A method for urban logistics transportation based on the collaboration of drones and buses

Abstract

This invention relates to an urban logistics transportation method based on the collaboration between drones and buses. The purpose of this invention is to address the problems of short driving range and limited delivery area of ​​existing drones. In intra-city logistics transportation scenarios, a transportation mode based on the collaboration between drones and buses can be adopted. A drone takes off from a local logistics station carrying a package, delivers the package to the roof of a nearby bus, and the bus continues its route carrying the package. When it is about to reach the destination logistics station, a drone takes off from that station, retrieves the package from the bus roof, and transports it back to the destination logistics station. This collaborative transportation method can overcome the shortcomings of traditional drone transportation, significantly improve logistics transportation capacity by leveraging the advantages of the urban public transportation system, and also increase the economic benefits of public transportation companies, promoting their sustainable development. This invention is applicable to the field of intelligent logistics transportation.

Description

Technical Field

[0001] This invention belongs to the field of intelligent logistics transportation and relates to an urban logistics transportation method based on the collaboration of drones and buses. Background Technology

[0002] Ensuring the normal transportation and delivery of express parcels has become a significant challenge for logistics companies. Drones offer advantages such as high flight speed, low transportation costs, and flexible operation, and some logistics companies have begun exploring drone-based parcel delivery models. However, limited by battery capacity, small drones have short ranges and limited delivery areas; especially in urban areas, the significant noise from drones has also drawn criticism from residents.

[0003] In light of this, some studies have proposed logistics transportation methods based on the collaboration between drones and social vehicles or trucks to overcome the problem of short driving range of drones. However, on the one hand, social vehicles have their own planned travel routes, and if logistics companies cannot match suitable social vehicles, it will affect the efficiency of package transportation; on the other hand, the purchase cost of trucks is high, and most cities prohibit trucks from driving during the day, making it impossible to transport packages. Summary of the Invention

[0004] The purpose of this invention is to solve the problems of short driving range and limited delivery range of existing drones, and to propose an urban logistics transportation method based on the collaboration of drones and buses.

[0005] The specific process of an urban logistics transportation method based on the collaboration of drones and buses is as follows:

[0006] Step 1: Basic Data Survey; the specific process is as follows:

[0007] Step 1.1: Define a and b as logistics stations at both ends of the parcel transportation route, responsible for receiving and sending express parcels, updating parcel information within the stations, and replacing drone batteries;

[0008] Step 1.2: Select a bus route l between logistics stations a and b, define the direction of the bus from a to b as the upward direction and the direction of the bus from b to a as the downward direction, and select four bus stops on route l as the connection points for the coordinated transportation of packages by drones and buses.

[0009] The nearest upstream station to logistics station a is l1, and the nearest downstream station is l2;

[0010] The nearest upstream station to logistics station b is l3, and the nearest downstream station is l4;

[0011] The northbound bus services on route l are numbered s according to their departure order, where s = 1, 2, ..., S, and S is the number of northbound bus services on that day. The arrival times of the s-th bus at stops l1 and l3 in the northbound direction are T1 and T2, respectively. s T3 s ;

[0012] The southbound bus services on route l are numbered u according to their departure order, where u = 1, 2, ..., U, and U is the number of southbound bus services on that day. The arrival times of the u-th bus at stops l2 and l4 in the southbound direction are T2 and T4, respectively. u T4 u ;

[0013] Step 2: Divide the daily operating hours of the logistics station;

[0014] Step 3: Let T' = T + Δt, where T' is the time point for the next decision, T is the current decision time, and Δt is the time unit;

[0015] Determine whether the current decision time T satisfies the condition T≤T end If yes, proceed to step 4; otherwise, execute step 11.

[0016] Where T end To indicate the end time of the day's operations;

[0017] Step 4: Determine the status of the drone group, the delivery package, the upbound bus, and the downbound bus;

[0018] Step 5: Based on Step 4, perform state division and proceed to Step 6, Step 7, Step 8, and Step 9 respectively;

[0019] Step 6: Decision on retrieving the package, determining whether to proceed to step 9;

[0020] Step 7: Delivery task decision, determine whether to proceed to step 9;

[0021] Step 8: Decision-making for the "deliver first, pick up later" task, determining whether to proceed to Step 9;

[0022] Step 9: No decision is needed, and the current decision time T is updated. Proceed to Step 10.

[0023] Step 10: Determine whether T = T' is satisfied, where T' is the time point for the next decision. If satisfied, return to step 3; otherwise, return to step 9.

[0024] Step 11: When the end of the operation is reached, the logistics station will stop releasing drones to perform express delivery tasks. The operation will end for the day after all drones have been retrieved.

[0025] The beneficial effects of this invention are as follows:

[0026] In intra-city logistics transportation scenarios, a transportation model based on drone and bus collaboration can be adopted. A drone takes off from the local logistics station carrying packages, delivers the packages to the roof of a nearby bus, and the bus continues its route carrying the packages. When it is about to reach the destination logistics station, a drone takes off from that station, retrieves the packages from the bus roof, and transports them back to the destination logistics station. This collaborative transportation method can overcome the shortcomings of traditional drone transportation, significantly improve logistics transportation capacity by leveraging the advantages of the urban public transportation system, and also increase the economic benefits of public transportation companies, promoting their sustainable development.

[0027] This invention shortens the flight time and transport distance of drones, reduces noise pollution, and lowers express delivery costs.

[0028] This invention leverages the advantages of a dense public transportation network and strong transport capacity to achieve rapid transportation of express parcels within urban areas, thereby improving logistics and transportation capabilities.

[0029] Public transportation companies can charge transportation fees to logistics companies to increase their own revenue. Attached Figure Description

[0030] Figure 1 A schematic diagram of a logistics transportation network that integrates buses and drones;

[0031] Figure 2 A flowchart illustrating the urban logistics transportation process involving drones and buses (taking logistics station a as an example). Detailed Implementation

[0032] Specific Implementation Method 1: The specific process of this implementation method for urban logistics transportation based on the collaboration between drones and buses is as follows:

[0033] Step 1: Basic Data Survey; the specific process is as follows:

[0034] Step 1.1: Define a and b as logistics stations at both ends of the parcel transportation route, responsible for receiving and sending express parcels, updating parcel information within the stations, replacing drone batteries, etc.

[0035] This invention enables two-way logistics transportation between logistics stations a and b through the coordinated use of drones and buses, such as... Figure 1 As shown.

[0036] Step 1.2: Select a bus route l between logistics stations a and b, define the direction of the bus from a to b as the upward direction and the direction of the bus from b to a as the downward direction, and select four bus stops on route l as the connection points for the coordinated transportation of packages by drones and buses.

[0037] The nearest upstream station to logistics station a is l1, and the nearest downstream station is l2;

[0038] The nearest upstream station to logistics station b is l3, and the nearest downstream station is l4;

[0039] The northbound bus services on route l are numbered s according to their departure order, where s = 1, 2, ..., S, and S is the number of northbound bus services on that day. The arrival times of the s-th bus at stops l1 and l3 in the northbound direction are T1 and T2, respectively. s T3 s ;

[0040] The southbound bus services on route l are numbered u according to their departure order, where u = 1, 2, ..., U, and U is the number of southbound bus services on that day. The arrival times of the u-th bus at stops l2 and l4 in the southbound direction are T2 and T4, respectively. u T4 u ;

[0041] This invention takes logistics station a as an example to illustrate the specific implementation steps of the collaborative logistics transportation method; the collaborative logistics transportation method for logistics station b is similar.

[0042] Step 2: Divide the daily operating hours of the logistics station;

[0043] Step 3: Let T' = T + Δt, where T' is the time point for the next decision, T is the current decision time, and Δt is the time unit;

[0044] Determine whether the current decision time T satisfies the condition T≤T end If yes, proceed to step 4; otherwise, execute step 11.

[0045] Where T end To indicate the end time of the day's operations;

[0046] The system is a computer, and the decision-making process is completed within the computer.

[0047] Step 4: Determine the status of the drone group, the delivery package, the upbound bus, and the downbound bus;

[0048] Step 5: Based on Step 4, perform state division and proceed to Step 6, Step 7, Step 8, and Step 9 respectively;

[0049] Step 6: Decision on retrieving the package, determining whether to proceed to step 9;

[0050] Step 7: Delivery task decision, determine whether to proceed to step 9;

[0051] Step 8: Decision-making for the "deliver first, pick up later" task, determining whether to proceed to Step 9;

[0052] Step 9: No decision is needed, and the current decision time T is updated. Proceed to Step 10.

[0053] Step 10: Determine whether T = T' is satisfied, where T' is the time point for the next decision. If satisfied, return to step 3; otherwise, return to step 9.

[0054] Step 11: When the end of the operation is reached, the logistics station will stop releasing drones to perform express delivery tasks. The operation will end for the day after all drones have been retrieved.

[0055] Specific Implementation Method Two: This implementation method differs from Specific Implementation Method One in that step 2 divides the daily operating hours of the logistics station; the specific process is as follows:

[0056] The daily operating time of the logistics station is divided into units of time, with Δt as the unit of time; it is recommended that Δt be 2 (min).

[0057] The system makes decisions only at the beginning of each time unit;

[0058] Let T represent the current decision-making moment, T end It indicates the end of the day's operations.

[0059] The other steps and parameters are the same as in Specific Implementation Method 1.

[0060] Specific Implementation Method Three: This implementation method differs from Specific Implementation Method One or Two in that step 4 involves determining the status of the unmanned aerial vehicle (UAV) group; the specific process is as follows:

[0061] Calculate the set of unmanned aerial vehicle groups F that can be used for the current decision T. T F T [k] represents the set of unmanned aerial vehicles (UAVs) F. T The kth drone in the middle;

[0062] If there are drones available for use, i.e., F T If the value is not equal to φ, then the drones available for use at the current decision T logistics station will be sorted in descending order according to their remaining battery power. E represents the current remaining battery power of the k-th drone, in kWh. rated The rated capacity of the battery for each drone is given in kWh.

[0063] Other steps and parameters are the same as in specific implementation method one or two.

[0064] Specific Implementation Method Four: This implementation method differs from Specific Implementation Methods One to Three in that step 4 involves determining the status of the delivery package; the specific process is as follows:

[0065] Define set P T Let P be the set of packages that need to be delivered in the current decision T. T [i] represents set P T The i-th package, Describe set P T The weight of the i-th package, in kg;

[0066] If there are currently packages that need to be delivered, i.e., P T If ≠φ, then group them:

[0067] (1) Since a drone can carry multiple packages at a time, in order to make full use of the drone's carrying capacity, the packages to be delivered are freely combined in the current decision T. All combinations within the drone's maximum load capacity Q are selected, and a set D is defined. T Let D be the set of current decision package combinations T (all combinations within the maximum payload Q limit of the drone). T [j] represents set D T The j-th combination;

[0068] (2) Calculate the weighted waiting time for each package combination. As shown in equation (1), the package group set D is sorted according to the weighted waiting time from largest to smallest. T Sort;

[0069]

[0070] in, The weighted waiting time for the j-th package combination is expressed in seconds. This represents the number of packages in the j-th package combination; This represents the time when the m-th package in the j-th package combination arrives at logistics station a.

[0071] The other steps and parameters are the same as those in one of the specific implementation methods one to three.

[0072] Specific Implementation Method Five: This implementation method differs from Specific Implementation Methods One to Four in that step 4 involves determining the upward bus status; the specific process is as follows:

[0073] Determine whether, at the current decision time T, an uphill bus with a drone capable of delivering the package arrives, i.e., whether the following conditions are met.

[0074]

[0075] Where time t(a) x ,l 1x The result is obtained from equation (2):

[0076]

[0077] In the formula: a x Location of logistics station a; l 1x The location of bus stop l1 (upbound); t(a x ,l 1x The time taken for the drone to fly from logistics station a to bus stop l1 is in seconds. T1 is the maximum hovering time of a drone before a bus at the station, measured in seconds. s The time when the northbound bus arrives at station l1; r(a x ,l 1x ) represents the distance between logistics station a and bus stop l1, in meters; v represents the flight speed of the drone, in meters per second.

[0078] The other steps and parameters are the same as those in one of the specific implementation methods one to four.

[0079] Specific Implementation Method Six: This implementation method differs from Specific Implementation Methods One to Five in that step 4 involves determining the downstream bus status; the specific process is as follows:

[0080] Determine at time T whether a downstream bus arrives with a drone capable of retrieving the package, i.e., whether the condition is met.

[0081]

[0082] Where time t(a) x ,l 2x The result is obtained from equation (3):

[0083]

[0084] In the formula a x Location of logistics station a; l 2x The location of bus stop l2 on the downhill route; t(a x ,l 2x The time taken for the drone to fly from logistics station a to bus stop l2 is in seconds. The maximum hovering time of a drone before a bus at the station, measured in seconds; The time when the downstream bus arrives at station l2; r(a x ,l 2x ) represents the distance between logistics station a and bus stop l2, in meters.

[0085] The other steps and parameters are the same as those in one of the specific implementation methods one to five.

[0086] Specific Implementation Method Seven: This implementation method differs from Specific Implementation Methods One to Six in that, in step 5, the state is divided based on step 4, and then proceeds to steps 6, 7, 8, and 9 respectively; the specific process is as follows:

[0087] Step 5.1: When the system status displays UAV group F T =φ, meaning if there are no available drones, proceed to step 9;

[0088] Step 5.2: Proceed to Step 9 if any of the following three conditions occur:

[0089] (1) When the system status displays the unmanned aerial vehicle group F T ≠φ, Package P for delivery T =φ, the upward bus does not meet the requirements. Downstream bus does not meet the requirements This means that there are currently drones available for deployment, but there are no packages to be delivered, no buses going up to pick them up, and no buses going down to pick them up;

[0090] (2) When the system status displays the unmanned aerial vehicle group F T ≠φ, Package P for delivery T =φ, the upward bus satisfies Downstream bus service not meeting requirements This means that there are currently drones available for deployment and buses going uphill that can carry passengers, but there are no packages to be delivered and no buses going downhill have arrived.

[0091] (3) When the system status displays the unmanned aerial vehicle group F T ≠φ, Package P for delivery T ≠φ, upward-bound bus does not meet the requirements Downstream bus service not meeting requirements This means that there are currently drones available for dispatch and packages that need to be delivered, but there are no buses going up to pick them up, nor are there any buses going down to pick them up;

[0092] Step 5.3: Proceed to Step 6 if any of the following three conditions are met:

[0093] (1) When the system status displays the unmanned aerial vehicle group F T ≠φ, Package P for delivery T =φ, the upward bus does not meet the requirements. Downward bus service meets This means that there are currently drones available and a downbound bus has arrived, but there are no packages to be delivered and no upbound bus to pick them up;

[0094] (2) When the system status displays the unmanned aerial vehicle group F T ≠φ, Package P for delivery T =φ, the upward bus satisfies T+t(ax ,l 1x )+t h max ≤T1 s Downward bus service meets That is, there are currently drones available for deployment, and there are buses going up and down to pick them up, but there are no packages to be delivered;

[0095] (3) When the system status displays the unmanned aerial vehicle group F T ≠φ, Package P for delivery T ≠φ, upward-bound bus does not meet the requirements Downward bus service meets That is, there are currently drones available for use, and there are packages that need to be delivered, and there are also downbound buses that have arrived, but there are no upbound buses available to pick them up;

[0096] Step 5.4: When the system status displays UAV group F T ≠φ, Package P for delivery T ≠φ and the upward bus meets the requirements Downstream bus service not meeting requirements If there is a drone available for dispatch, and there are packages to be delivered, and there is also an upbound bus that can pick up the package, but no downbound bus has arrived, proceed to step 7.

[0097] Step 5.5: When the system status displays UAV group F T ≠φ, Package P for delivery T ≠φ and the upward bus meets the requirements Downward bus also meets If there are available drones, packages to be delivered, and buses going up and down to pick them up, proceed to step 8.

[0098] The other steps and parameters are the same as those in one of the specific implementation methods one to six.

[0099] Specific Implementation Method Eight: This implementation method differs from Specific Implementation Methods One to Seven in that the package retrieval task decision is made in step 6; the specific process is as follows:

[0100] Step 6.1: Determine whether the downstream bus is carrying the package group r (r = 1, 2, ..., R) that needs to be retrieved. If so, proceed to step 6.2; otherwise, proceed to step 9.

[0101] Step 6.2: Calculate the power E consumed by the drone in performing the retrieval mission. r (kWh):

[0102] E r =[2(θQ dr +η)+θQ r ]·t(ax ,l 2x ) / 3600+(θQ dr +η)·t h / 3600 (4)

[0103] In the formula: Q dr Q is the sum of the weight of the drone's fuselage and battery, expressed in kg. r This indicates the weight of the package group r being transported, in kg; t(a x ,l 2x ) represents the flight time of the drone from the logistics station to the bus stop, and the return time t(l) represents the time taken to return from the logistics station to the bus stop. 2x ,a x (The flight time of the drone from the bus stop to the logistics station) is the same, in seconds; θ is the power consumed per unit weight, in kW; η is the power required for the drone to hover, in kW; · is a multiplication sign, t h This indicates the time (in seconds) during which the drone waits for the bus to arrive at the bus stop.

[0104] Step 6.3: Determine the drone group set F T The first drone F in the middle T [1] Electricity E FT[1] Is the power supply sufficient to meet the power consumption required to perform the retrieval task?

[0105] If satisfied, then call drone F. T [1] Take off at the current decision time T to retrieve package group r, and proceed to step 9;

[0106] Otherwise, replace the battery and take off; at this time, the drone F T [1] indicates a fully charged state, i.e. Proceed to step 9.

[0107] The other steps and parameters are the same as those in any of the specific implementation methods one to seven.

[0108] Specific Implementation Method Nine: This implementation method differs from Specific Implementation Methods One to Eight in that the delivery task decision is made in step 7; the specific process is as follows:

[0109] Step 7.1: Select package group set D T The combination with the longest weighted waiting time, D T [1] Perform delivery and determine the delivery status of package group D by drone. T [1] Maximum waiting time Does the package r need to be retrieved within the specified time frame? In other words, does it meet the requirements? If a package group is retrieved within the maximum waiting time, proceed to step 7.2; otherwise, proceed to step 7.3.

[0110] Step 7.2: Calculate the first delivery group D of packages by drone. T [1] Retrieve the power consumed by package group r:

[0111]

[0112] In the formula: t(l 1x ,l 2x The drone was launched from the upstream bus stop. 1x Fly to the downbound bus stop 2x The time consumed is measured in seconds (s); t w Indicates that the drone is at the downlink station l 2x The waiting time for the bus to arrive is measured in seconds (s); Q DT[1] Describes set D T The weight of the first package group, in kg;

[0113] Step 7.3: Calculate the power consumption of the drone during the delivery mission. 2x :

[0114]

[0115] In the formula: This indicates the weight of the package group being transported, in kg; t(a x ,l 1x ) represents the flight time of the drone from the logistics station to the bus stop, and the return time t(l) represents the time taken to return from the logistics station to the bus stop. 1x ,a x The same applies, but the unit is seconds (s).

[0116] Step 7.4: Determine set F T The first drone F in the middle T [1] Electricity E F[1] Whether it can meet the power consumption required to perform the task;

[0117] If satisfied, then call drone F. T [1] Departure and delivery are initiated at the current decision time T, proceeding to step 9;

[0118] Otherwise, take off after replacing the battery; at this time, the drone F T [1] indicates a fully charged state, i.e. Proceed to step 9.

[0119] The other steps and parameters are the same as those in one of the specific implementation methods one to eight.

[0120] Specific Implementation Method Ten: This implementation method differs from Specific Implementation Methods One to Nine in that the task decision of sending before retrieving is made in step 8; the specific process is as follows:

[0121] Step 8.1: Determine whether the downstream bus is carrying the package group r (r = 1, 2, ..., R) that needs to be retrieved. If so, proceed to step 8.2; otherwise, proceed to step 8.5.

[0122] Step 8.2: Determine the package group D that the drone will need to deliver. T [1] Whether the package can be caught by the oncoming or offcoming bus and retrieved after being placed on the upbound bus, i.e., whether it satisfies the following conditions: If the condition is met, proceed to step 8.3; otherwise, proceed to step 8.4.

[0123] Step 8.3: Calculate the first delivery group D of the drone using formula (5). T [1] Retrieve the power consumed by package group r;

[0124] Judgment set F T The first drone F in the middle T [1] Drone battery power Whether it can meet the power consumption required to perform the delivery-then-reply task;

[0125] If the conditions are met, then the first drone F is invoked. T [1] Take off and retrieve at the current decision time T, then proceed to step 9;

[0126] Otherwise, take off after replacing the battery, at which point the drone will be fully charged. Proceed to step 9;

[0127] Step 8.4: Calculate the power consumption of the UAV in performing the retrieval mission using formula (4), and call set F. T The first drone F in the middle T [1] Determine the battery level E of the first drone. F[1] Is the power supply sufficient to meet the power consumption required to perform the retrieval task?

[0128] If the conditions are met, then the first drone F is invoked. T [1] Take off to retrieve package group r at the current decision T, and proceed to step 8.5;

[0129] Otherwise, take off after replacing the battery. At this point, the drone will be fully charged. Proceed to step 8.5;

[0130] Step 8.5: Determine if there are any drones available for use in the drone group. If so, return to step 7; otherwise, proceed to step 9.

[0131] The other steps and parameters are the same as those in any of the specific implementation methods one to nine.

[0132] This invention may have other embodiments. Without departing from the spirit and essence of this invention, those skilled in the art can make various corresponding changes and modifications according to this invention, but these corresponding changes and modifications should all fall within the protection scope of the appended claims.

Claims

1. A method for urban logistics transportation based on the collaboration of unmanned aerial vehicles (UAVs) and buses, characterized in that: The specific process of the method is as follows: Step 1: Basic Data Survey; Step 2: Divide the daily operating hours of the logistics station; Step 3: Let , This will be the point in time for the next decision. For the current decision-making moment, For time units; Determine whether the current decision time T satisfies the condition. If yes, proceed to step 4; otherwise, execute step 11. in To indicate the end time of the day's operations; Step 4: Determine the status of the drone group, the delivery package, the upbound bus, and the downbound bus; Step 5: Based on Step 4, perform state division and proceed to Step 6, Step 7, Step 8, and Step 9 respectively; Step 6: Decision on retrieving the package, determining whether to proceed to step 9; Step 7: Delivery task decision, determine whether to proceed to step 9; Step 8: Decision-making for the "deliver first, pick up later" task, determining whether to proceed to Step 9; Step 9: No decision is needed, and the current decision time T is updated. Proceed to Step 10. Step 10: Determine if the condition is met. , This is the time point for the next decision. If the condition is met, return to step 3; otherwise, return to step 9. Step 11: When the end of the operation is reached, the logistics station will stop releasing drones to perform express delivery tasks. The operation will end for the day after all drones have been retrieved. In step 4, the status of the delivery package is determined; The specific process is as follows: Define a set Let T be the set of packages that need to be delivered in the current decision. Represents a set The i-th package, Represents a set The weight of the i-th package, in kg; If there are packages that need to be delivered at present, that is Then group them: (1) In the current decision The packages to be delivered can be freely combined, and those within the maximum payload capacity of the drone can be selected. Define a set of all combinations within the constraints. Let T be the set of combinations of the current decision. Represents a set The Middle A combination; (2) Calculate the weighted waiting time for each package combination. As shown in equation (1), the package groups are sorted in descending order of weighted waiting time. Sort; （1） in, The weighted waiting time for the j-th package combination is expressed in seconds. This represents the number of packages in the j-th package combination; This represents the time when the m-th package in the j-th package combination arrives at logistics station a; Step 4 involves determining the status of the upward-bound bus; the specific process is as follows: Judgment at the current decision moment Is there an upbound bus service where drones can deliver packages, i.e., does it meet the requirements? ; Among them time Calculated from equation (2): （2） In the formula: For logistics stations Location; For the upbound bus stop Location; For drones from logistics stations Fly to the bus stop The sailing time, in seconds; The maximum hovering time of a drone before a bus at the station, measured in seconds; For the bus arrival station in the northbound direction The moment; For logistics stations with bus stops The distance between them, in meters; The speed of the drone is expressed in m / s. In step 4, the status of the downstream bus is determined; The specific process is as follows: Judgment at time Is there a downstream bus that can be used to retrieve the package by drone? Does this meet the requirements? ; Among them time Calculated from equation (3): （3） In the formula For logistics stations Location; For southbound bus stops Location; For drones from logistics stations Fly to the bus stop The sailing time, in seconds; The maximum hovering time of a drone before a bus at the station, measured in seconds; For the destination of the downbound bus The moment; For logistics stations with bus stops The distance between them, in meters.

2. The urban logistics transportation method based on the collaboration of unmanned aerial vehicles and buses according to claim 1, characterized in that: The basic data survey in step 1; The specific process is as follows: Step 1.1: Definition , These are logistics stations at both ends of the parcel transportation route, responsible for receiving and sending express parcels, updating parcel information within the stations, and replacing drone batteries. Step 1.2: Select a logistics station , A bus route between The regulations stipulate that arrive For the direction of bus travel upwards, from arrive For the southbound direction of the bus, select the route. The four bus stops above serve as connection points for the collaborative transportation of packages between drones and public buses; With logistics stations The nearest station in the up direction is The stations in the down direction are ; With logistics stations The nearest station in the up direction is The stations in the down direction are ; According to the departure order, the routes are arranged... The northbound bus routes are numbered as follows , s=1,2,...S If the number of northbound bus trips on that day is [number], then the [number]th ... Bus routes arrive at the stops in the direction of travel. , The times are respectively , ; According to the departure order, the routes are arranged... The outbound bus routes are numbered as follows , , If the number of southbound bus trips on that day is [number], then the [number]th ... Buses arrive at stops in the southbound direction , The times are respectively , .

3. The urban logistics transportation method based on the collaboration between unmanned aerial vehicles and buses according to claim 2, characterized in that: Step 2 involves dividing the daily operating hours of the logistics station; the specific process is as follows: by The daily operating hours of the logistics station are divided into time units; The system makes decisions only at the beginning of each time unit; Let T represent the current decision-making moment. It indicates the end of the day's operations.

4. The urban logistics transportation method based on the collaboration between unmanned aerial vehicles and buses according to claim 3, characterized in that: Step 4 involves determining the status of the unmanned aerial vehicle (UAV) group; the specific process is as follows: Statistics on current decisions Available drone group collection ,in Represents a group of drones The kth drone in the middle; If there are drones available for use, that is Then, the current decision will be based on the current remaining battery power. The drones available for use at the logistics station are sorted in descending order. This indicates the current remaining battery power of the k-th drone, in kWh. The rated capacity of the battery for each drone is given in kWh.

5. A method for urban logistics transportation based on the collaboration of unmanned aerial vehicles and buses according to claim 4, characterized in that: In step 5, the state is divided based on step 4, and then proceeds to steps 6, 7, 8, and 9 respectively; the specific process is as follows: Step 5.1: When the system status displays the drone group If there are no available drones, proceed to step 9. Step 5.2: Proceed to Step 9 if any of the following three conditions occur: (1) When the system status displays the drone group Package delivery collection Upward-bound buses do not meet the requirements Downstream buses do not meet the requirements This means that there are drones available for deployment, but there are no packages to be delivered, no buses going up to pick them up, and no buses going down to pick them up. (2) When the system status displays the drone group Package delivery collection Upward bus meets Downstream buses do not meet the requirements This means that there are currently drones available for deployment and buses going uphill that can pick them up, but there are no packages to be delivered and no buses going downhill have arrived. (3) When the system status displays the drone group Package delivery collection Upward-bound buses do not meet the requirements Downstream buses do not meet the requirements This means that there are drones available for use and packages that need to be delivered, but there are no buses going up to pick them up or buses going down to pick them up. Step 5.3: Proceed to Step 6 if any of the following three conditions are met: (1) When the system status displays the drone group Package delivery collection Upward-bound buses do not meet the requirements Downward bus service meets This means that there are currently drones available and a downbound bus has arrived, but there are no packages to be delivered and no upbound bus to pick them up; (2) When the system status displays the drone group Package delivery collection Upward bus meets Downward bus service meets This means that there are currently drones available for deployment, and there are buses going up and down to pick them up, but there are no packages to be delivered. (3) When the system status displays the drone group Package delivery collection Upward-bound buses do not meet the requirements Downward bus service meets This means that there are currently drones available for deployment, packages that need to be delivered, and downbound buses that have arrived, but there are no upbound buses available to pick up passengers. Step 5.4: When the system status displays the drone group Package delivery collection And the upward bus meets the requirements. Downstream buses do not meet the requirements If there is a drone available for use, and there are packages to be delivered, and there is also an upbound bus that can pick up the package, but no downbound bus has arrived, proceed to step 7. Step 5.5: When the system status displays the drone group Package delivery collection And the upward bus meets the requirements. The southbound bus also meets the requirements. If there are available drones, packages to be delivered, and buses going up and down to pick them up, then proceed to step 8.

6. A method for urban logistics transportation based on the collaboration of unmanned aerial vehicles and buses according to claim 5, characterized in that: The package retrieval task decision in step 6 is as follows: Step 6.1: Determine whether the outgoing bus is carrying the package group r (r=1, 2,…, R) that needs to be retrieved. If so, proceed to step 6.2; otherwise, proceed to step 9. Step 6.2: Calculate the power consumed by the drone in performing the retrieval mission. (kWh): （4） In the formula: This is the sum of the weight of the drone's fuselage and battery, expressed in kg. This indicates the weight of the package group r being transported, in kg. This refers to the flight time of the drone from the logistics station to the bus stop, and the return time. Similarly, the unit is seconds (s). Power consumed per unit weight, measured in kW; The power required to keep a drone hovering, measured in kW; It is a multiplication sign. This indicates the time (in seconds) during which the drone waits for the bus to arrive at the bus stop. Step 6.3: Determine the drone group set The first drone in China Battery life Is the power supply sufficient to meet the power consumption required to perform the retrieval task? If the conditions are met, then the drone will be deployed. At this moment of decision-making Take off and retrieve package group r, proceed to step 9; Otherwise, replace the battery and take off; at this time, the drone It is fully charged, that is Proceed to step 9.

7. A method for urban logistics transportation based on the collaboration of unmanned aerial vehicles and buses according to claim 6, characterized in that: The delivery task decision-making process in step 7 is as follows: Step 7.1: Select package group collection The combination with the longest weighted waiting time To carry out delivery and determine the location of the drone delivery package group. Maximum waiting time after (s) Whether the package r that needs to be retrieved arrives within s, i.e., whether the condition is met. If a package group is retrieved within the maximum waiting time, proceed to step 7.

2. Otherwise proceed to step 7.3; Step 7.2: Calculate the drone delivery package group The power consumed by retrieving package group r: （5） In the formula: For drones from the upbound bus stop Fly to the downbound bus stop The time taken is measured in seconds (s). Indicates the drone at the downlink station The waiting time for the bus to arrive is measured in seconds (s). Describes set D T The weight of the first package group, in kg; Step 7.3: Calculate the power consumption of the drone during the delivery mission. : （6） In the formula: This indicates the weight of the package group being transported, in kg. This refers to the flight time of the drone from the logistics station to the bus stop, and the return time. Similarly, the unit is seconds (s). Step 7.4: Determine the set The first drone in China Battery life Whether it can meet the power consumption required to perform the task; If the conditions are met, then the drone will be deployed. At this moment of decision-making Delivery has commenced; proceed to step 9. Otherwise, take off after replacing the battery; at this time, the drone It is fully charged, that is Proceed to step 9.

8. A method for urban logistics transportation based on the collaboration of unmanned aerial vehicles and buses according to claim 7, characterized in that: The task decision-making process in step 8, which involves sending before retrieving, is as follows: Step 8.1: Determine whether the outbound bus is carrying the package group r (r=1,2,…,R) that needs to be retrieved. If so, proceed to step 8.2; otherwise, proceed to step 8.

5. Step 8.2: Determine the group of packages that the drone will need to deliver. Whether the package can be retrieved after being placed on the upward-bound bus and caught by the downward-bound bus (r), i.e., whether the condition is met. If the condition is met, proceed to step 8.3; otherwise, proceed to step 8.

4. Step 8.3: Calculate the first batch of packages to be delivered by the drone using formula (5). Retrieve the power consumed by package group r; Determine Set The first drone in China Drone battery Whether it can meet the power consumption required to perform the delivery-then-reply task; If the conditions are met, then the first drone will be invoked. At this moment of decision-making Take off and retrieve; proceed to step 9. Otherwise, take off after replacing the battery, at which point the drone will be fully charged. Proceed to step 9; Step 8.4: Calculate the power consumption of the UAV in performing the retrieval task using formula (4), and call the set The first drone in China Determine the battery level of the first drone. Is the power supply sufficient to meet the power consumption required to perform the retrieval task? If the conditions are met, then the first drone will be invoked. In the current decision Take off and retrieve package group r, proceed to step 8.5; Otherwise, take off after replacing the battery. At this point, the drone will be fully charged. Proceed to step 8.5; Step 8.5: Determine if there are any drones available for use in the drone group. If so, return to step 7; otherwise, proceed to step 9.

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