A hitchhiking shared ride path matching method based on commuting travel

Abstract

The application discloses a hitchhiking shared ride path matching method based on commuting travel, unlike in traditional shared rides, drivers will selectively go to the location of passengers to obtain higher profits, in commuting shared rides, all shared riders should be picked up as far as possible to meet the going requirements of the pickers, so that the system is optimized. In order to improve the shared ride rate, a penalty factor is introduced for the travel time of the riders who have not completed the shared ride pairing. In addition, the discomfort of the shared ride personnel will increase with the increase of the travel time, and the total travel time is taken as the target to reduce the discomfort in travel. The method of the application is mainly used for the hitchhiking shared ride problem, and ensures that the commuters on the same route are quickly matched.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of transportation and traffic engineering, and relates to the field of commuter shared travel carpool path selection, and more particularly to a hitchhiking shared carpool path matching method based on commuter travel. BACKGROUND

[0002] At present, the number of motor vehicles in the country has exceeded 390 million, while the average number of passengers in a car during peak hours is less than 1.6. The one-person-one-car travel mode causes urban roads to be congested during peak hours. With the popularity of networking, the shared carpool mode is gradually accepted by people. This mode can improve the occupancy rate of motor vehicles, thereby reducing part of private car travel, saving road resources, and reducing environmental pollution, and is considered an effective method to solve urban congestion problems.

[0003] In existing research, shared carpooling is mainly applied to taxi and online car travel. As an important part of urban traffic, taxi service has existed for a long time, and its occupancy rate is higher than that of private vehicles. The development of “Internet+” has promoted the rise of online car services, which are deeply loved by travelers due to their more convenient and efficient services and lower costs. In addition to traditional “hailing” services, many domestic and foreign Internet companies have launched hitchhiking services to facilitate same-direction travelers to travel by “carpooling”.

[0004] Taxi and online carpooling services have been applied to actual life, but under the drive of the profit model, a large number of drivers have developed professionally, which not only increases the number of vehicles on the road but also restricts the development of public transportation, further aggravating urban congestion.

[0005] There are two states of “pick-up” and “ride” in shared carpooling. Therefore, commuters are divided into pickers and riders. After determining the commuters participating in carpooling, the picker travels to the location of each rider in the maximum acceptable travel time and maximum detour time. Due to the uncertainty of the location and the limitation of the number of carpoolers, the picker tries to carry the riders as much as possible to save the total travel time and relieve the discomfort of the passengers. After receiving the service of the picker, the riders go to the same destination together with the picker.

[0006] Existing shared carpooling algorithms for commuters usually only calculate and plan the shortest route in terms of time and distance for the riders to meet the comfort level of the riders, and less consideration is given to the pickup level of the pickers. However, in actual application, the experience of the pickers in hitchhiking is not comfortable. SUMMARY

[0007] The present application aims to provide a hitchhiking sharing carpooling path matching method based on commuting travel, so as to solve the problem that the existing hitchhiking algorithm does not consider the psychological state of commuters.

[0008] To solve the above technical problems, the hitchhiking sharing carpooling path matching method based on commuting travel comprises the following steps:

[0009] Step 1: Determine the hitchhiking sharing carpooling matching parameters, including the number of commuters, the number of passengers p and the number of pickers g, the number of vehicle capacity N, the maximum travel time D that the pickers can accept max , the maximum detour time R that the pickers can accept max , the waiting time t spent by each passenger s , and the penalty factor α.

[0010] Step 2: According to the geographical position of the number of passengers p and the number of pickers g, determine the path matching selection of the pickers and the passengers.

[0011] Step 3: According to the number of vehicle capacity N and the location of the commuters, determine the arrival order of the passengers in the hitchhiking driving path.

[0012] Step 4: Calculate the arrival time of all nodes.

[0013] Step 5: According to the maximum travel time D that the pickers can accept max , limit the matching distance range of the shared carpooling.

[0014] Step 6: Repeat steps 2-5 to optimize the overall path matching with the goal of minimizing the total travel time of all commuters to the destination.

[0015] Further, the path matching selection determination method of the pickers and the passengers in step 2 comprises the following steps:

[0016] Step 21: To ensure that all commuters go to the destination, it is calculated as shown in formula (1):

[0017]

[0018] In the formula, S is the set of all nodes, S={1,2,…,p,…,g,n}, n is the total number of nodes, and the nth node is the destination; x ij is a 0-1 variable, which takes 1 to represent that the commuter moves from node i to node j, and takes 0 to represent that the commuter does not move from node i to node j.

[0019] It also includes calculating the carpooling or individual travel of the commuters to the destination, and the commuters do not leave after arriving at the destination, which is calculated as shown in formula (2) and formula (3):

[0020]

[0021]

[0022] Also included is the calculation of the pick-up leaving the location where the pick-up is not returned, which is calculated as shown in equation (4) and equation (5):

[0023]

[0024]

[0025] In the formula: G is the set of pick-ups, G = {p+1, p+2, …, g};

[0026] Also included is the calculation of the pick-up leaving the location where the pick-up is not returned, which is calculated as shown in equation (4) and equation (5):

[0027]

[0028]

[0029] In the formula: P is the set of passengers, P = {1, 2, …, p};

[0030] Also included is the calculation of the pick-up leaving the location where the pick-up is not returned, which is calculated as shown in equation (4) and equation (5):

[0031]

[0032] In the formula: h is the vehicle number of the pick-up.

[0033] Further, the method for determining the arrival order of commuters in the vehicle travel path in step 3 includes the following steps:

[0034] Step 31: Calculate the arrival order of each node to keep consistent, which is calculated as shown in equation (9) and equation (10):

[0035]

[0036]

[0037] In the formula: S is the set of all nodes, S = {1, 2, …, p, …, g, n}, n is the total number of nodes, where the nth node is the destination; G is the set of pick-ups, G = {p+1, p+2, …, g}; u h,i is the arrival order of node i in the travel path of pick-up h; M is the maximum value; x ij is a 0-1 variable, taking 1 means that the commuter moves from node i to node j, and taking 0 means that the commuter does not move from node i to node j;

[0038] Further, the step of calculating the pickup and drop-off points of the passengers in the carpooling path includes the following steps:

[0039]

[0040]

[0041] wherein P is the passenger set, P = {1, 2, …, p}; N is the vehicle capacity;

[0042] Further, the step of calculating the pickup and drop-off points of the passengers in the carpooling path includes the following steps:

[0043]

[0044]

[0045] Further, the step of calculating the arrival time of all nodes in step 4 includes the following steps:

[0046] Step 41: Calculate the path time and waiting time in the carpooling path, and the arrival time of the next node is not earlier than the previous node, which is calculated as shown in formula (15) and formula (16):

[0047]

[0048]

[0049] wherein S is the set of all nodes, S = {1, 2, …, p, …, g, n}, n is the total number of nodes, wherein the nth node is the destination; G is the set of drop-off points, G = {p+1, p+2, …, g}; P is the set of passengers, P = {1, 2, …, p}; is the arrival time of node i in the travel path of drop-off point h; d ij is the Euclidean distance from node i to node j; v y is the travel speed of the car of drop-off point h; t s is the waiting time spent by each passenger; u h,i is the arrival order of node i in the travel path of drop-off point h; M is the maximum value; x ij is a 0-1 variable, taking 1 means the commuter moves from node i to node j, and taking 0 means the commuter does not move from node i to node j;

[0050] The time of arrival of the passenger of the uncompleted carpooling pair at the destination is calculated, and the time of arrival is later than the time of departure. The calculation is shown in equation (17) and equation (18):

[0051]

[0052]

[0053] In the equation: is the time of arrival of the passenger i of the uncompleted carpooling pair at the node n by driving by himself / herself; v w is the speed of the passenger driving to the destination by himself / herself;

[0054] The total travel time of the carpooling path and the total travel time of the passenger of the uncompleted carpooling pair are calculated. The calculation is shown in equation (19) and equation (20):

[0055]

[0056]

[0057] Further, the step of sharing the carpooling matching range in step 5 includes the following steps:

[0058] Step 51: Calculate the time of arrival of the pickup person before the specified time, and calculate the travel time of each carpooling path not to exceed the maximum travel time acceptable by the pickup person. The calculation is shown in equation (21):

[0059]

[0060] In the equation: G is the set of pickup persons, G = {p+1, p+2, …, g}; is the time of arrival of the pickup person h at the node i in the driving path; D max is the maximum travel time acceptable by the pickup person;

[0061] The total detour time of each carpooling path is calculated not to exceed the maximum detour time acceptable by the pickup person. The calculation is shown in equation (22):

[0062]

[0063] In the equation: d ij is the Euclidean distance from the node i to the node j; v y is the driving speed of the vehicle of the pickup person; R max is the maximum detour time acceptable by the pickup person. The pickup person will not detour infinitely to pick up the passenger according to the principle of "on the way".

[0064] Further, the optimization method of the overall path matching in step 6 includes the following steps:

[0065] Step 61: Calculate the total travel time of all commuters to the destination as the objective function, as shown in equation (23):

[0066] max T = t y + αt w (23)

[0067] In the equation, T is the total travel time of all commuters to the destination; t y is the total time of all drop-off passengers to the destination; t w is the total time of passengers who have not completed carpooling to the destination; and α is the penalty factor. The discomfort of carpoolers increases with the travel time, and to reduce the discomfort during travel, the total travel time is minimized.

[0068] Further, the maximum detour time R max acceptable by the drop-off passenger is collected. Method, comprising:

[0069] S1: Collect historical drop-off data of the drop-off passenger, including the same drop-off destination; and collect driving data of the vehicle state in the historical drop-off data of the drop-off passenger;

[0070] S2: Screen valid historical drop-off data, including historical drop-off data arriving at the destination before a specified time node; and the specified time node is based on the time point with the highest frequency of arrival at the destination in the historical drop-off data;

[0071] S3: The screening condition is the longest commuting time T min and the shortest commuting time T max in the valid historical drop-off data in S2; calculate the time difference T x = T max -T min between the longest commuting time and the shortest commuting time.

[0072] S4: The maximum detour time R max acceptable by the drop-off passenger is T x *(1-G x )*100%, Gx = T o / T p , where T p is the total duration of vehicle driving in the historical drop-off data; and T o is the total duration of vehicle driving acceleration greater than 2 m / s 2 in the historical drop-off data.

[0073] The technical solution utilizes historical data of the pickers and droppers to perform dynamic analysis, and effectively filters accurate commuting data. According to the high-frequency acceleration state of the pickers and droppers in the historical driving process, the psychological state of the pickers and droppers is judged. In the driving process, if the high-speed acceleration ratio is high, it indicates that the picker and dropper are in a hurry for time, and thus it is reflected that the picker and dropper can bear a short maximum detour time. If the low acceleration ratio is high, it indicates that the picker and dropper is in a relaxed state for time, and thus it is reflected that the picker and dropper can bear a long maximum detour time. Through dynamic analysis and judgment on the historical pick-up data of the pickers and droppers, the maximum detour time that can be accepted by the pickers and droppers is output, the driving experience of the pickers and droppers is effectively improved, and the commuting efficiency is improved.

[0074] Advantages: Compared with the prior art, the present application has the following advantages:

[0075] The method of the present application considers the psychological endurance of the commuters on the way to work and the discomfort of the passengers in carpooling, and improves the success rate of carpooling pairing as much as possible under the restrictions of the acceptable travel time and detour time of the pickers and droppers. BRIEF DESCRIPTION OF DRAWINGS

[0076] Figure 1 The flowchart of the method of the present application.

[0077] Figure 2 The aggregated data case path result graph of the method of the present application.

[0078] Figure 3 The discrete data case path result graph of the method of the present application.

[0079] Figure 4 The mixed data case path result graph of the method of the present application. DETAILED DESCRIPTION

[0080] The technical solution of the present application is described in detail in combination with the drawings and embodiments

[0081] Embodiment one

[0082] A carpooling path matching method based on commuting travel, comprising the following steps:

[0083] Step 1: determining the carpooling matching parameters, including commuters, the number of commuters including the number of passengers p and the number of pickers and droppers g, the number of vehicles N, the maximum travel time D that can be accepted by the pickers and droppers max , the maximum detour time R that can be accepted by the pickers and droppers max , the waiting time t spent by each passenger s , and the penalty factor a;

[0084] Step 2: Determine the path matching selection of the pickup person g and the passenger p according to the position of the passenger p and the pickup person g;

[0085] The path matching selection determination method of the pickup person and the passenger in step 2 includes the following steps:

[0086] Step 21: To ensure that all commuters go to the destination, it is calculated as shown in formula (1):

[0087]

[0088] In the formula: S is the set of all nodes, S = {1, 2, …, p, …, g, n}, p is the number of passengers, g is the number of pickup persons, n is the total number of nodes, and the nth node is the destination; x ij is a 0-1 variable, which takes 1 to represent that the commuter moves from node i to node j, and takes 0 to represent that the commuter does not move from node i to node j;

[0089] It also includes calculating the commuter carpooling or going to the destination alone, and the commuter does not leave the destination again after arriving at the destination, which is calculated as shown in formula (2) and formula (3):

[0090]

[0091]

[0092] It also includes calculating the pickup person who does not return after leaving the location, which is calculated as shown in formula (4) and formula (5):

[0093]

[0094]

[0095] In the formula: G is the set of pickup persons, G = {p+1, p+2, …, g};

[0096] It also includes calculating the number of nodes that the passenger enters and exits no more than once, which is calculated as shown in formula (6) and formula (7):

[0097]

[0098]

[0099] In the formula: P is the set of passengers, P = {1, 2, …, p};

[0100] It also includes calculating the flow conservation of the nodes that the passenger enters and exits, which is calculated as shown in formula (8):

[0101]

[0102] wherein h is the vehicle serial number of the pickup.

[0103] Step 3: Determine the arrival order of the riders in the carpooling path according to the vehicle capacity N and the location of the commuters.

[0104] The method for determining the arrival order of the commuters in the vehicle path in Step 3 includes the following steps:

[0105] Step 31: Calculate the arrival order of each node to maintain consistency, which is calculated as shown in Equations (9) and (10):

[0106]

[0107]

[0108] wherein S is the set of all nodes, S = {1, 2, …, p, …, g, n}, p is the number of riders, g is the number of pickups, n is the total number of nodes, and the nth node is the destination; G is the set of pickups, G = {p+1, p+2, …, g}; u h,i is the arrival order of node i in the pickup h's path; M is the maximum value; x ij is a 0-1 variable, taking 1 to indicate that the commuter moves from node i to node j, and taking 0 to indicate that the commuter does not move from node i to node j;

[0109] It also includes calculating that the riders will not be the starting and ending points in the carpooling path, and the number of riders p carried by the vehicle will not exceed the vehicle capacity N, which is calculated as shown in Equations (11) and (12):

[0110]

[0111]

[0112] wherein P is the set of riders, P = {1, 2, …, p}; N is the vehicle capacity;

[0113] It also includes calculating that the pickups will be limited to the starting point of their carpooling path, which is calculated as shown in Equations (13) and (14):

[0114]

[0115]

[0116] Step 4: Calculate the arrival time of all nodes.

[0117] Step 4: Calculate the arrival time of all nodes.

[0118] Step 41: Calculate the path time and waiting time existing in the path, and the arrival time of the latter node is not earlier than the former node, which is calculated as shown in formula (15) and formula (16):

[0119]

[0120]

[0121] In the formula: S is the set of all nodes, S = {1, 2, …, p, …, g, n}, p is the number of passengers, g is the number of pickers, and n is the total number of nodes, where the nth node is the destination; G is the picker set, G = {p+1, p+2, …, g}; P is the passenger set, P = {1, 2, …, p}; is the arrival time of node i in the driving path of picker h; d ij is the Euclidean distance from node i to node j; v y is the driving speed of the picker's vehicle; t s is the waiting time spent by each passenger; u h,i is the arrival order of node i in the driving path of picker h; M is the maximum value; x ij is a 0-1 variable, taking 1 means that the commuter moves from node i to node j, and taking 0 means that the commuter does not move from node i to node j;

[0122] Also includes calculating the path time of the passenger in the uncompleted carpooling pairing, and the arrival time at the destination is later than the departure time, which is calculated as shown in formula (17) and formula (18):

[0123]

[0124]

[0125] In the formula: is the arrival time of passenger i who goes to node n by himself; v w is the speed of the passenger going to the destination by himself;

[0126] Also includes calculating the total travel time of the carpooling path and the total travel time of the passenger in the uncompleted carpooling pairing, which is calculated as shown in formula (19) and formula (20):

[0127]

[0128]

[0129] Step 5, according to the maximum travel time D max Limit the matching distance range of shared carpooling;

[0130] The restrictions of sharing the carpool matching range in step 5 include the following steps:

[0131] Step 51: Calculate the arrival time of the pickers before the specified time, and calculate the travel time of each carpool path that does not exceed the maximum travel time acceptable by the picker, which is calculated as shown in equation (21):

[0132]

[0133] In the formula: G is the set of pickers, G = {p+1, p+2, …, g}, p is the number of riders, and g is the number of pickers; is the arrival time of node i in the travel path of picker h; D max is the maximum travel time acceptable by the picker;

[0134] Also includes calculating the total detour time of each carpool path that does not exceed the maximum detour time acceptable by the picker, which is calculated as shown in equation (22):

[0135]

[0136] In the formula: d ij is the Euclidean distance from node i to node j; v y is the driving speed of the picker's vehicle; R max is the maximum detour time acceptable by the picker. The picker will not detour indefinitely to pick up riders based on the principle of "on the way".

[0137] Step 6: Repeat steps 2-5 to optimize the overall path matching with the goal of minimizing the total travel time of all commuters to the destination.

[0138] The optimization method of the overall path matching in step 6 includes the following steps:

[0139] Step 61: Calculate the goal of minimizing the total travel time, which is calculated as shown in equation (23):

[0140] max T = t y + αt w (23)

[0141] In the formula: T is the total travel time of all commuters to the destination; t y is the total time of all pickers to the destination; t w is the total time of riders who have not completed carpool pairing to the destination; α is the penalty factor. The discomfort of carpoolers increases with the increase of travel time, so the goal is to minimize the total travel time to reduce discomfort during travel.

[0142] In the process of implementing the above method, the embodiment generates three types of 100 node data, including aggregation, dispersion, and mixing. Taking the number of passengers p = 75, the number of pickers-up g = 25, the number of vehicles N = 4, the maximum travel time D max = 60 min, the maximum detour time R max = 20 min, the vehicle driving speed v y = 1 min / km of the pickers-up, the speed v w = 0.6 min / km of the passengers going to the destination by themselves, the waiting time t s = 2 min of each passenger, and the penalty factor a = 2.

[0143] Considering the uncertainty of the locations of the pickers-up and the passengers, different locations may have different effects on the carpooling. For the three types of 100 node data, the 25 nodes farthest and closest to the destination are selected as the locations of the pickers-up, and three groups of random locations of the pickers-up are generated, forming five groups of different location combinations to test the effects of different locations on carpooling. The discarded points are the passengers who do not complete the carpooling pairing. The calculation results and the number of discarded points of each group are shown in Table 1.

[0144] Table 1: Calculation results of each group

[0145]

[0146] As the number of passengers who do not complete the carpooling pairing decreases, the total travel time also decreases. The path results of the aggregation type data case of the farthest group are shown in Figure 1 , the path results of the dispersion type data case are shown in Figure 2 , and the path results of the R mixing type data case are shown in Figure 3 . The calculation results and the number of discarded points of the farthest group are much lower than those of the closest group. The farther the location of the pickers-up from the destination, the higher the probability of "on the way" when the passengers are picked up, the more the total time is reduced, and the better the carpooling pairing effect. When the location of the pickers-up is close to the destination, the location of the passengers is relatively farther from the destination, and the pickers-up need to "detour" to pick up the passengers, which is limited by the maximum detour time. Only a small part of the passengers can complete the carpooling pairing, and most of the commuters still have to go to the destination by themselves, resulting in poor carpooling effect. Comparing the three groups of randomly generated location combinations, the calculation results of the aggregation type data of random group 1 are worse than those of the closest group, and the calculation results of the aggregation type data and the mixing type data of random group 3 are better than those of the farthest group. The farther the location of the pickers-up from the destination, the better the carpooling effect is not necessarily true. The distribution and the relative location of the passengers will affect the results, especially in the aggregation type data, which is more obvious.

[0147] Embodiment Two

[0148] The embodiment is different from the embodiment one in that the maximum detour time R acceptable by the pick-up person is further collected max The method comprises:

[0149] S1, collecting historical pick-up data of the pick-up person, the historical pick-up data comprising the same pick-up destination; and collecting driving data of a vehicle state in the historical pick-up data of the pick-up person;

[0150] S2, screening effective historical pick-up data, the effective historical pick-up data comprising historical pick-up data arriving at the destination before a specified time node; the specified time node being determined according to a time point with the highest frequency of arrival at the destination in the historical pick-up data;

[0151] S3, screening a condition that a longest commuting time T min and a shortest commuting time T max in the effective historical pick-up data in S2; x max ; min ;

[0152] S4, the maximum detour time R max acceptable by the pick-up person x = T x *(1-G o )*100%, Gx=T p / T p , wherein T o is a total duration of vehicle driving in the historical pick-up data; and T 2 is a total duration of vehicle driving with an acceleration greater than 2 m / s in the historical pick-up data.

[0153] The technical solution utilizes historical data of the pick-up person for dynamic analysis, and accurately screens effective commuting data. The psychological state of the pick-up person is determined according to a high-frequency acceleration state in a historical driving process of the pick-up person. In the driving process, a high proportion of high-speed acceleration indicates that the psychological state of the pick-up person is anxious about time, and thus the maximum detour time acceptable by the pick-up person is short. A high proportion of low acceleration indicates that the psychological state of the pick-up person is relaxed about time, and thus the maximum detour time acceptable by the pick-up person is long. The embodiment dynamically analyzes the historical pick-up data of the pick-up person and determines the maximum detour time acceptable by the pick-up person, thereby effectively improving the driving experience of the pick-up person and improving commuting efficiency.

[0154] ​The above-mentioned are only embodiments of the present application, and the common knowledge of specific structures and characteristics in the scheme is not described too much. It should be pointed out that for those skilled in the art, without departing from the structure of the present application, a number of modifications and improvements can be made, which should also be considered as the protection scope of the present application, which will not affect the effect and practicality of the patent. The protection scope claimed in this application should be subject to the content of its claims, and the specific implementation mode and the like recorded in the specification can be used to explain the content of the claims.

Claims

1. A method for matching ride-sharing routes based on commuting, characterized in that, The method includes the following steps: Step 1: Determine the matching parameters for ride-sharing, including the number of commuters, which includes the number of passengers. Number of pick-up and drop-off passengers Vehicle passenger capacity The maximum travel time that the pick-up / drop-off person can accept. The maximum detour time that the pick-up and drop-off passengers can accept. The waiting time for each passenger Punishment factor ; Step 2: Based on the number of passengers Number of pick-up and drop-off passengers Based on the geographical location, determine the route matching selection for the pick-up person and the passenger; Step 3: Based on the vehicle's passenger capacity Based on the commuter's location, determine the arrival order of passengers along the ride-sharing route; Step 4: Calculate the arrival time of all nodes; Step 5: Determine the maximum travel time acceptable to the pick-up / drop-off person. Limit the matching distance range for shared rides; Step 6: Repeat steps 2-5 to optimize the overall route matching with the goal of minimizing the total travel time for all commuters to reach their destinations; The method for determining the route matching and selection of pick-up and drop-off passengers in step 2 includes the following steps: Step 21: To ensure that all commuters reach their destination, the calculation is as shown in equation (1): （1） In the formula: For the set of all nodes, , Let be the total number of nodes, where the th is the th . The point is the destination; It is a 0-1 variable, with a value of 1 indicating that the commuter comes from the node. Move to node A value of 0 indicates that the commuter did not depart from the node. Move to node ; It also includes calculating whether commuters travel to their destination alone or share a ride, and whether the commuters do not leave after arriving at their destination. The calculation is shown in equations (2) and (3): （2） （3） It also includes the calculation that the pick-up / drop-off person will not return after leaving the location, as shown in equations (4) and (5): （4） （5） In the formula: Gather for those picking up or dropping off. ; It also includes calculating that the passenger's entry and exit points will not exceed once, as shown in equations (6) and (7): （6） （7） In the formula: Gather for passengers. ; It also includes calculating the flow conservation at the passenger entry and exit nodes, as shown in equation (8): （8） In the formula: The vehicle number for the person picking up or dropping off; The method for determining the arrival order of commuters along the vehicle's travel route in step 3 includes the following steps: Step 31: Calculate the arrival order of each node to ensure consistency. The calculation is shown in equations (9) and (10): （9） （10） In the formula: For the set of all nodes, , Let be the total number of nodes, where the th is the th . The point is the destination; Gather for those picking up or dropping off. ; For pick-up and drop-off In the driving path, nodes The order of arrival; It is the maximum value; It is a 0-1 variable, with a value of 1 indicating that the commuter comes from the node. Move to node A value of 0 indicates that the commuter did not depart from the node. Move to node ; It also includes calculating the number of passengers who will not be the origin or destination of the ride-sharing route, and the number of passengers carried in the vehicle. It will not exceed the vehicle capacity N, and its calculation is shown in equations (11) and (12): （11） （12） In the formula: Gather for passengers. ; For vehicle passenger capacity; It also includes calculating the starting point of the ride-sharing route to restrict the pick-up and drop-off person to the same point, as shown in equations (13) and (14): （13） （14）。 2. The method for matching ride-sharing routes based on commuting trips according to claim 1, characterized in that, Step 4, calculating the arrival time of all nodes, includes the following steps: Step 41: Calculate the path time and waiting time in the carpooling route, ensuring that the arrival time of the next node is not earlier than that of the previous node. The calculation is shown in equations (15) and (16): （15） （16） In the formula: For the set of all nodes, , Let be the total number of nodes, where the th is the th . The point is the destination; Gather for those picking up or dropping off. ; Gather for passengers. ; For pick-up and drop-off In the driving path, nodes The arrival time; For nodes To the node Euclidean distance; The speed of the vehicle used by the person picking up or dropping off; The waiting time spent to pick up each passenger; For pick-up and drop-off In the driving path, nodes The order of arrival; It is the maximum value; It is a 0-1 variable, with a value of 1 indicating that the commuter comes from the node. Move to node A value of 0 indicates that the commuter did not depart from the node. Move to node ; It also includes calculating the travel time of passengers who have not completed ride-sharing pairings and whose arrival time at the destination is later than their departure time, as shown in equations (17) and (18): （17） （18） In the formula: For passengers who have not completed ride-sharing pairing Go to the node yourself The arrival time; The speed at which passengers travel to their destination on their own. It also includes calculating the total travel time of the ride-sharing route and the total travel time of passengers who did not complete the ride-sharing pairing, as shown in equations (19) and (20): （19） （20）。 3. The method for matching ride-sharing routes based on commuting trips according to claim 1, characterized in that, The limitations on the shared ride-sharing matching range in step 5 include the following steps: Step 51: Calculate the arrival time of the pick-up and drop-off person before the specified time, and calculate the travel time of each carpooling route to be no more than the maximum travel time acceptable to the pick-up and drop-off person. The calculation is shown in Equation (21): （21） In the formula: Gather for those picking up or dropping off. ; For pick-up and drop-off In the driving path, nodes The arrival time; The maximum travel time that the pick-up / drop-off person can accept; It also includes calculating that the total detour time for each ridesharing route does not exceed the maximum detour time acceptable to the pick-up and drop-off passengers, as shown in equation (22): （22） In the formula: For nodes To the node Euclidean distance; The speed of the vehicle used by the person picking up or dropping off; This represents the maximum detour time that the person picking up or dropping off can accept.

4. The method for matching ride-sharing routes based on commuting trips according to claim 1, characterized in that, The overall path matching optimization method in step 6 includes the following steps: Step 61: Calculate the total travel time with the objective of minimizing the total travel time, as shown in equation (23): （23） In the formula: The total travel time for all commuters to reach their destination; The total time for all pick-ups and drop-offs to reach their destination; The total time for passengers who did not complete a ride-sharing pairing to reach their destination; This is a penalty factor.

5. A method for matching ride-sharing routes based on commuting trips according to any one of claims 1-4, characterized in that, It also includes collecting the maximum detour time that the pick-up and drop-off personnel can accept. Methods, including: S1, collect historical pick-up and drop-off data of the pick-up and drop-off users, including the same pick-up and drop-off users with the same destination; it also includes the driving data of the vehicle status in the historical pick-up and drop-off data of the pick-up and drop-off users. S2, filter valid historical pick-up and drop-off data. Valid historical pick-up and drop-off data includes historical pick-up and drop-off data that arrived at the destination before a specified time point; the specified time point is the time point with the highest frequency of arrival at the destination in the historical pick-up and drop-off data. S3, the filtering criterion is the longest commute time T among the valid historical pick-up and drop-off data in S2. min With the shortest commute time T max Calculate the time difference T between the longest and shortest commuting time. x =T max -T min ; S4, the maximum detour time acceptable to the pick-up / drop-off person. =T x *(1-G x )*100%, G x =T o / T p T p The total driving time of vehicles in historical pick-up and drop-off data; T o For historical pick-up and drop-off data, the vehicle's acceleration is greater than 2 m / s². 2 Total duration.

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