Offline navigation method and offline navigation system without intervention of background command center

Abstract

The invention provides an off-line navigation method and an off-line navigation system without intervention of a background command center. A vehicle-mounted device selects path nodes through an evaluation function, analyzes real-time traffic flow conditions, dynamically adjusts the evaluation function, obtains an optimal path and sends the optimal path to a credit control center platform through a wireless private network; the vehicle-mounted equipment calculates the time when the vehicle arrives at a plurality of intersections according to the optimal path and the real-time positioning information of the vehicle so as to determine the signal lamp adjustment time of the intersections, and sends the signal lamp adjustment time to the corresponding countdown controllers through a wireless private network; the countdown controller adjusts the traffic lights according to the corresponding signal light adjusting time. The optimal path can be selected in real time according to the actual road condition, the traffic light is controlled through the vehicle-mounted equipment, and the police dispatching efficiency and safety are improved.

Description

Technical Field

[0001] The present invention relates to a traffic control system, and more particularly, to an offline navigation method and an offline navigation system that do not require the intervention of a back-end command center. Background Art

[0002] Navigation is the process of monitoring and controlling the movement of a vehicle from one place to another. The technology of commercial navigation software on the market is already very mature, which greatly facilitates the travel of the public. However, for information security considerations, public security organs do not use this type of online commercial navigation software when dispatching police, but mainly rely on offline maps. For example, the offline navigation method, device and mobile carrier disclosed in the patent document CN118603109A.

[0003] Although using an offline map for navigation can guide the vehicle to the destination normally, the offline map does not know the actual road traffic conditions, that is, it can only plan the shortest path, but cannot plan the fastest path. It cannot ensure that the vehicle reaches the destination quickly. Therefore, in the actual use of public security organs, it is still necessary to guide the vehicle according to the road video data through the back-end command center to avoid driving into congested sections. However, this solution is affected by the communication network delay, and it is easy to cause both parties to fail to receive information in time and cause delays.

[0004] In view of this, it is necessary to further improve the police dispatch speed on the basis of offline map navigation. Summary of the Invention

[0005] Aiming at the deficiencies in the prior art, the purpose of the present invention is to provide an offline navigation method and an offline navigation system that do not require the intervention of a back-end command center.

[0006] According to an offline navigation method provided by the present invention that does not require the intervention of a back-end command center, it includes: Path planning step: Select path nodes through an evaluation function, analyze the real-time traffic flow situation, dynamically adjust the evaluation function, and obtain the optimal path; Linkage control step: The in-vehicle device calculates the time for the vehicle to reach multiple intersections according to the optimal path and the real-time positioning information of the vehicle, thereby determining the signal light adjustment time for multiple intersections, and sending the signal light adjustment times for multiple intersections to the corresponding countdown controllers through a wireless private network; Signal light control step: The countdown controller adjusts the time of the traffic lights according to the corresponding signal light adjustment time.

[0007] Further, the formula of the evaluation function is:

[0008] Wherein, is the evaluation value of path node n, is the actual cost from the starting point to path node n, is the estimated cost from path node n to the destination. Analyze the real-time traffic flow situation to make adjustments and select the path node with the smallest value as the current path node and loop accordingly to obtain the optimal path.

[0009] Furthermore, the current traffic flow of section i is , and the maximum carrying capacity is ; Dynamic adjustment coefficient :

[0010]

[0011] is the length of section i, is the set of sections passed by the path from the starting point to path node n;

[0012] ( , ) are the coordinates of the destination, and ( , ) are the coordinates of the current path node.

[0013] Furthermore, the methods for determining the signal light adjustment times of multiple intersections include: The distance of the vehicle from the first intersection is , the current vehicle speed is , the signal light cycle of the first intersection is , the remaining green light time is , the distance between the first intersection and the second intersection is , and the signal light cycle of the second intersection is ; Calculate the time required for the vehicle to reach the first intersection . If > , then adjust the green light time of the first intersection . After the vehicle passes through the first intersection , the current vehicle speed is , and the vehicle travels from the first intersection to the second intersection Required time , adjust the second intersection green light time , which is the remaining green light time when the vehicle arrives.

[0014] Furthermore, the real-time positioning information of the vehicle is obtained through an in-vehicle positioning system.

[0015] An offline navigation system provided by the present invention includes: An in-vehicle positioning system for obtaining the real-time positioning information of the vehicle; An in-vehicle device: capable of establishing a wireless communication connection with the selected camera and signal lamp, selecting a path node through an evaluation function, connecting to the camera corresponding to the selected path node through a wireless network, analyzing the real-time traffic flow situation based on the video collected by the camera, dynamically adjusting the evaluation function to obtain the optimal path; calculating the time for the vehicle to reach multiple intersections according to the optimal path and the real-time positioning information of the vehicle, thereby determining the signal lamp adjustment time for multiple intersections, and sending the signal lamp adjustment times for multiple intersections to the corresponding signal lamps through a wireless private network.

[0016] Furthermore, the in-vehicle positioning system includes a GPS navigation system or a Beidou navigation system.

[0017] Furthermore, the cameras are arranged on all path nodes, and the cameras include a wireless communication module for wireless communication connection with the in-vehicle device.

[0018] Furthermore, the signal lamps include a wireless communication module for wireless communication connection with the in-vehicle device.

[0019] Furthermore, the signal lamps include a countdown controller for adjusting the red and green light times according to the received signal lamp adjustment time.

[0020] Compared with the prior art, the present invention has the following beneficial effects: The real-time traffic condition analysis and optimized path planning algorithm of the present invention, as well as the multi-intersection collaborative traffic light control directly through the in-vehicle device, can greatly shorten the police dispatch time and ensure rapid arrival at the scene in case of emergency. The path planned by the intelligent algorithm fully considers road safety factors, avoiding safety risks caused by choosing dangerous or congested roads. At the same time, the present invention does not require a background command center to remotely and real-time guide vehicle traffic and control signal lamps, avoiding the problem of reduced police dispatch efficiency caused by network line delay. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] By reading the detailed description of the non-limiting embodiments with reference to the following drawings, other features, objects, and advantages of the present invention will become more apparent: Figure 1 This is the flowchart of the present invention. Specific embodiments

[0022] The present invention will be described in detail below in conjunction with specific embodiments. The following embodiments will help those skilled in the art to further understand the present invention, but do not limit the present invention in any form. It should be noted that for those of ordinary skill in the art, without departing from the concept of the present invention, several changes and improvements can still be made. These all belong to the protection scope of the present invention.

[0023] As Figure 1 shown, an offline navigation method without the intervention of a background command center includes: Path planning step: The in-vehicle device selects path nodes through an evaluation function, analyzes the real-time traffic flow situation, dynamically adjusts the evaluation function, and obtains the optimal path.

[0024] The formula of the evaluation function is: . Wherein, is the evaluation value of path node n, is the actual cost from the starting point to path node n. is the estimated cost from path node n to the destination, and usually the Manhattan distance or Euclidean distance is used as the estimation function. Analyze the real-time traffic flow situation to adjust , and select the path node with the smallest value as the current path node and loop accordingly to obtain the optimal path.

[0025] Considering the dynamic situation of the road, such as the real-time change of traffic flow, dynamically adjust . The current traffic flow of section i is , and the maximum carrying capacity is ; Dynamic adjustment coefficient :

[0026]

[0027] is the length of section i, is the set of sections passed by the path from the starting point to path node n;

[0028] ( , ) are the destination coordinates, and ( , ) are the coordinates of the current path node.

[0029] For example, assume there is a path from the starting point S to node N, passing through sections A and B. The length of section A is l A = 2 km, the current traffic flow is 200 vehicles per hour, and the maximum carrying capacity is 500 vehicles per hour. The length of section B is l B = 3 km, the current traffic flow is 300 vehicles per hour, and the maximum carrying capacity is 600 vehicles per hour. Then = 1.4, = 1.5, = 1.4 * 2 + 1.5 * 3 = 7.3.

[0030] Linkage control step: The in-vehicle device calculates the time for the vehicle to reach multiple intersections based on the optimal path and the real-time positioning information of the vehicle, thereby determining the signal adjustment times of multiple intersections, and sending the signal adjustment times of multiple intersections to the corresponding countdown controllers through the wireless private network.

[0031] Considering the coordinated control between multiple intersections and the speed changes during the vehicle's driving process, the following calculation method is adopted.

[0032] The ways to determine the signal adjustment times of multiple intersections include: The distance of the vehicle from the first intersection is , the current vehicle speed is , the signal cycle of the first intersection is , the remaining green time is , the distance between the first intersection and the second intersection is , the signal cycle of the second intersection is .

[0033] Calculate the time required for the vehicle to reach the first intersection . If > , then adjust the green time of the first intersection . After the vehicle passes through the first intersection , the current vehicle speed is . The time required for the vehicle to reach the second intersection from the first intersection . Adjust the green time of the second intersection . The remaining green light time when the police car arrives. In this way, the coordinated control of traffic lights at multiple intersections is achieved to ensure that vehicles can pass quickly.

[0034] Steps for traffic light control: The countdown controller adjusts the time of the traffic lights according to the corresponding traffic light adjustment time.

[0035] The present invention also provides an offline navigation system, which can be implemented by executing the process steps of the offline navigation method without the intervention of a background command center. That is, those skilled in the art can understand the offline navigation method without the intervention of a background command center as the preferred implementation manner of the offline navigation system. The system includes: A vehicle-mounted positioning system for obtaining the real-time positioning information of the vehicle; Vehicle-mounted device: capable of establishing a wireless communication connection with the selected cameras and traffic lights, selecting path nodes through an evaluation function, connecting to the cameras corresponding to the selected path nodes through a wireless network, analyzing the real-time traffic flow situation based on the videos collected by the cameras, dynamically adjusting the evaluation function to obtain the best path; calculating the time for the vehicle to reach multiple intersections based on the best path and the real-time positioning information of the vehicle, thereby determining the traffic light adjustment times for multiple intersections, and sending the traffic light adjustment times for multiple intersections to the corresponding traffic lights through a wireless private network.

[0036] Among them, the vehicle-mounted positioning system includes a GPS navigation system or a Beidou navigation system. Cameras are arranged at all path nodes, and both the cameras and the traffic lights include wireless communication modules for wireless communication connection with the vehicle-mounted device. The traffic lights also include a countdown controller for adjusting the time of the traffic lights according to the received traffic light adjustment time.

[0037] Those skilled in the art know that in addition to implementing the system and its various devices, modules, and units provided by the present invention in the form of pure computer-readable program code, the method steps can be logically programmed to enable the system and its various devices, modules, and units provided by the present invention to be implemented in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers, etc. to achieve the same functions. Therefore, the system and its various devices, modules, and units provided by the present invention can be considered as a hardware component, and the devices, modules, and units included therein for implementing various functions can also be regarded as the structures within the hardware component; the devices, modules, and units for implementing various functions can also be regarded as both software modules for implementing the method and the structures within the hardware component.

[0038] The specific embodiments of the present invention have been described above. It should be understood that the present invention is not limited to the above specific embodiments, and those skilled in the art can make various changes or modifications within the scope of the claims, which does not affect the essence of the present invention. Without conflict, the embodiments of the present application and the features in the embodiments can be combined with each other arbitrarily.

Claims

1. An offline navigation method without the intervention of a background command center, characterized in that, Including: Path planning step: Select path nodes through an evaluation function, analyze the real-time traffic flow situation, dynamically adjust the evaluation function, and obtain the optimal path; Linkage control step: The in-vehicle device calculates the time for the vehicle to reach multiple intersections based on the optimal path and the real-time positioning information of the vehicle, thereby determining the signal light adjustment times for multiple intersections, and sending the signal light adjustment times for multiple intersections to the corresponding countdown controllers through a wireless private network; Signal light control step: The countdown controller adjusts the red and green light times according to the corresponding signal light adjustment times.

2. The offline navigation method without the intervention of a background command center according to claim 1, characterized in that The formula of the evaluation function is: Among them, is the evaluation value of path node n, is the actual cost from the starting point to path node n, is the estimated cost from path node n to the destination. Analyze the real-time traffic flow situation and adjust to select the path node with the smallest value as the current path node and loop accordingly to obtain the optimal path.

3. The offline navigation method without the intervention of a background command center according to claim 2, characterized in that The current traffic flow of section i is , and the maximum carrying capacity is ; Dynamic adjustment coefficient : is the length of section i, is the set of sections passed by the path from the starting point to path node n; (( , )) is the destination coordinate, and (( , )) is the coordinate of the current path node.

4. The offline navigation method without the intervention of a background command center according to claim 1, characterized in that The method for determining the signal light adjustment times for multiple intersections includes: The vehicle's distance from the first intersection is , the current vehicle speed is , the signal cycle of the first intersection is , the remaining time of the green light is , the first intersection and the second intersection is , the signal cycle of the second intersection is ; Calculate the time required for the vehicle to reach the first intersection Required time , if > , then adjust the green light time of the first intersection Green light time , after the vehicle passes through the first intersection , the current vehicle speed is , the vehicle starts from the first intersection to reach the second intersection Required time , adjust the green light time of the second intersection Green light time , Is the remaining green light time when the vehicle arrives 5. The offline navigation method without the intervention of a background command center according to claim 1, characterized in that The real-time positioning information of the vehicle is obtained through an in-vehicle positioning system.

6. An offline navigation system, characterized in that, Including: An in-vehicle positioning system that obtains the real-time positioning information of the vehicle; An in-vehicle device: capable of establishing a wireless communication connection with the selected cameras and signal lights, selecting path nodes through an evaluation function, connecting to the cameras corresponding to the selected path nodes through a wireless network, and analyzing the real-time traffic flow situation based on the videos collected by the cameras, dynamically adjusting the evaluation function to obtain the optimal path; calculating the time for the vehicle to reach multiple intersections based on the optimal path and the real-time positioning information of the vehicle, thereby determining the signal light adjustment times for multiple intersections, and sending the signal light adjustment times for multiple intersections to the corresponding signal lights through a wireless private network.

7. The offline navigation system according to claim 6, characterized in that, The in-vehicle positioning system includes a GPS navigation system or a Beidou navigation system.

8. The offline navigation system according to claim 6, wherein The cameras are arranged on all path nodes, and the cameras include a wireless communication module for wireless communication connection with the in-vehicle device.

9. The offline navigation system according to claim 6, characterized in that, The signal lights include a wireless communication module for wireless communication connection with the in-vehicle device.

10. The offline navigation system according to claim 6, characterized in that The signal lights include a countdown controller that adjusts the red and green light times according to the received signal light adjustment times.

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