Intelligent pick-up method and intelligent pick-up system

Abstract

The embodiment of the invention relates to the technical field of student pick-up, and discloses an intelligent pick-up method and an intelligent pick-up system, and the method comprises the steps: obtaining a first position of a target user and a second position of a target vehicle after a pick-up request is issued, determining a safe boarding point set based on the first position, and determining a first time and a second time from the first position and the second position to each safe boarding point, determining an optimal boarding point in the safe boarding point set according to the first time and the second time, generating a walking path from the first position to the optimal boarding point, and sending the walking path to the target user. And generating a driving path from the second position to the optimal boarding point and sending the driving path to the target vehicle. By means of the technical scheme, the optimal boarding point can be selected, it is avoided that all pick-up vehicles are concentrated in a single place, pick-up traffic flow is dispersed in advance, tidal congestion is relieved from the source, pick-up time is shortened, meanwhile, it can be guaranteed that the vehicles are safely parked on non-congested road sections, mixed driving of people and vehicles is avoided, and student safety is guaranteed.

Description

Technical Field

[0001] This invention relates to the field of student pick-up and drop-off technology, specifically to an intelligent pick-up and drop-off method and system. Background Technology

[0002] Picking up children from school has become a difficult social issue with many pain points, mainly in the following aspects: time conflict, children usually get out of school early, around 3 or 4 pm, while parents usually get off work at 5 or 6 pm or even later, this time mismatch makes dual-income families exhausted; traffic pressure, traffic congestion during rush hour in big cities increases parents' commuting time from work to school; safety anxiety, parents are worried about letting their children go home alone, and the quality of after-school care programs varies, which also makes parents anxious.

[0003] Existing passenger pick-up and drop-off schemes mostly use fixed pick-up points. However, when students are leaving school, the flow of people is relatively large. If students are picked up and dropped off at fixed pick-up points at the same time, it will directly lead to increased congestion around the school. Moreover, the mixing of pedestrians and vehicles can easily cause safety accidents. Summary of the Invention

[0004] In view of the above problems, embodiments of the present invention provide an intelligent pick-up and drop-off method and an intelligent pick-up and drop-off system to solve the problem that the existing pick-up and drop-off methods are not suitable for student pick-up and drop-off scenarios, which can easily aggravate congestion and create safety hazards.

[0005] According to one aspect of the present invention, an intelligent pick-up and drop-off method is provided, applied to a cloud platform. The method includes: after receiving a pick-up and drop-off request from a first terminal device of a target user, obtaining a first location of the target user and a second location of a target vehicle, and obtaining a set of safe pick-up points within a preset area where the first location is located; determining a first time from the first location to each safe pick-up point in the set of safe pick-up points, and determining a second time from the second location to the same safe pick-up point; determining an optimal pick-up point in the set of safe pick-up points based on the first time and the second time corresponding to each safe pick-up point; generating a walking path for the target user and a pick-up and drop-off instruction and driving path for the target vehicle according to the optimal pick-up point, and sending the walking path to the first terminal device and the pick-up and drop-off instruction and driving path to the target vehicle.

[0006] According to another aspect of the present invention, an intelligent pick-up and drop-off method is provided, applied to a target vehicle, the target vehicle being pre-parked at a second location, the method comprising: obtaining a driving route; and driving from the second location to an optimal pick-up point according to the driving route.

[0007] According to another aspect of the present invention, an intelligent pick-up and drop-off system is provided, comprising: a cloud platform, a first terminal device of a target user, a target vehicle, a second terminal device of the target user's guardian, and a preset associated device. The first terminal device and the target vehicle are respectively connected to the cloud platform, and the second terminal device and the preset associated device are connected to the target vehicle. The cloud platform includes: a memory and a processor, which are communicatively connected to each other. The memory stores computer instructions, and the processor executes the computer instructions to perform the intelligent pick-up and drop-off method of the first aspect or any corresponding embodiment described above. The target vehicle is used to perform the intelligent pick-up and drop-off method of the second aspect or any corresponding embodiment described above.

[0008] The intelligent pick-up and drop-off method provided by this invention involves, after a target user sends a pick-up and drop-off request to their first terminal device, determining a set of safe pick-up points within a preset area based on the target user's first location, determining the first time the target user travels from their first location to each safe pick-up point, and determining the second time the target vehicle travels from a second location to each safe pick-up point. Based on the first and second times for each safe pick-up point, an optimal pick-up point is determined, and a walking route is generated and sent to the target user's first terminal device. A driving route is also generated and sent to the target vehicle. This invention, by pre-setting multiple safe and compliant pick-up points for different preset areas, can select the optimal pick-up point from among these safe pick-up points based on the user's and vehicle's locations when pick-up and drop-off are needed. This avoids all pick-up and drop-off vehicles concentrating at a single location, thus dispersing traffic flow in advance, alleviating tidal congestion at the source, shortening pick-up and drop-off times, and ensuring vehicles can safely park in uncongested areas, avoiding pedestrian-vehicle mixing and guaranteeing student safety.

[0009] The above description is merely an overview of the technical solutions of the embodiments of the present invention. In order to better understand the technical means of the embodiments of the present invention and to implement them in accordance with the contents of the specification, and to make the above and other objects, features and advantages of the embodiments of the present invention more apparent and understandable, specific embodiments of the present invention are described below. Attached Figure Description

[0010] The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Furthermore, the same reference numerals denote the same parts throughout the drawings. In the drawings: Figure 1 A schematic diagram of the structure of a first embodiment of the intelligent pick-up and drop-off system provided by the present invention is shown; Figure 2 A flowchart illustrating a first embodiment of the intelligent pick-up and drop-off method provided by the present invention is shown; Figure 3 This invention illustrates a flowchart of the boarding point determination process for the intelligent pick-up and drop-off method provided by the present invention. Figure 4 A flowchart illustrating a second embodiment of the intelligent pick-up and drop-off method provided by the present invention is shown. Figure 5 A flowchart illustrating a third embodiment of the intelligent pick-up and drop-off method provided by the present invention is shown; Figure 6 This invention provides an overall flowchart of the intelligent pick-up and drop-off method. Figure 7 A schematic diagram of the hardware structure of the cloud platform for intelligent pick-up and drop-off provided by the present invention is shown. Detailed Implementation

[0011] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0012] As an optional application scenario of this invention, such as Figure 1 As shown, the constructed intelligent pick-up and drop-off system includes: a cloud platform 101, a first terminal device 102 of the target user, a target vehicle 103, a second terminal device 104 of the target user's guardian, and a preset associated device 105. The first terminal device 102 and the target vehicle 103 are respectively connected to the cloud platform 101, and the second terminal device 104 and the preset associated device 105 are connected to the target vehicle 103.

[0013] Taking student pick-up and drop-off as an example, the target user is the student. The student's first terminal device 102 can be a smartwatch or mobile phone, etc., and the student's guardian's second terminal device 104 can be a smartwatch or mobile phone, etc. The preset associated device 105 can be a home security device, such as a smart door lock or camera. The preset associated device is pre-added to the target vehicle 103's cockpit ecosystem, and can interact with the target vehicle 103 and the guardian's second terminal device 104. The target vehicle 103 is equipped with a corresponding backend server to receive and store the information transmitted by the target vehicle 103 and provide the information to the parent's mobile terminal. In this embodiment of the invention, the cloud platform 101 is a vehicle management platform used to receive pick-up and drop-off task information and summon the target vehicle 103 to a designated destination. The target vehicle 103 is a private car that supports autonomous driving, so the target vehicle 103 can automatically drive to a safe parking area near the school before the students get out of school. After class, the students can send a pick-up and drop-off request through the first terminal device 102, which is then analyzed and processed by the cloud platform 101. The platform selects the best drop-off point from a pre-set candidate drop-off point database, and the target vehicle 103 automatically drives to the best drop-off point, while the students walk to the best drop-off point, thus completing the pick-up and drop-off task. Using autonomous vehicles to complete student pick-up and drop-off tasks provides a smart pick-up and drop-off system that balances safety and timeliness for dual-income families, resolving the time conflict between the guardian's off-get off work time and the student's off-school time. At the same time, the smart pick-up and drop-off system also supports guardians to drive their own vehicles to pick up and drop off students, that is, it provides guardians with the best pick-up point, which they can drive themselves to.

[0014] Therefore, embodiments of the present invention provide an intelligent pick-up and drop-off method that determines the optimal pick-up point among multiple safe pick-up points to avoid congestion and ensure pick-up and drop-off safety.

[0015] According to an embodiment of the present invention, an intelligent pick-up and drop-off method embodiment is provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0016] Figure 2 A flowchart of a first embodiment of the intelligent pick-up and drop-off method of the present invention is shown, which is executed by the aforementioned cloud platform. Figure 2 As shown, the method includes the following steps: Step S201: After receiving the pick-up and drop-off request from the first terminal device of the target user, obtain the first location of the target user and the second location of the target vehicle, and obtain the set of safe pick-up points within the preset area where the first location is located.

[0017] Specifically, in this embodiment of the invention, taking students as the target users for pick-up and drop-off as an example, safe pick-up points that comply with traffic rules and have been approved are pre-selected around each school. These safe pick-up points can be deployed on different roads around the schools, thereby avoiding congestion caused by all target vehicles concentrating on the same road to pick up and drop off students. The selected safe pick-up points are stored in a candidate pick-up point database and categorized according to the location of the corresponding school, thus forming different sets of safe pick-up points. Simultaneously, a corresponding pick-up and drop-off APP is developed. When deployed on the student's first terminal device, the student can initiate a pick-up and drop-off request through the APP; when deployed on the guardian's second terminal device, the guardian can view the pick-up and drop-off status through the APP.

[0018] Taking students wearing smartwatches as an example, such as Figure 3 As shown, students can send pick-up and drop-off requests via a pick-up and drop-off app installed on their smartwatches before or after class. Upon receiving the request, the cloud platform obtains the target user's initial location, which is collected by the GPS / BeiDou module deployed on the smartwatch and sent to the cloud platform. Based on this initial location, the cloud platform determines a set of safe pick-up points within a preset area. Since this initial location corresponds to the school's location, it can directly determine the set of safe pick-up points corresponding to the school's location from a pre-built candidate pick-up point database.

[0019] Simultaneously, the second location of the target vehicle is obtained. The target vehicle is pre-matched with the target user, and this second location is collected by the GPS / BeiDou module deployed on the target vehicle and sent to the cloud platform. If the target vehicle is in autonomous driving mode, it has already been pre-parked in a safe parking area near the school; therefore, the second location is its specific location within that safe parking area. Furthermore, the cloud platform can further obtain the target vehicle's status information, including battery level and driving status. If multiple target vehicles exist, one is selected based on the status information, for example, the vehicle with the higher battery level.

[0020] In some alternative implementations, such as Figure 3 As shown, if no safe pick-up point is set up within the preset area of ​​the first location, a backup plan will be activated. This involves generating a temporary pick-up point based on the road conditions of the preset area and using this temporary pick-up point as the optimal pick-up point. Simultaneously, if multiple pick-up / drop-off tasks occur within this area, the developers will be alerted to set up a safe pick-up point within this area as soon as possible.

[0021] Step S202: Determine the first time when the target user travels from the first location to each safe pick-up point in the set of safe pick-up points, and determine the second time when the target vehicle travels from the second location to the same safe pick-up point.

[0022] Specifically, in this embodiment of the invention, the set of safe pick-up points includes multiple safe and compliant pick-up points. If students and target vehicles can arrive at a certain safe pick-up point simultaneously, allowing for immediate drop-off and pick-up, congestion can be avoided to some extent, and accidents caused by students lingering can also be prevented. Therefore, this embodiment of the invention iterates through each safe pick-up point in the set, calculates the first time it takes for a student to walk from a first location to each safe pick-up point, and simultaneously calculates the second time it takes for the target vehicle to travel from a second location to each safe pick-up point. Based on the first and second times, the optimal pick-up point is selected.

[0023] Step S203: Based on the first time and second time corresponding to each safe boarding point, determine the optimal boarding point from the set of safe boarding points.

[0024] Specifically, in this embodiment of the invention, the first time represents the time required for a student to walk from a first location to a safe boarding point, and the second time represents the time required for a target vehicle to travel from a second location to the same safe boarding point. In order to minimize the waiting time for students and target vehicles, the optimal boarding point is selected from the safe boarding points based on the time difference between the first and second times.

[0025] Step S204: Generate a walking route based on the first location and the optimal pick-up point, generate a driving route based on the second location and the optimal pick-up point, and send the walking route to the first terminal device and the driving route to the target vehicle.

[0026] Specifically, in this embodiment of the invention, after determining the optimal pick-up point, the cloud platform obtains high-precision map information from third-party service APIs such as Gaode Maps and Baidu Maps. Based on the first location and the optimal pick-up point, it generates a walking route and sends it to the student's smartwatch. The student then walks to the optimal pick-up point according to the navigation prompts on their smartwatch. Simultaneously, based on the high-precision map information, the cloud platform generates a driving route and pick-up / drop-off instructions based on the second location and the optimal pick-up point, and sends these instructions to the target vehicle. The target vehicle then drives itself to the optimal pick-up point based on the navigation prompts. After the student and the target vehicle arrive at the optimal pick-up point, the student gets in the vehicle, the target vehicle initiates autonomous driving, and using the student's home as the target location, replans the route and drives to the target location, thus completing the pick-up / drop-off task.

[0027] The intelligent pick-up and drop-off method provided by this invention involves, after a target user sends a pick-up and drop-off request to their first terminal device, determining a set of safe pick-up points within a preset area based on the target user's first location, determining the first time the target user travels from their first location to each safe pick-up point, and determining the second time the target vehicle travels from a second location to each safe pick-up point. Based on the first and second times for each safe pick-up point, an optimal pick-up point is determined, and a walking route is generated and sent to the target user's first terminal device. A driving route is also generated and sent to the target vehicle. This invention, by pre-setting multiple safe and compliant pick-up points for different preset areas, can select the optimal pick-up point from among these safe pick-up points based on the user's and vehicle's locations when pick-up and drop-off are needed. This avoids all pick-up and drop-off vehicles concentrating at a single location, thus dispersing traffic flow in advance, alleviating tidal congestion at the source, shortening pick-up and drop-off times, and ensuring vehicles can safely park in uncongested areas, avoiding pedestrian-vehicle mixing and guaranteeing student safety.

[0028] Figure 4 A flowchart of another embodiment of the intelligent pick-up and drop-off method of the present invention is shown, which is executed by the aforementioned cloud platform. Figure 4 As shown, the method includes the following steps: Step S401: After receiving the pick-up request from the target user's first terminal device, obtain the target user's first location and the target vehicle's second location, and obtain a set of safe pick-up points within a preset area where the first location is located. For details, please refer to [link to details]. Figure 2 Step S201 of the illustrated embodiment will not be described again here.

[0029] Step S402: Determine the first time when the target user travels from the first location to each safe pick-up point in the set of safe pick-up points, and determine the second time when the target vehicle travels from the second location to the same safe pick-up point.

[0030] Specifically, step S402 includes: Step S4021: Obtain the third position of each safe boarding point in the set of safe boarding points.

[0031] Specifically, in this embodiment of the invention, when storing multiple safe boarding points in the candidate boarding point database, the third position of each safe boarding point is stored simultaneously. Therefore, after determining the set of safe boarding points from the candidate boarding point database, the third position of each safe boarding point in the set of safe boarding points is obtained simultaneously.

[0032] Step S4022: For any safe boarding point, plan a walking route based on the first and third locations, and determine the first time based on the walking route.

[0033] Specifically, in this embodiment of the invention, each safe boarding point in the set of safe boarding points is traversed. Using the student's first position and the third position of the traversed safe boarding point as a reference, a walking path is planned according to the actual scenario. During the planning process, priority is given to continuous paths along the inner side of the school wall, community sidewalks, and municipal sidewalks, ensuring that the entire path is physically isolated (e.g., guardrails, green belts) and covered by surveillance. If there are intersections along the path, priority is given to intersections equipped with pedestrian crossing lights and guarded by traffic police or security personnel. Unprotected motor vehicle lanes, construction sections, secluded alleys, and entrances to shops with high pedestrian traffic are strictly avoided. Overpasses are avoided as much as possible, and these are just examples and not limitations.

[0034] Once the walking path between the first and third positions is determined, the first time required for the student to walk along that path is also determined. At this point, the students' walking speed can be further considered to ensure timely response. The accuracy and reliability of walking speed are ensured. For example, a pre-set age-appropriate walking speed database is used, with a default speed of 3-4 km / h for lower grade students (grades 1-3) and 4-5 km / h for middle and upper grade students (grades 4-6). Parents can customize the speed using a first or second terminal device (e.g., setting 2.5 km / h for slower-moving students). Furthermore, factors such as weather and pedestrian traffic in real-world scenarios can be considered.

[0035] Step S4023: For the same safe boarding point, plan the driving route based on the second and third locations, and determine the second time based on the driving route.

[0036] Specifically, in this embodiment of the invention, when traversing the first time corresponding to each safe boarding point in the set of safe boarding points, the driving route is simultaneously planned based on the second position of the target vehicle and the second position of the traversed safe boarding points, according to the actual road conditions and traffic control. During the planning process, smooth road sections are selected as much as possible to ensure traffic efficiency. For example, if the shortest distance route passes through the main road at the school gate, but the congestion index is ≥80% during school dismissal time, a secondary road 500 meters away is automatically selected, with a congestion index ≤40%, to ensure that the calculated second time at this time closely matches the actual arrival time.

[0037] Once the driving route between the second and third locations is determined, the second time required for the target vehicle to drive along that route is determined. At this point, the driving speed of the target vehicle is determined based on actual road conditions to ensure a timely response. The accuracy and reliability of the calculation. This embodiment of the invention simultaneously calculates the first time. Second time This ensures a balance between student walking safety and vehicle traffic efficiency, avoiding excessive waiting times or pedestrian-vehicle congestion caused by unreasonable route planning.

[0038] Step S403: Based on the first time and second time corresponding to each safe boarding point, determine the optimal boarding point from the set of safe boarding points.

[0039] Specifically, step S403 includes: Step S4031: Calculate the time difference between the first time and the second time corresponding to each safe boarding point.

[0040] Specifically, in this embodiment of the invention, the first time corresponding to each safe boarding point is calculated respectively. With the second time Time difference Time difference This represents the waiting time required for a student to arrive at the optimal pick-up point but the target vehicle has not yet arrived at the optimal pick-up point, or the waiting time required for the target vehicle to arrive at the optimal pick-up point but the student has not yet arrived at the optimal pick-up point.

[0041] Step S4032: Sort all safe boarding points by time difference from smallest to largest, and select the first preset number of safe boarding points as alternative boarding points.

[0042] Specifically, in this embodiment of the invention, the ideal goal is to achieve simultaneous arrival of the target vehicle and the student, i.e. The time difference is infinitely close to 0. However, if only the time difference is considered without considering the actual road conditions around the safe boarding point, it will lead to a difference between the student's actual arrival time and the first time, or between the target vehicle's actual arrival time and the second time, or traffic congestion after the student boards the vehicle. Therefore, this embodiment of the invention considers the time difference corresponding to all safe boarding points. Sort the safe boarding points from smallest to largest, and select the top preset number of safe boarding points as alternative boarding points, for example, by selecting time difference. The top three safe pick-up points after sorting are used as alternative pick-up points, so that the best pick-up point can be selected from multiple alternative pick-up points based on the actual road conditions, while focusing on the waiting time.

[0043] Step S4033: Determine the overall load rate of each candidate boarding point, and select the candidate boarding point with the lowest load rate as the optimal boarding point.

[0044] Specifically, in this embodiment of the invention, the parking area load rate, road network load rate, environmental compliance load rate, and sidewalk load rate of each candidate pick-up point are calculated to determine the comprehensive load rate. The comprehensive load rate reflects the actual road conditions around the candidate pick-up point, and the candidate pick-up point with the lowest load rate is selected as the optimal pick-up point to ensure that the actual arrival time of the student is the same as the first time, or the actual arrival time of the target vehicle is the same as the second time, or the student can leave quickly after boarding.

[0045] In some optional implementations, step S4033 above includes: Step a1: Obtain the number of available parking spaces and the number of parking spaces requested within the preset area corresponding to each candidate pick-up point, calculate the ratio of the number of parking spaces requested to the number of available parking spaces, and obtain the parking area load rate of the candidate pick-up point.

[0046] Specifically, in this embodiment of the invention, the parking area load rate focuses on the supply and demand relationship between vehicles seeking parking spaces and available parking spaces around the candidate pick-up points, directly reflecting the ease of vehicle parking. For example, a circular area with a radius of 100 meters is defined as the preset evaluation range, centered on the third location of the candidate pick-up point. This range covers a reasonable radiation area for temporary vehicle parking while avoiding cross-regional data interference, but is not limited to this. First, real-time available parking space data can be obtained by connecting to the management system API of surrounding parking lots. The number of vacant parking spaces in compliant temporary parking areas along the roadside can also be identified through the onboard camera of the target vehicle, thereby determining the number of available parking spaces. Second, the number of parking spaces sought can be determined based on floating car data from traffic management departments and the number of navigation requests from vehicles whose destination is this area on the navigation platform. Finally, the parking area load rate is calculated according to the following formula:

[0047] To facilitate subsequent weighted calculations, the results can be mapped to standardized values ​​of 0-1: when the number of available parking spaces is 0, the load rate is directly defined as 1 (maximum load); when the number of requests is 0, the load rate is defined as 0.1 (basic load, to avoid the weights becoming invalid due to a value of 0); in other cases, the actual ratio is used for calculation, and if the ratio is greater than 1, it is taken as 1 (e.g., if there are 15 requests and 10 available parking spaces, the load rate = 15 ÷ 10 = 1.5, which is 1 after standardization). For example: if there are 8 available parking spaces around a candidate pick-up point and 10 vehicles are requesting parking spaces in real time, the load rate of the parking area = 10 ÷ 8 = 1.25, which is 1 after standardization.

[0048] Step a2: Obtain the traffic flow and design capacity within the preset area, calculate the ratio of traffic flow to design capacity, and obtain the road network load rate of the candidate pick-up points.

[0049] Specifically, in this embodiment of the invention, the road network load rate assesses the matching degree between traffic flow and design capacity of core road segments along the driving path surrounding candidate pick-up points, providing data support for vehicle traffic efficiency. Core road segments (such as entrance road segments into the assessment area and parking sections within 50 meters of the pick-up point) are extracted within a preset area of ​​the candidate pick-up points, prioritizing secondary roads and arterial roads with ≤2 lanes (these road segments are prone to congestion and have a greater impact on parking). Real-time traffic flow (unit: vehicles / 5 minutes) is obtained through fixed traffic sensors on both sides of the road (such as loop detectors and video checkpoints), which can be corrected by combining the surrounding vehicle density data collected by the target vehicle's onboard radar to obtain the traffic flow. The design capacity of the road segment is retrieved from the traffic engineering database; if there are temporary lane adjustments (such as tidal flow lanes), the design capacity is updated according to the real-time number of lanes. If the preset area contains multiple core road segments, the load rate of each core road segment within the preset area is calculated separately.

[0050] Then, the weighted summation based on the weights of the stopping sections and the entrance sections yields the final road network load rate. For example, if the traffic flow around a candidate pick-up point is 600 vehicles / hour and the design capacity is 1000 vehicles / hour (load rate 0.6), and the traffic flow at the entrance section is 800 vehicles / hour and the design capacity is 1200 vehicles / hour (load rate 0.67), then the road network load rate = 0.6 × 0.6 + 0.4 × 0.67 ≈ 0.63. The calculation result is also standardized to the range of 0-1, with a value greater than 1 taken as 1.

[0051] Step a3: Determine the estimated parking duration of the alternative pick-up points based on the first and second time points, and determine the environmental compliance load rate of the alternative pick-up points based on the estimated parking duration and the illegal parking rules of the preset area.

[0052] Specifically, in this embodiment of the invention, the environmental compliance load rate is a risk indicator that combines the expected parking duration with the regional parking rules, and it primarily addresses the issue of whether vehicle parking is compliant. First, the expected parking duration is calculated based on the first time (student arrival time) and the second time (vehicle arrival time) of the same alternative pick-up point, with a primary focus on the longest time a vehicle needs to wait for students. Furthermore, this embodiment of the invention pre-defines a "regional parking rule library," storing rules such as no-parking periods, limited-time parking durations, and permitted vehicle types according to the type of area to which the alternative pick-up point belongs (e.g., around schools, within residential areas, municipal roads). The environmental compliance load rate (0-1 point, higher score indicates higher risk and load) of alternative pick-up points is calculated using a rule-matching scoring method: ① Fully compliant: Expected parking time ≤ the time limit and within the permitted parking period, 0.1 points (basic compliance load); ② Partially compliant: Expected parking time exceeds the time limit by 1-2 minutes but within the permitted period, or within the permitted period but the vehicle type is restricted to parking, 0.5 points; ③ Completely non-compliant: Expected parking time exceeds the time limit by more than 3 minutes, or within a no-parking period (e.g., no-parking around schools from 15:00-16:00), 1 point. For example: Alternative pick-up points around schools allow 5-minute time-limited parking from 15:40-16:00, and a vehicle's expected parking time is 6 minutes (exceeding the limit by 1 minute), then the environmental compliance load rate is 0.5.

[0053] Step a4: Obtain the pedestrian flow and traffic capacity of the sidewalk within the preset area, calculate the ratio of pedestrian flow to traffic capacity, and obtain the sidewalk load rate of the candidate boarding points.

[0054] Specifically, in this embodiment of the invention, the sidewalk load rate represents the usage pressure of the sidewalks around the candidate pick-up points, preventing vehicle parking from encroaching on pedestrian space. Its assessment needs to consider the characteristics of student flow after school. Centered on the candidate pick-up points, a pre-defined area of ​​sidewalks is designated as the assessment scope (covering the core walking route from school to the pick-up point). Using AI human recognition technology through video surveillance equipment around the school, real-time pedestrian density (unit: people / square meter) is statistically analyzed. Combined with the location data from the first terminal device (the number of terminals carried by students), the pedestrian flow data is corrected to obtain the pedestrian traffic volume. The traffic capacity is calculated based on the sidewalk width (e.g., a 1.5-meter-wide sidewalk has a traffic capacity of 800 people / hour). If there are obstacles on the sidewalk (such as trees or bus stop signs), the traffic capacity is calculated based on the actual available width. Furthermore, the sidewalk load rate is calculated as follows:

[0055] The calculation results are standardized to a range of 0-1. When calculating the pedestrian load factor, adjustments need to be made for student pick-up and drop-off scenarios, including: ① Peak dismissal time adjustment: If it is during peak student dismissal time (e.g., 15:30-16:00), the load factor is calculated by multiplying the result by 1.1 (because the student population density is high, even slight congestion can affect traffic flow); ② Bus stop connection adjustment: If the pedestrian walkway directly connects to a bus stop (students need to wait in this area), the pedestrian flow in that area is increased by 20% (estimated number of waiting students) before calculating the load factor. For example: If the pedestrian walkway capacity around a bus stop is 1000 people / hour, the real-time flow is 800 people / hour, and it is during peak dismissal time, its load factor = (800 ÷ 1000) × 1.1 = 0.88.

[0056] Step a5: Weighted summation of parking area load rate, road network load rate, environmental compliance load rate, and sidewalk load rate to determine the overall load rate of the candidate pick-up points.

[0057] Specifically, in this embodiment of the invention, weighting coefficients are pre-set for parking area load rate, road network load rate, environmental compliance load rate, and sidewalk load rate. For example, the weighting coefficient for parking area load rate is... (Priority given to ease of parking), weighted by road network load rate (Traffic efficiency is secondary), environmental compliance load rate is the next most important factor. (Safety and compliance are paramount), pedestrian load factor (Pedestrian safety auxiliary assessment), and .

[0058] Furthermore, the weighting coefficients can be modified by the user or dynamically adjusted by the cloud platform based on actual scenarios. For example, if the scenario involves heavy rain near a school, the environmental compliance load rate weight can be dynamically increased to 0.4 (to avoid penalties for illegal parking), while other weights are correspondingly reduced. Then, the parking area load rate, road network load rate, environmental compliance load rate, and sidewalk load rate are weighted and summed according to their respective weighting coefficients, as shown in the following formula:

[0059] After the calculation is completed, all candidate boarding points are sorted in ascending order of comprehensive load rate, and the point with the lowest load rate is selected as the best boarding point.

[0060] Step S404: Generate a walking route based on the first location and the optimal pick-up point, and generate a driving route based on the second location and the optimal pick-up point. Send the walking route to the first terminal device and the driving route to the target vehicle. For details, please refer to [link to details]. Figure 2 Step S204 of the illustrated embodiment will not be described again here.

[0061] The intelligent pick-up and drop-off method provided by this invention involves, after a target user sends a pick-up and drop-off request to their first terminal device, determining a set of safe pick-up points within a preset area based on the target user's first location, determining the first time the target user travels from their first location to each safe pick-up point, and determining the second time the target vehicle travels from a second location to each safe pick-up point. Based on the first and second times for each safe pick-up point, an optimal pick-up point is determined, and a walking route is generated and sent to the target user's first terminal device. A driving route is also generated and sent to the target vehicle. This invention, by pre-setting multiple safe and compliant pick-up points for different preset areas, can select the optimal pick-up point from among these safe pick-up points based on the user's and vehicle's locations when pick-up and drop-off are needed. This avoids all pick-up and drop-off vehicles concentrating at a single location, thus dispersing traffic flow in advance, alleviating tidal congestion at the source, shortening pick-up and drop-off times, and ensuring vehicles can safely park in uncongested areas, avoiding pedestrian-vehicle mixing and guaranteeing student safety.

[0062] This embodiment provides an intelligent pick-up and drop-off method, which can be used for the aforementioned target vehicle. Figure 5 This is a flowchart of an intelligent pick-up and drop-off method according to an embodiment of the present invention, such as... Figure 5 As shown, the process includes the following steps: Step S501: Obtain the driving route.

[0063] Specifically, in embodiments of the present invention, such as Figure 6 As shown, after determining the optimal pick-up point, the cloud platform plans a driving route based on the target vehicle's second location and the optimal pick-up point, and then sends the driving route to the target vehicle. The target vehicle then obtains the driving route and simultaneously receives the pick-up and drop-off instructions.

[0064] Step S502: Drive from the second position to the optimal pick-up point according to the driving route.

[0065] Specifically, in this embodiment of the invention, if the target vehicle is currently in a manually driven state, the driver directly starts the vehicle and drives along the driving path from the current second position to the optimal pick-up point. If the target vehicle is currently in an autonomous driving state, the vehicle starts automatically and drives along the driving path from the current second position to the optimal pick-up point, such as... Figure 6 As shown.

[0066] Step S503: Identify the target user and unlock the car door after successful identification to allow the target user to enter the target vehicle.

[0067] Specifically, in this embodiment of the invention, when the target vehicle arrives at the optimal pick-up point, the students may have already arrived, arrived at the same time, or are about to arrive. For example... Figure 6As shown, once a student is at the optimal boarding point, the target vehicle activates identification technologies (such as facial recognition, fingerprint recognition, RFID recognition, etc.) to detect the target user. After detecting the target user, the vehicle locks onto the user and performs identity verification. Only after successful identity verification can the vehicle door unlock, ensuring that the student is boarding the correct vehicle and that the vehicle is picking up the correct child.

[0068] Step S504: After the target user enters the target vehicle, the vehicle is driven based on the target location, and driving information and the target user's status information are obtained during the driving process. The driving information and status information are then sent to the second terminal device of the target user's guardian.

[0069] Specifically, in this embodiment of the invention, the target vehicle pre-stores the target location, i.e., the home address. If it is an autonomous driving system, after detecting a student entering the vehicle, the vehicle is locked and started, automatically planning a route and driving based on the target location. For example... Figure 6 As shown, during the driving process, cameras installed inside and outside the vehicle are used for full-process monitoring, collecting real-time driving information and the student's status information inside the vehicle. This information is then transmitted wirelessly to a backend server, and subsequently sent to the guardian's second terminal device. Parents can use a mobile app or other terminal devices to view their child's status and road conditions in real time, and understand the child's journey progress.

[0070] Step S505: After driving to the target location, acquire external environmental information and detect whether there is any danger information based on the external environmental information.

[0071] Specifically, in this embodiment of the invention, after the target vehicle travels to the target location corresponding to the home address, external environmental information is collected by calling the vehicle's external camera or on-board sensors, and the presence of dangerous information in the external environment is detected, such as whether there are dangerous objects or people around.

[0072] In step S506, if there is a danger message, the car door is locked and a safety warning message is issued, and the danger message is sent to the second terminal device.

[0073] Specifically, in this embodiment of the invention, if there is danger outside the vehicle, the doors are locked to prevent students from getting off, and a safety warning is broadcast through the vehicle's speakers to remind students of the danger and not to get off. If the danger disappears or is determined not to be dangerous, the doors are unlocked and students are reminded to get off. External scene information is continuously collected and assessed for any remaining danger as students get off. If danger is detected, a safety warning is broadcast through the external speakers to remind students to get off safely or go home as soon as possible. Simultaneously, the danger information is sent to the parents' mobile phones.

[0074] Step S507: Obtain the arrival information sent by the preset associated device and send the arrival information to the second terminal device.

[0075] Specifically, in this embodiment of the invention, the target vehicle is pre-associated with smart devices in the home, such as smart locks and cameras. After the student returns home, the smart lock and camera devices interact with the vehicle system to obtain the student's arrival information, such as receiving a "Student safely home" notification from the lock, thus confirming the child's return home point-to-point. Simultaneously, the arrival information is sent to the parent's terminal device, such as a mobile app, allowing the parent to receive a notification of their child's arrival, further ensuring the child's safety.

[0076] The intelligent pick-up and drop-off method provided by this invention obtains the driving route from the target vehicle after the pick-up and drop-off task is issued, and drives from a second location to the optimal pick-up point according to the driving route to execute the pick-up and drop-off task. After picking up the target user, the method starts full-process monitoring, including identity recognition, road condition information and target user status information collection, danger detection, and home arrival confirmation. This ensures that the target user can safely and conveniently return home from school, allows parents to know the target user's status and road conditions in real time, solves the core pain point of picking up children for dual-income families, builds a pick-up and drop-off ecosystem that is safe for students, reassuring for parents, and efficient in traffic, reduces the communication costs between parents and children, and reduces the distraction of parents' work energy.

[0077] Figure 7 The diagram shows a structural schematic of an embodiment of the cloud platform in the intelligent pick-up and drop-off system of the present invention. The specific embodiments of the present invention do not limit the specific implementation of the cloud platform.

[0078] like Figure 7 As shown, the cloud platform may include: a processor 702, a communications interface 704, a memory 706, and a communications bus 708.

[0079] The processor 702, communication interface 704, and memory 706 communicate with each other via communication bus 708. Communication interface 704 is used to communicate with other network elements such as clients or other servers. The processor 702 executes program 710, specifically performing the relevant steps described above in the embodiment of the intelligent pick-up and drop-off method.

[0080] Specifically, program 710 may include program code, which includes computer-executable instructions.

[0081] Processor 702 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention. The cloud platform includes one or more processors, which may be processors of the same type, such as one or more CPUs; or processors of different types, such as one or more CPUs and one or more ASICs.

[0082] Memory 706 is used to store program 710. Memory 706 may include high-speed RAM memory, and may also include non-volatile memory, such as at least one disk storage device.

[0083] Specifically, program 710 can be called by processor 702 to enable the cloud platform to perform the functions defined in the intelligent pick-up and drop-off method of this embodiment of the invention.

[0084] The algorithms or displays provided herein are not inherently related to any particular computer, virtual system, or other device. Furthermore, the embodiments of this invention are not directed to any particular programming language.

[0085] Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. Similarly, for the sake of brevity and to aid in understanding one or more aspects of the invention, in the description of exemplary embodiments of the invention above, various features of the embodiments are sometimes grouped together in a single embodiment, figure, or description thereof. The claims, which follow the detailed description, are hereby expressly incorporated into that detailed description, wherein each claim itself is a separate embodiment of the invention.

[0086] Those skilled in the art will understand that the modules in the device of the embodiment can be adaptively changed and placed in one or more devices different from that embodiment. Modules, units, or components in the embodiment can be combined into a single module, unit, or component, and further, they can be divided into multiple sub-modules, sub-units, or sub-components, except that at least some of such features and / or processes or units are mutually exclusive.

[0087] It should be noted that the above embodiments are illustrative of the invention and not restrictive, and that those skilled in the art can devise alternative embodiments without departing from the scope of the appended claims. In the claims, any reference signs placed between parentheses should not be construed as limiting the claims. The word "comprising" does not exclude the presence of elements or steps not listed in the claims. The word "a" or "an" preceding an element does not exclude the presence of a plurality of such elements. The invention can be implemented by means of hardware comprising several different elements and by means of a suitably programmed computer. In the unit claims enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names. The steps in the above embodiments, unless otherwise specified, should not be construed as limiting the order of execution.

Claims

1. An intelligent pick-up and drop-off method, applied to a cloud platform, characterized in that, The method includes: After receiving a pick-up request from the first terminal device of the target user, the system obtains the first location of the target user and the second location of the target vehicle, and obtains a set of safe pick-up points within a preset area where the first location is located. Determine the first time when the target user travels from the first location to each safe pick-up point in the set of safe pick-up points, and determine the second time when the target vehicle travels from the second location to the same safe pick-up point; Based on the first time and the second time corresponding to each of the safe boarding points, the optimal boarding point is determined from the set of safe boarding points; A walking route is generated based on the first location and the optimal pick-up point, and a driving route is generated based on the second location and the optimal pick-up point. The walking route is then sent to the first terminal device, and the driving route is sent to the target vehicle.

2. The method according to claim 1, characterized in that, Determining the first time the target user travels from the first location to each safe pick-up point in the set of safe pick-up points, and determining the second time the target vehicle travels from the second location to the same safe pick-up point, includes: Obtain the third position of each safe boarding point in the set of safe boarding points; For any of the safe boarding points, a walking route is planned based on the first location and the third location, and the first time is determined based on the walking route; For the same safe boarding point, a driving route is planned based on the second location and the third location, and the second time is determined based on the driving route.

3. The method according to claim 1, characterized in that, The step of determining the optimal boarding point from the set of safe boarding points based on the first time and the second time corresponding to each of the safe boarding points includes: Calculate the time difference between the first time and the second time corresponding to each of the safe boarding points; Sort all the safe boarding points by time difference from smallest to largest, and select the first preset number of safe boarding points as alternative boarding points; Determine the overall load rate of each of the candidate boarding points, and select the candidate boarding point with the lowest load rate as the optimal boarding point.

4. The method according to claim 3, characterized in that, Determining the overall load rate of each of the candidate boarding points includes: Obtain the number of available parking spaces and the number of parking spaces sought within the preset area corresponding to each of the candidate pick-up points, calculate the ratio of the number of parking spaces sought to the number of available parking spaces, and obtain the parking area load rate of the candidate pick-up point; Obtain the traffic flow and design capacity within the preset area, calculate the ratio of the traffic flow to the design capacity, and obtain the road network load rate of the candidate boarding point; The estimated parking duration of the alternative pick-up point is determined based on the first time and the second time, and the environmental compliance load rate of the alternative pick-up point is determined based on the estimated parking duration and the illegal parking rules of the preset area. Obtain the pedestrian flow and traffic capacity of the sidewalk within the preset area, calculate the ratio of pedestrian flow to traffic capacity, and obtain the sidewalk load rate of the candidate boarding point; The overall load rate of the candidate pick-up point is determined by weighted summation of the load rates of the parking area, the road network, the environmental compliance, and the sidewalk.

5. The method according to claim 1, characterized in that, The method further includes: If no safe pick-up point is set up within the preset area where the first location is located, a temporary pick-up point is generated based on the road condition information of the preset area, and the temporary pick-up point is used as the optimal pick-up point.

6. An intelligent pick-up and drop-off method, applied to a target vehicle, characterized in that, The target vehicle is pre-parked in a second location, and the method includes: Obtain the driving route; Drive from the second location to the optimal pick-up point according to the driving route.

7. The method according to claim 6, characterized in that, After traveling to the optimal pick-up point according to the stated driving route, the method further includes: The system identifies the target user and unlocks the car door upon successful identification, allowing the target user to enter the target vehicle. After the target user enters the target vehicle, the system drives based on the target location and acquires driving information and the target user's status information during the driving process. The driving information and the status information are then sent to the second terminal device of the target user's guardian.

8. The method according to claim 7, characterized in that, After reaching the target location, the method further includes: Acquire external environmental information and detect the presence of hazardous information based on the external environmental information; If the aforementioned danger information is present, the vehicle doors will be locked and a safety warning will be issued, and the danger information will be sent to the second terminal device.

9. The method according to claim 8, characterized in that, After the target user disembarks, the method further includes: Obtain the arrival information sent by the preset associated device and send the arrival information to the second terminal device.

10. An intelligent pick-up and drop-off system, characterized in that, include: The cloud platform, the first terminal device of the target user, the target vehicle, the second terminal device of the guardian of the target user, and the preset associated device are connected to the cloud platform, respectively, and the second terminal device and the preset associated device are connected to the target vehicle. The cloud platform includes a memory and a processor, which are interconnected. The memory stores computer instructions, and the processor executes the computer instructions to perform the intelligent pick-up and drop-off method according to any one of claims 1 to 5. The target vehicle is used to perform the intelligent pick-up and drop-off method according to any one of claims 6 to 9.

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