Vehicle navigation system and method using surrounding vehicle as reference

Abstract

The invention relates to the field of vehicle navigation, and discloses a vehicle navigation system and method using surrounding vehicles as reference, and the system comprises a detection module, a path prediction module, an instruction generation module and a user interface. The detection module comprises an ADAS module, detects and recognizes surrounding vehicles through sensors such as a camera, a radar and a laser radar, and collects types, license plate information, colors, positions and speed information of the surrounding vehicles and surrounding driving environment information; the path prediction module is used for predicting possible paths of surrounding vehicles through the information collected by the detection module and Internet of Vehicles communication and judging expected operations of the surrounding vehicles; the instruction generation module is used for matching the traditional navigation data with the information of the detection module and the path prediction module to generate an enhanced navigation instruction; and the user interface provides instructions for the driver through visual display or voice prompt and the like. The navigation system has the advantages of convenience in navigation, low user learning cost and the like.

Description

Technical Field

[0001] The present invention relates to the field of vehicle navigation, and particularly to a vehicle navigation system and method using surrounding vehicles as a reference. Background Art

[0002] Traditional vehicle navigation systems usually provide turn-by-turn navigation instructions for drivers through visual displays and voice prompts. However, due to issues with the timing of navigation instructions, complex operations, or inaccuracies in inertial navigation and map matching, these instructions can sometimes be difficult to follow. For example, Chinese Patent CN112477873A - An assisted driving and vehicle safety management system based on the vehicle Internet of Things. In addition, the mental load or state of the driver can also make it more difficult to execute these instructions in a timely and safe manner. Therefore, there is an urgent need for a more intuitive navigation system to reduce the driver's cognitive burden and enhance driving safety. Summary of the Invention

[0003] The present invention addresses the drawbacks in the prior art and provides a vehicle navigation system that uses surrounding vehicles as a reference.

[0004] A vehicle navigation system that uses surrounding vehicles as a reference includes a detection module, a path prediction module, an instruction generation module, and a user interface; The detection module, including an ADAS module, detects and identifies surrounding vehicles through sensors such as cameras, radars, and lidars, and collects information on the types, license plate numbers, colors, positions, and speeds of nearby vehicles, as well as information on the surrounding driving environment; The path prediction module predicts the possible paths of surrounding vehicles based on the information collected by the detection module and vehicle Internet of Things communication, and determines the expected operations of surrounding vehicles; The instruction generation module matches traditional navigation data with the information from the detection module and the path prediction module to generate enhanced navigation instructions; The user interface provides instructions to the driver through means such as visual displays or voice prompts.

[0005] Preferably, the path prediction module collects path information of surrounding vehicles through the vehicle Internet of Things, and the path information is limited to the path trajectories of surrounding vehicles in the next 10s.

[0006] Preferably, the information collected by the detection module includes information on the lights of surrounding vehicles, where the position information of surrounding vehicles includes their coordinate information relative to the vehicle itself, as well as the lane information in which the surrounding vehicles are located; the surrounding environment information includes lane information, information on surrounding pedestrians, and traffic indicator information.

[0007] Preferably, the instruction generation module matches the vehicle navigation data with the information of each surrounding vehicle predicted by the path prediction module and selects one of them to follow, and issues a following instruction.

[0008] Preferably, the instruction generation module includes two modes. One is to directly generate instructions to follow a fixed vehicle. The other is that the instruction generation module inputs vehicles similar to the vehicle navigation system into the user interface for the user to select the following vehicle.

[0009] Preferably, the detection module, the path prediction module, the instruction generation module, and the user interface perform information collection and interaction in real time.

[0010] A vehicle navigation method using surrounding vehicles as references includes the following steps. Step 1: Enter the current vehicle navigation information. Then, the detection module collects information about surrounding vehicles, including license plate information, vehicle type, vehicle color, vehicle position, vehicle speed, and vehicle lighting information of the surrounding vehicles. At the same time, the detection module will collect current road information, traffic signal information, and surrounding pedestrian and obstacle information. Step 2: The information of the detection module is transmitted to the path prediction module. The path prediction module predicts the driving trajectories of surrounding vehicles based on the data of the detection module. The duration of the predicted trajectory is 6s. Step 3: The path prediction module transmits the predicted trajectories of surrounding vehicles to the instruction generation module. The instruction generation module matches the predicted trajectories of surrounding vehicles with the current vehicle's navigation information. The matching information includes lane information and subsequent trajectory route information. Select a vehicle consistent with the navigation information for voice prompt to follow.

[0011] Preferably, in Step 2, the path prediction of surrounding vehicles is combined with vehicle networking data for prediction.

[0012] Preferably, it further includes a setting module for setting information parameters of the following vehicle and the type of the preferred following vehicle.

[0013] This solution has the following beneficial effects compared with the prior art: The invention integrates surrounding vehicles as dynamic reference points into navigation instructions, providing an innovative vehicle navigation method. This system helps drivers more easily pass through complex driving situations with reduced mental burden, thereby improving driving safety and solving common problems in traditional navigation systems. Detailed implementation mode

[0014] Embodiment 1 A vehicle navigation system using surrounding vehicles as references includes a detection module, a path prediction module, an instruction generation module, and a user interface. The detection module, including the ADAS module, detects and identifies surrounding vehicles through sensors such as cameras, radars, and lidar, and collects information on the types, license plate information, colors, positions, and speeds of nearby vehicles, as well as information on the surrounding driving environment. The information collection is real-time and communicates with other modules in real-time.

[0015] The path prediction module predicts the possible paths of surrounding vehicles and judges the expected operations of surrounding vehicles through the information collected by the detection module and vehicle network communication. The vehicle network is a V2X vehicle network system. Of course, if the surrounding vehicle owners share navigation information, the vehicle will be preferentially collected by the system. The instruction generation module matches the traditional navigation data with the information of the detection module and the path prediction module to generate enhanced navigation instructions. The navigation instructions include voice prompts or image prompts. The prompt information includes the types and colors of vehicles. Other vehicle information can be selected by the user for output. During the logical thinking process of instruction generation, the system will preferentially follow the vehicle network navigation information that is consistent with the vehicle's own navigation information, and secondly, follow the vehicles with consistent predicted trajectory information for prompting. The default time for the navigation information to be consistent is 6s, and the user can set it according to their own needs. The waiting time for traffic lights is not included in this information.

[0016] The user interface provides instructions to the driver through visual displays or voice prompts, etc. In this embodiment, the path prediction module collects the path information of surrounding vehicles through the vehicle network, and the path information is limited to the path trajectories of surrounding vehicles in the next 6s.

[0017] The information collected by the detection module includes the lighting information of surrounding vehicles. The position information of surrounding vehicles includes their coordinate information relative to the vehicle itself, as well as the lane information where the surrounding vehicles are located. The surrounding environment information includes lane information, surrounding pedestrian information, and traffic indicator information.

[0018] In this embodiment, the instruction generation module matches the vehicle navigation data with the information of each surrounding vehicle predicted by the path prediction module, selects one of them for following prompt, and makes a following reminder instruction.

[0019] In this solution, the detection module, the path prediction module, the instruction generation module, and the user interface collect and interact information in real-time.

[0020] Embodiment 2 The difference from Embodiment 1 is that the instruction generation module includes two modes. One is to directly generate instructions to follow a fixed vehicle. The other is that the instruction generation module inputs the vehicles similar to the vehicle navigation system into the user interface for the user to select the following vehicle.

[0021] Embodiment 3 Based on the navigation systems of Embodiment 1 and Embodiment 2, a vehicle navigation method using surrounding vehicles as references is provided, including the following steps: Step 1: Input the current vehicle navigation information, and then the detection module collects information of surrounding vehicles, including license plate information, vehicle type, vehicle color, vehicle position, vehicle speed, and vehicle lighting information of the surrounding vehicles. At the same time, the detection module will collect current road information, traffic signal information, and surrounding pedestrian and obstacle information; Step 2: The information of the detection module is transmitted to the path prediction module. The path prediction module predicts the driving trajectories of surrounding vehicles based on the data of the detection module, and the duration of the predicted trajectory is 6s; Step 3: The path prediction module transmits the predicted trajectories of surrounding vehicles to the instruction generation module. The instruction generation module matches the predicted trajectories of surrounding vehicles with the current vehicle's navigation information. The matching information includes lane information and subsequent trajectory route information; Select a vehicle that is consistent with the navigation information for voice prompt following.

[0022] Preferably, in Step 2, the path prediction of surrounding vehicles is combined with vehicle networking data for prediction.

[0023] Preferably, it further includes a setting module for setting information parameters of the following vehicle and the type of the preferred following vehicle.

[0024] Example: When approaching a navigation instruction, the system will identify surrounding vehicles that can be used as references. For example, if the detected vehicle is turning and the direction is consistent with the navigation route, the system will instruct the driver to follow the vehicle. By following a specific vehicle, the driver can more easily pass through complex intersections or operations without relying on abstract instructions.

[0025] Compared with the prior art, this solution has the following beneficial effects: By integrating surrounding vehicles as dynamic reference points into navigation instructions, the invention provides an innovative vehicle navigation method. This system helps drivers more easily pass through complex driving situations with reduced mental burden, thereby improving driving safety and solving common problems in traditional navigation systems.

Claims

1. A vehicle navigation system that uses surrounding vehicles as a reference, characterized in that: It includes a detection module, a path prediction module, an instruction generation module, and a user interface; The detection module includes an ADAS module, which detects and identifies surrounding vehicles through sensors such as cameras, radars, and lidar, and collects information on the types, license plate information, colors, positions, and speeds of nearby vehicles, as well as information on the surrounding driving environment; The path prediction module predicts the possible paths of surrounding vehicles based on the information collected by the detection module and vehicle-to-infrastructure communication, and judges the expected operations of surrounding vehicles; The instruction generation module matches traditional navigation data with the information of the detection module and the path prediction module to generate enhanced navigation instructions; The user interface provides instructions to the driver through visual displays or voice prompts, etc.

2. The vehicle navigation system using surrounding vehicles as a reference according to claim 1, characterized in that: The path prediction module collects the path information of surrounding vehicles through vehicle-to-infrastructure communication. The path information is limited to the path trajectories of surrounding vehicles in the next 10 seconds.

3. The vehicle navigation system using surrounding vehicles as a reference according to claim 2, characterized in that: The information collected by the detection module includes the lighting information of surrounding vehicles. The position information of surrounding vehicles includes their coordinate information relative to the vehicle itself, and also includes the lane information where the surrounding vehicles are located; The surrounding environment information includes lane information, surrounding pedestrian information, and traffic light information.

4. The vehicle navigation system using surrounding vehicles as a reference according to claim 3, characterized in that: The instruction generation module matches the vehicle navigation data with the information of each surrounding vehicle predicted by the path prediction module and selects one of them to follow, and issues a following instruction.

5. The vehicle navigation system using surrounding vehicles as a reference according to claim 4, characterized in that: The instruction generation module includes two modes. One is to directly generate instructions to follow a fixed vehicle. The other is that the instruction generation module inputs the vehicles similar to the vehicle navigation system into the user interface for the user to select the following vehicle.

6. The vehicle navigation system using surrounding vehicles as a reference according to claim 4, characterized in that: The detection module, the path prediction module, the instruction generation module, and the user interface collect and interact information in real time.

7. A vehicle navigation method using surrounding vehicles as a reference, characterized in that: It includes the following steps, Step 1: Enter the current vehicle navigation information, and then the detection module collects information on surrounding vehicles, including license plate information, vehicle type, vehicle color, vehicle position, vehicle speed, and vehicle lighting information of surrounding vehicles. At the same time, the detection module will collect current road information, traffic signal information, and surrounding pedestrian and obstacle information; Step 2: The information of the detection module is transmitted to the path prediction module. The path prediction module predicts the driving trajectories of surrounding vehicles based on the data of the detection module. The duration of the predicted trajectory is 6 seconds; Step 3: The path prediction module transmits the predicted trajectories of surrounding vehicles to the instruction generation module. The instruction generation module matches the predicted trajectories of surrounding vehicles with the current vehicle's navigation information. The matching information includes lane information and subsequent trajectory route information; Select the vehicle that is consistent with the navigation information for voice prompt to follow.

8. The vehicle navigation method using surrounding vehicles as a reference according to claim 7, characterized in that: Among them, in Step 2, the path prediction of surrounding vehicles is combined with vehicle-to-infrastructure data for prediction.

9. The vehicle navigation method using surrounding vehicles as a reference according to claim 7, characterized in that: It also includes a setting module, which is used to set the information parameters of the following vehicle and the type of the preferred following vehicle.