Travel route planning method for vehicle, storage medium, and vehicle

Abstract

The application provides a driving path planning method of a vehicle, a storage medium and the vehicle. The method comprises the following steps: when it is determined that charging is needed based on a current position of the vehicle, a remaining range of a battery and a target position, a plurality of candidate charging station sets are obtained based on a navigation path and the remaining range; a driving path set of the vehicle is determined based on the current position, the target position and the plurality of candidate charging station sets; a comprehensive satisfaction score of each driving path is calculated based on user preferences, a total travel time of each driving path is obtained, and a total charging cost is obtained based on charging information of charging stations on the driving path; a comprehensive score of the driving path is calculated based on the comprehensive satisfaction score, the total travel time and the total charging cost; and a target driving path is determined based on the comprehensive score of each driving path in the driving path set. Thus, the charging demand and the user preferences are combined to generate a path that is more in line with actual use habits and preferences, thereby improving the travel experience of the user.

Description

Technical Field

[0001] This application relates to the field of vehicle technology, specifically to a method for planning a vehicle's driving path, a storage medium, and a vehicle. Background Technology

[0002] For electric vehicles, charging is an unavoidable phenomenon during long-distance travel. Currently, electric vehicle route planning only considers factors such as mileage, battery level, and charging speed. However, during the charging process, users often have no choice but to wait passively near the charging station, resulting in a poor user travel experience. Summary of the Invention

[0003] This application provides a method for planning a vehicle's driving route, a storage medium, and a vehicle. It combines charging needs and user preferences to generate an optimal planned route, which is more in line with the user's actual usage habits and preferences, thereby improving the user's travel experience.

[0004] To achieve the above objectives, the embodiments of this application adopt the following technical solutions: Firstly, a method for planning vehicle driving routes is provided, comprising: when it is determined that charging is required based on the vehicle's current location, the remaining battery range, and the target location; obtaining a set of multiple candidate charging stations based on the navigation route and the remaining battery range; determining a set of driving routes for the vehicle based on the current location, the target location, and the multiple candidate charging station sets, wherein each driving route includes at least one charging station; calculating a comprehensive satisfaction score for the driving route based on user preferences, obtaining the total travel time of the driving route, and obtaining the total charging cost based on the charging information of the charging stations along the driving route; calculating a comprehensive score for the driving route based on the comprehensive satisfaction score, the total travel time, and the total charging cost; and determining a target driving route based on the comprehensive score of each driving route in the set of driving routes.

[0005] According to the vehicle route planning method of this application embodiment, when it is determined that charging is needed based on the vehicle's current location, the remaining battery range, and the target location, multiple candidate charging station sets are obtained based on the navigation route and the remaining range. A set of vehicle routes is determined based on the current location, the target location, and the multiple candidate charging station sets. A comprehensive satisfaction score for the route is calculated based on user preferences, and the total travel time of the route is obtained. The total charging cost is also obtained based on the charging information of the charging stations along the route. A comprehensive score for the route is calculated based on the comprehensive satisfaction score, the total travel time, and the total charging cost. Finally, a target route is determined based on the comprehensive score of each route in the route set. Therefore, this method can combine charging needs and user preferences to plan a route with the optimal total travel time and the highest user satisfaction, better aligning with users' actual usage habits and preferences, and improving the user's travel experience.

[0006] In some embodiments of this application, a target driving path is determined based on the comprehensive score of each driving path in the driving path set, including: obtaining the maximum value of the comprehensive scores of all driving paths; and taking the driving path corresponding to the maximum value as the target driving path, wherein the target driving path includes the name of the charging station, the location of the charging station, recommended entertainment activities, and the total travel time.

[0007] In some embodiments of this application, the comprehensive score of a driving route is calculated based on the comprehensive satisfaction score, total travel time, and total charging cost, including: obtaining a first weighting coefficient for the comprehensive satisfaction score and a second weighting coefficient for the total charging cost; obtaining a first weight based on the product of the comprehensive satisfaction score and the first weighting coefficient, and obtaining a second weight based on the product of the total charging cost and the second weighting coefficient; and determining the comprehensive score of the driving route based on the sum of the difference between the total travel time and the second weight and the first weight.

[0008] In some embodiments of this application, calculating the overall satisfaction score for each driving route based on user preferences includes: calculating the satisfaction score for each POI area surrounding a charging station along the driving route based on user preferences, wherein user preferences are determined based on historical driving data and user consumption records; and determining the overall satisfaction score based on the sum of the satisfaction scores for all POI areas surrounding charging stations along the driving route.

[0009] In some embodiments of this application, the satisfaction score of the POI area surrounding each charging station along the driving route is calculated based on user preferences, including: obtaining multiple service items based on user preferences, the service items including at least one of catering, leisure and entertainment, shopping, and rest; calculating the satisfaction score of each preferred entertainment in the surrounding POI area; and determining the satisfaction score of the POI area surrounding the charging station based on the satisfaction scores of all preferred entertainment.

[0010] In some embodiments of this application, the total trip time includes the total service time and driving time. Obtaining the total trip time for each travel route includes: obtaining the total service time on the travel route; and determining the total trip time based on the sum of the total service time and driving time.

[0011] In some embodiments of this application, obtaining the total service time along the driving route includes: calculating the charging time based on the charging power of the charging station and the preset charging amount; determining the target service item based on the satisfaction score of each service item in the POI area around the charging station, and determining the dwell time based on the target service; determining the service time of the charging station based on the charging time and the dwell time; and determining the total service time based on the service time of all charging stations along the driving route.

[0012] In some embodiments of this application, the service time of a charging station is determined based on charging time and dwell time, including: determining the service time of the charging station based on the maximum value of charging time and dwell time.

[0013] In some embodiments of this application, the driving route includes the charging time at each charging station. The total charging cost is obtained based on the charging information of the charging stations along the driving route, including: determining the charging cost based on the charging fee, charging time, and charging duration of each charging station; and determining the total charging cost based on the sum of the charging costs of all charging stations along the driving route.

[0014] In some embodiments of this application, multiple candidate charging station sets are obtained based on navigation paths and remaining driving range, including: determining a charging station set based on navigation paths; and determining candidate charging stations based on current remaining driving range, preset driving range safety margin, and the charging station set.

[0015] In some embodiments of this application, the above-described vehicle driving path planning method further includes: determining a preset range safety margin based on weather information and road information on the navigation path.

[0016] In some embodiments of this application, the above-described vehicle driving route planning method further includes: responding to a user's request instruction, the request instruction including minimizing the total travel time; and determining a driving route based on the request instruction, the current location, the target location, and the remaining driving range.

[0017] Secondly, embodiments of this application provide a computer-readable storage medium having a program stored thereon that, when executed by a processor, implements the vehicle driving path planning method of the first aspect.

[0018] According to the computer-readable storage medium of the present application embodiment, by executing the above-described vehicle driving route planning method, charging demand and user preferences can be combined to plan a route with the optimal total time and the highest user satisfaction, which is more in line with the user's actual usage habits and preferences and improves the user's travel experience.

[0019] Thirdly, embodiments of this application provide a vehicle, including: a memory, a processor, and a program stored in the memory and executable on the processor. When the processor executes the program, it implements the vehicle driving path planning method of the first aspect.

[0020] According to the vehicle embodiment of this application, by executing the above-described vehicle travel route planning method, charging needs and user preferences can be combined to plan a route with the optimal total travel time and the highest user satisfaction, which is more in line with the user's actual usage habits and preferences and improves the user's travel experience.

[0021] Additional aspects and advantages of this application will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of this application. Attached Figure Description

[0022] Figure 1 This is a flowchart of a vehicle driving path planning method according to some embodiments of this application.

[0023] Figure 2 This is a schematic diagram of vehicle travel path planning according to some embodiments of this application.

[0024] Figure 3 This is a flowchart of a vehicle driving path planning method according to other embodiments of this application.

[0025] Figure 4 This is a block diagram of a vehicle according to some embodiments of this application. Detailed Implementation

[0026] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0027] As mentioned in the background section, charging is an unavoidable phenomenon for electric vehicles during long-distance travel. Currently, electric vehicle route planning only considers factors such as mileage, battery level, and charging speed. However, during the charging process, users often have no choice but to passively wait near charging stations, resulting in a poor user experience. For example, when users need to eat, shop, or rest during their journey, existing route planning schemes cannot effectively combine charging waiting time with these needs, forcing users to spend extra time searching for relevant places after charging, thus reducing overall travel efficiency. Furthermore, different users have different preferences during the charging waiting period. Some users want to use the waiting time for short leisure activities, while others prefer to handle work matters. However, existing technologies fail to provide customized route suggestions for these individual needs, resulting in a poor user experience during the charging waiting process and failing to meet their diverse travel expectations.

[0028] To address the aforementioned issues, this application provides a vehicle driving path planning method that deeply couples necessary charging needs with users' personalized entertainment, consumption, and rest needs, planning an integrated charging + entertainment path with the optimal total time and highest user satisfaction.

[0029] The following description, with reference to the accompanying drawings, outlines a vehicle path planning method, a computer-readable storage medium, and a vehicle according to embodiments of this application.

[0030] Figure 1 This is a flowchart of a vehicle driving path planning method according to some embodiments of this application.

[0031] The driving path planning method provided in this application can be applied to various new energy vehicles. New energy vehicles include various types of vehicles, such as cars, buses, and trucks, and this application does not impose any special restrictions on the specific form of the vehicle.

[0032] like Figure 1 As shown, the vehicle driving path planning method of this application embodiment may include the following steps: S101, based on the vehicle's current location, the remaining range of the battery, and the target location, if it is determined that charging is required, obtain a set of multiple candidate charging stations based on the navigation route and the remaining range.

[0033] Specifically, by setting the vehicle's current location and target location (destination) in the navigation software, a navigation route is generated, including distance and travel time. The system determines whether charging is needed based on the remaining driving range and distance. For example, if the remaining driving range is less than the distance, charging is considered necessary; if the remaining driving range is greater than the distance, charging is considered unnecessary.

[0034] In some embodiments, the remaining driving range can be estimated based on the current battery charge, energy consumption per 100 kilometers, average speed, and battery temperature.

[0035] Specifically, the battery management system collects real-time data on the current battery charge (e.g., 90%) and battery temperature. It estimates energy consumption per 100 kilometers based on inherent vehicle attributes (e.g., vehicle weight, drag coefficient), current load (e.g., number of passengers, luggage weight), and user driving habits. The vehicle speed sensor collects average speed over a distance. These parameters are then input into a pre-defined range estimation model. This model can be an empirical formula fitted from experimental data or a predictive model trained through machine learning to calculate the approximate remaining driving range of the vehicle under the current conditions.

[0036] In some embodiments of this application, multiple candidate charging station sets are obtained based on navigation paths and remaining driving range, including: determining a charging station set based on navigation paths; and determining candidate charging stations based on current remaining driving range, preset driving range safety margin, and the charging station set.

[0037] Specifically, when charging is determined to be needed, all charging stations within a few kilometers of the navigation path are retrieved. Then, range feasibility is filtered based on the current location and remaining driving range. This process of determining candidate charging stations based on the current remaining driving range, a preset range safety margin, and the set of charging stations requires first calculating the vehicle's maximum actual driving range at the current location. The maximum actual driving range equals the current remaining driving range minus the preset range safety margin. For example, if the vehicle's current remaining driving range is 200 kilometers and the preset range safety margin is 20 kilometers, then the maximum actual driving range is 180 kilometers. For each charging station in the set, the navigation distance between it and the vehicle's current location is calculated. If this distance is less than or equal to the maximum actual driving range, the charging station is included in the candidate charging station set. For example, if... Figure 2 As shown, the starting point is 'a', the destination is 'b', and all charging stations within a few kilometers of the navigation path include charging stations A1, A2, A3, A4, A5, and A6. Assuming the vehicle's current location is 'a' and the remaining range allows it to reach charging station A3, the vehicle can charge at any of the three charging stations: A1, A2, and A3. In this case, the candidate charging station set for location 'a' is {A1, A2, A3}. If the user is charging at charging station A1, the vehicle's current location is also 'A1'. Assuming the remaining range allows it to reach charging station A5, the vehicle can charge at any of the three charging stations: A2, A3, A4, and A5. In this case, the candidate charging station set for location 'A1' is {A2, A3, A4, A5}. If the user is charging at charging station A4 and the remaining range allows it to reach the destination, no further charging is needed. This results in a final set of multiple candidate charging stations, which cover different locations and types of charging options along the navigation route.

[0038] In some embodiments of this application, the above-described vehicle driving path planning method further includes: determining a preset range safety margin based on weather information and road information on the navigation path.

[0039] Specifically, the preset range safety margin is a reserve of mileage to cope with unexpected situations such as changes in road conditions (e.g., traffic jams, hill climbs) and weather effects (e.g., low temperatures reducing battery range). It is usually based on user settings or system defaults. For example, when the navigation route includes continuous uphill sections, the preset range safety margin is 30 kilometers to cope with increased vehicle energy consumption during uphill driving. If real-time weather information indicates that the destination or route will experience temperatures below -10°C, the vehicle will turn on the air conditioning for heating, increasing the battery's rate of energy consumption. In this case, the preset range safety margin is 40 kilometers.

[0040] S102, determine the vehicle's driving path set based on the current location, the target location, and multiple candidate charging station sets, wherein the driving path includes at least one charging station.

[0041] Specifically, firstly, a basic driving path network is constructed using the vehicle's current location as the starting point and the target location as the ending point, combined with electronic map data. Then, each charging station in multiple candidate charging station sets is considered a potential waypoint and embedded into the basic driving path network. A path search algorithm generates multiple possible driving paths containing different combinations and sequences of charging stations. For example, if the candidate charging station set includes charging station A1 at the beginning of the path, charging station A2 in the middle, and charging station A3 at the end, possible driving paths include: current location → charging station A1 → target location, current location → charging station A2 → target location, current location → charging station A3 → target location, current location → charging station A1 → charging station A2 → target location, current location → charging station A1 → charging station A3 → target location, current location → charging station A2 → charging station A3 → target location, etc. Each driving path must satisfy the continuity requirement that the vehicle starts from the starting point, passes through the selected charging stations in sequence, and finally reaches the destination. Through this method, the final set of driving paths will contain complete driving schemes under various charging strategies.

[0042] For example, with Figure 2 As shown in the example, taking the candidate charging station sets {A1, A2, A3} and {A2, A3, A4, A5} of the above embodiment as an example, the driving path can include any charging station passed along the way from a to b, such as a→A1→A2→b, a→A1→A3→b, a→A1→A4→b, a→A1→A5→b.

[0043] S103 calculates the overall satisfaction score of the driving route based on user preferences, obtains the total travel time of the driving route, and obtains the total charging cost based on the charging information of charging stations along the driving route.

[0044] Specifically, user preferences generally include enjoying food, watching movies, resting, and shopping during leisure time, with different preferences corresponding to different weighting coefficients. After determining the driving route, the system obtains the POI areas surrounding each charging station along the route. Based on the location, type, service duration, rating, and walking distance of the POI areas surrounding the charging stations, satisfaction scores are assigned to different preferences. For example, if a user's preference is food, the system prioritizes searching for restaurant POIs within a certain range around each charging station along the driving route, counting the number of restaurants with high ratings, short walking distances, and short expected queue times, and calculating the satisfaction score for this preference based on the percentage of restaurants and the average rating. If a user's preference is resting, the system focuses on whether there are quiet parks, cafes, etc., near the charging station, combining opening hours, environment ratings, and walking distance for a comprehensive score. Furthermore, the weighting coefficients for different preferences can be preset by the user or automatically adjusted by the system based on historical behavior data. For example, if a user has recently frequently selected shopping-related POIs, the weighting coefficient for shopping preferences will be increased accordingly. After completing the satisfaction ratings for each preference, a weighted summation method is used to obtain the overall satisfaction rating for the driving route. The sum of the weight coefficients is 1 to ensure the normalization of the rating results.

[0045] Total trip time generally includes driving time and time spent at charging stations. Driving time is calculated based on real-time traffic information provided by the vehicle's navigation system, the total mileage of the route, and the vehicle's current average speed. Time spent at charging stations is primarily determined by charging duration and the user's activity time in the surrounding POI area; the greater of these two factors is taken as the time spent at the charging station. Charging duration is calculated based on the vehicle's remaining battery power, the target charging amount, and the charging station's charging pile power. For example, when the vehicle's remaining battery power is 20%, the target charging amount is 80%, and the charging pile power is 60kW, the theoretical charging time is approximately (battery capacity × (80% - 20%)) / charging pile power. The user's activity time in the surrounding POI area is estimated based on the user's selection of preferred POIs, the POI's service duration, walking distance, and other factors. For example, if a user chooses to dine at a restaurant near the charging station, the walking distance is 100 meters, and the estimated dining time is 40 minutes, then this activity time is the sum of the round-trip walking time and the dining time.

[0046] The total charging cost is obtained by tracking charging information from charging stations along the driving route. This information includes remaining battery capacity, charging duration, unit price, and whether the charging time falls during off-peak or peak hours. Specifically, the required charging amount is determined based on the vehicle's current remaining battery capacity and the target charging amount, which is the difference between the target charging amount and the remaining battery capacity. For example, if the vehicle's current remaining battery capacity is 30%, the target charging amount is 80%, and the battery capacity is 100kWh, then the required charging amount is 100 × (80% - 30%) = 50kWh. Next, the unit price information of each charging station is used. If the charging station is during off-peak hours with a unit price of 0.5 yuan / kWh, the charging cost is 50 × 0.5 = 25 yuan. If the charging time falls during peak hours with a unit price of 1.2 yuan / kWh, the charging cost is 50 × 1.2 = 60 yuan. This method allows the calculation of the charging cost for each charging station. Summing up the charging costs for all charging stations along the driving route yields the total charging cost.

[0047] S104 calculates a comprehensive score for the driving route based on the overall satisfaction score, total travel time, and total charging cost.

[0048] S105, determine the target driving route based on the comprehensive score of each driving route in the driving route set.

[0049] Specifically, a weighted summation method can be used to calculate the overall score. Weighting coefficients are pre-assigned to the overall satisfaction score, total travel time, and total charging cost. For example, the weight of the overall satisfaction score could be 0.5, the weight of the total travel time 0.3, and the weight of the total charging cost 0.2. Assume a certain travel route has an overall satisfaction score of 85 points (out of 100), a total travel time of 180 minutes, and a total charging cost of 50 yuan. To enable weighted calculation of indicators with different dimensions, the total travel time and total charging cost need to be normalized. For example, the minimum total travel time is mapped to 100 points, and the maximum to 0 points. A linear transformation formula is used to convert 180 minutes into a corresponding normalized score, say 70 points. Similarly, the total charging cost is normalized in a similar way; assume 50 yuan corresponds to a normalized score of 80 points. Then, the overall score is calculated according to the set weights: 85 × 0.5 + 70 × 0.3 + 80 × 0.2 = 42.5 + 21 + 16 = 79.5 points. In this way, the indicators from various dimensions are integrated into a single comprehensive score. The overall score for each driving route can be calculated using the same method.

[0050] After calculating the comprehensive score for each driving path, the path with the highest comprehensive score is selected from the set of driving paths as the target driving path. For example, as shown in the above embodiment, the driving paths are a→A1→A2→b, a→A1→A3→b, a→A1→A4→b, and a→A1→A5→b. The comprehensive score for driving path a→A1→A2→b is 85 points, the comprehensive score for driving path a→A1→A3→b is 88 points, the comprehensive score for driving path a→A1→A4→b is 70 points, and the comprehensive score for driving path a→A1→A5→b is 75 points. Therefore, the driving path a→A1→A3→b with a comprehensive score of 88 is selected as the target driving path. Then, vehicle control is performed based on the target driving path.

[0051] It should be noted that if multiple driving routes have the same and highest overall rating, then the overall satisfaction rating, total travel time, or total charging cost can be compared separately. For example, comparing the overall satisfaction ratings of these routes, the route with the highest overall satisfaction rating can be selected as the target driving route. Similarly, comparing the total travel time of these routes, the route with the shortest total travel time can be selected as the target driving route. Furthermore, comparing the total charging cost of these routes, the route with the lowest total charging cost can be selected as the target driving route.

[0052] In some embodiments of this application, a target driving path is determined based on the comprehensive score of each driving path in the driving path set, including: obtaining the maximum value of the comprehensive scores of all driving paths; and taking the driving path corresponding to the maximum value as the target driving path, wherein the target driving path includes the name of the charging station, the location of the charging station, recommended entertainment activities, and the total travel time.

[0053] Specifically, the process iterates through each driving path in the set of driving paths, calculates and records the comprehensive score for each path, and filters out the driving path corresponding to the highest comprehensive score. If there is only one highest score, the driving path corresponding to that score is selected as the target driving path. If multiple highest scores exist, the driving paths corresponding to these scores are combined into a subset of candidate paths, and then these paths are further compared according to a preset priority order (priority order of comprehensive satisfaction score, total travel time, and total charging cost). For example, if the preset priority order is comprehensive satisfaction score, total travel time, and total charging cost, then first, the comprehensive satisfaction scores of these paths are compared, and the path with the highest comprehensive satisfaction score is selected as the target driving path. If the comprehensive satisfaction scores are also the same, then the total travel time is compared, and the path with the shortest total travel time is selected as the target driving path. If the total travel time is still the same, then the total charging cost is compared, and the path with the lowest total charging cost is selected as the target driving path. In this way, it is ensured that the target driving path that best meets the user's actual needs and preferences is selected from multiple possible high-scoring paths. The target driving route includes the specific names of the charging stations along the way, the precise geographical location information of each charging station, a list of entertainment options recommended based on user preferences and surrounding facilities, and the estimated total time to complete the entire trip.

[0054] In some embodiments of this application, such as Figure 3 As shown, the comprehensive score of the driving route is calculated based on the overall satisfaction score, total travel time, and total charging cost, including the following steps: S301, obtain the first weighting coefficient for the overall satisfaction score and the second weighting coefficient for the total charging cost.

[0055] S302, the first weight is obtained by multiplying the comprehensive satisfaction score and the first weight coefficient, and the second weight is obtained by multiplying the total charging cost and the second weight coefficient.

[0056] S303. Based on the difference between the total travel time and the second weight, and the sum of the first weight, a comprehensive score for the travel route is determined.

[0057] Specifically, assuming the overall satisfaction rating is Its corresponding first weighting coefficient is Ws, and the total charging cost is Its corresponding second weighting coefficient is Wc, and the total travel time is Then the first weight is The product of Ws, the second weight is The product of Wc. Next, calculate the total travel time. The difference between the second weight and the second weight is obtained. - ×Wc, then compare this difference result with the first weight. The sum of ×Ws is the overall score for the driving route. For example, when the overall satisfaction score of a driving route is... The score is 85 points, the first weighting coefficient Ws is 0.4, and the total travel time is... The charging time is 180 minutes, which is normalized to 80 minutes. The total charging cost is... The cost is 60 yuan, which is 70 points after normalization. When the second weighting coefficient Wc is 0.3, the first weight is 85 × 0.4 = 34, and the second weight is 7 × 0.3 = 21. The comprehensive score for this route is 80 - 31 + 34 = 83 points. This formula allows for the quantitative integration of evaluation indicators from different dimensions, leading to a more objective comprehensive assessment of each driving route.

[0058] In some embodiments of this application, calculating the overall satisfaction score for each driving route based on user preferences includes: calculating the satisfaction score for each POI area surrounding a charging station along the driving route based on user preferences, wherein user preferences are determined based on historical driving data and user consumption records; and determining the overall satisfaction score based on the sum of the satisfaction scores for all POI areas surrounding charging stations along the driving route.

[0059] In some embodiments of this application, the satisfaction score of the POI area surrounding each charging station along the driving route is calculated based on user preferences, including: obtaining multiple service items based on user preferences, the service items including at least one of catering, leisure and entertainment, shopping, and rest; calculating the satisfaction score of each preferred entertainment in the surrounding POI area; and determining the satisfaction score of the POI area surrounding the charging station based on the satisfaction scores of all preferred entertainment.

[0060] Specifically, user preferences can be trained using historical driving data, in-cabin entertainment system usage records, and app consumption records. For example: dining (food: 0.4), leisure and entertainment (movies / shopping malls): 0.3, rest (cafes / parks): 0.2, shopping (supermarkets): 0.1. The surrounding POI area includes: location (Lpoi), POI type (Tpoi), POI service duration (Tservice, e.g., a 120-minute movie), rating (Rpoi), and walking distance (Dwalk). For each charging station along the driving route, information on various POIs within a preset range (e.g., 1 km) is obtained. This information specifically includes location (Lpoi), POI type (Tpoi), POI service duration (Tservice), rating (Rpoi), and walking distance (Dwalk). Then, based on the weights of various POIs in the user's preferences (e.g., dining (food) 0.4, leisure and entertainment (movies / shopping malls) 0.3, rest (cafes / parks) 0.2, shopping (supermarkets) 0.1), each POI is initially screened, prioritizing POI types with higher user preference weights. For the selected POIs, their satisfaction sub-ratings are further calculated. The POI score (Rpoi) directly influences the sub-rating; a higher score results in a higher sub-rating. Walking distance (Dwalk) is negatively correlated with the sub-rating; shorter walking distances indicate greater convenience for users to reach the POI, leading to a higher sub-rating. A walking distance threshold can be set; when the walking distance is less than or equal to the threshold, the walking distance factor is 1. The POI service duration (Tservice) needs to be considered in conjunction with the user's expected stay at the charging station. If the POI service duration is too long, exceeding the user's expected stay, the user may not be able to fully enjoy the POI service, thus reducing the service duration factor. For example, if a user expects to stay at the charging station for 40 minutes, but a movie POI's service duration is 120 minutes, significantly exceeding the expected stay, the POI's service duration factor is 0. If the service duration of a coffee shop can be controlled by the user, with a typical user resting for about 20 minutes, then the service duration factor is 1. Multiplying the rating factor, walking distance factor, and service duration factor of a POI by the weight of that POI type in user preferences yields its satisfaction sub-rating. Then, the satisfaction sub-ratings of all POIs around each charging station that match user preferences are summed to obtain the overall satisfaction rating for the POI area surrounding that charging station. Finally, the satisfaction ratings of all POI areas around charging stations along the driving route are added together to obtain the comprehensive satisfaction rating for that driving route.

[0061] In some embodiments of this application, the total trip time includes the total service time and driving time. Obtaining the total trip time for each travel route includes: obtaining the total service time on the travel route; and determining the total trip time based on the sum of the total service time and driving time.

[0062] In some embodiments of this application, obtaining the total service time along the driving route includes: calculating the charging time based on the charging power of the charging station and the preset charging amount; determining the target service item based on the satisfaction score of each service item in the POI area around the charging station, and determining the dwell time based on the target service; determining the service time of the charging station based on the charging time and the dwell time; and determining the total service time based on the service time of all charging stations along the driving route.

[0063] In some embodiments of this application, the service time of a charging station is determined based on charging time and dwell time, including: determining the service time of the charging station based on the maximum value of charging time and dwell time.

[0064] Specifically, charging time is calculated based on the charging station's charging power and preset charging capacity. The formula is: Charging Time = Preset Charging Capacity ÷ Charging Power. For example, if the preset charging capacity is 30kWh and the charging station's charging power is 60kW, the charging time would be 30 ÷ 60 = 0.5 hours, or 30 minutes. The preset charging capacity can be determined based on the difference between the vehicle's current remaining battery level and the target battery level. The target battery level can be set by the user according to their trip needs or set to a default value of 80%-90%. When determining the target service based on the satisfaction rating of each service in the surrounding POI area, the POI service with the highest satisfaction rating can be selected. If multiple services have the same and highest satisfaction rating, further selection can be made based on the user's historical preferences or real-time needs. After determining the target service, the corresponding dwell time can be determined based on the average service duration of that POI service, the user's historical dwell time data in similar POIs, or the user's currently set dwell preferences.

[0065] When a vehicle is charging at a charging station, the charging process takes time. Simultaneously, users may choose to consume or enjoy services at nearby Points of Interest (POIs), resulting in dwell time. Since charging and staying at a POI can occur concurrently—for example, a user might stop by a nearby cafe while the vehicle is charging—the longest of the two times, from when the vehicle finishes charging to when the user ends their POI service, is taken as the actual service time of the charging station. Therefore, using the larger of the charging time and the dwell time as the service time more accurately reflects the actual duration of the user's stay at the charging station. For example, if charging takes 40 minutes and the user's stay at a nearby restaurant is 60 minutes, then the user's service time at the charging station is 60 minutes; if charging takes 50 minutes and the user only stays briefly at a nearby convenience store for 10 minutes, then the service time at the charging station is 50 minutes. This ensures that the recommended POI service time closely matches the actual charging wait time, achieving a user experience where users can charge and play simultaneously, with the vehicle fully charged at the same time.

[0066] In some embodiments of this application, the driving route includes the charging time at each charging station. The total charging cost is obtained based on the charging information of the charging stations along the driving route, including: determining the charging cost based on the charging fee, charging time, and charging duration of each charging station; and determining the total charging cost based on the sum of the charging costs of all charging stations along the driving route.

[0067] Specifically, the charging cost per unit time at each charging station (e.g., yuan / minute) is obtained. This cost is then combined with the vehicle's charging duration at that station. The charging cost per unit time is multiplied by the charging duration to calculate the charging cost per station. For example, if a charging station charges 0.5 yuan / minute and the vehicle charges for 40 minutes at that station, the charging cost for that station is 0.5 × 40 = 20 yuan. After calculating the charging costs for each charging station along the travel route, these individual charging costs are summed to obtain the total charging cost for the entire route. For instance, if the travel route includes two charging stations, the first charging station has a charging cost of 20 yuan, and the second charging station charges 0.6 yuan / minute with a charging duration of 30 minutes, its charging cost is 0.6 × 30 = 18 yuan. The total charging cost is then 20 + 18 = 38 yuan.

[0068] It's worth noting that the system can also determine whether electricity consumption is during peak or off-peak hours based on the time a user arrives at the charging station, thus dynamically adjusting the charging cost per unit time. For example, if the peak electricity period in a certain area is 8:00-22:00, and the off-peak period is 22:00-8:00 the next day, with a peak electricity cost of 0.6 yuan / minute and an off-peak electricity cost of 0.3 yuan / minute, then if a vehicle is expected to arrive at a charging station at 10:00 AM, which is during peak hours, the charging cost per unit time will be calculated at 0.6 yuan / minute. If the vehicle is expected to arrive at the charging station at 1:00 AM, which is during off-peak hours, the charging cost per unit time will be calculated at 0.3 yuan / minute. This method more accurately reflects the differences in electricity costs at different times, making the calculated charging cost per charging station and the total charging cost more closely reflect actual electricity consumption.

[0069] In some embodiments of this application, the above-described vehicle driving route planning method further includes: responding to a user's request instruction, the request instruction including minimizing the total travel time; and determining a driving route based on the request instruction, the current location, the target location, and the remaining driving range.

[0070] Specifically, when a user selects the option with the shortest total travel time in the navigation system, considering the possibility of an emergency, the system will not consider user preferences when planning the route; instead, it will directly select the route with the shortest travel time. Specifically, the system obtains the vehicle's current real-time location information, including precise latitude and longitude coordinates and the specific location on the road, and receives the user's input target location. This, combined with the vehicle's remaining driving range, serves as the basic parameter for route planning. Next, it calls the map service interface to obtain all possible driving routes from the current location to the target location. For each route, it comprehensively considers real-time traffic information (such as road congestion levels, accident information, construction sections, etc.), road type (such as highways, urban expressways, ordinary roads, etc.) traffic efficiency, and whether there are detours along the way. For each candidate route, the system simulates and calculates the travel time based on real-time traffic data. For example, the average speed on highways under smooth conditions is usually higher than on urban roads, while congested sections significantly increase travel time. In addition, the system also considers the vehicle's remaining range to determine whether the selected route requires charging. If charging is needed, the system incorporates charging station search and charging time estimation (including waiting time and actual charging time) into the total trip time calculation. For example, a shorter route might have a longer estimated travel time due to severe real-time congestion, while another slightly longer route might have smooth traffic and require no charging, resulting in a shorter overall travel time. By comparing the total travel time of all candidate routes, the system ultimately selects the route with the shortest travel time as the recommended route and displays detailed information about it on the navigation interface, including estimated travel time, major roads along the route, potential congestion points, and whether charging is required, allowing users to make an informed choice based on their actual needs.

[0071] In summary, the vehicle route planning method according to the embodiments of this application, when determining that charging is needed based on the vehicle's current location, remaining battery range, and target location, obtains multiple candidate charging station sets based on the navigation route and remaining range. It then determines a set of vehicle routes based on the current location, target location, and multiple candidate charging station sets. A comprehensive satisfaction score for the route is calculated based on user preferences, and the total travel time for the route is obtained. The total charging cost is also obtained based on the charging information of charging stations along the route. A comprehensive score for the route is calculated based on the comprehensive satisfaction score, total travel time, and total charging cost. Finally, a target route is determined based on the comprehensive score of each route in the route set. Therefore, this method combines charging needs with user preferences to plan a route with optimal total travel time and highest user satisfaction, better aligning with users' actual usage habits and preferences, and improving the user's travel experience.

[0072] Corresponding to the above embodiments, this application also proposes a computer-readable storage medium.

[0073] The computer-readable storage medium of this application embodiment stores a program that, when executed by a processor, implements the above-described vehicle driving path planning method.

[0074] According to the computer-readable storage medium of the present application embodiment, by executing the above-described vehicle driving route planning method, charging demand and user preferences can be combined to plan a route with the optimal total time and the highest user satisfaction, which is more in line with the user's actual usage habits and preferences and improves the user's travel experience.

[0075] Corresponding to the above embodiments, this application also proposes a vehicle.

[0076] like Figure 4 As shown, the vehicle 400 in this embodiment includes: a memory 410, a processor 420, and a program stored in the memory 410 and executable on the processor 420. When the processor 420 executes the program, it implements the above-described vehicle driving path planning method.

[0077] According to the vehicle embodiment of this application, by executing the above-described vehicle travel route planning method, charging needs and user preferences can be combined to plan a route with the optimal total travel time and the highest user satisfaction, which is more in line with the user's actual usage habits and preferences and improves the user's travel experience.

[0078] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0079] Those skilled in the art will understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the foregoing method embodiments, and will not be repeated here.

[0080] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0081] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0082] In addition, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0083] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program verification codes, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0084] It should be noted that in the description of this application, the terms "first," "second," "third," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance. Furthermore, in the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0085] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0086] The above are merely preferred embodiments of this application and are not intended to limit this application. Any modifications or equivalent substitutions made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for planning the driving path of a vehicle, characterized in that, The method includes: If it is determined that charging is needed based on the vehicle's current location, the battery's remaining range, and the target location, a set of multiple candidate charging stations is obtained based on the navigation path and the remaining range. A set of vehicle travel paths is determined based on the current location, the target location, and a set of multiple candidate charging stations, wherein the travel path includes at least one charging station; The overall satisfaction score of the driving route is calculated based on user preferences, the total travel time of the driving route is obtained, and the total charging cost is obtained based on the charging information of the charging stations along the driving route. The comprehensive score of the driving route is calculated based on the overall satisfaction score, the total travel time, and the total charging cost. The target driving route is determined based on the comprehensive score of each driving route in the set of driving routes.

2. The vehicle travel path planning method according to claim 1, characterized in that, The process of determining the target driving route based on the comprehensive score of each driving route in the set of driving routes includes: Obtain the maximum value of the overall score for all driving routes; The driving path corresponding to the maximum value is taken as the target driving path, which includes the charging station name, charging station location, recommended entertainment activities, and total travel time.

3. The vehicle driving path planning method according to claim 1, characterized in that, The calculation of the comprehensive score for the driving route based on the overall satisfaction score, the total travel time, and the total charging cost includes: Obtain the first weighting coefficient of the overall satisfaction score and the second weighting coefficient of the total charging cost; A first weight is obtained by multiplying the comprehensive satisfaction score and the first weight coefficient, and a second weight is obtained by multiplying the total charging cost and the second weight coefficient. The comprehensive score of the travel route is determined based on the difference between the total travel time and the second weight, and the sum of the result and the first weight.

4. The vehicle driving path planning method according to claim 1, characterized in that, The calculation of the overall satisfaction score for each driving route based on user preferences includes: Based on the user preferences, a satisfaction score is calculated for the POI area surrounding each charging station along the driving route, wherein the user preferences are determined based on historical driving data and user consumption records; The overall satisfaction score is determined by summing the satisfaction scores of all POI areas surrounding the charging stations along the driving route.

5. The vehicle driving path planning method according to claim 4, characterized in that, The process of calculating a satisfaction score for the POI area surrounding each charging station along the driving route based on the user preferences includes: Based on the user preferences, multiple service items are obtained, including at least one of dining, leisure and entertainment, shopping, and rest; Calculate the satisfaction score for each preferred entertainment in the surrounding POI area; The satisfaction score of the POI area surrounding the charging station is determined based on the satisfaction scores of all the aforementioned entertainment preferences.

6. The vehicle driving path planning method according to claim 1, characterized in that, The total trip time includes total service time and driving time. Obtaining the total trip time for each travel route includes: Obtain the total service time along the driving route; The total trip time is determined based on the sum of the total service time and the driving time.

7. The vehicle driving path planning method according to claim 6, characterized in that, Obtaining the total service time along the travel route includes: The charging time is calculated based on the charging power and preset charging amount of the charging station. The target service item is determined based on the satisfaction score of each service item in the POI area around the charging station, and the dwell time is determined based on the target service. The service time of the charging station is determined based on the charging time and the dwell time. The total service time is determined based on the service time of all charging stations along the driving route.

8. The vehicle driving path planning method according to claim 7, characterized in that, Determining the service time of the charging station based on the charging time and the dwell time includes: The service time of the charging station is determined based on the maximum value of the charging time and the dwell time.

9. The vehicle driving path planning method according to claim 1, characterized in that, The driving route includes the charging time at each charging station, and obtaining the total charging cost based on the charging information of the charging stations along the driving route includes: The charging cost is determined based on the charging fee of the charging station, the charging time, and the charging duration. The total charging cost is determined based on the sum of the charging costs of all charging stations along the driving route.

10. The vehicle driving path planning method according to claim 1, characterized in that, The process of obtaining a set of multiple candidate charging stations based on the navigation path and the remaining driving range includes: The set of charging stations is determined based on the navigation path; Candidate charging stations are determined based on the current remaining driving range, the preset driving range safety margin, and the set of charging stations.

11. The vehicle driving path planning method according to claim 10, characterized in that, The method further includes: The preset range safety margin is determined based on weather and road information along the navigation route.

12. The vehicle driving path planning method according to claim 1, characterized in that, The method further includes: responding to a user's request instruction, the request instruction including minimizing the total trip time; The driving route is determined based on the request command, the current location, the target location, and the remaining driving range.

13. A computer-readable storage medium, characterized in that, It stores a program that, when executed by a processor, implements the vehicle driving path planning method according to any one of claims 1-12.

14. A vehicle, characterized in that, include: A memory, a processor, and a program stored in the memory and executable on the processor, wherein when the processor executes the program, it implements the vehicle driving path planning method according to any one of claims 1-12.

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