A universal mobile carrier navigation control method fusing a safety area and a human flow density

Abstract

This invention discloses a universal mobile carrier navigation control method that integrates safety zone and pedestrian density, belonging to the field of intelligent navigation and safety control technology. This method constructs a multi-layered digital navigation map under a unified coordinate system; it acquires real-time pedestrian density and environmental data around the carrier through a sensor network and cloud interface; in normal mode, it plans conventional paths to avoid high-density pedestrian traffic based on a safety-first principle; when the carrier malfunctions or triggers an emergency signal, the system automatically switches to an emergency avoidance mode, selects the nearest avoidance area that meets safe stopping conditions, and controls the carrier to move along the avoidance path and complete a precise stop. This invention has strong versatility and is applicable to various carriers such as aircraft, ground vehicles, robots, and ships, significantly reducing the safety risks in the operation of urban mobile carriers.

Description

Technical Field

[0001] This invention relates to the technical fields of intelligent navigation, safety control, and emergency rescue, and in particular to a universal mobile carrier navigation and control method that integrates safe areas and population density. Background Technology

[0002] With the rapid development of urban low-altitude logistics, autonomous driving, service robots, and intelligent aquatic equipment, the operating environment of mobile vehicles is becoming increasingly complex. Existing navigation systems generally suffer from the following shortcomings: Insufficient safety: Conventional route planning only focuses on distance and time, without taking safe areas and real-time crowd density as core constraints. This makes it easy to enter densely populated areas and cause mass casualties. Poor versatility: Navigation systems for different carriers (such as drones and cars) are independent of each other and lack a unified architecture, resulting in high development costs and maintenance difficulties. Delayed emergency response: In the event of a malfunction or emergency, the emergency mode cannot be automatically switched, and there is an over-reliance on manual operation, resulting in a slow response and a high risk of secondary disasters. The risk avoidance strategy is too simplistic: the lack of dynamic assessment of risk avoidance areas (such as population density and terrain adaptability) makes it difficult to ensure the safe docking of the vehicle. Therefore, there is an urgent need for a navigation and control method that is highly versatile, has a high safety level, and can automatically respond to emergencies and avoid risks. Summary of the Invention

[0003] The purpose of this invention is to overcome the shortcomings of existing technologies and provide a universal mobile carrier navigation control method that integrates safe zones and pedestrian density, achieving safe driving under normal conditions and automatic fault avoidance. The technical solution of this invention is as follows: 1. Constructing a unified map: Establishing a multi-layer navigation map including safe zones, restricted zones, and no-entry / no-stopping zones. 2. Real-time perception: Integrating onboard sensor data and cloud data to obtain pedestrian density and environmental information in real time. 3. Safety planning: In normal mode, using a weighted function model, pedestrian density is assigned the highest negative weight to actively avoid crowds. 4. Automatic takeover: When a fault is triggered, the system takes over control with the highest priority, blocking manual intervention and switching to emergency mode. 5. Dynamic fault avoidance: In emergency mode, considering distance, pedestrian density, terrain, and remaining power, the optimal avoidance area is selected and the vehicle automatically docks. The beneficial effects of this invention are: 1. High versatility: One system can be adapted to aircraft, vehicles, robots, and ships, significantly reducing development and maintenance costs. 2. Proactive safety: Normally avoiding high-density pedestrian flow reduces risk at the source; automatic fault avoidance in emergencies reduces secondary disasters. 3. Rapid Response: Dual-mode map sharing eliminates the need for repeated map construction, enabling millisecond-level switching and high reliability. Detailed Implementation: The invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. Embodiment 1: Navigation and Emergency Landing of Urban Logistics Drones This embodiment is applied to an urban low-altitude logistics delivery scenario, using a hexacopter drone as the mobile carrier. Map building: The system pre-marks rooftop helipads and open spaces in parks as "safe areas" on an electronic map, and airport airspaces and high-voltage lines as "restricted areas." Routine operation: The drone performs delivery tasks. If the route needs to cross a commercial pedestrian street (extremely high pedestrian density), the system automatically selects route two (low pedestrian density) along the main road based on a weighted function model, achieving proactive avoidance. Emergency trigger: An abnormal current in motor 3 is detected during flight. The system determines it to be a power failure, immediately blocks the manual passage, and takes over flight control. Hazard avoidance execution: The system scans the area within 2 kilometers of the current location. The nearest area is a school playground (low pedestrian density during school hours), and the next nearest area is an intersection (high pedestrian density). The system calculates the "distance-safety" comprehensive cost and locks the playground as the hazard avoidance point. The system controls the drone to adjust its attitude, shuts off some power, lands safely, and sends a rescue report. Example 2: Emergency parking of an autonomous vehicle This embodiment is applied to an urban ground-based autonomous driving passenger scenario (RoboTaxi). Normal operation: The vehicle uses radar and cameras to detect a large number of pedestrians gathering on both sides of a zebra crossing (density exceeding a threshold), proactively planning an alternate route or slowing down in advance to prevent blind spot accidents. Emergency trigger: During high-speed driving, a sudden drop in brake line pressure triggers a critical malfunction in the system. Emergency avoidance execution: The system activates emergency mode. It detects high pedestrian and vehicle density in the right-hand non-motorized vehicle lane and an available bus bay 200 meters to the left. The system controls the vehicle to smoothly change lanes using remaining braking force, slowly stopping at the bus bay, activating hazard lights to avoid colliding with pedestrians in the non-motorized vehicle lane. Example 3: Emergency wind and hazard avoidance on unmanned watercraft. This embodiment is applied to the cleaning and maintenance of urban rivers and lakes. Normal operation: When the unmanned vessel is operating, it automatically moves 50 meters away from swimming areas (where many people are in the water) to ensure it does not approach crowds. Emergency trigger: In the event of a sudden thunderstorm with strong winds exceeding the threshold and the battery level dropping sharply due to wind resistance. Hazard avoidance execution: The system prioritizes searching for safe harbors. It detects a densely populated dock on the north bank and an abandoned cargo dock on the south bank. Although the north bank is closer, the system chooses the south bank for safety. It controls the vessel to adjust its attitude against the wind and automatically drives it to the south bank to moor and secure itself. Attached Figure Description Figure 1 : Schematic diagram of the method flow of the present invention (steps S1-S6). Figure 2 : A schematic diagram of the system architecture of this invention (including a navigation map, a perception module, a main control module, and a mobile carrier). Figure 3 : Schematic diagram of the internal structure of a computer device.

[0004] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0005] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0006] like Figures 1-2 As shown, this application provides a universal mobile carrier navigation control method that integrates safety area and pedestrian density, including: S1: Construct a multi-layer digital navigation map, wherein the map layers include at least a safe zone layer, a restricted zone layer, and a no-entry / no-stopping zone layer under a unified coordinate system; S2: Real-time environmental data of the surrounding area of ​​the mobile vehicle's current location is acquired through a sensor network. The environmental data includes real-time pedestrian density, road traffic conditions, and meteorological information. S3: When the vehicle is in normal driving or flight mode, based on the principle of safety priority, and combined with the safety zone layer and real-time crowd density data, the optimal conventional route to avoid densely populated areas and dangerous areas is planned. S4: Real-time monitoring of carrier status parameters. When a carrier malfunction, power system alarm, or emergency status signal is detected, the system automatically switches from normal working mode to emergency avoidance mode. S5: In emergency mode, based on the current location, quickly select the nearest safe zone that meets the conditions for safe shutdown. The selection criteria for the safe zone include the lowest threshold of population density and terrain adaptability, and / or select the nearest safe zone or rescue response point with the lowest population density. S6: Generate automatic control commands from the current location to the hazard avoidance area, control the vehicle to move along the planned hazard avoidance path, and complete precise docking, landing or stopping actions.

[0007] In one embodiment, by constructing a unified electronic navigation map layer and standardized control interfaces, an innovative approach of "one navigation solution applicable to all platforms" has been achieved. Whether it's an aircraft, ground vehicle, robot, or ship, all can utilize the same navigation kernel, significantly reducing the development cost and maintenance difficulty of urban intelligent transportation systems and laying the foundation for unified scheduling and management of multimodal urban traffic in the future.

[0008] By integrating dynamic data on pedestrian density, proactive safety in daily operations is significantly improved; Traditional navigation technologies primarily focus on the physical properties of a route, often neglecting the crucial safety factor of population density in the environment. By incorporating real-time pedestrian density as a core parameter into the route planning algorithm, densely populated areas can be proactively avoided during daily driving. This "preventative" navigation strategy can fundamentally reduce the probability of mass casualties in accidents involving mobile vehicles, making it particularly suitable for safety management in densely populated urban areas.

[0009] It has fully automatic emergency avoidance capabilities, which greatly reduces the risk of secondary disasters in the event of a malfunction; When the vehicle malfunctions or is in an emergency, manual operation often leads to errors due to long reaction times and high psychological pressure. An independent emergency avoidance mode is in place. Once the system detects an anomaly, it can automatically take over control within milliseconds and quickly select the safest area with the "closest distance" and "lowest pedestrian density" for forced landing or stopping based on real-time environmental data. This mechanism effectively solves the problem of the vehicle crashing into crowds due to loss of control or erratic movement in emergency situations, achieving comprehensive safety protection for the public and property around the vehicle.

[0010] The architecture is highly efficient and the data is easily reusable. The design approach, which uses the same map security layer for both normal and emergency modes, avoids redundant map data construction and storage. Simultaneously, the system automatically switches modes based on the carrier's status without manual intervention, ensuring rapid response even in extreme situations. This efficient data architecture and response mechanism make this method highly valuable for commercial application.

[0011] As described in the steps above, the general mobile carrier also includes, but is not limited to, aircraft, ground vehicles, mobile robots, surface vessels, and rail transit equipment; cross-platform general navigation is achieved by adapting the kinematic models and control commands of different carriers through a unified interface protocol.

[0012] Preferably, the normal working mode and the emergency evacuation mode share the same set of preset map safety layers, eliminating the need to repeatedly construct map data for different modes; the safety zone layer has differentiated attribute labels according to different types of carriers, including the maximum allowable load weight, the allowable landing / parking method, and the applicable carrier type.

[0013] Preferably, the acquisition of the crowd density data integrates multi-source data, including local crowd identification data obtained through carrier visual sensors and macro-level crowd statistics for specific urban areas obtained through cloud interfaces; the response sensitivity of the path planning is dynamically adjusted according to the data update frequency.

[0014] Preferably, the path planning algorithm in the normal working mode adopts a weighted function model. The weighted function model comprehensively considers the distance, estimated time, pedestrian density coefficient of the path area and historical safety level, and assigns the highest negative weight value to the pedestrian density coefficient and safety level to ensure that the path planning results actively avoid high-density crowds.

[0015] As a preferred option, the system automatically switches modes based on the carrier's status. When the carrier's fault level exceeds a preset threshold or an externally triggered SOS signal is received, the system immediately interrupts the current task path planning, blocks the manual intervention channel, takes over the carrier's control with the highest priority, and enters the emergency avoidance mode.

[0016] Preferably, the specific types of safe areas include open spaces, rooftop helipads, dedicated emergency parking points, emergency lanes, calm water areas, and pre-designated blind landing zones; when selecting safe areas, accessibility is calculated based on the vehicle's current remaining power, range, and degree of damage, and inaccessible areas are eliminated.

[0017] As an alternative, a multi-target safe zone screening mechanism is also included. When the population density of the nearest safe zone exceeds the safety threshold, the system automatically calculates the distance-safety comprehensive cost and selects the second-best safe zone with the lowest comprehensive cost, ensuring that the collision risk is minimized during the process of reaching the safe zone.

[0018] Preferably, the control vehicle's actions of docking, landing, or stopping include an attitude adjustment process; based on the flatness of the ground, the wave conditions of the water, or the form of the docking facilities in the evacuation area, the approach angle, descent speed, and final stopping attitude of the vehicle are automatically adjusted to prevent rollover, slippage, or sinking in the final stage of evacuation.

[0019] As an option, it also includes an information feedback step after an emergency: when the vehicle completes an emergency stop, landing or parking, the system automatically generates an emergency report containing geographical location, status information and on-site image data, and sends it to a preset monitoring center or operation management platform via a wireless communication network.

[0020] In one embodiment, application scenario one: delivery and emergency landing of urban logistics drones: This embodiment is applied to urban low-altitude logistics delivery scenarios, and the mobile carrier is a hexacopter drone.

[0021] Map Construction and Preset: The system pre-constructs a multi-layer structure in the city's electronic navigation map. Among them, the "Safe Zone Layer" marks rooftop helipads, open spaces in parks, and specific emergency parachute drop zones in the city; the "Restricted Area Layer" marks airport airspace, military control zones, and high-voltage power line corridors; and the "Restricted Area Layer" marks the airspace above residential areas where flights are restricted at specific times due to noise control.

[0022] Real-time data acquisition: The drone's onboard visual sensors and communication modules collect real-time environmental data. Simultaneously, it connects to the city's smart city infrastructure via a 5G network to obtain real-time heatmap data of pedestrian flow in the target area and the surrounding area.

[0023] Normal working mode: When a drone performs a delivery mission from point A to point B, the navigation control module calculates the path. Assume there are two paths: Path 1 is the shortest but crosses a commercial pedestrian street (with extremely high real-time pedestrian density); Path 2 is slightly longer but flies above a main urban road (with low pedestrian density). Based on the "safety priority principle" of this invention, the system automatically assigns a penalty to the path with extremely high "pedestrian density," ultimately planning and selecting Path 2 as the optimal conventional path, and the drone flies along Path 2.

[0024] Emergency evacuation mode triggered: During flight, the UAV's onboard diagnostic system detected an abnormal current in motor No. 3, issued a power system fault warning, and then triggered an "emergency state".

[0025] Emergency Path Planning and Control: The system automatically takes over flight control and instantly switches to emergency avoidance mode.

[0026] Filtering: The system scans a "safe zone layer" with a radius of 2 kilometers centered on the drone's current location. The nearest area was found to be a school playground (currently during school hours, low pedestrian density), and the next nearest area was an intersection (extremely high pedestrian density).

[0027] Decision: The system calculates the overall cost of "distance-safety", eliminates the crossroads, and identifies the school playground as the final refuge point.

[0028] Execution: The system generates an emergency trajectory for a straight descent or glide, controls the drone to adjust its attitude, avoids surrounding buildings, quickly heads to the school playground, and shuts off its power before touching down to mitigate the impact, ultimately landing safely. At the same time, it sends a rescue request containing coordinates to the operations center.

[0029] Application Scenario 2: Safe Driving and Emergency Roadside Parking of Autonomous RoboTaxi This embodiment applies to an urban ground-based autonomous driving passenger scenario, where the mobile carrier is an L4-level autonomous vehicle.

[0030] Map Construction and Presets: The navigation map includes the city's road network topology and areas with special attributes. Among them, the "Safety Zone Layer" defines emergency lanes, roadside temporary parking spots, and wide road edges; the "No Entry Layer" includes sidewalks and sections of road where vehicles drive against the flow of traffic.

[0031] Normal working mode: The vehicle was traveling during the evening rush hour. The system analyzes the surrounding environment in real time using onboard cameras and radar, and obtains information on road conditions and pedestrian density. When driving through a busy commercial area, the system detected that although there were gaps between vehicles ahead of the right-turn lane, a large number of pedestrians were gathered on both sides of the zebra crossing (pedestrian density exceeded the threshold). To prevent safety accidents caused by blind spots or sudden pedestrian violations, the navigation system proactively planned a slightly longer straight detour route, or anticipated and slowed down before the stop line, ensuring absolute avoidance of crowds during the journey.

[0032] Emergency evacuation mode triggered: While the vehicle was traveling at high speed, the forward collision warning system detected a sudden drop in brake line pressure, resulting in a 50% decrease in braking efficiency, which was determined to be a critical malfunction.

[0033] Emergency Path Planning and Control: The system immediately activated the emergency avoidance mode and turned on the hazard lights to warn surrounding vehicles.

[0034] Filtering: The system quickly searches the surrounding environment of the current road. The right side of the current road is a solid line (no parking), and there are a large number of electric vehicles traveling in the non-motorized vehicle lane (high pedestrian / vehicle density); there is a bus bay 200 meters away on the left side of the road, but no buses are stopping there at the moment (low pedestrian density).

[0035] Decision: Based on comprehensive assessment, parking on the right side is extremely risky, while parking on the left side is relatively safe and within the vehicle's coasting range.

[0036] Execution: The navigation system controls the vehicle to activate the left turn signal, and uses remaining braking force and engine braking to smoothly change lanes and merge into the left lane. As it approaches the stop, the system controls the vehicle to slowly pull over at low speed, eventually stopping inside the bay-style stop, thus avoiding a collision with pedestrians in the non-motorized vehicle lane.

[0037] Application Scenario 3: Operation and sheltering from wind and danger for unmanned cleaning vessels on water: This embodiment is applied to the cleaning and maintenance of urban rivers and lakes, and the mobile carrier is an unmanned water surface cleaning vessel.

[0038] Map construction and presets: The electronic map of the water features preset "safe areas" (such as harbors, dock berths, and shallow, slow-flowing areas) and "restricted areas" (such as swimming areas and water sports areas).

[0039] Normal working mode: The cleaning boat is collecting trash from the lake. The system monitors the surrounding environment in real time. When it approaches the swimming area, it detects a large number of people entering the water. Based on the principle of safety first, the navigation system automatically shifts the cleaning boat's work path 50 meters outward, cleaning along the outer boundary of the swimming area. This ensures coverage while avoiding proximity to people and preventing the propeller from injuring swimmers.

[0040] Emergency evacuation mode triggered: When suddenly caught in a localized thunderstorm with strong winds, the wind speed sensor readings exceeded the safety threshold, and the battery was being drained too quickly due to increased wind resistance, triggering a low battery emergency alarm.

[0041] Emergency Path Planning and Control: The system has switched to emergency mode.

[0042] Filtering: The system prioritizes searching for the nearest safe harbor. At the same time, video analysis revealed that the nearest north shore pier was experiencing passenger and vessel activity (high density of people / ships), while there was an abandoned cargo pier 500 meters away on the south shore (open and deserted).

[0043] Decision: Although the north bank is closer, the system selects the abandoned cargo terminal on the south bank as the safe haven to avoid the risk of hitting dock personnel in the event of loss of control.

[0044] Execution: The system controls the cleaning vessel to adjust its bow against the wind, reduce its wind-caught area, plan the optimal wind-resistant path, automatically drive to the abandoned dock on the south bank, moor and secure it, and wait for rescue.

[0045] The present invention also provides a computer device, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps of the above-described general mobile carrier navigation control method that integrates safety area and crowd density.

[0046] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described general mobile carrier navigation control method that integrates safety area and crowd density.

[0047] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in this application and in the embodiments can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual-speed SDRAM (SSRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0048] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, apparatus, article, or method that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, apparatus, article, or method. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, apparatus, article, or method that includes that element.

[0049] The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Any equivalent structural or procedural transformations made based on the content of the present invention's specification and drawings, or direct or indirect applications in other related technical fields, are similarly included within the patent protection scope of the present invention.

Claims

1. A method for navigation control of a general mobile carrier fusing a safety area with a human flow density, characterized by, Includes the following steps: A multi-layered digital navigation map with a unified coordinate system is constructed, comprising at least a safe zone layer, a restricted zone layer, and a no-entry / no-stopping zone layer. Environmental data surrounding the mobile vehicle's current location is collected in real-time via a sensor network and cloud data interface. This environmental data includes real-time pedestrian density, road traffic conditions, and meteorological information. During normal operation, based on a safety-first principle, and combining the safe zone layer with real-time pedestrian density data, a conventional route is planned to avoid densely populated and dangerous areas. The vehicle's status parameters are monitored in real-time. When a fault, power system alarm, or emergency trigger signal is detected, the system automatically switches from normal mode to emergency avoidance mode. In emergency mode, the system selects the nearest avoidance zone centered on the current location that meets the pedestrian density threshold, has suitable terrain, and is power-accessible. Control commands are generated for the avoidance zone, controlling the vehicle to move along the avoidance path and perform precise docking, landing, or stopping maneuvers.

2. The method according to claim 1, characterized in that, The mobile carriers include aircraft, ground vehicles, mobile robots, and surface vessels; the system adapts the kinematic models of each carrier through a unified interface protocol to achieve universal navigation across carriers.

3. The method according to claim 1, characterized in that, The normal mode and emergency evacuation mode share the same map safety layer; the safety zone layer is configured with attribute labels according to the carrier type, including maximum load capacity, docking / landing method, and applicable carrier type.

4. The method according to claim 1, characterized in that, The pedestrian density data is obtained by fusing local visual recognition data of the carrier with macro-level pedestrian flow statistics of the urban area, and the sensitivity of path planning is dynamically adjusted according to the data update frequency.

5. The method according to claim 1, characterized in that, The conventional path is planned using a weighted function model, which takes into account distance, time, crowd density coefficient, and historical safety level. Crowd density and safety level are given the highest negative weights to achieve active obstacle and pedestrian avoidance.

6. The method according to claim 5, characterized in that, When the fault level exceeds the threshold or an SOS signal is received, the system interrupts the current path, blocks manual intervention, takes over control with the highest priority, and enters emergency avoidance mode.

7. The method according to claim 5, characterized in that, The safe zones include open areas, helipads, emergency parking spots, emergency lanes, calm waters, and instrument landing zones; during the screening process, accessibility is calculated based on remaining range and the extent of damage, and inaccessible areas are eliminated.

8. The method according to claim 5, characterized in that, When the population density in the nearest safe zone exceeds the threshold, the second-best safe zone is selected based on the combined cost of distance and safety to reduce the risk of collision.

9. The method according to claim 5, characterized in that, When docking / landing / stopping, the approach angle, descent speed and stopping attitude are automatically adjusted according to the flatness of the site, the wave conditions and the docking facilities to prevent rollover, slippage and sinking.

10. The method according to claim 5, characterized in that, After the vehicle completes its safe landing, it automatically generates an emergency report containing its location, status, and on-site images, and sends it to the monitoring center or management platform.

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