Method and device for determining driving route

Abstract

The invention relates to the technical field of vehicles, and discloses a method and device for determining a driving route. The method comprises the steps of obtaining at least one piece of associated information corresponding to a target vehicle; wherein the target area indicates an area through which the target vehicle needs to run from the starting point position to the target position, and the associated information comprises at least one of the following items: average vehicle speed data of the target area, fault data of the target area and traffic flow data of the target area; determining a driving route according to the associated information corresponding to the target vehicle; and sending the driving route to the vehicle end, so that the vehicle end controls the target vehicle to drive from the starting point position to the target position based on the driving route.

Description

Technical Field

[0001] The present invention relates to the field of vehicle technology, and in particular to a method and device for determining a driving route. Background Art

[0002] In related technologies, vehicles often travel from a starting point to a destination along a fixed route. However, with the growth of urban traffic, road conditions are changing in real time. Traveling along a fixed route from a starting point to a destination can easily cause traffic congestion, reducing the efficiency and safety of vehicles reaching their destination. Summary of the Invention

[0003] In view of this, the present invention provides a method and device for determining a driving route.

[0004] In a first aspect, the present invention provides a method for determining a driving route, the method comprising: obtaining at least one associated information corresponding to a target vehicle; wherein the target area indicates the area through which the target vehicle needs to travel from a starting position to a target position, and the associated information comprises at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area; determining the driving route based on the associated information corresponding to the target vehicle; and sending the driving route to a vehicle end so that the vehicle end controls the target vehicle to travel from the starting position to the target position based on the driving route.

[0005] The method for determining a driving route provided in this embodiment takes into account that a fixed route cannot be adjusted according to real-time road conditions. The driving route determined based on associated information can be adjusted based on at least one of the average vehicle speed data of the target area, the fault data of the target area, and the traffic flow data of the target area, thereby preventing vehicles from getting stuck in congestion or facing safety risks, and ensuring safe and smooth driving of the target vehicle.

[0006] In one possible implementation, the method further includes: sending a correction instruction to the vehicle end during the process of the target vehicle traveling from the starting position to the target position, so that the vehicle end controls the target vehicle according to the correction instruction so that the position of the target vehicle is on the driving path, wherein the correction instruction is generated by monitoring the deviation of the target vehicle from the driving path, and the correction instruction is sent when the driving offset of the target vehicle is less than the deviation reference value.

[0007] The method for determining the driving route provided in this embodiment can detect abnormal situations during vehicle driving in advance by real-time monitoring of the deviation position of the target vehicle from the driving path and generating correction instructions in a timely manner, thereby reducing the risk of traffic accidents.

[0008] In one possible implementation, the method also includes: in the process of the target vehicle traveling from the starting position to the target position, when an obstacle is detected within a preset range of the target vehicle, determining the target driving path based on the contour information of the obstacle and the driving path of the target vehicle; and sending the target driving path to the vehicle end so that the vehicle end travels from the starting position to the target position according to the target driving path.

[0009] The method for determining a driving route provided by this embodiment detects obstacles within a preset range in real time and plans a target driving route based on their outline information. This allows vehicles to avoid obstacles in advance, significantly reducing the likelihood of collision. Furthermore, the target driving route, determined by combining the target vehicle's driving path with obstacle outline information, not only takes obstacle avoidance into account but also ensures the rationality of the route to the greatest extent possible. This allows vehicles to avoid obstacles while minimizing the increase in driving distance and travel time.

[0010] In one possible implementation, determining the driving route according to the associated information corresponding to the target vehicle includes: determining the priority of multiple pending routes according to the associated information corresponding to the target vehicle; and determining the route with the highest priority among the multiple pending routes as the driving route.

[0011] The method for determining a driving route provided in this embodiment can quickly select the route that best suits the current situation from among numerous possible routes by determining the priorities of multiple pending routes.

[0012] In one possible implementation, the method also includes: obtaining the current time when the target vehicle is started; wherein the current time when the target vehicle is started indicates the starting time of the target vehicle in the process of traveling from the starting position to the target position; determining the service recommendation corresponding to the target vehicle based on the current time when the target vehicle is started; sending the service recommendation corresponding to the target vehicle to the vehicle end, so that the vehicle end controls the target vehicle to broadcast the service recommendation, and in response to the user's permission instruction, controls the controller of the target vehicle to start according to the service recommendation.

[0013] The method for determining a driving route provided in this embodiment obtains the current time the target vehicle was started, accurately determining the start time of the user's trip. Based on this time, the user can be provided with service recommendations more tailored to their travel scenario. Furthermore, based on the vehicle start time, combined with real-time traffic data and historical road condition information, the system can plan the optimal driving route for the user in advance.

[0014] In a possible implementation, determining the driving route according to the associated information corresponding to the target vehicle includes: using a route planning model to determine the driving route according to the associated information corresponding to the target vehicle.

[0015] The method for determining a driving route provided in this embodiment integrates a large amount of geographic information, traffic rules and other data through a route planning model, and can accurately calculate the optimal driving route based on the associated information of the target vehicle (such as the starting point, destination, real-time road conditions, etc.).

[0016] In a second aspect, the present invention provides a device for determining a driving route, the device comprising: an acquisition module for acquiring at least one associated information corresponding to a target vehicle; wherein the target area indicates the area through which the target vehicle needs to travel from a starting position to a target position, and the associated information comprises at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area; a determination module for determining the driving route based on the associated information corresponding to the target vehicle; and a sending control module for sending the driving route to a vehicle end, so that the vehicle end controls the target vehicle to travel from the starting position to the target position based on the driving route.

[0017] In a third aspect, the present invention provides a computer device comprising: a memory and a processor, the memory and the processor being communicatively connected to each other, the memory storing computer instructions, and the processor executing the method for determining a driving route according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0018] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for determining a driving route according to the first aspect or any corresponding embodiment thereof.

[0019] In a fifth aspect, the present invention provides a computer program product comprising computer instructions for causing a computer to execute the method for determining a driving route according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0020] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0021] Figure 1 is a flowchart of a method for determining a driving route according to an embodiment of the present invention;

[0022] Figure 2 is a structural block diagram of an apparatus for determining a driving route according to an embodiment of the present invention;

[0023] Figure 3Schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] To make the purpose, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without making creative efforts shall fall within the scope of protection of the present invention.

[0025] According to an embodiment of the present invention, an embodiment of a method for determining a driving route is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0026] In this embodiment, a method for determining a driving route is provided, which can be used in computer devices, such as computers, servers, etc. Figure 1 FIG. 1 is a flow chart of a method for determining a driving route according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps:

[0027] Step S101, obtaining at least one associated information corresponding to the target vehicle; wherein the target area indicates the area that the target vehicle needs to pass through when traveling from the starting position to the target position, and the associated information includes at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area.

[0028] The target vehicle may be any vehicle to which the method provided by the embodiments of the present disclosure can be applied.

[0029] The target area may indicate the geographical range that the target vehicle will pass through during its travel from the starting position to the target position. The target area may include multiple road sections, intersections, etc.

[0030] The associated information may be data used to determine the driving route, wherein the associated data includes at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area.

[0031] Average vehicle speed data refers to the average speed of vehicles traveling normally within a target area, reflecting the smoothness of roads in that area. Fault data can include faults that occur on roads within the target area, such as road construction and traffic accidents, which can reduce road capacity. Traffic volume data represents the number of vehicles passing through a specific location within the target area during a specific time period, reflecting the traffic congestion level in that area.

[0032] In a specific implementation, various related information of the target area that the target vehicle needs to pass through is obtained. The related information can be detected by cameras configured on the road, or obtained by other means, which are not specifically limited here.

[0033] In one scenario, an online ride-hailing platform receives an order from Community A to Mall B. The target vehicle is the ride-hailing vehicle that accepted the order. The platform first determines the target area, which may be the main road and surrounding area passing through Community A to Mall B. The platform then collaborates with traffic management authorities to obtain average vehicle speed data for the target area, such as 20 km / h during peak hours and 40 km / h during off-peak hours. Fault data from a real-time traffic information platform reveals that a road in the target area is under construction, resulting in partial lane closures. Traffic flow data from sensors installed on the road indicates that a particular arterial road experiences high traffic volume during specific time periods.

[0034] Step S102: determining a driving route based on the associated information corresponding to the target vehicle.

[0035] After determining the associated information corresponding to the target vehicle, the driving route can be further determined based on the associated information.

[0036] In one scenario, the ride-hailing platform uses the relevant information it obtains to calculate a route. The algorithm takes into account factors such as average vehicle speed, breakdowns, and traffic volume. For example, it avoids roads under construction and selects routes with relatively low traffic volume and higher average speeds. The algorithm ultimately determines a route that starts from Residential Area A, passes through a relatively unobstructed main road, and then turns to Mall B.

[0037] As an example, consider a rule-based route planning algorithm: Routes are planned based on pre-set rules, such as those with high average speeds, few breakdowns, and light traffic. For example, a weighting system is established to score various road indicators and select the route with the highest overall score.

[0038] As an example, historical traffic data and user feedback can be used to train a machine learning model, allowing it to learn the impact of different factors on route selection. For example, a neural network model in deep learning can be used to input relevant information and output the optimal route.

[0039] As an example, in route planning, multiple objectives are considered simultaneously, such as minimizing travel time, minimizing distance, and maximizing road comfort. Multi-objective optimization algorithms, such as genetic algorithms and particle swarm optimization, are used to find a balance between these multiple objectives and determine the optimal route.

[0040] In step S103, the driving route is sent to the vehicle end, so that the vehicle end controls the target vehicle to travel from the starting position to the target position based on the driving route.

[0041] The driving route determined in step S102 is sent to the vehicle-side device of the target vehicle, so that the vehicle-side device can control the target vehicle to drive smoothly from the starting position to the target position according to this route.

[0042] In one scenario, a ride-hailing platform sends a planned route to a ride-hailing vehicle via an in-vehicle terminal. The vehicle receives the route and displays it on the in-vehicle navigation screen. Simultaneously, the autonomous driving system (if any) uses this information to control the vehicle's planned route, starting from Community A, passing designated roads, and ultimately arriving at Shopping Mall B.

[0043] As an example, the driving route is sent directly to the vehicle's onboard navigation device, and the driver or autonomous driving system is guided to follow the route through voice prompts and screen displays.

[0044] As an example, if the target vehicle's vehicle-side device is connected to a mobile application (such as an online car-hailing driver-side APP), the route information can be pushed to the driver through the APP, and the driver can drive according to the navigation instructions on the APP.

[0045] As an example, by using vehicle networking technology, the driving route can be directly transmitted to the vehicle's autonomous driving control system, allowing the vehicle to autonomously follow the route without human intervention.

[0046] The method for determining a driving route provided in this embodiment takes into account that a fixed route cannot be adjusted according to real-time road conditions. The driving route determined based on associated information can be adjusted based on at least one of the average vehicle speed data of the target area, the fault data of the target area, and the traffic flow data of the target area, thereby preventing vehicles from getting stuck in congestion or facing safety risks, and ensuring safe and smooth driving of the target vehicle.

[0047] In one possible implementation, the above method also includes: sending a correction instruction to the vehicle end during the process of the target vehicle traveling from the starting position to the target position, so that the vehicle end controls the target vehicle according to the correction instruction so that the position of the target vehicle is on the driving path, wherein the correction instruction is generated by monitoring the deviation of the target vehicle from the driving path, and the correction instruction is sent when the driving offset of the target vehicle is less than the deviation reference value.

[0048] The correction instruction can be used to correct the current driving route of the target vehicle. The correction instruction can be received from the online ride-hailing platform, and the correction instruction is generated by the online ride-hailing platform when it monitors that the target vehicle deviates from the driving path. When the online ride-hailing platform detects that the driving deviation of the target vehicle is less than the deviation reference value, the online ride-hailing platform can send the correction instruction to the vehicle end of the target vehicle, and the vehicle end of the target vehicle can receive the correction instruction from the online ride-hailing platform. After receiving the correction instruction, the vehicle-end device controls the driving status of the target vehicle according to the adjustment information in the instruction, such as adjusting the steering wheel angle, throttle or brake force, etc., so as to return the vehicle's position to the driving path.

[0049] In one scenario, an online ride-hailing vehicle is traveling along a planned route. The vehicle's GPS positioning system and inertial navigation system continuously monitor the vehicle's actual location. The planned route data is also pre-stored. By comparing the vehicle's actual location with the route, it was discovered that the vehicle did not follow the planned turn at an intersection, causing it to stray approximately 50 meters from the route. After detecting the vehicle's deviation from the route, the online ride-hailing platform calculates the necessary adjustment parameters to return the vehicle to the route based on the deviation location, current speed, and direction. For example, a 10-degree left turn and a 5 km / h speed reduction are required. These parameters constitute the correction instructions. The online ride-hailing platform transmits the generated correction instructions to the vehicle's onboard terminal using vehicle-to-vehicle communication technology. Upon receiving the instructions, the terminal passes them on to the autonomous driving control system or displays a prompt to the driver.

[0050] In the case of a self-driving ride-hailing vehicle, upon receiving the correction command, the autonomous driving control system automatically adjusts the steering wheel angle, turning it 10 degrees to the left, and appropriately reduces the throttle to reduce the vehicle's speed by 5 km / h, gradually returning the vehicle to its path. In the case of a manually driven ride-hailing vehicle, the onboard terminal will inform the driver through voice prompts or screen displays that they need to turn 10 degrees left and reduce the vehicle's speed. The driver then follows the prompts to return the vehicle to its path.

[0051] The method for determining the driving route provided in this embodiment can detect abnormal situations during vehicle driving in advance by real-time monitoring of the deviation position of the target vehicle from the driving path and generating correction instructions in a timely manner, thereby reducing the risk of traffic accidents.

[0052] In one possible implementation, the method further includes:

[0053] Step S201 , when a target vehicle is traveling from a starting position to a target position, if an obstacle is detected within a preset range of the target vehicle, a target driving path is determined based on the outline information of the obstacle and the driving path of the target vehicle.

[0054] Obstacles can indicate static obstacles, such as fixed obstacles on the road, etc. Obstacles can also be dynamic obstacles, such as vehicles running on the road, pedestrians on the road, etc.

[0055] The starting point indicates the starting point of the target vehicle's journey, which in the case of ride-hailing services is typically the passenger's boarding location. The target point indicates the target vehicle's final destination, which in the case of ride-hailing services is the passenger's designated drop-off location. The preset range indicates a pre-defined spatial area surrounding the target vehicle, used to monitor for obstacles that may affect its movement. The size of this range can be adjusted based on factors such as vehicle type and speed.

[0056] As the target vehicle travels from its starting point to its target location, it continuously monitors the vehicle's preset range. If an obstacle is detected within the preset range, the system obtains the obstacle's outline and, based on the target vehicle's original path, uses specific algorithms or rules to determine a new target path to avoid the obstacle.

[0057] As an example, by emitting a laser beam and measuring the time it takes for the reflected light to determine the distance and position of an obstacle, the three-dimensional outline of the obstacle can be obtained. LiDAR offers the advantages of high precision and high resolution, enabling accurate obstacle detection in complex environments. The target driving path is determined based on pre-defined rules, such as the distance from the obstacle to the vehicle and the size of the obstacle. For example, if the obstacle is close to the vehicle and large, a longer detour is chosen; if the obstacle is farther away and smaller, a shorter detour is chosen.

[0058] As an example, image recognition technology analyzes camera images to identify obstacles within them, and algorithms estimate their size, shape, and position. Based on the vehicle's current speed, acceleration, and other motion states, a series of possible trajectories are sampled in velocity space. These trajectories are then evaluated based on objective functions (such as distance to obstacles and progress toward the target point), and the optimal trajectory is selected as the target driving path. The DWA algorithm is suitable for dynamic environments and can adjust the path in real time to avoid unexpected obstacles.

[0059] In step S202, the target driving path is sent to the vehicle end so that the vehicle end drives from the starting position to the target position according to the target driving path.

[0060] The determined target driving route is sent to the vehicle-side device of the target vehicle. After receiving the route, the vehicle-side device controls the target vehicle to drive from the starting position to the target position according to the route, ensuring that the vehicle can reach the destination safely and smoothly.

[0061] In one scenario, an online-hailing vehicle is traveling along a planned route. Sensors such as lidar and cameras continuously monitor a preset radius (e.g., 50 meters) around the vehicle. Suddenly, the lidar detects a private car 30 meters ahead that suddenly changes lanes and stops, thus detecting an obstacle. The camera captures the car's outline, including its length, width, height, and specific position and posture on the road. The vehicle's system also stores the original route. Based on the car's outline and the original route, the autonomous driving control system applies a path planning algorithm to determine a new target route, such as bypassing the car and passing through a wider space to its left or right. The autonomous driving control system transmits the determined target route to the vehicle's onboard terminal via the vehicle's communication module. The terminal displays the route on the onboard navigation screen and sends control commands to the autonomous driving system. Based on the target route, the autonomous driving system automatically adjusts the steering wheel angle, accelerator, and brake pressure to steer the online-hailing vehicle from its starting position, bypassing the obstacle, and continuing toward the target location.

[0062] The method for determining a driving route provided by this embodiment detects obstacles within a preset range in real time and plans a target driving route based on their outline information. This allows vehicles to avoid obstacles in advance, significantly reducing the likelihood of collision. Furthermore, the target driving route, determined by combining the target vehicle's driving path with obstacle outline information, not only takes obstacle avoidance into account but also ensures the rationality of the route to the greatest extent possible. This allows vehicles to avoid obstacles while minimizing the increase in driving distance and travel time.

[0063] In one possible implementation, step S102 includes:

[0064] Step S1021: Determine the priorities of multiple pending routes based on the associated information corresponding to the target vehicle.

[0065] Priority is a metric used to measure the quality of a potential route under current conditions. This involves collecting various types of information related to the target vehicle, collectively referred to as contextual information. This information may encompass multiple dimensions, such as the vehicle's status, passenger needs, and road conditions. Based on this contextual information, specific rules or algorithms are applied to evaluate and rank multiple potential routes, thereby determining the priority of each. The priority reflects the quality of the route under current conditions.

[0066] As an example, the vehicle's own status information, such as battery level / fuel level, driving speed, etc., is obtained in real time through sensors installed on the vehicle, such as power sensors, fuel level sensors, speed sensors, etc. A weight is assigned to each piece of associated information, and a score is assigned based on the performance of each pending route on each piece of associated information. Then, each score is multiplied by the corresponding weight and added together to obtain the total score of each route. The higher the total score, the higher the priority. For example, weights of 0.4, 0.3, and 0.3 are assigned to associated information such as driving time, route distance, and charging conditions, respectively. The route is scored based on its actual performance (e.g., the shorter the driving time, the higher the score), and the total score is calculated.

[0067] As an example, multiple pieces of associated information are used as optimization targets, and an optimal route combination that meets the multiple targets is found through iterative search, thereby determining the priority of each route.

[0068] Step S1022: Determine the route with the highest priority among the multiple pending routes as the driving route.

[0069] Among the multiple pending routes whose priorities have been determined, the route with the highest priority is selected and used as the final driving route of the target vehicle.

[0070] In one scenario, an online ride-hailing platform receives a request to travel from location A (starting point) to location B (destination point). The platform collects the following information: the vehicle's battery currently has 60% remaining, with an estimated range of 200 kilometers. There are three pending routes from location A to location B, with distances of 50 kilometers, 60 kilometers, and 70 kilometers, respectively. The passenger requires arrival at location B within 30 minutes. Real-time traffic conditions indicate that route 1 (50 kilometers) is slightly congested, with an estimated travel time of 28 minutes; route 2 (60 kilometers) is partially under construction, with an estimated travel time of 32 minutes; and route 3 (70 kilometers) is in good condition, with an estimated travel time of 25 minutes. Routes 1 and 3 are expressways with tolls; route 2 is a regular road with no tolls. Based on this information, the system sets the following rules to prioritize routes: routes with shorter travel times and more battery life are prioritized; if travel times are similar, tolls are considered. According to this rule, the three pending routes are evaluated and ranked: although Route 3 has the longest distance, it has the shortest driving time (25 minutes), and the vehicle has sufficient power (the remaining power can travel 200 kilometers, far more than 70 kilometers). Although there are tolls, it has a higher priority overall. Route 1 has the second longest driving time (28 minutes), has slight congestion, and has tolls, so it has the next highest priority. Route 2 has the longest driving time (32 minutes), which exceeds the 30 minutes required by passengers. Although there are no tolls, it has the lowest priority. The final priority of the three pending routes is: Route 3 > Route 1 > Route 2.

[0071] The method for determining a driving route provided in this embodiment can quickly select the route that best suits the current situation from among numerous possible routes by determining the priorities of multiple pending routes.

[0072] In one possible implementation, the method further includes:

[0073] Step S301, obtaining the current time when the target vehicle is started; wherein the current time when the target vehicle is started indicates the starting time when the target vehicle is traveling from the starting position to the target position.

[0074] The current time when the target vehicle is started can represent the specific moment when the target vehicle starts traveling from the starting position, and is used to identify the starting time point of the trip.

[0075] Get the current time when the target vehicle starts, which clearly indicates the starting moment of the process of the target vehicle starting from the starting position and heading to the target position.

[0076] As an example, a high-precision clock module is installed on the target vehicle. When the vehicle is started, the clock module automatically records the current time and transmits the time information to the vehicle's intelligent system.

[0077] For example, a vehicle connected to the Internet via IoV technology obtains the current standard time from an Internet time server. When the vehicle is started, it automatically synchronizes with the Internet time to obtain the accurate start time.

[0078] As an example, if a passenger or driver's mobile device (such as a cell phone) is connected to the vehicle's onboard system via Bluetooth or Wi-Fi, the vehicle can obtain the current time from the mobile device and use it as the current time when the target vehicle is started.

[0079] Step S302: determining a service recommendation corresponding to the target vehicle according to the current time when the target vehicle is started.

[0080] Service recommendations can be determined by factors such as the start-up time of the target vehicle. The recommended service content related to the target vehicle's current trip may include air conditioning temperature settings, music playback selections, driving route preferences, etc.

[0081] Based on the current time when the target vehicle is started, combined with preset rules, historical data or other relevant information, service recommendations that match the target vehicle are determined.

[0082] As an example, a rule library is pre-established that stores the mapping between different time periods and corresponding service recommendations. For example, between 7:00 AM and 9:00 AM, service recommendations include providing a coffee or tea purchase reminder (if the vehicle has such a feature) and playing upbeat morning music; after 10:00 PM, service recommendations include dimming the interior lights and playing soothing sleep music. After obtaining the current start time of the target vehicle, the system searches the rule library for the corresponding service recommendation.

[0083] For example, in addition to considering time, weather information is also used to determine service recommendations. For example, in the summer between 12:00 PM and 2:00 PM, when the weather is hot, the service recommendation is to lower the air conditioning temperature; in the winter evenings, when the weather is cold and snowy, the service recommendation is to turn on the seat heating function in advance.

[0084] In step S303, the service suggestion corresponding to the target vehicle is sent to the vehicle end, so that the vehicle end controls the target vehicle to broadcast the service suggestion, and in response to the user's permission instruction, controls the controller of the target vehicle to start according to the service suggestion.

[0085] The confirmed service recommendations are sent to the target vehicle's on-board device. The on-board device first controls the target vehicle to announce the service recommendations to the vehicle's occupants (e.g., passengers and the driver). Simultaneously, it waits for the user (usually the passenger) to grant permission. Upon receiving this permission, the target vehicle's controller initiates the relevant operations according to the service recommendations.

[0086] For example, we collect a large amount of historical order data, including information such as vehicle start times and the services selected by passengers. We use machine learning algorithms (such as decision trees and neural networks) to analyze and model this data, training a model that can predict service recommendations based on vehicle start times. When a new target vehicle start time is entered, it is input into the model, which then outputs the corresponding service recommendations.

[0087] For example, we analyze each passenger's historical order data to learn their service preferences at different times of the day. For example, if a passenger often listens to news audio on their way to work in the morning, then when their ride-hailing vehicle starts in the morning, the system will prioritize news audio as a service suggestion.

[0088] In one scenario, a passenger places a ride through an online ride-hailing app. The driver accepts the order and heads to the passenger's pickup location. When the ride arrives at the pickup location, the passenger boards, and the driver starts the vehicle, the vehicle's intelligent system automatically retrieves the current time, for example, 9:30 AM. This time is the vehicle's startup time, marking the start of the journey from the pickup location to the destination. Suppose the ride-hailing platform, based on historical data, finds that between 9:00 AM and 10:00 AM, many passengers prefer an in-vehicle temperature of around 22°C and soft music. When the vehicle starts at 9:30 AM, the system, based on this startup time, recommends setting the in-vehicle air conditioning temperature to 22°C and playing a soft music playlist. The platform then sends this recommended service to the vehicle's onboard terminal. The on-board terminal first announces to the passengers and driver through the voice broadcast system: "Service suggestion for this trip: the air conditioning temperature in the car is set to 22℃, and a soft music playlist will be played. Do you allow it?" If the passenger indicates permission, for example by clicking the "Allow" button on the on-board screen or saying the voice command "Allow", after receiving the permission instruction, the on-board terminal controls the vehicle's air conditioning controller to adjust the temperature to 22℃, and at the same time controls the audio system to start playing the soft music playlist.

[0089] The method for determining a driving route provided in this embodiment obtains the current time the target vehicle was started, accurately determining the start time of the user's trip. Based on this time, the user can be provided with service recommendations more tailored to their travel scenario. Furthermore, based on the vehicle start time, combined with real-time traffic data and historical road condition information, the system can plan the optimal driving route for the user in advance.

[0090] In a possible implementation, the above step S102 includes: using a route planning model to determine a driving route according to associated information corresponding to the target vehicle.

[0091] Various relevant information about the target vehicle is collected. This information forms the basis for the route planning model's calculations. This information is then fed into a pre-built route planning model, which processes and analyzes it based on built-in algorithms and rules, calculating various route options. From the multiple route options calculated by the model, the final route is determined based on specific criteria (such as shortest distance, shortest time, and lowest cost) and output.

[0092] The method for determining a driving route provided in this embodiment integrates a large amount of geographic information, traffic rules and other data through a route planning model, and can accurately calculate the optimal driving route based on the associated information of the target vehicle (such as the starting point, destination, real-time road conditions, etc.).

[0093] In one possible implementation, using the route planning model and the associated information corresponding to the target vehicle, determining the driving route can be achieved through the following steps:

[0094] Integrate information from multiple channels, such as GPS positioning, traffic monitoring equipment, and social media platforms, to form a comprehensive dataset. Apply statistical methods to identify and remove outliers that may interfere with model training. Extract useful features, such as time period, geographic location, and weather conditions, to prepare model inputs.

[0095] The urban traffic network is abstracted into a graph consisting of nodes (intersections, landmarks) and edges (roads). Each node and edge is assigned corresponding attribute values, such as traffic flow, speed limit, and accident frequency. Based on real-time data, the state of each element in the graph is dynamically adjusted to maintain the model's timeliness. The GCN model is trained using extensive historical traffic data, enabling it to accurately predict road conditions over different time periods. The latest traffic information is obtained through APIs or other means as part of the model input. Based on current traffic conditions, the optimal route from the starting point to the destination is calculated, minimizing congestion. Upon detecting traffic anomalies or other emergencies, an emergency response process is immediately initiated to recalculate the optimal matching solution. Factors such as passenger wait time and driver workload are considered to identify solutions that maximize overall benefits. After each trip, the system collects feedback to refine the algorithm, forming a continuous learning and optimization loop. Detailed profiles are created based on the user's historical behavior and preferences. Service recommendations are provided based on specific needs in different scenarios, such as rush hour and weekend leisure travel. Passengers are encouraged to share their travel experiences, fostering a positive community atmosphere.

[0096] This embodiment also provides a device for determining a driving route, which is used to implement the above-mentioned embodiments and preferred embodiments. Details already described will not be repeated here. As used below, the term "module" may refer to a combination of software and / or hardware that implements a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, implementation using hardware, or a combination of software and hardware, is also possible and contemplated.

[0097] This embodiment provides a device for determining a driving route, such as Figure 2As shown, it includes: an acquisition module 201, used to obtain at least one associated information corresponding to the target vehicle; wherein, the target area indicates the area that the target vehicle needs to pass through when traveling from the starting position to the target position, and the associated information includes at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area; a determination module 202, used to determine the driving route according to the associated information corresponding to the target vehicle; a sending control module 203, used to send the driving route to the vehicle end, so that the vehicle end controls the target vehicle to travel from the starting position to the target position based on the driving route.

[0098] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0099] The device for determining the driving route in this embodiment is presented in the form of a functional unit, where the functional unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0100] The embodiment of the present invention also provides a computer device having the above Figure 2 The device for determining the driving route is shown.

[0101] See also Figure 3 , Figure 3 is a structural diagram of a computer device provided by an optional embodiment of the present invention, such as Figure 3 As shown, the computer device includes: one or more processors 10, memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components utilize different buses to communicate with each other and can be installed on a common mainboard or installed in other ways as needed. The processor can process the instructions executed in the computer device, including instructions stored in the memory or on the memory to display the graphical information of the GUI on an external input / output device (such as, a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories and multiple memories. Equally, multiple computer devices can be connected, and each device provides part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 3 A processor 10 is taken as an example.

[0102] The processor 10 may be a central processing unit, a network processor, or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic, or any combination thereof.

[0103] The memory 20 stores instructions that can be executed by at least one processor 10, so as to enable at least one processor 10 to execute the method shown in the above embodiment.

[0104] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system and application programs required for at least one function; the data storage area may store data created based on the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0105] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0106] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 can be connected via a bus or other means. Figure 3 The bus connection is taken as an example.

[0107] The input device 30 can receive input digital or character information and generate key signal input related to user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a trackpad, a touch pad, an indicator stick, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 can include a display device, an auxiliary lighting device (e.g., an LED), and a tactile feedback device (e.g., a vibration motor). The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display, and a plasma display. In some optional embodiments, the display device can be a touch screen.

[0108] The computer device further includes a communication interface for the computer device to communicate with other devices or a communication network.

[0109] The embodiment of the present invention also provides a computer-readable storage medium. The above-mentioned method according to the embodiment of the present invention can be implemented in hardware, firmware, or implemented as a computer code that can be recorded in a storage medium, or implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and downloaded through a network and will be stored in a local storage medium, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state drive, etc.; further, the storage medium can also include a combination of the above-mentioned types of memory. It can be understood that a computer, a processor, a microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor or hardware, the method shown in the above embodiment is implemented.

[0110] A portion of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the form in which the computer program instruction exists in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc. Accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium that can be accessed by the computer.

[0111] Although the embodiments of the present invention have been described with reference to the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention. Such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for determining a driving route, characterized in that: The method comprises: Acquire at least one piece of associated information corresponding to the target vehicle; wherein the target area indicates an area that the target vehicle needs to pass through when traveling from a starting position to a target position, and the associated information includes at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area; Determining a driving route according to the associated information corresponding to the target vehicle; The driving route is sent to the vehicle end, so that the vehicle end controls the target vehicle to travel from the starting position to the target position based on the driving route.

2. The method for determining a driving route according to claim 1, wherein: The method further comprises: During the process of the target vehicle traveling from the starting position to the target position, a correction instruction is sent to the vehicle end so that the vehicle end controls the target vehicle according to the correction instruction so that the position of the target vehicle is on the driving path, wherein the correction instruction is generated by monitoring the deviation of the target vehicle from the driving path, and the correction instruction is sent when the driving offset of the target vehicle is less than the deviation reference value.

3. The method for determining a driving route according to claim 1, wherein: The method further comprises: During the process of the target vehicle traveling from the starting position to the target position, when an obstacle is detected within a preset range of the target vehicle, a target driving path is determined based on the outline information of the obstacle and the driving path of the target vehicle; The target driving path is sent to the vehicle end so that the vehicle end travels from the starting position to the target position according to the target driving path.

4. The method for determining a driving route according to claim 1, wherein: The determining of the driving route according to the associated information corresponding to the target vehicle includes: Determining the priorities of multiple pending routes based on the associated information corresponding to the target vehicle; The route with the highest priority among the multiple pending routes is determined as the driving route.

5. The method for determining a driving route according to claim 1, wherein: The method further comprises: Acquire the current time when the target vehicle is started; wherein the current time when the target vehicle is started indicates the starting time when the target vehicle is traveling from the starting position to the target position; Determining a service recommendation corresponding to the target vehicle based on the current time at which the target vehicle is started; The service suggestion corresponding to the target vehicle is sent to the vehicle end, so that the vehicle end controls the target vehicle to broadcast the service suggestion, and in response to the user's permission instruction, controls the controller of the target vehicle to start according to the service suggestion.

6. The method for determining a driving route according to claim 1, wherein: The determining of the driving route according to the associated information corresponding to the target vehicle includes: The route planning model is used to determine the driving route according to the associated information corresponding to the target vehicle.

7. A device for determining a driving route, characterized in that: The device comprises: an acquisition module, configured to acquire at least one piece of associated information corresponding to a target vehicle; wherein the target area indicates an area that the target vehicle needs to pass through when traveling from a starting position to a target position, and the associated information includes at least one of the following: average vehicle speed data of the target area, fault data of the target area, and traffic flow data of the target area; A determination module, configured to determine a driving route based on the associated information corresponding to the target vehicle; The sending control module is used to send the driving route to the vehicle end, so that the vehicle end controls the target vehicle to travel from the starting position to the target position based on the driving route.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for determining a driving route according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for determining a driving route according to any one of claims 1 to 6.

10. A computer program product, characterized in that The method comprises computer instructions for causing a computer to execute the method for determining a driving route according to any one of claims 1 to 6.

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