A bus riding route planning method based on human-vehicle-road cooperation

Abstract

The application discloses a bus riding route planning method based on human-vehicle-road cooperation and belongs to the cross-application field of intelligent networked public transport system design. The method comprises the following steps: collecting passenger external origin-destination point demand data, real-time road condition data, bus station GIS data and road network GIS data; associating the external origin-destination point with the nearby bus station according to the passenger external origin-destination point demand data and the bus station GIS data; estimating the walking transfer time between the external origin-destination point and the corresponding bus station; sequentially connecting the bus stations associated with the external origin-destination point based on the shortest path principle to obtain the bus driving path; constructing an optimization model, with the target being the minimum total passenger travel time and the constraint condition being that the passengers only board from the bus stations associated with the external origin-destination point; and solving the optimization model to obtain the time and position information of the boarding and alighting bus stations.

Description

Technical Field

[0001] This invention relates to the cross-application field of intelligent connected public transportation system design, specifically to a bus route planning method based on human-vehicle-road collaboration. Background Technology

[0002] Intelligent connected buses rely on Internet of Things (IoT) technology to connect basic attributes such as people, vehicles, and roads, thereby maximizing the ability to plan bus routes and stops in real time based on passenger needs, thus improving the passenger travel experience and increasing travel efficiency.

[0003] The collaboration between people and vehicles can be achieved through a mobile app. When passengers have travel needs, they submit their requests through the app, and the backend system receives and processes these requests before allocating a vehicle. The collaboration between vehicles and roads involves obtaining real-time traffic information to optimize vehicle route planning, ensuring that vehicles travel on the most efficient routes.

[0004] How to rationally allocate passengers to appropriate bus stops is a key factor in the efficient operation of intelligent connected bus systems. A reasonable allocation scheme can effectively reduce passengers' travel time and improve the service level and profitability of intelligent connected buses. Therefore, exploring a bus passenger route planning method based on human-vehicle-road collaboration has significant practical implications.

[0005] In existing technological inventions, in terms of data acquisition, most rely on historical data to obtain passenger travel demand; while in terms of passenger waiting station allocation, most adopt clustering-based methods, mainly considering the relationship between passengers and nearby stations.

[0006] Shortcomings of existing methods or inventions:

[0007] (1) There is currently no publicly available passenger allocation method that is directly applicable to intelligent connected bus systems;

[0008] (2) The accuracy of the origin and destination locations of the demand data is insufficient, making it difficult to accurately quantify the distance between the passenger's origin and destination and nearby stations;

[0009] (3) Only the passenger connection distance or connection time is considered, without considering the total travel time. Summary of the Invention

[0010] To address the aforementioned shortcomings, this invention constructs a bus route planning method based on human-vehicle-road collaboration. This method fully considers parameters at each stage of the passenger's journey, including connection times, in-vehicle conditions, and other scenarios. It also uses a mobile app for location tracking to obtain the passenger's actual origin and destination information. Combined with bus stop layout information, it precisely quantifies the distance between the origin / destination points and nearby bus stops. The objective of this invention can be achieved through the following technical solutions:

[0011] A first aspect of the present invention relates to a bus route planning method, comprising the following steps:

[0012] Data on passenger demand at origin and destination points outside bus stops, real-time traffic data, bus stop GIS data, and road network GIS data are collected.

[0013] Passenger demand data at external origin and destination points is combined with GIS data from bus stops to link these external origin and destination points with nearby bus stops.

[0014] Estimate the walking transfer time for passengers between external origin and destination points and corresponding bus stops;

[0015] Based on the shortest path principle, bus stops that are associated with external origin and destination points are connected in an orderly manner to obtain the bus driving path;

[0016] Construct an optimization model with the goal of minimizing the total travel time for all passengers, under the constraint that passengers only board the bus at bus stops associated with the external origin and destination.

[0017] Solve the optimization model to obtain the time and location information of bus stops for boarding and alighting.

[0018] Optionally, the method for associating external origin and destination points with nearby public transport stops includes the following steps:

[0019] Step 1: Using each external origin and destination point as the center, form a circular area and obtain the bus stops within the circular area;

[0020] Step 2: If the number of corresponding bus stops is greater than 0 and does not exceed 3, then all of these bus stops will be used as associated bus stops for this external origin and destination.

[0021] If the number of corresponding bus stops exceeds 3, calculate the distance between the bus stops involved and the external origin and destination, sort them in ascending order of distance, and take the 3 bus stops with the closest distance.

[0022] If the number of bus stops is 0, then take the bus stop that is closest to the external origin and destination from all the bus stops in the external origin and destination demand data.

[0023] Step 3: Repeat steps 1 and 2 until all external origins and destinations are associated with bus stops.

[0024] Optionally, the method for estimating walking connection time includes the following steps:

[0025] Let L be the length of the shortest walking path between an external origin and destination point i and its associated bus stop m. imTaking the average walking speed of adults as a fixed value v, the walking time for a person from the external starting point i to the destination m is: In the formula, I is the total number of external origin and destination points, and N is the total number of external origin and destination points. i p is the number of bus stops associated with the external origin and destination point i. im q represents the number of passengers who walk from external starting point i to bus stop m, corresponding to the process of traveling to the bus stop. mi It represents the number of passengers who walk from bus stop m to external starting and ending points i, corresponding to the process of getting off the bus and heading to their destination.

[0026] Optionally, the method for constructing the optimization model includes the following steps:

[0027] Let T be the travel time of the vehicle between stations x and x+1. x,x+1 The time passengers get on and off at station x

[0028]

[0029] Among them, t up t represents the average boarding time per passenger. down To represent the average time each passenger spends getting off the bus, the number of passengers boarding at station x is: The number of passengers getting off the bus is

[0030] Therefore, the duration of a passenger's stay on the bus is:

[0031] Among them, P ix,jn For each external origin and destination point i matched to a bus departure station x, and for each external arrival point j matched to a bus arrival station n, N b This refers to the number of bus stops.

[0032] The estimated passenger transfer time is: L ix Match the distance from the external origin and destination point i to the bus departure station x; L jn Match the distance from external arrival point j to bus arrival station n;

[0033] The optimal model is obtained by adding the passenger's time on the bus to the estimated passenger transfer time:

[0034]

[0035] The constraint is: 0 ≤ P ix,jn ≤A ij A ij This indicates the demand between external origin and destination points.

[0036] Optionally, the method for solving the optimization model includes the following steps:

[0037] Step 1: Set the initial state so that passengers from each external point gather at the nearest bus stop, and obtain the initial total travel time value f0 for all passengers;

[0038] Step 2: Randomly allocate passengers from external point i (where bus stop x is clustered) to other bus stops corresponding to point i, ensuring that this allocation has never occurred before. Recalculate the total travel time for all passengers, denoted as f. z If f z If the value is less than f0, the current passenger allocation scheme replaces the initial scheme. For each better scheme, the number of passengers allocated to each bus stop is compared. If the number of passengers allocated is greater than the replaced scheme, the number of passengers in subsequent allocations will be guaranteed to be no less than that value. If it is less than that value, the number of passengers in the next allocation will be guaranteed to be no greater than that value. Otherwise, the initial scheme is retained.

[0039] Step 3: Repeat step 2 until the maximum number of state transitions is reached. The better solution obtained at this point is the optimal solution.

[0040] Optionally, the radius of the circular area is 300 meters.

[0041] A second aspect of the present invention relates to a computer-readable storage medium storing instructions that, when executed, enable the above-described bus route planning method.

[0042] A third aspect of the present invention relates to a mobile terminal, comprising the aforementioned storage medium and a processor, wherein the processor is configured to read and execute instructions in the storage medium.

[0043] The beneficial effects of this invention are:

[0044] (1) The bus route planning method proposed in this invention can take into account the influencing factors related to the connection and time spent in the vehicle during the entire passenger's journey, which is closer to actual operation and has enhanced practicality and scientificity.

[0045] (2) The optimization model solving algorithm proposed in this invention can minimize the overall travel time of passengers in the system within limited computing resources and time, while ensuring that most passengers have the shortest connection time, thereby improving the operating efficiency of public transportation. Attached Figure Description

[0046] The invention will now be further described with reference to the accompanying drawings.

[0047] Figure 1 A flowchart illustrating the implementation of the bus route planning method based on human-vehicle-road collaboration provided by this invention;

[0048] Figure 2 The data provided in this embodiment of the invention includes the distribution of external origin and destination points of passengers, nearby bus stops, and the shortest path map connecting these stops. Detailed Implementation

[0049] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] In one specific embodiment, a bus route planning method based on human-vehicle-road cooperation is provided, such as... Figure 1 As shown, the specific steps are as follows:

[0051] S1, Data Acquisition

[0052] Collect passenger demand data, real-time traffic data, and GIS (Geographic Information System) data on bus stops and road networks. The distribution of external origin and destination points for passenger demand is as follows: Figure 2 The circles indicate the distribution of nearby bus stops and road networks as follows: Figure 2 As shown by triangles and polylines, the demand OD matrix of passengers at external origin and destination points outside the bus stop is statistically obtained as A. The OD between any two external origin and destination points i and j is denoted as A0. ij For ease of description, we only retain the OD in one general direction, namely the 18 external demand points in the example, arranged in order from west to east. All passengers are traveling eastward, and we do not consider the case of traveling westward.

[0053] S2, Preliminary matching of bus stops

[0054] Using the outer starting and ending points as the center and a radius of 300 meters, select the three bus stops closest to the center within this radius as initial stops. If there is no bus stop within 300 meters, select the nearest bus stop. The resulting distribution of potentially involved bus stops is as follows: Figure 2 As shown, a total of 20 stations are involved. The correspondence between the external origin and destination points and the bus stops is shown in Table 1:

[0055] Table 1 Initial Correspondence between External Origin and Destination Points and Bus Stops

[0056]

[0057]

[0058] It should be noted that the circular range with a radius of 300 meters mentioned above is merely an example of this specific embodiment. The radius value or size of the range can be set and changed according to the needs of the user group or user to fit the actual usage scenario, and is therefore not limited to a circular range with a radius of 300 meters.

[0059] S3, Estimated Passenger Walking Transfer Time

[0060] Estimate the walking time of passengers between external origin and destination points and corresponding bus stops. For example, if the shortest path distance between external origin and destination point a1 and bus stop b1 is 271 meters, and the average walking speed of an adult is taken as 1.2 meters / second, then the time it takes for a passenger to walk from a1 to b1 or from b1 to a1 is approximately 3.8 minutes.

[0061] S4, connecting bus stops

[0062] Connect the 20 stations in order using the shortest path, such as Figure 2 As shown;

[0063] S5, Real-time travel time estimation of vehicles between bus stops

[0064] Based on real-time traffic information, the travel time of a bus between two adjacent bus stops is estimated. For example, if the path length between bus stops b1 and b2 is 455 meters, and the road conditions between b1 and b2 are good when the bus reaches b1, then the average bus speed is assumed to be 20 km / h. In this case, the travel time T is calculated. b1,b2 ≈1.4 minutes; however, when encountering intersections and the vehicle speed is below 20km / h, such as 12km / h, the time T to pass through is approximately 1.4 minutes. b1,b2 ≈2.3 minutes;

[0065] S6. Optimization Model Construction

[0066] Step 1: Estimate the time passengers spend on the vehicle. This time can be divided into two parts: the vehicle's travel time and the time the vehicle spends at stops waiting for passengers to board and alight. The travel time between stops x and x+1 is denoted as T. x,x+1 The time passengers get on and off at station x The following formula can be used to calculate:

[0067]

[0068] Among them, t up t represents the average boarding time per passenger. down To represent the average time each passenger spends getting off the bus, the number of passengers boarding at station x is: The number of passengers getting off the bus is

[0069] Therefore, the duration of a passenger's time on the bus can be expressed as: Among them, P ix,jn For each external origin-destination point i matched to a bus departure station x, and for each external origin-destination point j matched to a bus arrival station n, N b This refers to the number of bus stops.

[0070] Step 2: Estimate passenger transfer time.

[0071] Step 3: Combining Step 1 and Step 2, the optimal model is obtained as follows:

[0072]

[0073] The constraint is: 0 ≤ P ix,jn ≤A ij A ij This represents the demand between external origin and destination points, specifically the travel demand from point i to point j.

[0074] S7. Model Solution Method Design

[0075] Step 1: Set the initial state so that passengers from each external origin and destination gather at the nearest bus stop, i.e., P. im,jn =A ij The purpose of this is to ensure that the walking connection time is minimized, thus obtaining the initial total travel time value f0 for all passengers. In this example, the bus stops and corresponding passenger numbers for each external origin and destination point in the initial state are shown in Table 2:

[0076] Table 2 Initial Passenger Allocation at External Origin and Destination Points and Bus Stops

[0077]

[0078] Step 2: Passenger allocation state transition. Based on the previous state, randomly assign passengers from external origin-destination point i gathered at bus stop m to other bus stops corresponding to point i, ensuring that this scheme has never occurred before. Recalculate the total travel time for all passengers, denoted as f. z If f z If the value is less than f0, the current passenger allocation scheme replaces the initial scheme. For each better scheme, the number of passengers allocated to each bus stop is compared. If the number of passengers allocated is greater than the replaced scheme, the number of passengers in subsequent allocations will be guaranteed to be no less than that value. If it is less than that value, the number of passengers in the next allocation will be guaranteed to be no greater than that value. Otherwise, the initial scheme is retained.

[0079] Step 3: Repeat step 2 until the maximum number of repetitions is reached, which is set to 500 here;

[0080] Step 4: Output the optimal solution. The results are shown in Table 3.

[0081] Table 3 Optimal Passenger Allocation for External Origin and Destination Points and Bus Stops

[0082]

[0083]

[0084] S8. Information Feedback:

[0085] According to the optimal solution, relevant passengers will be notified of their boarding and alighting station information, as well as the arrival time of the bus at the relevant station, via a mobile app for their reference.

[0086] In other examples of the present invention, a mobile terminal is disclosed for implementing the bus route planning method in the above embodiments. The route planning method in the above embodiments can be stored in the mobile terminal in the form of instructions. Specifically, the mobile terminal can be an electronic device carried for use when out and about, more specifically, it can be, but is not limited to, mobile phones, laptops, tablets, pagers, and other devices with storage or communication functions. In addition, users can input their needs on the mobile terminal, and the corresponding planned route can be generated in real time, or a pre-set or stored planned route can be displayed on the terminal device.

[0087] In the description of this specification, references to terms such as "an embodiment," "example," "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0088] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The embodiments and descriptions in the specification are merely illustrative of the principles of the invention. Various changes and modifications can be made to the invention without departing from its spirit and scope, and all such changes and modifications fall within the scope of the claimed invention.

Claims

1. A method for planning bus routes, comprising the following steps: Collect passenger demand data at origin and destination points outside bus stops, real-time traffic data, bus stop GIS data, and road network GIS data; Based on passenger demand data at external origin and destination points and GIS data of bus stops, external origin and destination points are associated with nearby bus stops; Estimate the walking transfer time for passengers between external origin and destination points and corresponding bus stops; Based on the shortest path principle, bus stops that are associated with external origin and destination points are connected in an orderly manner to obtain the bus driving path; Construct an optimization model with the goal of minimizing the total travel time for all passengers, under the constraint that passengers only board the bus at bus stops associated with the external origin and destination. Solve the optimization model to obtain the time and location information of the bus stops for boarding and alighting; The method for constructing the optimization model includes the following steps: Assume the vehicle is at the station x and x+1 The travel time between them is recorded as Passengers x Station boarding and alighting time : in, The average boarding time per passenger. To represent the average time each passenger spends getting off the bus, the number of passengers boarding at station x is: The number of passengers getting off the bus is ; Therefore, the duration of a passenger's stay on the bus is: in, External origin and destination i Matched to bus departure station x Simultaneously, external arrival points j Matched bus arrival stations n The number of passengers, This refers to the number of bus stops. The estimated passenger transfer time is: ; v The average walking speed of an adult; L ix External origin and destination i Match the distance to the bus departure station x; L jn External arrival point j Matched bus arrival stations n The distance; The optimal model is obtained by adding the passenger's time on the bus to the estimated passenger transfer time: The constraints are: , This indicates the demand between external origin and destination points; The method for solving the optimization model includes the following steps: Step 5-1: Set the initial state so that passengers from each external location gather at the nearest bus stop, and obtain the initial total travel time value for all passengers. ; Step 5-2: Place the bus stop x Passengers at the gathered external point i are randomly assigned a number that is a multiple of 1 / 5 and rounded down. i For other bus stops corresponding to the location, and ensuring that this plan has never appeared before, recalculate the total travel time for all passengers, and record it as follows. ;like If the current passenger allocation scheme is used, the initial scheme is replaced. For each better scheme, the number of passengers allocated to each bus stop is compared. If the number of passengers allocated is greater than the replaced scheme, the number of passengers in subsequent allocations will be guaranteed to be no less than that value. If it is less, the number of passengers in the next allocation will be guaranteed to be no greater than that value. Otherwise, the initial scheme is retained. Step 5-3: Repeat step 5-2 until the number of repetitions reaches the set maximum number of state transitions. The better solution obtained at this point is taken as the optimal solution.

2. The bus route planning method according to claim 1, characterized in that, The method for associating external origin and destination points with nearby public transport stops includes the following steps: Step 1: Using each external origin and destination point as the center, form a circular area and obtain the bus stops within the circular area; Step 2: If the number of corresponding bus stops is greater than 0 and does not exceed 3, then all of these bus stops will be used as associated bus stops for this external origin and destination. If the number of corresponding bus stops exceeds 3, calculate the distance between the bus stops involved and the external origin and destination, sort them in ascending order of distance, and take the 3 bus stops with the closest distance. If the number of bus stops is 0, then take the bus stop that is closest to the external origin and destination from all the bus stops in the external origin and destination demand data. Step 3: Repeat steps 1 and 2 until all external origins and destinations are associated with bus stops.

3. The bus route planning method according to claim 1, characterized in that, The method for estimating walking connection time includes the following steps: Record the external origin and destination points i Related bus stops m The shortest walking path length between them is Then a person's origin and destination are external. i arrive m The walking time is , In the formula, This is the total number of external origin and destination points. External origin and destination i The number of associated bus stops, It is from the external starting and ending point. i Walk to the bus stop m The number of passengers corresponds to the process of getting to the destination. From the bus stop m Walk to the external starting and ending points i The number of passengers corresponds to the process of getting off the bus and going to the destination.

4. The bus route planning method according to claim 2, characterized in that, The radius of the circular area is 300-500 meters.

5. A computer-readable storage medium storing instructions, characterized in that, When the instruction is executed, it can realize the bus route planning method according to any one of claims 1 to 4.

6. A mobile terminal, comprising the storage medium of claim 5, and further comprising a processor, the processor being configured to read and execute instructions in the storage medium.

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