-risk event, and the system will immediately trigger a strong safety response (such as full-power ventilation, locking ignition-related circuits, and providing voice prompts to passengers). Furthermore, if only a single sensor slightly exceeds the limit, a mild safety response is executed (such as enhancing fresh air exchange).

[0051] It is worth noting that performing environmental detection and triggering safety responses based on the results while the driverless vehicle is occupied by passengers enables proactive identification and immediate intervention of potentially harmful or dangerous environmental factors within the cabin. This technological step can effectively reduce the health and safety risks to occupants caused by air pollution, accumulation of harmful gases, or sudden fires, thereby enhancing the environmental safety protection capabilities of driverless vehicles during passenger transport.

[0052] From the above steps S101 to S104, it can be seen that in this invention, by obtaining the order status information of the unmanned vehicle, and by determining that the unmanned vehicle has an order in the above order status information, the space occupancy status of the unmanned vehicle is further determined. This achieves the purpose of controlling the unmanned vehicle to perform corresponding operations through the space occupancy status of the unmanned vehicle, thereby realizing the technical effect of improving the riding safety and comfort of the unmanned vehicle. This solves the technical problem in the prior art that the unmanned vehicle cannot dynamically respond to changes in vehicle mode, resulting in low riding safety and comfort.

[0053] The method described in this embodiment will now be described in further detail.

[0054] Figure 2 This is a flowchart of a control method for an unmanned vehicle according to an embodiment of this application, such as... Figure 2 As shown, the process includes the following steps:

[0055] Step S201: In response to the order status information indicating that the unmanned vehicle has no orders, obtain the idle time of the unmanned vehicle when there are no orders.

[0056] Step S202: Compare the idle time with the preset time to obtain the first comparison result;

[0057] Step S203: In response to the first comparison result indicating that the idle time is greater than the preset time, the autonomous vehicle is determined to be in a stopped order-accepting state.

[0058] Step S204: In response to the unmanned vehicle being in a stopped order-accepting state, control the unmanned vehicle to perform cleaning operations.

[0059] In this embodiment, when the order status information indicates that there are currently no valid orders, the system reads the continuous period of no orders since the last order ended (or the vehicle went online) from the local clock or task management module, i.e., the "idle time". Specifically, the idle time is typically measured in seconds or minutes and is calculated synchronously by the onboard timer or scheduling platform. The system compares the current idle time with a preset duration (e.g., 1 hour) to generate a first comparison result, which indicates whether a threshold has been exceeded.

[0060] Furthermore, if the first comparison result is "idle time longer than preset time", the system updates the vehicle's current operating status to "stop accepting orders". This status does not mean that the autonomous vehicle is completely shut down, but rather that it temporarily exits the order-accepting queue in the scheduling logic and enters a low-priority standby mode.

[0061] Once it is confirmed that the current unmanned vehicle is in a "stop order-taking state", the system immediately activates the on-board cleaning actuators, such as starting ultraviolet germicidal lamps, ozone generators, air purification circulation, seat surface disinfection spray devices, or ground cleaning robots, to execute the preset cabin cleaning program.

[0062] The aforementioned idle time refers to the length of time that the autonomous vehicle has not received any new orders since it last completed an order (or went online).

[0063] The aforementioned preset duration is a time threshold set in advance by the operation strategy or system configuration to determine whether the vehicle has entered a long-term idle state. This duration can be determined by technicians based on the actual working conditions, and no further restrictions are imposed here.

[0064] The aforementioned "stop accepting orders" status refers to a vehicle's operational sub-state, indicating that although the vehicle is online, it is temporarily not accepting new orders. This is typically used for performing background tasks such as maintenance, charging, or cleaning.

[0065] The aforementioned cleaning operations refer to environmental maintenance activities such as disinfection, dust removal, and deodorization of the cabin interior using onboard automated equipment through physical or chemical means.

[0066] As an optional implementation, the autonomous vehicle periodically reports its order status to the cloud-based dispatch platform. The platform calculates the idle time of the autonomous vehicle in real time, and when it exceeds a preset threshold (such as 1 hour), it proactively issues a "stop order taking" command and a cleaning task. Upon receiving the cleaning task, the vehicle executes local cleaning equipment control.

[0067] As an alternative implementation, the vehicle-mounted task management module has a built-in state machine that continuously monitors changes in order status. Once it enters the "no orders" state, a local timer is started. When the timer expires (e.g., 45 minutes), it automatically switches to the "stop accepting orders" state and calls the cleaning subsystem interface to perform cleaning operations.

[0068] It is worth noting that through technical steps S201-S204, the idle state of the unmanned vehicle can be automatically identified and cleaning operations can be triggered when there are no orders for a long time. This ensures that the cabin environment is in a clean and usable state before being put back into operation. This achieves intelligent judgment of vehicle maintenance timing and automated execution of cleaning behavior, avoiding hygiene hazards caused by delays or omissions due to human intervention.

[0069] Step S301: In response to the unmanned vehicle completing the cleaning operation, detect the current battery level of the unmanned vehicle;

[0070] Step S302: Compare the current battery level with the preset battery level to obtain a second comparison result;

[0071] In step S303, in response to the second comparison result indicating that the current battery power is less than the preset battery power, the driverless vehicle is controlled to perform a charging operation.

[0072] In this embodiment, after cleaning operations (such as ultraviolet disinfection, air purification, ozone generation, etc.) are completed, the vehicle's battery management system (BMS) reads the real-time remaining charge (SOC, state of charge percentage) of the power battery via the CAN bus or internal communication interface as the "current battery charge". The system then compares the current battery charge with a pre-configured "preset battery charge" (such as an operational safety threshold of 20%) to generate a second comparison result, which is used to determine whether it is below the minimum charge level required to maintain normal order taking and driving.

[0073] Furthermore, if the second comparison result is "the current battery power is less than the preset battery power", the vehicle scheduling module plans a path to the nearest available charging station and initiates the automatic parking and charging docking process (such as automatic plug-in or wireless charging alignment) to enter the charging state.

[0074] The aforementioned current battery charge refers to the real-time remaining charge of the autonomous vehicle's power battery after the cleaning operation is completed, usually expressed as a percentage of SOC (State of Charge).

[0075] The aforementioned preset battery charge level is a threshold set by the operational strategy to determine whether the vehicle has sufficient energy to continue accepting orders or operating safely. If the charge level falls below this threshold, recharging must be prioritized. Specifically, this value can be determined by technicians based on actual operating conditions, and no further restrictions are imposed here.

[0076] The aforementioned charging operation refers to the technical actions of the unmanned vehicle autonomously or semi-autonomously driving towards the charging station and completing the physical docking (such as the robotic arm inserting the charging gun and the wireless charging pad aligning) and starting the charging process.

[0077] As an optional implementation, after the cleaning task is completed by the vehicle's main controller, the main control unit directly calls the BMS interface to obtain the SOC value and compares it with the locally stored preset battery level (e.g., 25%). If the battery level is insufficient, the route planning module is activated, and the vehicle autonomously navigates to the preset dedicated charging location to complete automatic parking and charging connection.

[0078] As an alternative implementation, after cleaning, the vehicle uploads its current battery level to a cloud-based operations and maintenance platform. The platform then combines the availability of charging stations in the area, the vehicle's location, and the battery level threshold to determine whether charging is necessary. If charging is required, the platform sends a "go to designated charging station" command to the vehicle, which then executes the navigation and charging process.

[0079] Optionally, the autonomous vehicle control system can further refine the accuracy of battery level detection. For example, the battery level trend can be predicted 10 seconds before the end of the cleaning operation, and the final SOC at the end of the operation can be predicted by combining the average power consumption model of the cleaning equipment, thus improving the accuracy of the judgment. At the same time, if the current battery level is detected to be slightly higher than the preset value but is in a rapid downward trend (such as due to reduced discharge efficiency caused by low temperature), a dynamic preset battery level mechanism can be introduced to adaptively adjust the threshold according to the ambient temperature, historical degradation curve, or battery health status.

[0080] In addition, the above charging operation can also include a tiered response strategy, that is, when the battery level is extremely low (e.g., <10%), fast charging stations are preferred, while when the battery level is moderately low (e.g., 10%~20%), slow charging can be selected to extend battery life.

[0081] It is worth noting that through steps S301-S303, after the cleaning operation is completed, the remaining battery power of the vehicle can be automatically assessed to see if it meets the subsequent operation needs. If the battery power is insufficient, the charging operation can be initiated proactively. This achieves the connection between cleaning tasks and energy management, ensuring that the vehicle has sufficient power to be put back into service after maintenance, and avoiding the unmanned vehicle from stopping midway or failing to be dispatched due to low battery power.

[0082] Step S401: In response to the space occupancy status being non-occupancy, determine the number of passengers based on the order status information;

[0083] Step S402: Determine the appropriate temperature for the driverless vehicle's order based on the number of passengers;

[0084] Step S403: Obtain the current interior temperature of the driverless vehicle;

[0085] In step S404, in response to the discrepancy between the current interior temperature and the ordered suitable temperature, the driverless vehicle is controlled to adjust the current interior temperature to the ordered suitable temperature.

[0086] In this embodiment, when the space occupancy status is "unoccupied" and an order already exists, the system parses the passenger quantity information from the order status information. Specifically, the passenger quantity information is typically synchronized to the dispatch platform after the user selects the number of passengers on the App when placing the order, and is then sent to the vehicle along with the order instructions.

[0087] The system converts passenger numbers into target cabin temperature based on preset mapping rules or empirical models. For example, 24 degrees Celsius corresponds to 1 person, 22 degrees Celsius to 2-3 people (requiring a lower setting due to increased heat dissipation from the body), and 20 degrees Celsius to 4 or more people. It's important to note that the above-mentioned suitable temperatures for each order are customized comfort target values ​​for that specific order, and are distinct from fixed default temperatures.

[0088] Furthermore, the vehicle's temperature and humidity sensor (usually located on the dashboard or near the air conditioning vents) collects the cabin's internal air temperature in real time as feedback input and compares the current interior temperature with the target value. If there is a deviation between the current interior temperature and the ordered suitable temperature (e.g., the absolute value of the difference > 1℃), the air conditioning system is activated. By adjusting parameters such as compressor power, blower speed, and vent opening, the system drives the cabin temperature towards the target value until it meets the preset tolerance range.

[0089] The aforementioned space occupancy status refers to whether there are passengers physically present in the carriage, and is divided into "non-occupancy status" (no passengers) and "passenger occupancy status" (passengers present).

[0090] The order status information mentioned above is structured data issued by the dispatch system, which includes business attributes such as order ID, number of passengers, boarding and alighting locations, and estimated arrival time.

[0091] The number of passengers mentioned above refers to the number of people who have booked a ride in the current order, which is usually an integer value of 1 to 4 people.

[0092] The above-mentioned suitable temperature for orders is a target cabin temperature dynamically determined based on the characteristics of the current order (mainly the number of passengers) and is used to guide the pre-adjustment of the air conditioning system.

[0093] As an alternative implementation, after receiving order data containing the number of passengers from the cloud, the vehicle queries the locally stored "number of passengers - suitable temperature" mapping table, thereby directly obtaining the target temperature by looking up the table.

[0094] As another alternative implementation, the system deploys a lightweight regression model (such as a linear regression model), with inputs including features such as the number of passengers, external ambient temperature, solar radiation intensity, and historical passenger preferences, thereby outputting a personalized order temperature.

[0095] Optionally, the autonomous vehicle control system can also add an external temperature correction factor when determining the suitable temperature for the order. For example, when the outside temperature is >35℃, the temperature will be automatically reduced by 1℃ from the original suitable temperature to offset the heat intrusion effect when the door is opened.

[0096] In addition, if the driverless car is equipped with zoned air conditioning (such as independent control of the left / right zone or the front and rear rows), the target temperature of different zones can be set according to the number of passengers and seating information (such as "sit in the back row" in the order), so as to achieve finer spatial adjustment.

[0097] Furthermore, the output power of the air conditioning system can be dynamically adjusted based on the estimated remaining time for picking up passengers. For example, if the remaining time is short (e.g., less than 2 minutes), a high-power rapid temperature adjustment mode can be activated; if there is ample time, a low-noise, low-energy-consumption slow mode can be used.

[0098] It is worth noting that through steps S401-S404, the cabin temperature can be dynamically set and actively adjusted to a suitable level based on the actual number of passengers, even before passengers have boarded the vehicle but before the order has been confirmed. This allows for personalized adaptation of the temperature adjustment strategy to the order, avoiding problems such as excessive cold, excessive heat, or adjustment lag caused by using a fixed temperature. As a result, a thermally comfortable environment matching the number of passengers is provided the moment they open the door and board the vehicle.

[0099] Step S501: In response to the space occupancy status being passenger occupancy status, multiple environmental parameters of the driverless vehicle are detected in real time. These multiple environmental parameters include carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration.

[0100] Step S502: Obtain multiple preset concentration thresholds corresponding to multiple environmental parameters, wherein each environmental parameter corresponds to a preset concentration threshold;

[0101] Step S503: Compare multiple environmental parameters with multiple preset concentration thresholds in real time to obtain a third comparison result;

[0102] Step S504: In response to the third comparison result indicating that any one of the multiple environmental parameters is greater than the corresponding preset concentration threshold, the unmanned vehicle is controlled to perform a safety warning operation.

[0103] In this embodiment, when the system confirms that the space occupancy status is "passenger occupancy status" (i.e., there are already passengers in the vehicle), it immediately activates the all-in-one air quality sensor module deployed in the cabin to continuously collect the following four types of parameters: carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration.

[0104] Furthermore, the system reads the safe upper or lower threshold values ​​for each type of environmental parameter from local configuration files or cloud policy libraries. For example, CO2 ≤ 1000 ppm, VOC ≤ 0.6 mg / m³, PM2.5 ≤ 35 μg / m³, and negative oxygen ions ≥ 1000 ions / cm³. Specifically, these concentration thresholds are typically set according to national indoor air quality standards.

[0105] The autonomous vehicle control system then compares each measured environmental parameter with its corresponding concentration threshold, generating a third comparison result. If any parameter exceeds its threshold (e.g., CO2 > 1000 ppm or negative oxygen ions < 1000 ions / cm³), it can be determined that the air inside the autonomous vehicle is abnormal. Furthermore, once the third comparison result indicates that any parameter exceeds the standard, the system should immediately trigger a safety warning.

[0106] The carbon dioxide concentration (CO2) mentioned above refers to the CO2 content per unit volume of air, and is often used to evaluate the ventilation efficiency of enclosed spaces.

[0107] The negative oxygen ion concentration mentioned above refers to the number of negatively charged oxygen molecules in the air. A high concentration helps to improve the feeling of air freshness.

[0108] The above-mentioned volatile organic compound (VOC) concentration refers to the total concentration of organic chemical substances that are easily volatile at room temperature, and is an assessment indicator of indoor air pollution.

[0109] The above-mentioned fine particulate matter concentration (PM2.5) refers to the mass concentration of particulate matter with an aerodynamic diameter of less than or equal to 2.5 micrometers.

[0110] The aforementioned preset concentration thresholds refer to the safety limits set for each type of environmental parameter, used to determine whether an early warning is triggered. Specifically, these preset concentration thresholds can be determined by technical personnel based on actual operating conditions, and no further restrictions are imposed here.

[0111] The aforementioned safety warning operation refers to the technical actions taken to issue risk alerts to passengers or operators through sound, light, information push, or other means when abnormal environmental parameters are detected.

[0112] As an optional implementation, the vehicle is equipped with an integrated air quality detection module, where all environmental parameters can be collected and processed by a single ECU. Multiple concentration thresholds are stored in a local storage module, and the comparison logic runs on the onboard microcontroller. If any environmental parameter concentration exceeds the standard, the voice chip is directly activated to issue a warning.

[0113] As an alternative implementation, sensor data is uploaded to the vehicle domain controller via CAN or Ethernet, and simultaneously synchronized to an edge server or cloud platform. The platform can dynamically issue personalized thresholds based on factors such as regional air quality history, season, and weather (e.g., relaxing VOC thresholds in winter).

[0114] Optionally, the autonomous vehicle control system can also set different warning levels based on the hazard level of the parameters. For example, a serious exceedance of VOC or CO will trigger a "high-risk red warning" (accompanied by an urgent voice and flashing lights), while a slight exceedance of PM2.5 will only trigger a "yellow warning" (silent app notification).

[0115] Furthermore, when the autonomous vehicle control system acquires the preset concentration threshold, it can also dynamically fine-tune the in-vehicle threshold based on the current external environment (such as outdoor PM2.5). For example, when outdoor PM2.5 > 150 μg / m³, the in-vehicle concentration can be allowed to briefly exceed 35 μg / m³ without issuing a warning, thus avoiding frequent false alarms.

[0116] In addition, while the system issues an alert, it will automatically record the timestamp, location, parameter values, and order ID, which can be used for subsequent operation and maintenance analysis or passenger service retrospective.

[0117] It is worth noting that through steps S501-S504, the cabin air quality can be monitored in real time from multiple dimensions while passengers are inside the vehicle, and a safety warning can be triggered immediately when any environmental parameter exceeds the safety threshold. This enables proactive identification and timely notification of potential air health risks, thereby enhancing passengers' perception and trust in environmental safety.

[0118] Step S601: In response to any environmental parameter being greater than the corresponding preset concentration threshold, control the unmanned vehicle to open its windows and send a warning message to the passengers.

[0119] Step S602: Obtain the current location information of the unmanned vehicle;

[0120] Step S603: Determine a safe area based on the location information, and control the unmanned vehicle to drive to the safe area to perform a parking operation.

[0121] In this embodiment, when the third comparison result determines that any environmental parameter (such as VOC, CO2, etc.) exceeds a preset threshold, the system immediately sends a command through the vehicle control module to drive the electric window system to lower all or some of the windows to a preset opening degree (such as 50%), so as to introduce fresh outside air to dilute pollutants. At the same time, multimodal warning information is pushed to passengers through the in-vehicle human-machine interaction system, such as a voice broadcast "Abnormal air quality detected in the vehicle, please ventilate", and a text prompt is displayed on the passenger's app or cabin screen.

[0122] Furthermore, the vehicle uses a high-precision positioning module to obtain its current geographic coordinates (latitude and longitude), lane-level position, and driving direction in real time, serving as the basic input for subsequent path planning. Simultaneously, the system accesses the "emergency parking area" layer in the high-precision map (such as roadside harbors, service areas, and auxiliary roads on non-main roads), and, combined with the current location, filters out the nearest and most accessible safe area. Subsequently, the autonomous driving planning and control module regenerates the local path, controls the vehicle to change lanes, decelerate, and enter the area, ultimately performing a smooth parking maneuver (including engaging the handbrake, shifting to Park, and activating the hazard lights).

[0123] The aforementioned safety warning operations refer to a series of coordinated measures automatically implemented to protect the health of occupants and ensure driving safety after a risk to the cabin environment is detected. These measures include ventilation, alarms, and emergency stops.

[0124] The aforementioned warning information is an immediate notification of environmental risks to passengers in the form of voice, text, or graphics.

[0125] The aforementioned current location information is the vehicle's real-time geographic coordinates and semantic location (such as "3rd lane southbound on XX Road") provided by the positioning system.

[0126] The aforementioned safe areas refer to temporary parking areas that comply with traffic regulations, have sufficient space, and do not affect mainstream commuting, such as emergency lanes, roadside parking spaces, and service areas.

[0127] As an optional implementation, the autonomous vehicle's local storage module carries a high-precision map labeled "emergency parking spot". When an alert is triggered, the path planning algorithm searches for the nearest legal parking spot within 500 meters of the current road segment (avoiding no-parking zones such as tunnels, bridges, and highway mainlines), and autonomously pulls over to park.

[0128] As another alternative implementation method, the vehicle uploads its current location to the cloud dispatch platform. The platform combines real-time traffic flow, road construction, accident reporting and other dynamic data to recommend the best safe parking location from a global perspective (such as the entrance of a nearby vacant parking lot) and sends the target coordinates to the vehicle, which then navigates to the safe area accordingly.

[0129] Optionally, the autonomous vehicle control system can also determine whether to drive to a safe area based on the type and degree of exceeding the standard parameters. For example, if only PM2.5 is slightly exceeded, it will only open the window and issue an alarm without triggering a stop. However, if a high concentration of VOCs or combustible gases is detected, it will force the vehicle to leave and stop.

[0130] Furthermore, when determining a safe area, it is not only necessary to select the nearest safe area, but also to comprehensively evaluate factors such as road surface smoothness, lighting conditions, communication signal coverage, and whether there is any shelter (e.g., in rainy weather, areas with roofs should be prioritized). Multiple candidate stops should be scored and ranked to select the best overall option.

[0131] In addition, after the vehicle comes to a complete stop, the unmanned vehicle control system will automatically send a "safely parked" status and environmental data snapshot to the remote monitoring center, enter standby mode, and wait for manual verification or remote cancellation command to prevent accidental resumption of operation.

[0132] It is worth noting that the safety warning operation in steps S601-S603 can simultaneously perform actions such as window ventilation, passenger alarm, location analysis, and autonomous driving to a safe area to stop when the cabin environmental parameters exceed the standard. This achieves a closed-loop response from "risk identification" to "physical isolation", effectively reducing the time passengers are continuously exposed to harmful environments and ensuring that the vehicle stops in a legal and safe location, avoiding secondary accidents caused by sudden health risks.

[0133] Step S701: In response to the order status information indicating that the unmanned vehicle has an order, monitor the current battery level of the unmanned vehicle in real time;

[0134] Step S702: Compare the current battery level with the preset battery level to obtain the fourth comparison result;

[0135] Step S703: In response to the fourth comparison result indicating that the current power value is less than the preset power value, determine the power supply status of the unmanned vehicle;

[0136] Step S704: Control the unmanned vehicle to perform energy-saving operations based on the power supply status.

[0137] In this embodiment, when the order status information indicates that the vehicle is in a valid service state, the vehicle battery management system continuously reads the real-time state of charge of the power battery through the CAN bus or internal communication interface, and expresses it as the "current charge value" in percentage form. The update frequency is usually once per second or higher.

[0138] Furthermore, the system compares the current battery level with a pre-configured "preset battery level" (e.g., 40%), outputting a fourth comparison result to indicate whether the system has entered a low battery risk zone. Specifically, this preset battery level is typically higher than the complete shutdown threshold, reserving a safety margin to complete the current order. If the fourth comparison result is "current battery level less than preset battery level," the system determines the current "power supply status" as "low battery power supply status." It's worth noting that this status is not a fault state, but rather an operating mode that requires the activation of energy efficiency optimization strategies.

[0139] Furthermore, based on the determined low power supply status, the vehicle control system automatically activates a set of predefined energy-saving strategies, such as replacing power supply equipment, reducing the power of the air conditioning compressor, turning off unnecessary lighting, limiting the operation of the cabin entertainment system, and lowering the sensor sampling frequency, in order to reduce energy consumption of non-core loads.

[0140] The above current battery level refers to the real-time remaining battery power of the autonomous vehicle during order execution, usually expressed as a percentage of SOC (State of Charge).

[0141] The aforementioned preset power level is a power threshold set by technicians (e.g., 30%-40%), used to trigger low power management strategies to ensure sufficient power to complete the current order and return safely.

[0142] The above power supply status is a status indicator describing the vehicle's current energy supply capability, including "normal power supply status" and "low power supply status".

[0143] The aforementioned energy-saving operations refer to technical actions that reduce the power consumption of unnecessary electrical equipment by means of shutting down, reducing frequency, limiting current, or replacing power supply equipment when the power supply is low.

[0144] As an optional implementation, after detecting a low battery power supply, the vehicle directly loads the corresponding energy-saving instruction set from the locally stored policy table and shuts down or reduces the load on non-critical subsystems according to priority.

[0145] As an alternative implementation, the control system can upload the current battery level along with data such as vehicle location, remaining travel distance, and road conditions to a cloud-based energy efficiency platform. The cloud-based energy efficiency platform uses a digital twin model to predict the minimum battery level required to complete the order and issues customized energy-saving instructions (such as "only turn off the rear screens, keep the front ventilation on").

[0146] Optionally, the autonomous vehicle control system can also set multiple preset battery levels (such as 30%, 20%, and 15%) to correspond to different levels of energy-saving operations. For example, at 30%, only the ambient lights are turned off; at 20%, the air conditioning power is reduced; and at 15%, the frame rate of the perception system is further limited.

[0147] Furthermore, when determining the power supply status, the control system can also integrate the remaining mileage of the current order provided by the navigation system with the historical power consumption data per 100 kilometers of the autonomous vehicle to estimate the power required to complete the order. If the predicted power is sufficient, even if the current power is lower than the preset value, strong energy-saving operations can be temporarily suspended to improve the riding experience.

[0148] In addition, during energy-saving operation, passenger-invisible or non-interactive devices (such as trunk lighting and some redundant radar channels) can be turned off first, thereby ensuring that the core passenger experience (such as basic air conditioning ventilation and emergency communication) is not affected.

[0149] It is worth noting that through steps S701-S704, the risk of insufficient power can be detected in real time during the order execution process, and the power supply status can be determined accordingly, thereby triggering corresponding energy-saving operations. This achieves dynamic control of vehicle energy use, effectively slows down the rate of power consumption without interrupting the current order service, improves the reliability of order completion, and avoids the unmanned vehicle from stopping midway due to power depletion.

[0150] Step S801: In response to the fact that the power supply status of the unmanned vehicle meets the solar power supply conditions, the power supply status of the unmanned vehicle is adjusted to solar power supply.

[0151] In step S802, in response to the fact that the power supply status of the unmanned vehicle does not meet the solar power supply conditions, the output power of the environmental control equipment of the unmanned vehicle is reduced.

[0152] In this embodiment, given that the vehicle is determined to be in a "low power supply state", the system detects whether the physical and environmental conditions for enabling solar power supply are met.

[0153] Specifically, the requirements for solar power supply include the following: whether the photovoltaic panels integrated on the roof or body of the vehicle are intact and not blocked; whether the current light intensity is higher than the start-up threshold (e.g., ≥200W / m²); and whether the solar power management system is online and has a stable output voltage.

[0154] If all the above conditions are met, the autonomous vehicle is deemed to meet the requirements for solar power supply. The system switches power supply priority through the power management unit, switching the power supply path of some or all low-voltage loads (such as cockpit control and communication modules) from the power battery to the output of the solar power generation system, thus achieving "solar power supply" mode. At this time, the power battery enters a low-load or dormant state, slowing down the discharge.

[0155] Furthermore, if insufficient sunlight, cloudy days, nighttime, or a photovoltaic system malfunction prevents the autonomous vehicle from using solar power, the system will send power reduction commands to environmental control equipment (such as air conditioning compressors, PTC heaters, and air purifier fans). For example, the blower speed will be reduced from level 5 to level 2, and the compressor duty cycle will be reduced from 80% to 40%, thereby significantly reducing power consumption.

[0156] The aforementioned power supply status refers to the vehicle's current energy supply mode or capability status. Specifically, in this application, it describes whether the autonomous vehicle can switch to alternative energy sources (such as solar energy) under low battery conditions.

[0157] The aforementioned solar power supply conditions refer to the prerequisites for enabling solar power generation and supplying power to on-board equipment, which simultaneously meet the following conditions: sufficient light intensity, normal function of the photovoltaic system, and no physical obstruction.

[0158] The aforementioned solar power supply refers to an operating mode in which photovoltaic modules integrated into the vehicle roof or body are used to convert sunlight into electrical energy, and then the power management system directly supplies power to the vehicle's low-voltage system or part of the load.

[0159] The aforementioned environmental control equipment refers to electromechanical equipment used to regulate the cabin thermal environment and air quality, including air conditioning compressors, blowers, PTC heaters, air purifiers, fresh air valves, etc.

[0160] As an optional implementation, the vehicle is equipped with a light intensity sensor and a photovoltaic panel output monitoring module. When a low battery state is triggered, the main controller reads the light intensity and photovoltaic output current / voltage, and determines locally whether to enable solar power supply based on a preset threshold. If enabled, the power path is switched via a relay or solid-state switch; otherwise, a PWM signal is directly sent to reduce the power consumption of ambient equipment.

[0161] As an alternative implementation, the system obtains the current location in real time during order execution and calls the cloud-based weather service interface to obtain the current solar irradiance forecast. Simultaneously, a high-precision map provides road shading information (such as whether the location is under an overpass, in a tunnel, or along a tree-lined road). A comprehensive assessment is then made to determine whether effective sunlight will be available within the next 5 minutes. If the forecast is favorable, the solar power system is activated in advance; otherwise, a power reduction strategy is implemented immediately.

[0162] Optionally, the autonomous vehicle control system can also classify power supply levels according to real-time light intensity (e.g., low light only supplies the communication module, while strong light can support some air conditioning fans) to achieve more precise energy allocation, rather than a simple "on / off" switch.

[0163] Furthermore, the control system can also define a list of energy-saving priorities for equipment (such as turning off the air purifier first, then the seat heater, and finally the air conditioning), ensuring that the impact on passenger comfort is minimized while saving the same amount of energy.

[0164] In addition, soft start / stop or voltage synchronization technology can be used when switching power supplies to avoid electronic devices restarting or flickering due to power surges, thereby improving system stability.

[0165] It's worth noting that this energy-saving operation can intelligently select the power supply mode based on the availability of solar power when the battery is low. Furthermore, if conditions permit, it switches to solar power to reduce battery consumption; if not, the control system proactively reduces the output power of environmental control equipment to cut energy consumption. This technical step achieves dynamic adaptation to energy sources and on-demand adjustment of load, effectively slowing down the rate of battery depletion without interrupting order services, thus improving the energy reliability of the autonomous vehicle to complete its current journey.

[0166] Figure 3This is a schematic diagram of the control system architecture of an unmanned vehicle according to one embodiment of the present invention, specifically including four main logical modules: state perception layer, state judgment layer, strategy decision layer and execution control layer. Figure 3 It describes how unmanned vehicles dynamically perceive environmental, energy, and task information under different order and space occupancy states, and perform intelligent response operations such as temperature regulation, environmental safety monitoring, cleaning and maintenance, and energy-saving management accordingly.

[0167] In the state-aware layer, the system continuously collects three types of key information:

[0168] The first category is order status information from the dispatch platform or vehicle task management module, including two basic scenarios: "order exists" or "order does not exist," which can be further refined into sub-status such as order acceptance, proceeding to pick up passengers, driving with passengers, and trip completion.

[0169] The second category is the space occupancy status determined by occupant detection sensors (such as seat pressure sensors, infrared pyroelectric sensors, cabin cameras, etc.) or door signal fusion, which is clearly distinguished into "non-occupancy status" (there is an order but the passenger has not boarded the vehicle) and "passenger occupancy status" (the passenger is already in the vehicle).

[0170] The third category is the vehicle's own operating status parameters, including real-time data such as current battery charge, ambient air quality (CO2, VOC, PM2.5, negative oxygen ions, etc.), interior temperature, light intensity, and geographical location.

[0171] In the status judgment layer, the system first performs branch judgments based on order status information. If it determines that "no orders exist for the unmanned vehicle," the idle management process is initiated: the idle time is calculated, and when it exceeds a preset threshold, the vehicle status is set to "stop accepting orders," and cleaning operations (such as ultraviolet disinfection and air purification) are triggered. After cleaning, the system checks the battery level; if it is lower than a preset value, it automatically performs a charging operation to ensure that the vehicle is in a clean and fully charged state before being put back into operation.

[0172] If an order is determined to exist in the driverless vehicle, a second round of passenger flow is performed based on the space occupancy status. Specifically, when the space occupancy status is "unoccupied" (i.e., passengers have not yet boarded), the system focuses on pre-boarding comfort preparations. At this point, the system extracts the number of passengers from the order information and determines the "suitable temperature for the order" accordingly (e.g., 24 degrees Celsius for one person, and a lower temperature for multiple people to offset body heat). Then, the current interior temperature is obtained; if there is a deviation, the air conditioning system is controlled to adjust the temperature, ensuring that passengers are in an ideal thermal environment when they open the door and board.

[0173] Meanwhile, the system will monitor the battery level in real time. If the battery level is lower than the preset value, it will enter the energy-saving management branch: first, it will determine whether the conditions for solar power supply are met (such as sufficient sunlight and normal operation of the photovoltaic system). If they are met, it will switch to solar power supply; if not, it will reduce the output power of environmental control equipment (such as air conditioners and fans) to ensure the minimum range required to complete the current order.

[0174] Furthermore, when the space occupancy status is "passenger occupied" (i.e., passengers are already inside the vehicle), the system's focus shifts to ensuring safety during the journey. At this point, environmental monitoring is immediately initiated, real-time monitoring of multiple air quality parameters within the cabin, including CO2, VOCs, PM2.5, and negative oxygen ions. Each parameter is compared to its corresponding preset safety threshold. If any indicator exceeds the corresponding threshold (i.e., the "third comparison result" is abnormal), the system immediately executes a safety warning. On one hand, it opens the windows to introduce fresh air and sends voice / text warning prompts to the passengers. On the other hand, it obtains the current location, determines the nearest safe area (such as an emergency parking area or auxiliary road parking space) based on a high-precision map, and controls the vehicle to automatically drive to that area to complete the parking, thus isolating the risk.

[0175] The execution control layer aggregates all terminal actions, including: temperature adjustment, cleaning, charging, window control, warning prompts, safe parking, solar power switching, and power reduction of environmental equipment.

[0176] It is worth noting that, Figure 3 Multiple power monitoring and energy-saving feedback loops are installed throughout the system. For example, when an order exists and the vehicle is not occupied, the system not only adjusts the temperature but also simultaneously assesses the power consumption; after a safe parking is performed while the vehicle is occupied, it may also trigger subsequent charging or cleaning processes.

[0177] In addition, the determination of the space occupancy status of the autonomous vehicle also integrates door signals and occupant sensors, and the safety warning operation can be expanded into graded alarms based on the degree of exceedance of environmental parameters, while the energy-saving strategy provides alternative paths based on the availability of solar energy.

[0178] Figure 4 This is a system flowchart of a control method for an unmanned vehicle according to one embodiment of the present invention.

[0179] Depend on Figure 4 It is understood that after the system obtains the order status, weather information, and energy information, it performs multi-information data processing on the obtained information to determine the current scenario mode of the autonomous vehicle. For example, when the scenario mode of the autonomous vehicle is determined to be "unoccupied" (i.e., the vehicle has accepted the order but the passenger has not yet entered the vehicle), the main process enters the comfort preparation and energy management sub-process (i.e., generating control commands according to the scenario mode).

[0180] First, the system extracts the number of passengers (e.g., 1 person, 2 people, etc.) from the order status information and determines the "suitable temperature for the order" based on preset rules (e.g., the more people, the lower the target temperature). Then, it reads the "current in-vehicle temperature" collected by the temperature and humidity sensor. If there is a discrepancy between the two (exceeding the tolerance range), the air conditioning system is activated to perform temperature adjustment operations to ensure that the cabin is in a personalized, comfortable thermal environment when passengers board the vehicle.

[0181] Simultaneously, the system performs power monitoring and energy-saving decisions in parallel. It acquires the battery's "current power level" in real time and compares it with the "preset power level" (e.g., 40%). If the power level is sufficient, normal temperature control is maintained; if the power level is insufficient (i.e., the "fourth comparison result" is true), it further determines whether the current conditions for solar power supply are met (including whether the light intensity meets the standard, whether the photovoltaic panels are unobstructed, and whether the power generation system is online).

[0182] Through the above energy-saving strategies, comfort can be preset and energy risk assessment and response can be completed simultaneously during the "window period" before passengers board the vehicle, thus achieving synergistic optimization of experience and range.

[0183] Furthermore, when the system determines that the autonomous vehicle's scenario mode is "passenger occupied state" (i.e., passengers are already inside the vehicle), the process transitions to the safety response sub-process (i.e., generating control commands based on the scenario mode). At this point, the system's focus shifts from comfort to occupant health and driving safety.

[0184] First, the system immediately initiates multi-parameter environmental monitoring, collecting four key indicators in real time through an integrated air quality sensor: carbon dioxide concentration (reflecting ventilation efficiency in enclosed spaces), volatile organic compounds (VOCs, indicating harmful gas pollution), fine particulate matter concentration (PM2.5, measuring inhalable particulate pollution), and negative oxygen ion concentration (characterizing air freshness). Specifically, each parameter is compared in real time with its corresponding preset concentration threshold to generate a "third comparison result."

[0185] If any parameter in the third comparison result exceeds the standard (such as CO2 > 1000 ppm or VOC > 0.6 mg / m³), the system will immediately trigger a safety warning operation.

[0186] Specifically, safety warning operations include the following technical actions:

[0187] 1. Open the window: The electric window is lowered by driving the body control module to introduce fresh outside air to dilute pollutants.

[0188] 2. Send warning messages: Inform passengers that "abnormal air quality has been detected, please ensure ventilation" via voice announcement, pop-up window on the cabin screen or push notification on the passenger's mobile phone.

[0189] 3. Navigate to a safe parking area: The system obtains the current high-precision location information, combines it with the "emergency parking area" layer in the high-precision map, plans the route to the nearest legal and safe area (such as roadside bays or auxiliary road parking spaces), and controls the vehicle to automatically complete a smooth parking.

[0190] It should be noted that, Figure 4 All preset thresholds (including power level, temperature, gas concentration, etc.) can be configured remotely or updated locally, which allows the autonomous vehicle control strategy to be flexibly adjusted according to season, region, vehicle type or operating policy, enhancing the system's deployability and adaptability.

[0191] Ultimately, the system will also proactively trigger business linkages based on scenario patterns and control results. For example, if the air quality inside a vehicle is still not up to standard after it has undergone off-line cleaning, the system will automatically generate a work order and dispatch it to the ground support system.

[0192] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0193] According to an embodiment of this application, a control device for an unmanned vehicle is provided. It should be noted that the device can be used to execute the control method for the unmanned vehicle described above.

[0194] Figure 5 This is a structural block diagram of the control device for an unmanned vehicle according to one embodiment of the present invention, such as... Figure 5 As shown, the device includes: a first acquisition module 501, a first determination module 502, a first control module 503, and a second control module 504.

[0195] The first acquisition module 501 is used to acquire the order status information of the unmanned vehicle;

[0196] The first determining module 502 is used to determine the space occupancy status of the unmanned vehicle in response to the order status information indicating that the unmanned vehicle has an order. The space occupancy status includes an unoccupied status and a passenger-occupied status.

[0197] The first control module 503 is used to control the unmanned vehicle to perform temperature adjustment operations in response to the space occupancy state being non-occupancy state.

[0198] The second control module 504 is used to control the unmanned vehicle to perform environmental detection operations in response to the space occupancy status being passenger occupancy status, and to control the unmanned vehicle to perform safety response operations based on the environmental detection results.

[0199] Optionally, the control device for the unmanned vehicle further includes: a second acquisition module, used to acquire the idle time of the unmanned vehicle when the order status information indicates that the unmanned vehicle has no orders; a first comparison module, used to compare the idle time with a preset time to obtain a first comparison result; a second determination module, used to determine that the unmanned vehicle is in a stopped order-accepting state when the first comparison result indicates that the idle time is greater than the preset time; and a third control module, used to control the unmanned vehicle to perform cleaning operations when the unmanned vehicle is in a stopped order-accepting state.

[0200] Optionally, the control device of the unmanned vehicle further includes: a detection module for detecting the current battery level of the unmanned vehicle in response to the unmanned vehicle completing the cleaning operation; a second comparison module for comparing the current battery level with a preset battery level to obtain a second comparison result; and a fourth control module for controlling the unmanned vehicle to perform a charging operation in response to the second comparison result indicating that the current battery level is less than the preset battery level.

[0201] Optionally, the first control module includes: a first determining unit, configured to determine the number of passengers based on order status information in response to the space occupancy status being non-occupancy; a second determining unit, configured to determine the order-suitable temperature for the unmanned vehicle based on the number of passengers; a first acquiring unit, configured to acquire the current interior temperature of the unmanned vehicle; and a first control unit, configured to control the unmanned vehicle to adjust the current interior temperature to the order-suitable temperature in response to the inconsistency between the current interior temperature and the order-suitable temperature.

[0202] Optionally, the second control module includes: a detection unit, used to detect multiple environmental parameters of the unmanned vehicle in real time in response to the space occupancy state being a passenger occupancy state, wherein the multiple environmental parameters include carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration; a second acquisition unit, used to acquire multiple preset concentration thresholds corresponding to the multiple environmental parameters, wherein each environmental parameter corresponds to a preset concentration threshold; a comparison unit, used to compare the multiple environmental parameters with the multiple preset concentration thresholds in real time to obtain a third comparison result; and a second control unit, used to control the unmanned vehicle to perform a safety warning operation in response to the third comparison result indicating that any one of the multiple environmental parameters is greater than the corresponding preset concentration threshold.

[0203] Optionally, the second control unit includes: a first control subunit, used to control the unmanned vehicle to open its windows and send a warning message to passengers in response to any environmental parameter being greater than the corresponding preset concentration threshold; an acquisition subunit, used to acquire the current location information of the unmanned vehicle; and a second control subunit, used to determine a safe area based on the location information and control the unmanned vehicle to drive to the safe area to perform a parking operation.

[0204] Optionally, the control device for the unmanned vehicle further includes: a monitoring module, used to monitor the current battery level of the unmanned vehicle in real time in response to order status information indicating that the unmanned vehicle has an order; a third comparison module, used to compare the current battery level with a preset battery level to obtain a fourth comparison result; a third determination module, used to determine the power supply status of the unmanned vehicle in response to the fourth comparison result indicating that the current battery level is less than the preset battery level; and a fifth control module, used to control the unmanned vehicle to perform energy-saving operations based on the power supply status.

[0205] Optionally, the fifth control module further includes: an adjustment unit, used to adjust the power supply status of the unmanned vehicle to solar power supply in response to the unmanned vehicle's power supply status meeting the solar power supply conditions; and a reduction unit, used to reduce the output power of the unmanned vehicle's environmental control equipment in response to the unmanned vehicle's power supply status not meeting the solar power supply conditions.

[0206] Embodiments of this application also provide a vehicle, including: a memory storing an executable program; and a processor for running the program, wherein the program executes the methods described in various embodiments of this application when it runs.

[0207] Optionally, in this embodiment, the vehicle may be configured to store a computer program for performing the following steps:

[0208] Step S101: Obtain the order status information of the unmanned vehicle;

[0209] Step S102: In response to the order status information indicating that the unmanned vehicle has an order, determine the space occupancy status of the unmanned vehicle, wherein the space occupancy status includes the non-occupancy status and the passenger occupancy status;

[0210] Step S103: In response to the space occupancy status being changed to an unoccupied state, control the unmanned vehicle to perform a temperature adjustment operation;

[0211] In step S104, in response to the space occupancy status being passenger occupancy, the driverless vehicle is controlled to perform an environmental detection operation, and based on the environmental detection results, the driverless vehicle is controlled to perform a safety response operation.

[0212] Optionally, when the processor executes the program, it also implements the following steps: in response to the order status information indicating that the unmanned vehicle has no orders, it obtains the idle time of the unmanned vehicle without orders; compares the idle time with a preset time to obtain a first comparison result; in response to the first comparison result indicating that the idle time is greater than the preset time, it determines that the unmanned vehicle is in a stopped order-accepting state; in response to the unmanned vehicle being in a stopped order-accepting state, it controls the unmanned vehicle to perform cleaning operations.

[0213] Optionally, the processor may further implement the following steps when executing the program: in response to the unmanned vehicle completing the cleaning operation, detect the current battery level of the unmanned vehicle; compare the current battery level with a preset battery level to obtain a second comparison result; in response to the second comparison result indicating that the current battery level is less than the preset battery level, control the unmanned vehicle to perform a charging operation.

[0214] Optionally, the processor also performs the following steps when executing the program: in response to the space occupancy state being unoccupied, determining the number of passengers based on the order status information; determining the appropriate temperature for the unmanned vehicle based on the number of passengers; obtaining the current interior temperature of the unmanned vehicle; and in response to the current interior temperature being inconsistent with the appropriate temperature for the order, controlling the unmanned vehicle to adjust the current interior temperature to the appropriate temperature for the order.

[0215] Optionally, the processor, when executing the program, also implements the following steps: in response to the space occupancy state being a passenger occupancy state, it detects multiple environmental parameters of the unmanned vehicle in real time, wherein the multiple environmental parameters include carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration; it obtains multiple preset concentration thresholds corresponding to the multiple environmental parameters, wherein each environmental parameter corresponds to a preset concentration threshold; it compares the multiple environmental parameters with the multiple preset concentration thresholds in real time to obtain a third comparison result; in response to the third comparison result indicating that any one of the multiple environmental parameters is greater than the corresponding preset concentration threshold, it controls the unmanned vehicle to perform a safety warning operation.

[0216] Optionally, the processor also performs the following steps when executing the program: in response to any environmental parameter being greater than the corresponding preset concentration threshold, controlling the driverless car to open its windows and sending a warning message to the passenger; obtaining the current location information of the driverless car; determining a safe area based on the location information, and controlling the driverless car to drive to the safe area to perform a parking operation.

[0217] Optionally, when the processor executes the program, it also implements the following steps: in response to the order status information indicating that the unmanned vehicle has an order, it monitors the current battery level of the unmanned vehicle in real time; it compares the current battery level with a preset battery level to obtain a fourth comparison result; in response to the fourth comparison result indicating that the current battery level is less than the preset battery level, it determines the power supply status of the unmanned vehicle; and it controls the unmanned vehicle to perform energy-saving operations based on the power supply status.

[0218] Optionally, the processor may also perform the following steps when executing the program: in response to the unmanned vehicle's power supply status meeting the solar power supply conditions, adjust the unmanned vehicle's power supply status to solar power supply; in response to the unmanned vehicle's power supply status not meeting the solar power supply conditions, reduce the output power of the unmanned vehicle's environmental control equipment.

[0219] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0220] Embodiments of this application also provide a computer-readable storage medium including a stored executable program, wherein, when the executable program is running, it controls the device where the computer-readable storage medium is located to perform the methods of various embodiments of this application.

[0221] Step S101: Obtain the order status information of the unmanned vehicle;

[0222] Step S102: In response to the order status information indicating that the unmanned vehicle has an order, determine the space occupancy status of the unmanned vehicle, wherein the space occupancy status includes the non-occupancy status and the passenger occupancy status;

[0223] Step S103: In response to the space occupancy status being changed to an unoccupied state, control the unmanned vehicle to perform a temperature adjustment operation;

[0224] In step S104, in response to the space occupancy status being passenger occupancy, the driverless vehicle is controlled to perform an environmental detection operation, and based on the environmental detection results, the driverless vehicle is controlled to perform a safety response operation.

[0225] Optionally, the storage medium is configured to store program code for performing the following steps: in response to order status information indicating that the unmanned vehicle has no orders, obtaining the idle time of the unmanned vehicle when there are no orders; comparing the idle time with a preset time to obtain a first comparison result; in response to the first comparison result indicating that the idle time is greater than the preset time, determining that the unmanned vehicle is in a stopped order-accepting state; in response to the unmanned vehicle being in a stopped order-accepting state, controlling the unmanned vehicle to perform cleaning operations.

[0226] Optionally, the storage medium is configured to store program code for performing the following steps: in response to the autonomous vehicle completing the cleaning operation, detecting the current battery level of the autonomous vehicle; comparing the current battery level with a preset battery level to obtain a second comparison result; in response to the second comparison result indicating that the current battery level is less than the preset battery level, controlling the autonomous vehicle to perform a charging operation.

[0227] Optionally, the storage medium is configured to store program code for performing the following steps: in response to a space occupancy status of non-occupancy, determining the number of passengers based on order status information; determining the appropriate temperature for the autonomous vehicle based on the number of passengers; obtaining the current interior temperature of the autonomous vehicle; and in response to a discrepancy between the current interior temperature and the appropriate temperature for the order, controlling the autonomous vehicle to adjust the current interior temperature to the appropriate temperature for the order.

[0228] Optionally, the storage medium is configured to store program code for performing the following steps: in response to a space occupancy state being a passenger occupancy state, real-time detection of multiple environmental parameters of the autonomous vehicle, wherein the multiple environmental parameters include carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration; acquisition of multiple preset concentration thresholds corresponding to the multiple environmental parameters, wherein each environmental parameter corresponds to a preset concentration threshold; real-time comparison of the multiple environmental parameters with the multiple preset concentration thresholds to obtain a third comparison result; in response to the third comparison result indicating that any one of the multiple environmental parameters is greater than the corresponding preset concentration threshold, controlling the autonomous vehicle to perform a safety warning operation.

[0229] Optionally, the storage medium is configured to store program code for performing the following steps: in response to any environmental parameter being greater than the corresponding preset concentration threshold, controlling the driverless car to open its windows and sending a warning message to the passenger; obtaining the current location information of the driverless car; determining a safe area based on the location information, and controlling the driverless car to drive to the safe area to perform a parking operation.

[0230] Optionally, the storage medium is configured to store program code for performing the following steps: in response to order status information indicating that the unmanned vehicle has an order, monitor the current battery level of the unmanned vehicle in real time; compare the current battery level with a preset battery level to obtain a fourth comparison result; in response to the fourth comparison result indicating that the current battery level is less than the preset battery level, determine the power supply status of the unmanned vehicle; and control the unmanned vehicle to perform energy-saving operations based on the power supply status.

[0231] Optionally, the storage medium is configured to store program code for performing the following steps: adjusting the power supply state of the unmanned vehicle to solar power supply in response to the unmanned vehicle's power supply state meeting the solar power supply conditions; and reducing the output power of the unmanned vehicle's environmental control equipment in response to the unmanned vehicle's power supply state not meeting the solar power supply conditions.

[0232] Embodiments of this application also provide a computer program product, including a computer program that, when executed by a processor, implements the methods of various embodiments of this application.

[0233] Embodiments of this application also provide a computer program product, including a non-volatile computer-readable storage medium for storing a computer program that, when executed by a processor, implements the methods in various embodiments of this application.

[0234] Embodiments of this application also provide a computer program that, when executed by a processor, implements the methods described in the various embodiments of this application.

[0235] In the above embodiments of this application, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0236] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units can be a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some interfaces; indirect couplings or communication connections between units or modules may be electrical or other forms.

[0237] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0238] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0239] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0240] The above are merely preferred embodiments of this application. It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A control method for an unmanned vehicle, characterized in that, include: Obtain the order status information for the autonomous vehicles; In response to the order status information indicating that the unmanned vehicle has an order, the space occupancy status of the unmanned vehicle is determined, wherein the space occupancy status includes an unoccupied status and a passenger-occupied status; In response to the space occupancy state being the unoccupied state, the driverless vehicle is controlled to perform a temperature adjustment operation; In response to the space occupancy status being the passenger occupancy status, the driverless vehicle is controlled to perform an environmental detection operation, and based on the environmental detection results, the driverless vehicle is controlled to perform a safety response operation.

2. The control method for an unmanned vehicle according to claim 1, characterized in that, The method further includes: In response to the order status information indicating that the unmanned vehicle has no orders, the idle time of the unmanned vehicle without orders is obtained; The idle time is compared with the preset time to obtain a first comparison result; In response to the first comparison result indicating that the idle time is greater than the preset time, the autonomous vehicle is determined to be in a stopped order-accepting state. In response to the unmanned vehicle being in the stopped order-accepting state, the unmanned vehicle is controlled to perform a cleaning operation.

3. The control method for an unmanned vehicle according to claim 2, characterized in that, The method further includes: In response to the autonomous vehicle completing the cleaning operation, the current battery level of the autonomous vehicle is detected; The current battery level is compared with the preset battery level to obtain a second comparison result; In response to the second comparison result indicating that the current battery charge is less than the preset battery charge, the driverless vehicle is controlled to perform a charging operation.

4. The control method for an unmanned vehicle according to claim 1, characterized in that, In response to the space occupancy state being the unoccupied state, controlling the unmanned vehicle to perform the temperature adjustment operation includes: In response to the space occupancy status being the unoccupied status, the number of passengers is determined based on the order status information; The appropriate temperature for the driverless vehicle's order is determined based on the number of passengers. Obtain the current interior temperature of the unmanned vehicle; In response to the discrepancy between the current interior temperature and the ordered suitable temperature, the driverless vehicle is controlled to adjust the current interior temperature to the ordered suitable temperature.

5. The control method for an unmanned vehicle according to claim 1, characterized in that, In response to the space occupancy status being the passenger occupancy status, controlling the autonomous vehicle to perform the environmental detection operation, and controlling the autonomous vehicle to perform the safety response operation based on the environmental detection result includes: In response to the space occupancy status being the passenger occupancy status, multiple environmental parameters of the driverless vehicle are detected in real time, including carbon dioxide concentration, negative oxygen ion concentration, volatile compound concentration, and fine particulate matter concentration. Obtain multiple preset concentration thresholds corresponding to the multiple environmental parameters, wherein each environmental parameter corresponds to one preset concentration threshold; The multiple environmental parameters are compared with the multiple preset concentration thresholds in real time to obtain a third comparison result; In response to the third comparison result indicating that any one of the plurality of environmental parameters is greater than the corresponding preset concentration threshold, the unmanned vehicle is controlled to perform a safety warning operation.

6. The control method for an unmanned vehicle according to claim 5, characterized in that, Controlling the unmanned vehicle to perform the safety warning operation includes: In response to any environmental parameter being greater than the corresponding preset concentration threshold, the driver controls the windows of the unmanned vehicle to open and sends a warning message to the passenger. Obtain the current location information of the unmanned vehicle; Based on the location information, a safe area is determined, and the unmanned vehicle is controlled to drive to the safe area to perform a parking operation.

7. The control method for an unmanned vehicle according to claim 1, characterized in that, The method further includes: In response to the order status information indicating that the unmanned vehicle has the order, the current battery level of the unmanned vehicle is monitored in real time; The current battery level is compared with the preset battery level to obtain a fourth comparison result; In response to the fourth comparison result indicating that the current power value is less than the preset power value, the power supply status of the unmanned vehicle is determined; The unmanned vehicle is controlled to perform energy-saving operations based on the power supply status.

8. The control method for an unmanned vehicle according to claim 7, characterized in that, Controlling the unmanned vehicle to perform the energy-saving operation based on the power supply status includes: In response to the fact that the power supply status of the unmanned vehicle meets the conditions for solar power supply, the power supply status of the unmanned vehicle is adjusted to solar power supply; In response to the unmanned vehicle's power supply status not meeting the solar power supply conditions, the output power of the unmanned vehicle's environmental control equipment is reduced.

9. A vehicle, characterized in that, include: Memory, which stores executable programs; A processor for running the program, wherein the program executes the control method for the unmanned vehicle according to any one of claims 1 to 8 when it runs.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored executable program, wherein, when the executable program is executed, it controls the device where the storage medium is located to perform the control method of the unmanned vehicle according to any one of claims 1 to 8.

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