Vehicle interaction system based on LBS and interaction method thereof

Abstract

The invention provides an LBS-based vehicle interaction system and an interaction method thereof, and relates to the field of vehicle information interaction.The LBS-based vehicle interaction system comprises a vehicle-mounted edge server, a cloud server, a communication module, an LBS module, a processing module and a vehicle-mounted detection module; the communication module is used for information interaction between vehicles, between the vehicle and people, between the vehicle and the vehicle-mounted edge server and between the vehicle and the cloud server; the vehicle position on the road is accurately positioned in real time through the LBS module, the vehicle-mounted detection module is matched with the processing module, the vehicle-mounted edge server, the cloud server and the communication module to construct a real-time traffic flow model, and the real-time traffic flow model is displayed to a user through the man-machine interaction panel to assist the user in driving on the road, so that the user experience is improved. And meanwhile, voice reminding can be immediately performed on the user for some emergencies, obstacles and road condition information, so that the driving experience of the user is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of vehicle information interaction, and in particular to a vehicle interaction system based on LBS and an interaction method thereof. Background Art

[0002] Currently, vehicle interaction technology based on LBS (location-based service) has been widely used in navigation, location sharing, real-time traffic information push and other fields; common application scenarios include: in-vehicle navigation and positioning services.

[0003] Most LBS systems mainly rely on GPS and map data to provide path planning and real-time navigation. However, these systems are usually unable to perceive the dynamic changes of surrounding vehicles, traffic facilities or the environment in real time, resulting in poor user experience and inability to handle emergency or sudden traffic situations in a timely manner. Therefore, the present invention proposes a vehicle interaction system based on LBS and an interaction method thereof to solve the problems existing in the prior art. Summary of the invention

[0004] In response to the above problems, the present invention proposes a vehicle interaction system and an interaction method based on LBS. The vehicle interaction system and the interaction method based on LBS use the LBS module to accurately locate the vehicle position on the road in real time, and then build a real-time traffic flow model through the on-board detection module, the processing module, the on-board edge server, the cloud server and the communication module, and display it to the user through the human-computer interaction panel to assist the user in driving on the road.

[0005] To achieve the purpose of the present invention, the present invention is implemented through the following technical solutions: a vehicle interaction system based on LBS, including a vehicle edge server, a cloud server, a communication module, an LBS module, a processing module and a vehicle detection module, the communication module is used for information interaction between vehicles, vehicles and people, vehicles and vehicle edge servers, and vehicles and cloud servers, the vehicle edge server is used for transmission services of vehicle speed information and vehicle condition information, the cloud server is used for transmission services of road weather, geometry, slope and speed limit information, the LBS module is used to locate the position of the vehicle, and the vehicle detection module is used for detection of the vehicle and its surrounding environment; The on-board detection module monitors the vehicle's surrounding environment information and vehicle information and transmits it to the on-board edge server through the communication module. The processing module integrates and processes the received information of the on-board edge server, and then cooperates with the LBS module to locate the vehicle position, thereby constructing a traffic flow model.

[0006] A further improvement is that the construction range of the traffic flow model is 1 km before and after the vehicle.

[0007] A further improvement is that the vehicle-mounted detection module includes a vehicle-mounted radar, a vehicle-mounted probe, a vehicle sensor unit and a vehicle-mounted diagnostic unit, the vehicle-mounted radar monitors obstacles around the vehicle, the vehicle-mounted probe records information about the vehicle's surroundings, the vehicle sensor unit measures the speed of the vehicle, the vehicle-mounted diagnostic unit monitors and diagnoses the vehicle system, the processing module is connected to the vehicle sensor unit and the vehicle-mounted diagnostic unit, and monitors the vehicle's speed information and the vehicle's status in real time.

[0008] A further improvement is that the communication module includes a human-computer interaction panel and a C-V2X communication module, the human-computer interaction panel is used to present the traffic model to the user, the human-computer interaction panel is also used for voice interaction with the user, and the C-V2X communication module cooperates with the on-board edge server for real-time transmission of information between vehicles, wherein the information transmitted between vehicles includes road obstacle information received by the on-board radar, video image information of the vehicle's surrounding environment received by the on-board probe, vehicle speed information received by the vehicle sensor unit, and vehicle system status information received by the on-board diagnostic unit.

[0009] A further improvement is that a timing module is provided in the vehicle-mounted edge server, and the data storage time of the vehicle-mounted edge server reaches the set time of the timing module, and can be overwritten by new storage data.

[0010] A further improvement is that the steps of constructing the traffic flow model include: S1. Data collection: collecting environmental information of the vehicle and its surroundings through the vehicle-mounted radar, vehicle-mounted probe, vehicle sensor unit and vehicle-mounted diagnostic unit in the vehicle-mounted detection module, obtaining road weather, geometry, slope and speed limit information from the cloud server through the communication module, and transmitting and collecting road condition information and vehicle information transmitted by other vehicles through the C-V2X communication module; S2, data processing, the processing module removes the received erroneous data and duplicate data, then receives the road obstacle information through the vehicle radar, receives the video image of the vehicle surrounding environment through the vehicle probe, receives the vehicle speed information through the vehicle sensor unit, and receives the vehicle system status information through the vehicle diagnostic unit, and integrates all the received information; S3, construction of a road model, the processing module constructs a road model of the vehicle driving road by receiving road geometry, slope and speed limit information, and generates the shape of the road by simulating the longitude and latitude of the road and the road geometry information through a 3D simulator, generates the slope of the road by simulating the slope information, generates a speed limit reminder by the speed limit information of the road, and simulates the surrounding environment of the road according to the video image of the surrounding environment of the vehicle; S4, constructing a vehicle model, based on the generated road model, determining the longitude and latitude of the vehicle through the LBS module, and then matching the longitude and latitude of the vehicle with the longitude and latitude on the road model, so as to locate the vehicle on the road model, and simulating a corresponding vehicle model on the road model according to the positioning; S5, constructing a traffic flow model. On the basis of constructing the vehicle model and the road model, the processing module assigns the vehicle model speed through the received vehicle speed information, and assigns the road model the number of lanes through the received vehicle surrounding environment information. Then, the vehicle model and the road model are combined to form a traffic flow model. The processing module further fills the traffic flow model by putting the vehicle surrounding information transmitted between vehicles into the vehicle model generated by the information source vehicle, and displays a more intuitive road condition to the user through the traffic flow model, thereby assisting the user in driving. S6. Construction of an environmental model: the processing module constructs a lane environmental model by receiving road weather information, and calculates the friction resistance between the vehicle and the road through the environmental model to further assist the user in driving.

[0011] A further improvement is that the processing module uses the LBS module and the C-V2X communication module in conjunction with the on-board edge server to update the position of the vehicle model and the vehicle surrounding environment simulated in the traffic model in real time.

[0012] The interaction method using the LBS-based vehicle interaction system comprises the following steps: W1. Generate an APP on the human-computer interaction panel, and the user can choose to build a traffic flow model by opening the APP; W2. After receiving the traffic flow model construction command, the processing module constructs the traffic flow model according to the traffic flow model construction steps; W3. After the traffic flow model is successfully constructed, it is displayed on the human-computer interaction panel. Users can intuitively understand the road condition information 1 km before and after the vehicle through the traffic flow model; W4. When a traffic accident or a breakdown of the vehicle ahead occurs, users can receive warnings earlier through the traffic model.

[0013] The beneficial effects of the present invention are as follows: the present invention uses the LBS module to accurately locate the position of vehicles on the road in real time, and then uses the on-board detection module to cooperate with the processing module, the on-board edge server, the cloud server and the communication module to build a real-time traffic model, and display it to the user through the human-computer interaction panel to assist the user in driving on the road. At the same time, for some emergencies, obstacles and road condition information, the user can be given instant voice reminders, thereby increasing the user's driving experience and further ensuring driving safety. At the same time, the denser the vehicles, the more specific the traffic model generated by this system is, which further assists the user in safe driving under dense traffic flow. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the structure of the system of the present invention. DETAILED DESCRIPTION

[0015] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with examples. The examples are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0016] according to Figure 1 As shown, this embodiment proposes a vehicle interaction system based on LBS, including an on-board edge server, a cloud server, a communication module, an LBS module, a processing module and an on-board detection module, wherein the communication module is used for information interaction between vehicles, vehicles and people, vehicles and on-board edge servers, and vehicles and cloud servers, the on-board edge server is used for transmission services of vehicle speed information and vehicle condition information, the cloud server is used for transmission services of road weather, geometry, slope and speed limit information, the LBS module is used for locating the position of the vehicle, and the on-board detection module is used for detection of the vehicle and its surrounding environment; The on-board detection module monitors the vehicle's surrounding environment information and vehicle information and transmits it to the on-board edge server through the communication module. The processing module integrates and processes the received information of the on-board edge server, and then cooperates with the LBS module to locate the vehicle position, thereby constructing a traffic flow model.

[0017] The construction range of the traffic flow model is 1 km before and after the vehicle.

[0018] The vehicle-mounted detection module includes a vehicle-mounted radar, a vehicle-mounted probe, a vehicle sensor unit and a vehicle-mounted diagnostic unit. The vehicle-mounted radar monitors obstacles around the vehicle, the vehicle-mounted probe records information about the vehicle's surroundings, the vehicle sensor unit measures the speed of the vehicle, and the vehicle-mounted diagnostic unit monitors and diagnoses the vehicle system. The processing module is connected to the vehicle sensor unit and the vehicle-mounted diagnostic unit, and monitors the vehicle's speed information and status in real time.

[0019] The communication module includes a human-computer interaction panel and a C-V2X communication module. The human-computer interaction panel is used to present the traffic model to the user. The human-computer interaction panel is also used for voice interaction with the user. The C-V2X communication module cooperates with the on-board edge server for real-time transmission of information between vehicles. The information transmitted between vehicles includes road obstacle information received by the on-board radar, video image information of the vehicle's surrounding environment received by the on-board probe, vehicle speed information received by the vehicle sensor unit, and vehicle system status information received by the on-board diagnostic unit.

[0020] The vehicle-mounted edge server is provided with a timing module, and when the storage time of the data of the vehicle-mounted edge server reaches the setting time of the timing module, the data is overwritten by new storage data.

[0021] The steps of constructing the traffic flow model include: S1. Data collection: collecting environmental information of the vehicle and its surroundings through the vehicle-mounted radar, vehicle-mounted probe, vehicle sensor unit and vehicle-mounted diagnostic unit in the vehicle-mounted detection module, obtaining road weather, geometry, slope and speed limit information from the cloud server through the communication module, and transmitting and collecting road condition information and vehicle information transmitted by other vehicles through the C-V2X communication module; S2, data processing, the processing module removes the received erroneous data and duplicate data, then receives the road obstacle information through the vehicle radar, receives the video image of the vehicle surrounding environment through the vehicle probe, receives the vehicle speed information through the vehicle sensor unit, and receives the vehicle system status information through the vehicle diagnostic unit, and integrates all the received information; S3, construction of a road model, the processing module constructs a road model of the vehicle driving road by receiving road geometry, slope and speed limit information, and generates the shape of the road by simulating the longitude and latitude of the road and the road geometry information through a 3D simulator, generates the slope of the road by simulating the slope information, generates a speed limit reminder by the speed limit information of the road, and simulates the surrounding environment of the road according to the video image of the surrounding environment of the vehicle; S4, constructing a vehicle model, based on the generated road model, determining the longitude and latitude of the vehicle through the LBS module, and then matching the longitude and latitude of the vehicle with the longitude and latitude on the road model, so as to locate the vehicle on the road model, and simulating a corresponding vehicle model on the road model according to the positioning; S5, constructing a traffic flow model. On the basis of constructing the vehicle model and the road model, the processing module assigns the vehicle model speed through the received vehicle speed information, and assigns the road model the number of lanes through the received vehicle surrounding environment information. Then, the vehicle model and the road model are combined to form a traffic flow model. The processing module further fills the traffic flow model by putting the vehicle surrounding information transmitted between vehicles into the vehicle model generated by the information source vehicle, and displays a more intuitive road condition to the user through the traffic flow model, thereby assisting the user in driving. S6. Construction of an environmental model: the processing module constructs a lane environmental model by receiving road weather information, and calculates the friction resistance between the vehicle and the road through the environmental model to further assist the user in driving.

[0022] The network structure formed by longitude and latitude can form a lane model more accurately. At the same time, the longitude and latitude of the vehicle can be determined through the LBS module, and the vehicle model is generated on the lane model by comparing the longitude and latitude. The road model and the vehicle model are further filled in with the help of the on-board hood, on-board radar, vehicle sensor and on-board diagnostic unit to obtain the traffic flow model. Through the traffic flow model, the driver can understand the road information more intuitively, and the vehicles behind can avoid traffic accidents and other unexpected situations earlier, thereby increasing driving safety.

[0023] The processing module uses the LBS module and the C-V2X communication module in conjunction with the on-board edge server to update the location of the vehicle model and the vehicle surrounding environment simulated in the traffic model in real time.

[0024] The on-board edge server is set up to cooperate with the cloud server to transmit information better and more timely, thereby speeding up the update rate of the traffic model.

[0025] The interaction method using the LBS-based vehicle interaction system comprises the following steps: W1. Generate an APP on the human-computer interaction panel, and the user can choose to build a traffic flow model by opening the APP; W2. After receiving the traffic flow model construction command, the processing module constructs the traffic flow model according to the traffic flow model construction steps; W3. After the traffic flow model is successfully constructed, it is displayed on the human-computer interaction panel. Users can intuitively understand the road condition information 1 km before and after the vehicle through the traffic flow model; W4. When a traffic accident or a breakdown of the vehicle ahead occurs, users can receive warnings earlier through the traffic model.

[0026] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A vehicle interaction system based on LBS, characterized by: It includes an on-board edge server, a cloud server, a communication module, an LBS module, a processing module and an on-board detection module. The communication module is used for information exchange between vehicles, vehicles and people, vehicles and on-board edge servers, and vehicles and cloud servers. The on-board edge server is used for transmission services of vehicle speed information and vehicle condition information. The cloud server is used for transmission services of road weather, geometry, slope and speed limit information. The LBS module is used to locate the position of the vehicle. The on-board detection module is used for detection of the vehicle and its surrounding environment. The vehicle detection module monitors the vehicle's surrounding environment information and vehicle information and transmits it to the vehicle edge server through the communication module. The processing module integrates and processes the received information of the vehicle edge server, and then cooperates with the LBS module to locate the vehicle position, thereby constructing a traffic flow model; The construction range of the traffic flow model is 1km before and after the vehicle; The vehicle-mounted detection module includes a vehicle-mounted radar, a vehicle-mounted probe, a vehicle sensor unit and a vehicle-mounted diagnostic unit. The vehicle-mounted radar monitors obstacles around the vehicle, the vehicle-mounted probe records information about the vehicle's surroundings, the vehicle sensor unit measures the speed of the vehicle, and the vehicle-mounted diagnostic unit monitors and diagnoses the vehicle system. The processing module is connected to the vehicle sensor unit and the vehicle-mounted diagnostic unit, and monitors the vehicle's speed information and status in real time.

2. The LBS-based vehicle interaction system according to claim 1, characterized in that: The communication module includes a human-computer interaction panel and a C-V2X communication module. The human-computer interaction panel is used to present the traffic model to the user. The human-computer interaction panel is also used for voice interaction with the user. The C-V2X communication module cooperates with the on-board edge server for real-time transmission of information between vehicles. The information transmitted between vehicles includes road obstacle information received by the on-board radar, video image information of the vehicle's surrounding environment received by the on-board probe, vehicle speed information received by the vehicle sensor unit, and vehicle system status information received by the on-board diagnostic unit.

3. The LBS-based vehicle interaction system according to claim 1, characterized in that: The vehicle-mounted edge server is provided with a timing module, and the data storage time of the vehicle-mounted edge server is overwritten by new storage data after reaching the set time of the timing module.

4. The LBS-based vehicle interaction system according to claim 2, characterized in that: The steps of constructing the traffic flow model include: S1. Data collection: collecting environmental information of the vehicle and its surroundings through the vehicle-mounted radar, vehicle-mounted probe, vehicle sensor unit and vehicle-mounted diagnostic unit in the vehicle-mounted detection module, obtaining road weather, geometry, slope and speed limit information from the cloud server through the communication module, and transmitting and collecting road condition information and vehicle information transmitted by other vehicles through the C-V2X communication module; S2, data processing, the processing module removes the received erroneous data and duplicate data, then receives the road obstacle information through the vehicle radar, receives the video image of the vehicle surrounding environment through the vehicle probe, receives the vehicle speed information through the vehicle sensor unit, and receives the vehicle system status information through the vehicle diagnostic unit, and integrates all the received information; S3, construction of a road model, the processing module constructs a road model of the vehicle driving road by receiving road geometry, slope and speed limit information, and generates the shape of the road by simulating the longitude and latitude of the road and the road geometry information through a 3D simulator, generates the slope of the road by simulating the slope information, generates a speed limit reminder by the speed limit information of the road, and simulates the surrounding environment of the road according to the video image of the surrounding environment of the vehicle; S4, constructing a vehicle model, based on the generated road model, determining the longitude and latitude of the vehicle through the LBS module, and then matching the longitude and latitude of the vehicle with the longitude and latitude on the road model, so as to locate the vehicle on the road model, and simulating a corresponding vehicle model on the road model according to the positioning; S5, constructing a traffic flow model. On the basis of constructing the vehicle model and the road model, the processing module assigns the vehicle model speed through the received vehicle speed information, and assigns the road model the number of lanes through the received vehicle surrounding environment information. Then, the vehicle model and the road model are combined to form a traffic flow model. The processing module further fills the traffic flow model by putting the vehicle surrounding information transmitted between vehicles into the vehicle model generated by the information source vehicle, and displays a more intuitive road condition to the user through the traffic flow model, thereby assisting the user in driving. S6. Construction of an environmental model: the processing module constructs a lane environmental model by receiving road weather information, and calculates the friction resistance between the vehicle and the road through the environmental model to further assist the user in driving.

5. The LBS-based vehicle interaction system according to claim 2, characterized in that: The processing module uses the LBS module and the C-V2X communication module in conjunction with the on-board edge server to update the location of the vehicle model and the vehicle surrounding environment simulated in the traffic model in real time.

6. An interaction method of a vehicle interaction system based on LBS according to claim 4, characterized in that: The steps include: W1. Generate an APP on the human-computer interaction panel, and the user can choose to build a traffic flow model by opening the APP; W2. After receiving the traffic flow model construction command, the processing module constructs the traffic flow model according to the traffic flow model construction steps; W3. After the traffic flow model is successfully constructed, it will be displayed on the human-computer interaction panel. Users can obtain the road condition information 1 km before and after the vehicle through the traffic flow model; W4. When a traffic accident or a breakdown of the vehicle ahead occurs, users can receive warnings through the traffic model.

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