Electric logistics distribution vehicle path planning method considering vehicle load

Abstract

The invention discloses an electric logistics distribution vehicle path planning method considering vehicle load, and relates to the field of logistics distribution, and the method comprises the steps: constructing a three-dimensional space-time state network according to the position information of a distribution center and a plurality of clients, and the weight of delivered goods, the weight of delivered goods and the distribution time of each client; according to the three-dimensional space-time state network, calculating the distance between the distribution center and the adjacent customer around the distribution center and the distance between the customer and other adjacent customers around the customer; calculating a priority score and a target function value corresponding to each customer, and determining a final planning route by meeting constraint conditions; according to the method, a mode of combining distribution with sending and taking is adopted during path planning, and the vehicle load, the energy consumption characteristic and the dynamic change of the road environment are considered.

Description

Technical Field

[0001] The present invention relates to the technical field of logistics distribution, and particularly relates to a path planning method for an electric logistics distribution vehicle considering vehicle load. Background Art

[0002] In the field of logistics distribution, electric logistics distribution vehicles have become an important choice for urban logistics distribution due to their significant advantages such as low energy consumption and zero emissions. Since the driving range of electric logistics distribution vehicles is limited, it is necessary to plan the path in advance and arrange charging when necessary, which poses many challenges for electric logistics distribution vehicles during distribution.

[0003] In the actual scenario of urban logistics distribution, the vehicle load is not constant but changes dynamically with the passage of time; at the same time, compared with single delivery services, the combined mode of delivery and pick-up and drop-off better meets the actual needs. In related technologies, most vehicle path problems mainly focus on the situation where the vehicle load is constant and only delivery services are provided, and most logistics distribution path planning methods focus on the shortest path or fixed delivery order, and rarely consider the cargo volume of delivery customer points and the energy consumption characteristics of vehicles during the planning process, or in urban terminal distribution, only factors such as road distance or traffic flow are taken into account, and the dynamic changes of vehicle load, energy consumption characteristics, and road environment are not fully combined to optimize the distribution path.

[0004] Therefore, there is an urgent need for a path planning method for an electric logistics distribution vehicle that has a combined mode of delivery and pick-up and drop-off and takes into account the dynamic changes of vehicle load, energy consumption characteristics, and road environment. Summary of the Invention

[0005] In view of this, the present invention provides a path planning method for an electric logistics distribution vehicle considering vehicle load to solve the technical problems existing in related technologies.

[0006] The present invention provides a path planning method for an electric logistics distribution vehicle considering vehicle load, including:

[0007] S1. Obtain the location information of the distribution center and multiple customers, as well as the weight of the goods sent out, the weight of the goods to be delivered, and the delivery time of each customer;

[0008] S2. Construct a three-dimensional spatio-temporal state network according to the location information of the distribution center and multiple customers, as well as the weight of the goods sent out, the weight of the goods to be delivered, and the delivery time of each customer; the three-dimensional spatio-temporal state network includes a set of spatio-temporal state nodes and a set of spatio-temporal state arcs;

[0009] S3. Calculate the distances between the distribution center and the customers adjacent to the distribution center, and the distances between customers and other customers adjacent to the customers according to the three-dimensional spatio-temporal state network;

[0010] S4. Calculate the priority score of the electric logistics delivery vehicle when it departs from the distribution center and reaches each customer according to the distances between the distribution center and the customers adjacent to it, the distances between customers and other customers adjacent to them, the weight of the goods sent by each customer, and the weight of the goods to be delivered.

[0011] S5. Take the first target customer with the highest priority score and meeting the constraint conditions as the customer in the first delivery order, and calculate the objective function when the electric logistics delivery vehicle departs from the distribution center and reaches the first target customer.

[0012] S6. Calculate the priority score of the electric logistics delivery vehicle when it departs from the first target customer and reaches all other customers except the first target customer according to the distances between the distribution center and the customers adjacent to it, the distances between customers and other customers adjacent to them, the weight of the goods sent by each customer, and the weight of the goods to be delivered.

[0013] S7. Take the second target customer with the highest priority score and meeting the constraint conditions as the customer in the second delivery order, and calculate the objective function when the electric logistics delivery vehicle departs from the first target customer and reaches the second target customer.

[0014] S8. Repeat steps S6 - S7 until finally obtaining the delivery order of the electric logistics delivery vehicle when it departs from the distribution center and reaches each customer in turn, as well as the multi - segment objective function when it departs from the distribution center and reaches each customer in turn.

[0015] S9. Add up the multi - segment objective function values to obtain the total objective function value; when the total objective function value is less than the first preset value, plan the delivery route according to the current delivery order.

[0016] In an alternative embodiment, after S9, the method further includes:

[0017] S10. Calculate the total delivery energy consumption according to the delivery route.

[0018] The calculation process of the total delivery energy consumption is as follows:

[0019] S101. Calculate the traction force F of the electric logistics delivery vehicle in the driving state w :

[0020]

[0021] where F rol is the rolling resistance of the vehicle during driving, F air is the aerodynamic resistance of the vehicle during driving, F slois the slope resistance during vehicle driving, M is the total vehicle weight, M = m + μ, where m is the net vehicle weight, μ is the weight of the goods on the vehicle, a is the acceleration of vehicle driving, ρ a is the air density at the vehicle's location, A f is the cross-sectional area of the vehicle facing the wind, C D is the aerodynamic drag coefficient, v is the vehicle driving speed, g is the acceleration due to gravity, f is the sliding friction coefficient, and θ is the road slope;

[0022] S102. Calculate the total distribution energy consumption E of the electric logistics delivery vehicle according to the traction force F w during the driving of the electric logistics delivery vehicle:

[0023]

[0024] where ε is the vehicle transmission system efficiency, E a is the battery energy consumption consumed by vehicle accessories, E w is the battery energy consumption consumed by the vehicle during driving, v is the vehicle driving speed, and t is the vehicle driving time; P a is the instantaneous power consumed by vehicle accessories;

[0025] S103. According to the traction force F w of the electric logistics delivery vehicle in the state of uniform driving on a horizontal road surface, the total distribution energy consumption E of the electric logistics delivery vehicle is further expressed as:

[0026] E = α + βM

[0027]

[0028] In an alternative embodiment, S1 includes:

[0029] S11. In response to distribution requests from multiple customers, obtain the order logistics information corresponding to each customer; the order logistics information includes: the location information of the distribution center and the customer, as well as the weight of the goods sent by the customer, the weight of the distributed goods, and the distribution time;

[0030] S12. Integrate the order logistics information corresponding to multiple customers into multiple distribution tasks, and represent them in the form of a tuple c i (i, a, a', M i , M i ', L i ); where c i is the identifier of the distribution task, c i∈C, where C is the total number of delivery tasks; i is the identifier of the customer, i ∈ R, R = {1, 2,..., r}, R is the total number of customers, and r represents the serial number corresponding to the customer identifier; a represents picking up goods and a = -1; a' represents delivering goods and a' = 1; M i is the weight of the goods to be delivered to customer i, M i ' is the weight of the goods sent out by customer i; L i is the delivery time to reach customer i.

[0031] In an alternative embodiment, S2 includes:

[0032] S21. Map the location information of the distribution center and multiple customers in the road network to obtain the location of the distribution center in the road network and the locations of multiple customers in the road network;

[0033] S22. Identify the weight of the goods to be delivered and the weight of the goods sent out corresponding to each customer from multiple delivery tasks, calculate the initial loading amount when the electric logistics delivery vehicle departs from the distribution center, and the real-time loading amount when it arrives at the location of each customer;

[0034] S23. Identify the delivery time of each customer from multiple delivery tasks, and determine the initial time when the electric logistics delivery vehicle departs from the distribution center according to the delivery time of each customer and the driving speed of the electric logistics delivery vehicle;

[0035] S24. Construct a set of spatio-temporal state nodes; the set of spatio-temporal state nodes includes the spatio-temporal node corresponding to the distribution center and multiple spatio-temporal nodes corresponding to multiple customers; wherein, the spatio-temporal node corresponding to the distribution center includes the location of the distribution center in the road network, the initial time and the initial loading amount when the electric logistics delivery vehicle departs from the distribution center; each spatio-temporal node corresponding to a customer includes the location of the customer in the road network, the delivery time and the real-time loading amount when the electric logistics delivery vehicle departs from the distribution center and arrives at the location of the customer;

[0036] S25. Construct a set of spatio-temporal state arcs according to the set of spatio-temporal state nodes; the set of spatio-temporal state arcs includes multiple spatio-temporal state arcs; the spatio-temporal state arc represents the delivery path of the electric logistics delivery vehicle between any two spatio-temporal nodes among all spatio-temporal nodes.

[0037] In an alternative embodiment, S4 includes:

[0038] S41. Calculate the shortest distance between the distribution center and each customer according to the distance between the distribution center and the customers adjacent to the distribution center and the distance between the customers and the other customers adjacent to the customers;

[0039] S42. Calculate the delivery priority of each customer according to the shortest distance between the distribution center and each customer and the weight of the goods to be delivered by each customer;

[0040] S43. Calculate the shortest distance for each customer to return to the distribution center after passing through all other customers except themselves according to the distance between the distribution center and the customers adjacent to the distribution center and the distance between the customers and other customers adjacent to them;

[0041] S44. Calculate the sending priority of each customer according to the shortest distance for each customer to return to the distribution center after passing through all other customers except themselves and the weight of the goods sent by each customer;

[0042] S45. Calculate the priority score when the electric logistics delivery vehicle departs from the distribution center and arrives at each customer according to the delivery priority and sending priority of each customer.

[0043] In an alternative embodiment, the specific calculation formula of the objective function is:

[0044]

[0045] Wherein, is the spatio-temporal state arc between spatio-temporal node N i and spatio-temporal node N j ; is the arc length of the spatio-temporal state arc ; is the path selection variable from spatio-temporal node N i to spatio-temporal node N j ; is the weight of the goods to be delivered at spatio-temporal node N j ; is the weight of the goods sent at spatio-temporal node N j ; u j is the service order of customer j, taking an integer value in the interval [1, r]; is the weight coefficient;

[0046] The constraint conditions are:

[0047]

[0048]

[0049] Wherein, is the path selection variable from spatio-temporal node N0 to spatio-temporal node N i ; is the spatio-temporal node N jPath selection variable to spatio-temporal node N0; R is the total number of customers; N is the set of spatio-temporal state nodes; N0 is the spatio-temporal node corresponding to the distribution center; b and k are preset parameters; For the electric logistics delivery vehicle to reach spatio-temporal node N from the previous spatio-temporal node i The priority score at this time; r is the serial number corresponding to the customer identifier.

[0050] In an alternative implementation, the calculation formula for the total objective function value is:

[0051]

[0052] Among them, Is the spatio-temporal state arc between spatio-temporal node N i To spatio-temporal node N j ; Is the spatio-temporal state arc Arc length of; Is the path selection variable from spatio-temporal node N i To spatio-temporal node N j ; Is the weight of the goods to be delivered at spatio-temporal node N j , Is the weight of the goods sent out at spatio-temporal node N j ; u j Is the service order of customer j, taking integer values in the interval [1, r]; Is the weight coefficient.

[0053] In an alternative implementation, the S42 includes:

[0054] Calculate the delivery priority of each customer according to the shortest distance between the distribution center and each customer and the weight of the goods to be delivered by each customer;

[0055]

[0056] Among them, Is the delivery priority of customer i; M i Is the weight of the goods to be delivered by customer i; d i Is the shortest distance between the distribution center and customer i;

[0057] The S44 includes:

[0058] Calculate the sending priority of each customer according to the shortest distance for each customer to return to the distribution center after passing through all other customers except themselves and the weight of the goods sent out by each customer;

[0059]

[0060] Among them, The sending priority for customer i; M i 'The weight of the goods delivered to customer i; d i 'The shortest distance for customer i to return to the distribution center after passing through all other customers except customer i

[0061] The S45 includes:

[0062] Calculate the priority score when the electric logistics delivery vehicle departs from the distribution center and arrives at each customer according to the delivery priority and sending priority of each customer

[0063]

[0064] Among them, is the priority score when the electric logistics delivery vehicle departs from the distribution center and arrives at customer i, and ω1 and ω2 are the weight coefficients of the delivery priority and sending priority respectively

[0065] In an alternative embodiment, the S9 further includes:

[0066] When the total objective function value is greater than or equal to the first preset value, gradually optimize the total objective function by adjusting the parameter values of b, k, ω1, and ω2 until the total objective function value is less than the first preset value to obtain an optimized total objective function

[0067] The present invention has the following beneficial effects:

[0068] (1) Compared with the distribution path planning with the shortest path as the single objective in the related art, the embodiment of the present invention considers the vehicle load, that is, the delivery volume of the delivery customer points, and can realize the priority delivery of customers with large delivery volume and short distance

[0069] (2) The embodiment of the present invention uses a three-dimensional spatio-temporal state network to describe the distribution path of the electric logistics delivery vehicle, and can observe the vehicle load in real time, which is convenient for timely adjusting the customer delivery order

[0070] (3) The embodiment of the present invention integrates the combination of delivery and pick-up into the three-dimensional spatio-temporal state network, meeting the different needs of customers

[0071] (4) The embodiment of the present invention can reduce the energy consumption of the vehicle by optimizing the distribution path of the electric logistics delivery vehicle compared with the single shortest path Description of the Drawings

[0072] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0073] Figure 1 is a schematic flowchart of a path planning method for an electric logistics distribution vehicle considering vehicle load according to an embodiment of the present invention;

[0074] Figure 2 is a schematic flowchart of a distribution process according to an embodiment of the present invention;

[0075] Figure 3 is a schematic diagram of a three-dimensional spatio-temporal state network according to an embodiment of the present invention;

[0076] Figure 4 is a conversion diagram of a traffic network model according to an embodiment of the present invention;

[0077] Figure 5 is a comparison schematic diagram of a path planning method according to an embodiment of the present invention and a traditional path planning method. Specific Embodiments

[0078] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the protection scope of the present invention.

[0079] Figure 1 is a path planning method for an electric logistics distribution vehicle considering vehicle load according to an embodiment of the present invention. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. And although the logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in a different order than here.

[0080] As Figure 1 shown, the process includes the following steps:

[0081] S1. Obtain the location information of the distribution center and multiple customers, as well as the weight of the goods sent by each customer, the weight of the goods to be distributed, and the distribution time.

[0082] In an optional embodiment, step S1 includes:

[0083] S11. In response to the delivery requests of multiple customers, obtain the order logistics information corresponding to each customer; the order logistics information includes: the location information of the distribution center and the customers, as well as the weight of the goods sent by the customers, the weight of the goods to be delivered, and the delivery time.

[0084] S12. Integrate the order logistics information corresponding to multiple customers into multiple delivery tasks, and represent them in the form of a tuple c i (i,a,a',M i ,M i ',L i ); where c i is the identifier of the delivery task, c i ∈C, C is the total number of delivery tasks; i is the identifier of the customer, i∈R, R = {1, 2,..., r}, R is the total number of customers, and r represents the serial number corresponding to the customer identifier; a represents picking up goods and a = -1; a' represents sending goods and a' = 1; M i is the weight of the goods to be delivered by customer i, M i ' is the weight of the goods sent by customer i; L i is the delivery time to reach customer i.

[0085] Among them, as Figure 2 shown, the delivery process mainly includes two main bodies: the customer and the electric logistics delivery vehicle. First, the customer fills in information such as the customer address, name, phone number, weight of the logistics goods, and delivery time on the mobile terminal according to their actual needs and submits a delivery request, and at the same time generates the corresponding order logistics information; after receiving the customer's delivery request, the distribution center obtains the order logistics information corresponding to the customer and integrates the order logistics information into tasks; then, constructs a three-dimensional spatio-temporal state network according to the integrated tasks, and conducts path planning according to the three-dimensional spatio-temporal state network; finally, the electric logistics delivery vehicle loads the goods and departs from the distribution center, and sequentially reaches the designated locations of each customer according to the planned path, and sends a notice to the corresponding customer. After the customer receives the notice, the customer distributes / sends and picks up the goods, and the electric logistics delivery vehicle completes all tasks and returns to the distribution center.

[0086] S2. Construct a three-dimensional spatio-temporal state network according to the location information of the distribution center and multiple customers, as well as the weight of the goods sent by each customer, the weight of the goods to be delivered, and the delivery time; the three-dimensional spatio-temporal state network includes a set of spatio-temporal state nodes and a set of spatio-temporal state arcs.

[0087] Among them, vehicle load is an important factor affecting vehicle energy consumption, and vehicle energy consumption is a reference basis for optimization in path planning. To better understand the position of an electric logistics delivery vehicle in an urban traffic network (referred to as a road network), as well as the change in the loading capacity of the electric logistics delivery vehicle in the road network, an embodiment of the present invention constructs a three-dimensional spatio-temporal state network (Load-Space-Time Networks, referred to as LSTN for short), that is, a three-dimensional spatio-temporal network of loading capacity - space - time, as Figure 3 shown. Among them, the first dimension represents the position of the electric logistics delivery vehicle in the road network, the second dimension represents the time during the driving process of the electric logistics delivery vehicle, and the third dimension represents the real-time load capacity of the electric logistics delivery vehicle. By constructing a three-dimensional spatio-temporal state network, the driving state of the electric logistics delivery vehicle can be understood more intuitively, and vehicle path planning can be better carried out.

[0088] Specifically, the three-dimensional spatio-temporal state network LSTN can be expressed as (N, A), where N is the set of spatio-temporal state nodes in the three-dimensional spatio-temporal state network, and A is the set of spatio-temporal state arcs in the three-dimensional spatio-temporal state network.

[0089] To achieve vehicle path planning that minimizes the energy consumption of a single vehicle for pick-up and delivery while meeting customer requirements and various constraints, the following assumptions are made for some situations before constructing the three-dimensional spatio-temporal state network:

[0090] (1) The delivery vehicles are all of the same model and have the same capacity;

[0091] (2) There is only one distribution center, and the location of the distribution center is known. The electric logistics delivery vehicle starts from the distribution center in a fully charged state, completes the distribution and pick-up / delivery operations, and returns to the distribution center;

[0092] (3) The delivery volume and pick-up volume of each customer are both less than the vehicle capacity, and the pick-up volume of the customer is less than the delivery volume;

[0093] (4) The load of the vehicle cannot exceed its maximum capacity;

[0094] (5) Each customer is served by exactly one vehicle;

[0095] (6) Special traffic conditions are not considered, the road is flat, and the driving speed is constant;

[0096] (7) The service time of each customer is the same, and there is no delivery time limit;

[0097] (8) The vehicle only consumes electric energy during driving and does not consume it during customer service.

[0098] (9) During the distribution process, the vehicle does not have a situation of insufficient battery power and does not require additional charging.

[0099] In an alternative embodiment, step S2 includes:

[0100] S21. Map the location information of the distribution center and multiple customers in the road network to obtain the location of the distribution center in the road network and the locations of multiple customers in the road network.

[0101] S22. Identify the weight of the goods to be delivered corresponding to each customer from multiple distribution tasks, calculate the starting loading amount of the electric logistics delivery vehicle when departing from the distribution center, and the real-time loading amount when arriving at the location of each customer.

[0102] S23. Identify the delivery time of each customer from multiple distribution tasks, and determine the starting time of the electric logistics delivery vehicle when departing from the distribution center according to the delivery time of each customer and the driving speed of the electric logistics delivery vehicle.

[0103] S24. Construct a set of spatio-temporal state nodes; the set of spatio-temporal state nodes includes the spatio-temporal node corresponding to the distribution center and multiple spatio-temporal nodes corresponding to multiple customers; among them, the spatio-temporal node corresponding to the distribution center includes the location of the distribution center in the road network, the starting time and starting loading amount of the electric logistics delivery vehicle when departing from the distribution center; the spatio-temporal node corresponding to each customer includes the location of the customer in the road network, the delivery time and real-time loading amount of the electric logistics delivery vehicle when arriving at the location of the customer after departing from the distribution center.

[0104] Specifically, the set of spatio-temporal state nodes N can be expressed as N = {N0} ∪ {N1, N2,..., N n}, n ∈ R, where N0 represents the spatio-temporal node corresponding to the distribution center; N1 to N n respectively represent the spatio-temporal nodes corresponding to R customers; R is the total number of customers.

[0105] Among them, the spatio-temporal node includes the location of the customer or distribution center in the road network, the time of the electric logistics delivery vehicle at the current spatio-temporal node, and the state quantity. Specifically, the spatio-temporal node N0 corresponding to the distribution center can be further expressed as N0(s0, t0, q0), s0 is the location of the distribution center in the road network (spatial element), t0 is the starting time of the electric logistics delivery vehicle when departing from the distribution center (time element), q0 is the starting loading amount of the electric logistics delivery vehicle when departing from the distribution center (state element); the spatio-temporal node N i corresponding to the customer can be further expressed as (s i , t i , q i ), i ∈ R, s i is the location of customer i in the road network, t i is the delivery time of the electric logistics delivery vehicle when arriving at the location of customer i after departing from the distribution center; q iis the loading capacity of the electric logistics delivery vehicle when it departs from the distribution center and arrives at the location of customer i. It should be noted that q i is the loading capacity of the electric logistics delivery vehicle after it departs from the distribution center and arrives at the location of customer i, and delivers the goods to customer i or loads the goods to be sent into the vehicle.

[0106] S25. Construct a spatio-temporal state arc set according to the spatio-temporal state node set; the spatio-temporal state arc set includes multiple spatio-temporal state arcs; the spatio-temporal state arc represents the distribution path of the electric logistics delivery vehicle between any two spatio-temporal nodes among all spatio-temporal nodes.

[0107] Specifically, the spatio-temporal state arc set A can be further expressed as represents the distribution path of the electric logistics delivery vehicle from spatio-temporal node N i (s i ,t i ,q i ) to N j (s j ,t j ,q j ). During this distribution process, the physical location, driving time and load capacity of the electric logistics delivery vehicle have all changed.

[0108] As Figure 4 shown, the embodiment of the present invention constructs a traffic network model based on the real road network, converts the traffic network model into a digital network model, that is, abstracts the road sections into line segments, abstracts the distribution customer points into nodes, converts the two-dimensional traffic network into a one-dimensional space dimension, and adds time and state dimensions to construct a three-dimensional spatio-temporal state network LSTN that conforms to the real distribution scenario.

[0109] S3. Calculate the distances between the distribution center and the customers adjacent to the distribution center, and the distances between the customers and other customers adjacent to the customers according to the three-dimensional spatio-temporal state network.

[0110] Exemplarily, as Figure 4 shown, the customer sites adjacent to the distribution center V0 include V1, V4 and V5. Then the distances between the distribution center V0 and the customer sites V1, V4, V5 are 3 km, 4 km, and 2 km respectively; taking the customer site V1 as an example, the other customer sites adjacent to the customer site V1 include V2 and V4. Then the distances between the customer site V1 and the customer sites V2 and V4 are 4 km and 3 km respectively. By analogy, the distances between any two adjacent spatio-temporal nodes can be calculated, that is, the distances between the distribution center and the customers adjacent to the distribution center, and the distances between the customers and other customers adjacent to the customers.

[0111] S4. Calculate the priority score when the electric logistics delivery vehicle departs from the distribution center and reaches each customer based on the distances between the distribution center and the customers adjacent to it, the distances between customers and other customers adjacent to them, the weight of the goods sent by each customer, and the weight of the goods to be delivered.

[0112] In an alternative embodiment, step S4 includes:

[0113] S41. Calculate the shortest distance between the distribution center and each customer based on the distances between the distribution center and the customers adjacent to it, and the distances between customers and other customers adjacent to them.

[0114] Continuing with the example, as Figure 4 shown, taking the distribution center V0 and the customer site V3 as an example, there are multiple paths from V0 to V3, including V0 - V4 - V3, V0 - V5 - V3, V0 - V1 - V2 - V3, etc., and the corresponding distances are 8 km, 5 km, 9 km, etc. Select the path with the shortest distance as the shortest distance between the distribution center V0 and the customer site V3; similarly, the shortest distances between the distribution center and other customers are calculated in the same way and will not be elaborated here.

[0115] S42. Calculate the delivery priority of each customer based on the shortest distance between the distribution center and each customer and the weight of the goods to be delivered to each customer:

[0116]

[0117] where is the delivery priority of customer i; M i is the weight of the goods to be delivered to customer i; d i is the shortest distance between the distribution center and customer i.

[0118] S43. Calculate the shortest distance for each customer to return to the distribution center after passing through all other customers except themselves based on the distances between the distribution center and the customers adjacent to it, and the distances between customers and other customers adjacent to them.

[0119] Continuing with the example, as Figure 4As shown in the figure, taking customer site V1 as an example, all other customer sites except customer site V1 include V2, V3, V4, and V5. There are also multiple paths for V1 to return to V0 after passing through V2, V3, V4, and V5, including V1-V2-V3-V4-V5-V0, V1-V4-V2-V3-V5-V0, V1-V2-V4-V3-V5-V0, etc. The corresponding distances are 15 km, 15 km, 18 km, etc. Select the path with the shortest distance from these paths as the shortest distance for customer site V1 to return to distribution center V0 after passing through all other customers except itself; similarly, other customers are calculated in this way, which will not be elaborated here.

[0120] S44. Calculate the shipping priority of each customer based on the shortest distance for each customer to return to the distribution center after passing through all other customers except itself and the weight of the goods sent by each customer:

[0121]

[0122] Among them, is the shipping priority of customer i; M i ' is the weight of the goods delivered by customer i; d i ' is the shortest distance for customer i to return to the distribution center after passing through all other customers except customer i.

[0123] S45. Calculate the priority score when the electric logistics delivery vehicle arrives at each customer starting from the distribution center according to the distribution priority and shipping priority of each customer.

[0124]

[0125] Among them, is the priority score when the electric logistics delivery vehicle arrives at customer i starting from the distribution center, and ω1 and ω2 are the weight coefficients of the distribution priority and shipping priority respectively.

[0126] S5. Take the first target customer with the highest priority score and meeting the constraint conditions as the customer for the first delivery order, and calculate the objective function when the electric logistics delivery vehicle arrives at the first target customer starting from the distribution center.

[0127] In an optional implementation manner, the specific calculation formula of the objective function is:

[0128]

[0129] Among them, is the spatio-temporal state arc between spatio-temporal node N i and spatio-temporal node N j ; is the spatio-temporal state arc Arc length; Is the space-time node N i To the space-time node N j Path selection variable; Is the space-time node N j Weight of the delivered goods at the space-time node N, Is the space-time node N j Weight of the shipped goods at the space-time node N; u j Is the service order of customer j, and the value is an integer in the interval [1, r]; Is the weight coefficient.

[0130] It should be noted that the objective function represents minimizing the weighted sum of the total vehicle delivery distance and the customer point cargo volume; the first term is the total closed-loop delivery distance of the vehicle, and the second term is that if a customer with a high priority score has a late access order (u j Value is large), the penalty is increased.

[0131] The constraint conditions are:

[0132]

[0133] Among them, Is the path selection variable from the space-time node N0 to the space-time node N i ; Is the space-time node N j To the path selection variable of the space-time node N0; R is the total number of customers; N is the set of space-time state nodes; N0 is the space-time node corresponding to the distribution center; b, k are preset parameters; Is the priority score when the electric logistics delivery vehicle arrives at the space-time node N from the previous space-time node i ; r is the serial number corresponding to the customer identifier.

[0134] It should be noted that the first and second constraint conditions indicate that the entire path of the electric logistics delivery vehicle is a closed loop, and the vehicle starts from the distribution center and finally returns to the distribution center; the third and fourth constraint conditions indicate that each space-time node must be visited and can only be visited once; the fifth constraint condition indicates that no sub-loop exists in any sub-graph, ensuring that all space-time nodes form a loop; the sixth constraint condition indicates that when planning the path, the value range of the path selection variable And the service order u of the customer j ; The seventh constraint condition indicates the value range of the weight coefficient , When the priority score of customer i is the largest and customer i is in the front sequence of the distribution, Otherwise

[0135] It should be especially noted that when calculating the objective function in step S5, the space-time node N iis the spatio-temporal node corresponding to the distribution center, and the spatio-temporal node N j is any one of the spatio-temporal nodes corresponding to R customers.

[0136] S6. Calculate the priority score when the electric logistics distribution vehicle departs from the first target customer and reaches all other customers except the first target customer according to the distances between the distribution center and the customers adjacent to the distribution center, the distances between the customers and other customers adjacent to the customers, the weight of the goods sent by each customer, and the weight of the goods to be distributed.

[0137] It should be noted that the calculation process of step S6 is the same as that of step S4. The only difference is that step S4 takes the distribution center as the starting point to calculate the priority score of reaching the customer with the first service order; while step S6 takes the customer with the first service order as the starting point to calculate the priority score of reaching the customer with the second service order.

[0138] In an alternative implementation, step S6 includes:

[0139] S61. Calculate the shortest distance between the first target customer and other customers according to the distances between the distribution center and the customers adjacent to the distribution center, and the distances between the customers and other customers adjacent to the customers.

[0140] Continuing with the example, as Figure 4 shown, assume that the customer in the first service order (i.e., the first target customer) is V1. Taking the customer site V1 and the customer site V3 as an example, there are multiple paths from V1 to V3, including V1-V4-V3, V1-V2-V3, V1-V4-V5-V3, etc. The corresponding distances are 7km, 6km, 9km, etc. Select the shortest distance among these paths as the shortest distance between the customer site V1 and the customer site V3; similarly, the shortest distances between the customer site V1 and other customer sites are also calculated in this way, which will not be elaborated here.

[0141] S62. Calculate the distribution priority of other customers according to the shortest distance between the first target customer and other customers and the weight of the goods to be distributed of other customers:

[0142]

[0143] where, is the distribution priority of customer i; M i is the weight of the goods to be distributed of customer i; d i is the shortest distance between the distribution center and customer i.

[0144] It should be noted that customer i is any one of all the customers remaining after excluding the first target customer.

[0145] S63. Calculate the shortest distance for the second target customer to return to the distribution center after passing through all other customers except themselves based on the distances between the distribution center and the customers adjacent to it, and the distances between customers and other customers adjacent to them; the other customers except themselves do not include the first target customer.

[0146] Continuing with the example, as Figure 4 shown, still assume that the customer in the first service order (i.e., the first target customer) is V1. Taking the customer site V4 (the second target customer) as an example, all other customer sites except the customer site V4 (excluding V1) include V2, V3, and V5. There are also multiple paths for V4 to pass through V2, V3, and V5 and then return to V0. Select the path with the shortest distance from these paths as the shortest distance for the customer site V4 to return to the distribution center V0 after passing through all other customers except itself; similarly, other customers V2, V3, and V5 are also calculated in this way, which will not be elaborated here.

[0147] S64. Calculate the shipping priority of each customer based on the shortest distance for the second target customer to return to the distribution center after passing through all other customers except themselves and the weight of the goods sent by each customer:

[0148]

[0149] where is the shipping priority of customer i; M i ' is the weight of the goods to be distributed for customer i; d i ' is the shortest distance for customer i to return to the distribution center after passing through all other customers except customer i.

[0150] It should be noted that customer i is any one of all the customers remaining after excluding the first target customer.

[0151] S65. Calculate the priority score when the electric logistics delivery vehicle departs from the first target customer and reaches all other customers except the first target customer based on the distribution priority and shipping priority of each customer:

[0152]

[0153] where is the priority score when the electric logistics delivery vehicle departs from the first target customer and reaches customer i, and ω1 and ω2 are the weight coefficients of the distribution priority and shipping priority respectively.

[0154] S7. Take the second target customer with the highest priority score and meeting the constraint conditions as the customer in the second delivery order, and calculate the objective function when the electric logistics delivery vehicle departs from the first target customer and reaches the second target customer.

[0155] It should be specifically noted that the calculation formula of the objective function and the constraint conditions in step S7 are the same as those in step S5. The only difference is the spatio-temporal node N i is the spatio-temporal node corresponding to the first target customer, and the spatio-temporal node N j is any one of the spatio-temporal nodes corresponding to all the remaining customers after excluding the first target customer among the R customers.

[0156] S8. Repeat steps S6 - S7. Finally, obtain the delivery sequence when the electric logistics delivery vehicle departs from the distribution center and arrives at each customer in turn, as well as the multi-segment objective functions when departing from the distribution center and arriving at each customer in turn.

[0157] Specifically, the path planning in the embodiment of the present invention is real-time planning according to multi-segment paths starting from the distribution center, and the customers at the next spatio-temporal node are determined in turn. In one example, assuming that there are a total of 5 customers, first, it is necessary to plan the path of the next customer point that the distribution center needs to reach. It is necessary to determine the customer point with the first service order from 5 customers and calculate the objective function of the section between the distribution center and the customer point with the first service order; then, determine the customer point with the second service order and calculate the objective function between the customer point with the first service order and the customer point with the second service order, and so on, until the 5 customers are determined in turn according to the service order. At this time, there will be 5 segments of objective functions.

[0158] S9. Add up the multi-segment objective function values to obtain the total objective function value; when the total objective function value is less than the first preset value, plan the delivery path according to the current delivery sequence.

[0159] In an alternative embodiment, the calculation formula of the total objective function value is:

[0160]

[0161] Among them, is the spatio-temporal state arc between the spatio-temporal node N i and the spatio-temporal node N j ; is the arc length of the spatio-temporal state arc ; is the path selection variable from the spatio-temporal node N i to the spatio-temporal node N j ; is the weight of the goods to be delivered at the spatio-temporal node N j , is the weight of the goods to be sent out at the spatio-temporal node N j ; u j is the service order of customer j, and the value is an integer in the interval [1, r]; is the weight coefficient.

[0162] The expansion of the total objective function value can also be further expressed as:

[0163]

[0164] In an alternative embodiment, after step S9, the method further includes:

[0165] S10. Calculate the total energy consumption of the distribution according to the distribution route;

[0166] The calculation process of the total energy consumption of the distribution is as follows:

[0167] S101. Calculate the traction force F of the electric logistics distribution vehicle in the driving state w :

[0168]

[0169] where F rol is the rolling resistance of the vehicle during driving, F air is the aerodynamic resistance of the vehicle during driving, F slo is the gradient resistance during the vehicle's driving, M is the total weight of the vehicle, M = m + μ, m is the net weight of the vehicle, μ is the weight of the goods on the vehicle, a is the acceleration of the vehicle during driving, ρ a is the air density where the vehicle is located, A f is the cross-sectional area of the vehicle facing the wind, C D is the aerodynamic drag coefficient, v is the speed of the vehicle during driving, g is the acceleration due to gravity, f is the sliding friction resistance coefficient, θ is the road gradient;

[0170] S102. Calculate the total energy consumption E of the electric logistics distribution vehicle according to the traction force F w of the electric logistics distribution vehicle in the driving state:

[0171]

[0172] where ε is the efficiency of the vehicle transmission system, E a is the battery energy consumption consumed by the vehicle accessories, E w is the battery energy consumption consumed by the vehicle during driving, v is the speed of the vehicle during driving, t is the driving time of the vehicle; P a is the instantaneous power consumed by the vehicle accessories;

[0173] S103. According to the traction force F w of the electric logistics distribution vehicle in the state of driving at a constant speed on a horizontal road surface, the total energy consumption E of the electric logistics distribution vehicle is further expressed as:

[0174] E = α + βM

[0175]

[0176] In an alternative embodiment, step S9 further includes:

[0177] When the total objective function value is greater than or equal to the first preset value, the total objective function is gradually optimized by adjusting the parameter values of b, k, ω1, and ω2 until the total objective function value is less than the first preset value, and the optimized total objective function is obtained.

[0178] The embodiments of the present invention have the following beneficial effects:

[0179] (1) Compared with the distribution path planning with the shortest path as the single objective in the related art, the embodiments of the present invention consider the vehicle load, that is, the distribution volume of the distribution customer points, and can give priority to the distribution of customers with large distribution volume and short distance;

[0180] (2) The embodiments of the present invention use a three-dimensional spatio-temporal state network to describe the distribution path of the electric logistics vehicle, and can observe the vehicle load in real time, which is convenient for timely adjusting the customer distribution order;

[0181] (3) The embodiments of the present invention integrate the method of combining distribution with pick-up and delivery into the three-dimensional spatio-temporal state network, meeting the different needs of customers.

[0182] (4) The embodiments of the present invention can reduce the energy consumption of the vehicle by optimizing the distribution path of the electric logistics vehicle compared with the single shortest path.

[0183] To verify the effects of the embodiments of the present invention, the following comparative description is made between the path planning method of the present invention and the traditional path planning method:

[0184] Transporting goods from the distribution center and finally returning to the distribution center, as Figure 3 shown, assuming that the self-weight of the electric logistics vehicle is m = 1500 kg, the speed is v = 40 km / h, the uniform driving acceleration is a = 0 m 2 / s, the air density is ρ a = 1.3 kg / m 3 , the cross-sectional area is A f = 3.6 m 2 , the aerodynamic drag coefficient is C D = 0.3, the gravitational acceleration is g = 9.8 m / s 2 , the sliding friction coefficient is f = 0.01, the road slope is θ = 0, the vehicle transmission efficiency is ε = 0.8, the power consumed by the vehicle accessories is P a = 2 kw, and the relevant parameter values are ω1 = 1, ω2 = 0, b = 1, k = 0.2.

[0185] According to the distribution task, as Figure 4As shown, the number of delivery customers, distance, and quantity of goods are determined, as shown in Table 1:

[0186] Table 1

[0187]

[0188] The calculated paths are L1: 0 - 1 - 2 - 3 - 4 - 5 - 0; L2: 0 - 1 - 4 - 2 - 3 - 5 - 0.

[0189] The traditional shortest path is: L3: 0 - 5 - 4 - 3 - 2 - 1 - 0.

[0190]

[0191] As Figure 5 shown, by calculating the power consumption of the three paths, compared with the traditional L3, the battery energy consumption of path L1 is reduced by 1.65%, and compared with the traditional L3, the battery energy consumption of path L2 is reduced by 1.81%.

[0192] Although embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations fall within the scope defined by the appended claims.

Claims

1. An electric logistics delivery vehicle path planning method considering vehicle load, characterized in that, Including: S1. Obtain the location information of the distribution center and multiple customers, as well as the weight of the goods sent by each customer, the weight of the goods to be delivered, and the delivery time; S2. Construct a three-dimensional spatio-temporal state network based on the location information of the distribution center and multiple customers, as well as the weight of the goods sent by each customer, the weight of the goods to be delivered, and the delivery time; the three-dimensional spatio-temporal state network includes a set of spatio-temporal state nodes and a set of spatio-temporal state arcs; S3. Calculate the distances between the distribution center and the customers adjacent to the distribution center, and the distances between customers and other customers adjacent to the customers according to the three-dimensional spatio-temporal state network; S4. Calculate the priority scores of the electric logistics delivery vehicle when it departs from the distribution center and reaches each customer according to the distances between the distribution center and the customers adjacent to the distribution center, the distances between customers and other customers adjacent to the customers, the weight of the goods sent by each customer, and the weight of the goods to be delivered; S5. Take the first target customer with the highest priority score and meeting the constraint conditions as the customer in the first delivery order, and calculate the objective function of the electric logistics delivery vehicle when it departs from the distribution center and reaches the first target customer; S6. Calculate the priority scores of the electric logistics delivery vehicle when it departs from the first target customer and reaches all other customers except the first target customer according to the distances between the distribution center and the customers adjacent to the distribution center, the distances between customers and other customers adjacent to the customers, the weight of the goods sent by each customer, and the weight of the goods to be delivered; S7. Take the second target customer with the highest priority score and meeting the constraint conditions as the customer in the second delivery order, and calculate the objective function of the electric logistics delivery vehicle when it departs from the first target customer and reaches the second target customer; S8. Repeat steps S6 - S7 until finally obtaining the delivery order of the electric logistics delivery vehicle when it departs from the distribution center and reaches each customer in turn, and the multi-segment objective functions when it departs from the distribution center and reaches each customer in turn; S9. Add up the multi-segment objective function values to obtain the total objective function value; When the total objective function value is less than the first preset value, plan the delivery route according to the current delivery order.

2. The method according to claim 1, characterized in that, After the S9, the method further includes: S10. Calculate the total delivery energy consumption according to the delivery route; The calculation process of the total delivery energy consumption is: S101. Calculate the traction force F of the electric logistics delivery vehicle in the driving state w : Among them, F rol is the rolling resistance during vehicle driving, F air is the aerodynamic drag during vehicle driving, F slo is the gradient resistance during vehicle driving, M is the total vehicle weight, M = m + μ, m is the net weight of the vehicle, μ is the weight of the goods on the vehicle, a is the acceleration of vehicle driving, ρ a is the air density where the vehicle is located, A f is the cross-sectional area of the vehicle facing the wind, C D is the aerodynamic drag coefficient, v is the speed of vehicle driving, g is the acceleration due to gravity, f is the sliding friction coefficient, and θ is the road gradient; S102. Calculate the total distribution energy consumption E of the electric logistics delivery vehicle according to the traction force F of the electric logistics delivery vehicle in the driving state: w ​ where ε is the vehicle driveline efficiency, E a is the battery energy consumption consumed by vehicle accessories, E w is the battery energy consumption consumed by the vehicle during driving, v is the vehicle speed, and t is the vehicle driving time; P a is the instantaneous power consumed by vehicle accessories; S103. According to the traction force F of the electric logistics delivery vehicle in a uniform motion state on a horizontal road surface w , the total distribution energy consumption E of the electric logistics delivery vehicle is further expressed as: E = α + βM 3. The method according to claim 1, wherein The S1 includes: S11. In response to the delivery requests of multiple customers, obtain the order logistics information corresponding to each customer; the order logistics information includes: the location information of the distribution center and the customers, as well as the weight of the goods sent by the customer, the weight of the goods to be delivered, and the delivery time; S12. Integrate the order logistics information corresponding to multiple customers into multiple distribution tasks, and represent them in the form of a tuple c i (i, a, a', M i , M i ', L i ); where c i is the identifier of the distribution task, c i ∈C, C is the total number of distribution tasks; i is the identifier of the customer, i∈R, R = {1, 2,..., r}, R is the total number of customers, and r represents the serial number corresponding to the customer identifier; a represents picking up goods and a = -1; a' represents sending goods and a' = 1; M i is the weight of the goods to be distributed for customer i, M i ' is the weight of the goods sent by customer i; L i is the distribution time to reach customer i.

4. The method according to claim 3, wherein The S2 includes: S21. Map the location information of the distribution center and multiple customers in the road network to obtain the location of the distribution center in the road network and the locations of multiple customers in the road network; S22. Identify the weight of the goods to be delivered and the weight of the goods sent by each customer from multiple delivery tasks, calculate the initial loading amount of the electric logistics delivery vehicle when it departs from the distribution center, and the real-time loading amount when it reaches the location of each customer; S23. Identify the delivery time for each customer from multiple delivery tasks, and determine the starting time when the electric logistics delivery vehicle departs from the distribution center based on the delivery time of each customer and the driving speed of the electric logistics delivery vehicle. S24. Construct a set of spatio-temporal state nodes; the set of spatio-temporal state nodes includes the spatio-temporal node corresponding to the distribution center, and multiple spatio-temporal nodes corresponding to multiple customers; wherein, the spatio-temporal node corresponding to the distribution center includes the location of the distribution center in the road network, the starting time when the electric logistics delivery vehicle departs from the distribution center, and the starting loading capacity; the spatio-temporal node corresponding to each customer includes the location of the customer in the road network, the delivery time when the electric logistics delivery vehicle departs from the distribution center and arrives at the location of the customer, and the real-time loading capacity. S25. Construct a set of spatio-temporal state arcs based on the set of spatio-temporal state nodes; the set of spatio-temporal state arcs includes multiple spatio-temporal state arcs; the spatio-temporal state arc represents the delivery path of the electric logistics delivery vehicle between any two spatio-temporal nodes among all spatio-temporal nodes.

5. The method according to claim 4, wherein The S4 includes: S41. Calculate the shortest distance between the distribution center and each customer based on the distances between the distribution center and the customers adjacent to the distribution center, and the distances between the customers and the other customers adjacent to the customers. S42. Calculate the delivery priority of each customer based on the shortest distance between the distribution center and each customer and the weight of the goods to be delivered by each customer. S43. Calculate the shortest distance for each customer to return to the distribution center after passing through all other customers except itself based on the distances between the distribution center and the customers adjacent to the distribution center, and the distances between the customers and the other customers adjacent to the customers. S44. Calculate the sending priority of each customer based on the shortest distance for each customer to return to the distribution center after passing through all other customers except itself and the weight of the goods sent by each customer. S45. Calculate the priority score when the electric logistics delivery vehicle departs from the distribution center and arrives at each customer based on the delivery priority and the sending priority of each customer.

6. The method according to claim 5, wherein The specific calculation formula of the objective function is: Among them, is the spatio-temporal state arc between spatio-temporal node N i and spatio-temporal node N j ; is the arc length of the spatio-temporal state arc ; is the path selection variable from spatio-temporal node N i to spatio-temporal node N j ; is the weight of the goods to be delivered at spatio-temporal node N j ; is the weight of the goods sent out at spatio-temporal node N j ; u j is the service order of customer j, taking integer values in the interval [1, r]; is the weight coefficient; The constraint conditions are: Among them, is the path selection variable from the spatio-temporal node N0 to the spatio-temporal node N i . is the path selection variable from the spatio-temporal node N j to the spatio-temporal node N0; R is the total number of customers; N is the set of spatio-temporal state nodes; N0 is the spatio-temporal node corresponding to the distribution center; b and k are preset parameters; is the priority score when the electric logistics delivery vehicle arrives at the spatio-temporal node N i from the previous spatio-temporal node; r is the serial number corresponding to the customer identifier.

7. The method according to claim 6, wherein The calculation formula of the total objective function value is: Among them, is the spatio-temporal node N i to the spatio-temporal node N j the spatio-temporal state arc in between; is the spatio-temporal state arc the arc length of; is the spatio-temporal node N i to the spatio-temporal node N j the path selection variable of; is the weight of the goods to be delivered at the spatio-temporal node N j ; is the weight of the goods sent out at the spatio-temporal node N j ; u j is the service order of customer j, taking integer values in the interval [1, r]; is the weight coefficient.

8. The method according to claim 7, characterized in that, The S42 includes: Calculate the delivery priority of each customer based on the shortest distance between the distribution center and each customer and the weight of the goods to be delivered by each customer. Among them, is the delivery priority of customer i; M i is the weight of the goods delivered to customer i; d i is the shortest distance between the distribution center and customer i; The S44 includes: Calculate the sending priority of each customer based on the shortest distance for each customer to return to the distribution center after passing through all other customers except itself and the weight of the goods sent by each customer. Among them, is the sending priority for customer i; M i ' is the weight of the goods delivered to customer i; d i ' is the shortest distance for customer i to return to the distribution center after passing through all other customers except customer i. The S45 includes: Calculate the priority score when the electric logistics delivery vehicle departs from the distribution center and arrives at each customer based on the delivery priority and the sending priority of each customer. Among them, is the priority score when the electric logistics delivery vehicle departs from the distribution center and arrives at customer i. ω1 and ω2 are the weight coefficients of the distribution priority and the sending priority respectively.

9. The method according to claim 8, wherein The S9 further includes: When the total objective function value is greater than or equal to the first preset value, gradually optimize the total objective function by adjusting the parameter values of b, k, ω1, and ω2 until the total objective function value is less than the first preset value to obtain the optimized total objective function.

Images