Bus transfer line network construction method and system, electronic equipment and storage medium

Abstract

The invention relates to a bus transfer line network construction method and system, electronic equipment and a storage medium, and the method comprises the steps: planning a reference line and total time according to the initial position of a passenger, planning a candidate line set in combination with the actual demand condition of the passenger, screening out the candidate line set meeting the requirements from the operation condition, and carrying out the construction of a bus transfer line network. The method comprises the following steps: when a passenger transfers according to a pushed route, calculating a route which consumes the least time in advance at a transfer node in a riding process, pushing a real-time recommended route and an alternative route to the passenger, and pushing a route which can be replaced on the transfer node to the passenger, so that the transfer time of the passenger in a journey is shortened, and the travel efficiency of the passenger is improved. And the actual use time of passengers on the bus is less.

Description

Technical Field

[0001] This application relates to the field of public transport interchange network construction technology, and in particular to public transport interchange network construction methods, systems, electronic devices, and storage media. Background Technology

[0002] With the advancement of urbanization and the increase in urban population, coupled with the increasingly severe traffic congestion and soaring oil prices, efficient and affordable public transportation has become the demand and aspiration of the vast majority of urban residents. Surveys indicate that most bus passengers require at least one transfer, resulting in a large number of passengers needing to change buses.

[0003] When passengers use public transportation, unpredictable waiting times and significant differences in departure times between lines at transfer points can lead to transfer time accounting for a large proportion of the total travel time, resulting in a longer overall journey than expected and thus increasing the travel time for passengers. Summary of the Invention

[0004] The technical problem this application aims to solve is that when passengers use public transportation, various situations can lead to excessive transfer time, which accounts for a large proportion of the total travel time, resulting in a longer overall journey than expected and thus increasing the travel time for passengers.

[0005] In order to solve the above problems, or at least partially solve the above technical problems, this application provides a method, system, electronic device, and storage medium for constructing a public transport interchange network.

[0006] In a first aspect, the present invention discloses a method for constructing a public transport interchange network, which includes the following steps: Based on the initial data, the baseline route and the total route duration are determined to obtain the baseline route and the first duration. The initial data includes OD demand data, bus network static data, bus historical operation data, and road characteristic data. The preprocessed data includes passenger station association data set and historical operation data set. The process involves acquiring constraint data and route operation data, planning a candidate route set based on the constraint data, and then filtering the candidate route set based on the route operation data to obtain a filtered route set. The route operation data includes statistics on repeated stops, historical passenger flow data for transfer nodes, and unit mileage cost data. The constraint data includes passenger transfer frequency data, transfer route connection efficiency data, route runtime data, route passenger flow data, and route stop coverage data. The filtered set of routes is used to construct a transfer network. The transfer network is sorted according to time sequence, and the first preset number of routes with the shortest total travel time are pushed to passengers. Passengers can choose routes to take according to their actual needs. Before a passenger reaches the transfer node, real-time parameter data is acquired. Based on the real-time parameter data, the remaining time for each route in the filtered route set is calculated. Based on the remaining time, the shortest route and a preset number of alternative routes are selected to obtain real-time recommended routes and alternative routes.

[0007] Preferably, the following steps are then included: The system recommends routes to passengers in real time, records the adjustment results, and updates the filtered route set based on the adjustment results after a preset time or a preset number of rides.

[0008] Preferably, the step of determining the baseline route and calculating the total route duration based on initial data to obtain the baseline route and the first duration specifically includes the following steps: Obtain the origin coordinates, destination coordinates, and travel volume for each time period of passenger trips, and classify them as OD demand data; The system obtains static and historical operational data of the public transport network in the city where the passenger is currently located from the urban transportation big data platform. The road grade, time-based congestion coefficient, and congestion time division standards of the route segments are obtained from the urban traffic monitoring platform and categorized into road characteristic data. The initial data is preprocessed to obtain preprocessed data. With the goal of minimizing the total travel cost for passengers, the optimal route is determined based on the preprocessed data to obtain the baseline route. The time taken on the baseline route is then calculated to obtain the first duration.

[0009] Preferably, the steps of acquiring constraint data and route operation data, planning a candidate route set based on the constraint data, and filtering the candidate route set based on the route operation data to obtain a filtered route set specifically include the following steps: Obtain constraint data, construct an integer programming model based on the constraint data, generate candidate routes that meet the constraint data, and integrate the candidate routes with their durations to obtain a candidate route set. The operation data of the routes is obtained, and the routes in the candidate route set are screened by combining the operation data of the routes with the candidate route set. The routes are screened from three aspects: route duplication rate, transfer node capacity, and route operation cost, and the filtered route set is obtained.

[0010] Preferably, the process of filtering the candidate routes by combining the operational data of the routes with the candidate route set specifically includes the following steps: Calculate the overlap rate between any two candidate routes, eliminate the route with the longer total time, and keep the route with the shorter total time to obtain the route with the shorter time. For routes with short travel times, query the historical maximum passenger flow data of transfer nodes, and remove routes whose historical maximum passenger flow of transfer nodes exceeds the preset rated capacity to obtain routes with low capacity. Calculate the unit mileage operating cost of candidate routes, eliminate routes with average operating costs higher than the preset cost, and obtain the filtered routes.

[0011] Preferably, the passenger selects a route from the filtered route set. A preset time before the passenger reaches the transfer point, real-time parameter data is acquired. Based on the real-time parameter data, the remaining time for each route in the filtered route set is calculated. The shortest route and a preset number of alternative routes are selected based on the remaining time to obtain a real-time recommended route and alternative routes. Specifically, this includes the following steps: The system selects the optimal route from the filtered route set and pushes it to the passenger for boarding. When the passenger is on the bus, real-time location, traffic conditions and passenger flow data are collected at a preset time before arriving at the transfer node to obtain real-time parameter data. The estimated arrival time to the destination is calculated based on real-time parameter data, the arrival time of the transfer route is corrected, the passenger flow situation of the transfer node is obtained based on passenger flow data, the congestion level is classified, and the transfer node with overcapacity is marked to obtain real-time constraints; the real-time constraints include the estimated arrival time, the corrected arrival time of the transfer route, and the passenger flow overcapacity data. The filtered route set is processed according to real-time constraints. The remaining travel time of the routes that meet the requirements is calculated. The routes are sorted according to the length of time, and the shortest route is used as the real-time recommended route. A preset number of routes at the top of the list are used as candidate routes.

[0012] Preferably, the step of filtering the selected route set according to real-time constraints, calculating the remaining travel time for routes that meet the real-time constraints, sorting them according to their travel time, and using the shortest route as the real-time recommended route, with a preset number of routes at the top of the list as candidate routes, specifically includes the following steps: From the filtered routes, extract all routes that pass through the current transfer node or alternative transfer nodes as candidate routes; According to the optimization target formula, calculate the remaining time of each candidate route one by one, and record its transfer waiting time and congestion level at the same time; Eliminate candidate routes where the transfer waiting time at transfer nodes exceeds the first preset time or the congestion level at transfer nodes exceeds the first preset threshold, and retain compliant routes. Among compliant routes, the route with the shortest remaining duration is selected as the real-time recommended route, while a first preset number of suboptimal routes are retained as alternative routes.

[0013] Secondly, the present invention discloses a public transport interchange network construction system, which includes the above-mentioned public transport interchange network construction method.

[0014] Thirdly, the present invention discloses an electronic device, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the above-described method for constructing a public transport interchange network.

[0015] Fourthly, the present invention discloses a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method for constructing a public transport interchange network.

[0016] The technical solution provided in this application has the following advantages compared with the prior art: The public transport transfer network construction method, system, electronic equipment, and storage medium provided in this application include a method that plans a baseline route and total travel time based on the passenger's starting location, plans a set of candidate routes based on the passenger's actual needs, selects suitable candidate routes from operational data, and allows passengers to transfer according to the recommended routes. During the journey, at the transfer nodes, the system calculates the route with the shortest travel time in advance and pushes real-time recommended routes and alternative routes to the passenger, reducing transfer time and allowing passengers to spend less time on public transport. Attached Figure Description

[0017] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with the invention and, together with the description, serve to explain the principles of the invention.

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 A flowchart illustrating a method for constructing a public transport interchange network provided in this application; Figure 2 A flowchart illustrating step S1 in a public transport interchange network construction method provided in this application; Figure 3 A flowchart illustrating step S2 in a public transport interchange network construction method provided in this application; Figure 4 A flowchart illustrating step S22 in a public transport interchange network construction method provided in this application; Figure 5 A flowchart illustrating step S4 in a public transport interchange network construction method provided in this application; Figure 6 This is a flowchart illustrating step S42 of a public transport interchange network construction method provided in this application. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0021] Firstly, see Figures 1-6 This invention discloses a method for constructing a public transport interchange network, which includes the following steps: Step S1: Determine the baseline route and calculate the total route duration based on the initial data to obtain the baseline route and the first duration; the initial data includes OD demand data, bus network static data, bus historical operation data, and road characteristic data, and the preprocessed data includes passenger station association data set and historical operation data set; Step S2: Obtain constraint data and route operation data; plan a candidate route set based on constraint data; filter the candidate route set based on route operation data to obtain a filtered route set; the route operation data includes route duplicate station statistics, historical passenger flow data of transfer nodes, and unit mileage cost data; the constraint data includes passenger transfer frequency data, transfer route connection efficiency data, route running time data, route passenger flow data, and route station coverage data. Step S3: The filtered route set is used to construct a transfer network. The transfer network is sorted according to time sequence, and the first preset number of routes with the shortest total travel time are pushed to passengers. Passengers can select routes to take according to their actual needs. Step S4: Before the passenger is at the transfer node, real-time parameter data is acquired. Based on the real-time parameter data, the remaining time of each route in the filtered route set is calculated. Based on the remaining time, the shortest route and a preset number of alternative routes are selected to obtain the real-time recommended route and alternative routes.

[0022] Specifically, in step S1, OD demand data, bus network static data, historical bus operation data, and road characteristic data are first collected. OD demand data includes passenger origin coordinates, destination coordinates, and time-of-day travel volume. Bus network static data includes route names, stops and coordinates, and distances between stops. Historical bus operation data includes time-of-day average speed, departure intervals, and historical transfer waiting times. Road characteristic data includes time-of-day congestion coefficients and road grades. Then, the initial data is preprocessed to form two core data sets: a passenger station association data set and a historical operation data set. The passenger station association data set includes matching passenger origins, destinations, and the nearest bus stops. The historical operation data set includes average speed data after outlier removal and missing value completion, and departure interval data after processing. Finally, based on the preprocessed data, a baseline route is determined using a path search algorithm, and the total duration of the baseline route is calculated as the first duration. For example, using Dijkstra's algorithm, the baseline route under the current conditions is determined with the goal of minimizing the total cost of walking, taking a bus, and transferring. The total duration of the baseline route is calculated based on the quantitative logic of walking time at the starting point + segmented bus time + segmented transfer waiting time + walking time at the destination.

[0023] Specifically, in step S2, firstly, constraint data and route operation data are acquired. Constraint data includes data on the upper limit of passenger transfer times, transfer route connection efficiency, route runtime limits, route passenger flow matching data, and route station coverage data. This constraint data can be obtained from passenger input data and the public transport operation big data platform. In this embodiment, the upper limit of passenger transfer times can be set to less than or equal to 2 times; the transfer route connection efficiency data can be set to an arrival-departure time difference of less than or equal to 5 minutes; the upper limit of route runtime can be set to less than or equal to 60 minutes; the route passenger flow matching data can be set to a designed passenger capacity greater than or equal to 1.1 times the predicted passenger flow; and the route station coverage data can be set to cover the nearest station between the origin and destination and serve a population greater than or equal to 90%. The constraint data can be adjusted according to specific circumstances. Route operation data includes statistics on repeated stations, historical passenger flow data for transfer nodes, and unit mileage cost data. This route operation data can be obtained from the public transport operation big data platform. The statistical data for duplicate stops on routes uses the overlap rate between any two routes. Historical passenger flow data for transfer nodes uses the node's maximum capacity. Unit mileage cost data includes vehicle depreciation and fuel costs. Then, based on the constraint data, an operations research optimization algorithm is used to plan a set of candidate routes whose total travel time is shorter than the first travel time. Finally, based on route operation data, the candidate routes are screened, removing routes with an overlap rate exceeding 30%, routes involving nodes with historically excessive passenger flow, and routes with unit mileage costs exceeding the average level by 1.1 times. The remaining routes form the filtered set, which is considered practically operationally feasible. The constraints ensure short travel times and a superior experience, while the operational data ensures that routes are not wasted and costs are controllable, balancing passenger demand with the operational capabilities of public transport companies. This makes the routes practically operable and avoids solutions that are optimized but cannot be operated.

[0024] Specifically, in step S3, the route set filtered in step S2 is first used to construct a complete transfer network based on the connections between stations and transfer nodes, ensuring interconnectivity between transfer nodes and forming a closed-loop travel network. Then, all routes in the transfer network are sorted sequentially by total travel time, prioritizing routes with the shortest total travel time. Next, a first preset number of routes with the shortest total travel time are selected and pushed to passengers, for example, 3-5 routes. Finally, passengers choose a route from the pushed routes based on their actual needs, such as whether they prefer less walking or are familiar with a particular transfer node. Multiple high-quality options are provided to suit the personalized needs of different passengers; for example, younger passengers might choose the shortest travel time, while older passengers might choose routes with fewer transfers.

[0025] Specifically, in step S4, a time is set so that the adjustment of the transfer route begins some time before the passenger arrives at the transfer node, such as 10 minutes, which means that the adjustment is triggered when the passenger has 10 minutes of travel time remaining before arriving at the transfer node. Some time before the transfer node, real-time bus operation data, real-time transfer node data, and real-time road condition data are acquired. The real-time bus operation data includes the real-time location, real-time speed, and estimated arrival time at the transfer node of the current route. The real-time transfer node data includes the real-time location, estimated arrival time, and real-time congestion level of the transferable routes in the filtered route set. The real-time road condition data includes the real-time congestion coefficient and real-time speed of the road segments through which the transferable routes pass. Based on real-time parameter data and the routes selected by passengers, the remaining time of each transferable route in the route set is calculated and filtered one by one. The remaining time includes the transfer waiting time, the remaining travel time of the subsequent route, and the walking time to the destination. Based on the calculated remaining time, the route with the shortest remaining time is selected as the real-time recommended route. At the same time, a preset number of routes with the second shortest remaining time are selected as backup routes. The real-time recommended route and the backup routes are pushed to the passenger at the same time to guide the passenger to adjust the route. This realizes dynamic adjustment of the passenger's route, further shortens the total travel time, avoids extra time for passengers due to real-time changes, and allows passengers to quickly switch to backup routes, reducing the risk of travel interruption.

[0026] It is understandable that a baseline route and total travel time are planned based on the passenger's starting location. A set of candidate routes is planned based on the passenger's actual needs. The set of candidate routes that meet the requirements is selected from the operational situation. When the passenger transfers according to the route pushed to them, the route with the shortest travel time is calculated in advance at the transfer node. The real-time recommended route and alternative routes are pushed to the passenger, and the route that can be changed at the transfer node is pushed to the passenger, reducing the transfer time in the passenger's journey and making the actual time spent by the passenger on the bus less.

[0027] Step S4 is followed by the following steps: Step S5: Recommend real-time routes to passengers, record the adjustment results, and update the filtered route set based on the adjustment results after a preset time or a preset number of rides.

[0028] Step 5 specifically includes the following steps: Step S51: Based on real-time recommended routes and alternative routes, push them to passengers through multiple scenarios; Step S52: Build a structured database and record key data, including passenger response data, actual operation data, and abnormal situation data; Step S53: Set trigger conditions to start the update, and optimize the filtered line set according to the set conditions to ensure that the network adapts to actual needs.

[0029] Specifically, in step S51, methods such as bus app pop-ups, in-vehicle broadcasts, and electronic screens at transfer points are used. The bus app pop-up method can directly push data such as route name, transfer point location, estimated arrival time, and remaining journey time to passengers, allowing them to obtain real-time information on recommended routes. At the same time, the key differences between alternative routes are highlighted so that passengers can choose according to their needs. The in-vehicle broadcasts can be adapted to users who do not use the app, such as elderly passengers. The electronic screens at transfer points use text and arrows to guide passengers to the waiting area, and also display the countdown to the departure of recommended routes.

[0030] Specifically, in step S52, a structured database is built to record key data, including passenger response data, actual operation data, and abnormal situation data. Passenger response data includes response rate, selection of recommended routes, and reasons for abandoning recommendations. Selection of recommended routes is obtained through data such as APP click records, on-board passenger flow statistics matching, and passenger bus check-in records. The response rate is calculated by the number of passengers who selected recommended routes and the total number of recommended passengers. Reasons for abandoning recommendations can be obtained through APP questionnaires or on-site observation. Actual operation data includes data such as actual transfer waiting time, actual remaining travel time, total travel time, real-time passenger flow at transfer nodes, and real-time congestion of the route. Abnormal situation data includes temporary emergencies and the results of responses to temporary emergencies. Temporary emergencies include problems such as road construction and equipment failure at transfer nodes.

[0031] Specifically, in step S53, trigger conditions are set, including time-based triggering and frequency-based triggering. An update can be initiated once either trigger condition is met. Time-based triggering includes a preset period during which an update is triggered once. Frequency-based triggering includes a preset cumulative number of rides per route, for example, each route being actually ridden 1000 times. Routes are differentiated based on response rate, actual time error, and frequent anomaly records, and are marked as routes to be retained, removed, or adjusted, thereby making the routes more aligned with actual needs and reducing passenger transfer times. As one implementation, the route set update criteria are as follows: Routes to be retained are those with a response rate ≥ 70%, actual travel time error less than or equal to 10%, and no frequent anomaly records; these are marked as core recommended routes. Routes to be removed are those with a response rate < 30% (low passenger acceptance), actual travel time consistently exceeding predicted values ​​by 20% (optimization effect ineffective), and frequent overcapacity at transfer nodes (high operational risk). Routes to be adjusted are those with a response rate of 30%-70% and an error of 10%-20%; if the adjusted parameters meet the criteria, they are retained; otherwise, they are removed. If records show new travel demand, the process returns to the initial route planning stage, and 1-2 new routes adapted to the new demand are generated and added to the filtered route set.

[0032] Step S1 specifically includes the following steps: Step S11: Obtain the origin coordinates, destination coordinates, and travel volume for each time period of the passenger's trip, and classify them as OD demand data; Step S12: Obtain static data and historical operation data of the public transport network in the city where the passenger is currently located from the urban transportation big data platform; Step S13: Obtain the road grade, time-based congestion coefficient, and congestion time division standard of the road sections along the route from the urban traffic monitoring platform, and classify them into road characteristic data; Step S14: Preprocess the initial data to obtain preprocessed data. With the goal of minimizing the total travel cost for passengers, determine the optimal route based on the preprocessed data to obtain the baseline route, and calculate the time taken on the baseline route to obtain the first duration.

[0033] First, three key types of information are collected through the urban transportation big data platform: passenger origin coordinates, time-segmented travel volume, and supplementary travel preference data. This platform includes systems such as public transport IC card readers, subway travel apps, and urban travel survey databases. Passenger origin and destination coordinates are collected in WGS84 format, accurate to within 10 meters to ensure matching the nearest bus stop. Time-segmented travel volume is divided into morning peak (7:00-9:00), evening peak (17:00-19:00), off-peak (9:00-17:00), and 19:00-7:00 the next day, counting the number of passengers traveling from origin to destination within each time period. Supplementary travel preference data is added based on survey information, such as preferences for fewer transfers or avoiding congested road sections. This information is then categorized and archived by origin-destination (OD) pair and time period to form structured OD demand data. Static bus network data and historical bus operation data are extracted from the urban traffic big data platform (or the bus company's dedicated operation system). The static bus network data includes basic information for all bus routes (route name, route number, origin / destination station names and coordinates), detailed information on stops along the route (name, coordinates, road mileage between stops, non-straight-line distance), and station service attributes (e.g., whether it is a transfer station, whether it has accessibility facilities). Historical bus operation data includes the historical average operating speed, departure intervals, historical transfer waiting time, and historical delay rate for each route during different time periods. Finally, the two types of data are linked and archived to form a linked dataset. Road-related data affecting bus operation efficiency are collected from the urban traffic monitoring platform, including road classification (e.g., arterial roads, secondary roads, local roads), time-of-day congestion coefficients, and congestion time segmentation standards for the road sections traversed by the routes. This data is then categorized to form a road feature dataset. Based on real-time traffic historical statistics and time-segmented congestion coefficients, this coefficient is used to correct travel time. The congestion time segmentation standard is consistent with the time segmentation of OD demand data, and special road segment information, such as long-term road construction or intersections prone to congestion during peak hours, is included. Preprocessing removes invalid data, fills in missing values, and standardizes data to avoid deviations in subsequent steps due to data chaos or anomalies, ensuring data quality for all optimization actions. The baseline route is the route most likely to be chosen by passengers, and the first duration is the actual travel time on the current route. Both together constitute the target for subsequent optimization. Specific quantitative targets can be directly set for subsequent optimizations, facilitating subsequent evaluation of optimization effectiveness.

[0034] Step S2 specifically includes the following steps: Step S21: Obtain constraint data, construct an integer programming model based on the constraint data, generate candidate routes that meet the constraint data, and integrate the candidate routes with their durations to obtain a candidate route set. Step S22: Obtain the operation data of the line, and combine the operation data of the line with the candidate line set to filter the lines in the candidate line set. The lines are filtered from three aspects: line duplication rate, transfer node capacity, and line operation cost, to obtain the filtered line set.

[0035] First, core constraint data supporting route planning is collected to clarify the requirements the route must meet, including transfer frequency constraints (maximum number of transfers per passenger trip), connection efficiency constraints (maximum allowable difference between arrival time of preceding and departure times of subsequent routes at transfer nodes), runtime constraints (maximum runtime of a single route), passenger flow matching constraints (time-segmented passenger flow and vehicle rated passenger capacity), and station coverage constraints (coordinates of the nearest station to the passenger's origin / destination and population data within a 500-meter service radius of the stations along the route). An integer programming model is constructed with the objective function: minT = starting point walking time + segmented travel time + segmented transfer waiting time + destination walking time. Here, the starting point walking time is the time a passenger walks from their origin (e.g., the entrance to their residential area or the building below their office) to the nearest bus stop; segmented travel time = Σx_ij × station mileage ÷ average speed; segmented transfer waiting time = Σy_mn × departure interval × 0.5; x_ij and y_mn are decision variables, locking in the stations along the route. For points and transfer nodes, x_ij takes a value of 0 or 1, where i represents the candidate route number to be planned (e.g., the 1st and 2nd candidate routes), j represents the city bus stop number, x_ij=1 indicates that the i-th candidate route passes through the j-th stop, and x_ij=0 indicates that the i-th candidate route does not pass through the j-th stop. y_mn takes a value of 0 or 1, where m represents the transfer node number (e.g., the 1st and 2nd transfer stations), n represents the connecting route number, and y_mn=1 indicates that the m-th transfer node connects the n-th route and the (n+1th)-th route. The route (i.e., transferring at this node), y_mn=0 indicates that the m-th transfer node does not connect the n-th and n+1-th routes (i.e., there is no transfer at this node); station mileage represents the road mileage between the j-th station and the next adjacent station, which is the actual road distance and is captured from the static network data; average speed represents the historical average driving speed of the i-th candidate route in the corresponding time period and is captured from historical operation data; departure interval represents the time-segmented departure interval of the n+1-th transfer route at the m-th transfer node and is captured from historical operation data. Then, based on the route operation data, the routes in the candidate route set are filtered from three dimensions: route duplication rate, transfer node capacity, and route operation cost. The routes filtered by all dimensions are integrated to generate the filtered route set. First, the premise problem of whether it is wasteful is solved, then the experience problem of whether it is congested is addressed, and finally the sustainability problem of whether it is cost-effective is controlled. This step-by-step approach ensures that the filtered routes are easy to use, easy to manage, and cost-effective. The candidate route set only meets theoretical constraints and may have operational problems such as high duplication rate, insufficient node capacity, and excessive cost. By screening through operational data, routes that cannot be implemented are eliminated to ensure that the final route set meets the actual operational capabilities of the bus company, balances passenger demand and operational efficiency, retains routes with short total time and good experience, and controls resource waste and operational pressure through duplication rate and cost screening.

[0036] Step S22 specifically includes the following steps: Step S221: Calculate the repetition rate of any two candidate routes, eliminate the route with the longer total time, and keep the route with the shorter total time to obtain the route with the shorter time. Step S222: For routes with short travel times, query the historical maximum passenger flow data of transfer nodes, and remove routes whose historical maximum passenger flow of transfer nodes exceeds the preset rated capacity to obtain routes with low capacity. Step S223: Calculate the unit mileage operating cost of the candidate routes, eliminate routes with average operating costs higher than the preset cost, and obtain the filtered routes.

[0037] Specifically, all route pairs in the candidate route set are traversed, and the repetition rate of each route pair is calculated one by one. If the repetition rate of a certain route pair is greater than a preset threshold, the total duration of the two routes is compared. The route with the longer total duration is eliminated, and the route with the shorter total duration is retained. The above operation is repeated until the repetition rate of any two routes in the candidate route set is less than or equal to 30%. Finally, a route set with short duration and low repetition is obtained. Routes with high repetition rates will cause multiple buses to run in parallel on the same road segment, which wastes vehicle resources and occupies road resources. By screening, network redundancy can be greatly reduced. By retrieving historical maximum passenger flow data from the city's public transport operation database for all transfer nodes involved in routes with short travel times (i.e., the highest hourly passenger flow at each node during peak hours), a preset rated capacity is determined for each transfer node. This preset rated capacity is calculated based on the node area, number of passageways, and waiting facility capacity. Each transfer node along the route of the short travel routes is then checked one by one. If the historical maximum passenger flow of any transfer node involved in the route exceeds the preset rated capacity, the route is directly eliminated. If the historical maximum passenger flow of all transfer nodes involved in the route is less than or equal to the preset rated capacity, the route is retained. This results in routes with lower capacity, ensuring that passengers have sufficient space and efficient passage during transfers, and avoiding additional waiting times due to node congestion. The cost structure includes bus depreciation costs, fuel or electricity costs, driver salary costs, and vehicle maintenance costs. All costs are calculated per unit mileage to obtain the operating cost per unit mileage. A preset cost threshold is determined, and the operating cost per unit mileage for each route with low capacity is calculated one by one. Routes with operating costs per unit mileage exceeding the preset cost threshold are eliminated. If all routes exceed the threshold, the routes with the lowest costs that meet the screening criteria of the first two steps are retained, resulting in a set of routes with short travel time, low duplication, compliant node capacity, and controllable costs, which is the filtered route set.

[0038] Step S4 specifically includes the following steps: Step S41: When passengers are taking the bus, real-time location, road conditions and passenger flow data are collected at a preset time before they arrive at the transfer node to obtain real-time parameter data; Step S42: Calculate the estimated arrival time at the destination based on real-time parameter data, correct the arrival time of the transfer route, obtain the passenger flow situation of the transfer node based on passenger flow data, classify the congestion level, and mark the transfer node with overcapacity to obtain real-time constraints; the real-time constraints include the estimated arrival time, the corrected arrival time of the transfer route, and the passenger flow overcapacity data. Step S43: Filter the selected route set according to real-time constraints, calculate the remaining travel time for the routes that meet the requirements, sort them according to the length of time, and use the shortest route as the real-time recommended route. The first preset number of routes in the sorted list are selected as candidate routes.

[0039] Specifically, based on the complexity of transfer nodes—for example, large transfer stations in the core area require more walking time to find the platform, while small stations in the suburbs have shorter walking times—a preset time is set before arriving at the transfer node, and real-time data is collected, including real-time location data, real-time traffic data, and real-time passenger flow data. Specifically, through the public transport GPS monitoring system, the system collects the latitude and longitude coordinates of the passenger's current route, real-time speed (km / h), remaining road distance (km) from the transfer node, and remaining number of stops every second, recording this as real-time location data. Through the urban traffic monitoring platform or navigation map API, the system obtains the congestion level (smooth / lightly congested / heavily congested) and real-time speed correction coefficient (smooth 1.0, lightly congested 1.1, heavily congested 1.3) of the road segments traversed by the subsequent routes to the transfer node every minute, forming real-time traffic data. The system also obtains real-time passenger flow data by using video counters within the transfer node and entrance / exit traffic flow, and real-time passenger flow data by using onboard passenger flow counters for the transfer routes. Based on real-time location data, the estimated arrival time at transfer nodes and the estimated total arrival time at the destination are calculated. From the filtered route set, the initial estimated arrival time of transferable routes is extracted. The arrival time of transfer routes is modified in conjunction with real-time traffic data. If the congestion of a transfer node exceeds the rated capacity threshold, it is marked as an overloaded node. Routes involving this node are avoided in subsequent screenings. Congestion is classified according to the real-time number of passengers at the node / the node's rated capacity. The estimated arrival time, the corrected arrival time of transfer routes, and the overloaded passenger data are integrated as real-time constraints to clarify the hard criteria for subsequent route screening. Routes that meet the real-time constraints are screened, and those that meet the real-time constraints are sorted by their travel time. The route with the shortest travel time is the real-time recommended route. The next best routes (usually 2-3) from the top of the sorted list are selected as candidate routes and pushed to passengers through the bus APP and onboard broadcasts.

[0040] Step S42 specifically includes the following steps: Step S421: Extract all routes that pass through the current transfer node or alternative transfer node from the filtered routes, and use them as candidate routes; Step S422: Calculate the remaining time for each candidate route according to the optimization target formula, and record its transfer waiting time and congestion level simultaneously; Step S423: Eliminate candidate routes where the transfer waiting time at the transfer node is greater than the first preset time or the congestion level at the transfer node is greater than the first preset threshold, and retain compliant routes; Step S424: Among the compliant lines, select the line with the shortest remaining time as the real-time recommended line, and retain the first preset number of suboptimal lines as alternative lines.

[0041] Specifically, firstly, focusing on the passenger's original planned transfer node and previously marked alternative transfer nodes within a walking distance of 300 meters or less from the current node, all routes passing through the current transfer node or alternative transfer nodes are systematically examined and extracted from the previously screened route set, forming a list of candidate routes (excluding routes irrelevant to both types of nodes to narrow down the subsequent calculation scope). Next, for each candidate route, the remaining time is calculated using the formula: Remaining Time = Transfer Waiting Time + Remaining Travel Time for Subsequent Routes + Walking Time to the Destination (where, Transfer Waiting Time = Corrected Arrival Time of Transfer Route - Estimated Arrival Time of Current Route at Transfer Node, and Subsequent Travel Time = Distance from Transfer Node to the Nearest Destination Station ÷ Real-Time Speed ​​of Transfer Route × 60). Simultaneously, the transfer waiting time and congestion level of each route are recorded (congestion level is graded according to real-time passenger volume ÷ rated capacity, e.g., less than or equal to 60% comfortable, 60%-80% moderate, greater than 80% congested), forming a candidate route-parameter comparison table. Next, non-compliant routes are eliminated to ensure a good user experience: two strict elimination criteria are set—transfer waiting time is greater than a first preset time (usually 3 minutes) and the congestion of transfer nodes / routes is greater than a first preset threshold (usually 80%). Each candidate route is checked against the parameter table, and routes meeting either non-compliant criterion are eliminated, leaving only routes that meet both criteria, forming a list of compliant routes. Finally, real-time recommended routes and alternative routes are determined: compliant routes are sorted by remaining time from shortest to longest, and the route with the shortest remaining time is selected as the real-time recommended route (the optimal time option in the current scenario); simultaneously, from the sorted compliant routes, a first preset number (usually 2-3) of the next best routes are selected as alternative routes, prioritizing routes with a remaining time difference of less than or equal to 2 minutes from the recommended route and lower congestion; if there is only one compliant route, that route is both the recommended route and the sole alternative; if there are no compliant routes, routes from other alternative transfer nodes are extracted, and the above calculation and filtering steps are repeated to determine the final recommended / alternative routes.

[0042] Secondly, the present invention discloses a public transport interchange network construction system, which includes the above-mentioned public transport interchange network construction system.

[0043] Specifically, the system implements the first aspect of the method, which mentions that a baseline route and total duration are planned based on the passenger's starting location, and a set of candidate routes is planned in combination with the passenger's actual needs. The set of candidate routes that meet the requirements is selected from the operational situation. When the passenger transfers according to the route pushed, during the journey, at the transfer node, the route with the shortest travel time is calculated in advance, and the real-time recommended route and alternative routes are pushed to the passenger. The system pushes the route that the passenger can transfer to at the transfer node, reducing the transfer time in the passenger's journey and making the actual time spent by the passenger on the bus less.

[0044] Thirdly, the present invention discloses an electronic device, which includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the above-described method for constructing a public transport interchange network.

[0045] Specifically, the processor implements the computer program in the memory, which implements the method of the first aspect. The method mentions that a baseline route and total duration are planned based on the passenger's starting position, and a set of candidate routes is planned in combination with the passenger's actual needs. The set of candidate routes that meet the requirements is selected from the operational situation. When the passenger transfers according to the route pushed, during the journey, at the transfer node, the route with the shortest time is calculated in advance, and the real-time recommended route and alternative routes are pushed to the passenger. The route that can be changed at the transfer node is pushed to the passenger, reducing the transfer time in the passenger's journey and making the passenger spend less time on the bus.

[0046] Fourthly, the present invention discloses a storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the above-described method for constructing a public transport interchange network.

[0047] Specifically, the storage medium implements the first aspect of the method, which mentions that a baseline route and total duration are planned based on the passenger's starting location, a set of candidate routes is planned in combination with the passenger's actual needs, a set of candidate routes that meet the requirements is selected from the operational situation, and the passenger transfers according to the pushed route. During the journey, at the transfer node, the route with the shortest travel time is calculated in advance, and the real-time recommended route and alternative routes are pushed to the passenger. The passenger is pushed the route that can be changed at the transfer node, reducing the transfer time in the passenger's journey and making the passenger spend less time on the bus.

[0048] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0049] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "length," "width," "thickness," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," "outer," "clockwise," and "counterclockwise," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0050] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0051] In this invention, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," and "fixing," etc., should be interpreted broadly. For example, they can refer to a connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0052] In this invention, unless otherwise explicitly specified and limited, "above" or "below" the second feature can include direct contact between the first and second features, or contact between the first and second features through another feature between them. Furthermore, "above," "over," and "on top" of the second feature includes the first feature directly above or diagonally above the second feature, or simply indicates that the first feature is at a higher horizontal level than the second feature. "Below," "below," and "under" the second feature includes the first feature directly below or diagonally below the second feature, or simply indicates that the first feature is at a lower horizontal level than the second feature.

[0053] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," 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. The illustrative expressions of the above terms in this specification should not be construed as necessarily referring 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. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0054] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Since these modifications and variations fall within the scope of the claims and their equivalents, this invention also intends to include these modifications and variations.

[0055] The above description describes specific embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method of constructing a bus interchange network, characterized by, The method comprises the following steps: Based on the initial data, the baseline route and the total time length of the route are determined to obtain the baseline route and the first time length; the initial data includes OD demand data, static data of bus line network, historical operation data of bus, and road characteristic data; the preprocessed data includes passenger station association data set and historical operation data set; Obtain constraint condition data and operation data of the route, plan a candidate route set based on the constraint condition data, and filter the candidate route set based on the operation data of the route to obtain a filtered route set; The operation data of the route includes route repeated station statistical data, transfer node historical passenger flow data, and unit mileage cost data; The constraint condition data includes passenger transfer frequency data, transfer route connection efficiency data, route operation time length data, route passenger flow data, and route station coverage data; The filtered route set is used to construct a transfer line network, the transfer line network is sorted according to time sequence, the first preset number of routes with the shortest total time consumption are pushed to passengers, and the passengers select routes according to actual needs to take the routes; Real-time parameter data is obtained at a preset time before the passenger reaches a transfer node, the remaining time length of each route in the filtered route set is calculated based on the real-time parameter data, the shortest route and a preset number of alternative routes are selected according to the remaining time length, and real-time recommended routes and alternative routes are obtained.

2. The method of claim 1, wherein, Then the method comprises the following steps: The real-time recommended routes are recommended to the passengers, the adjustment results are recorded, and the filtered route set is updated according to the adjustment results after a preset time or a preset number of rides.

3. The method of claim 1, wherein, The method of determining the baseline route and calculating the total time length of the route based on the initial data to obtain the baseline route and the first time length comprises the following steps: Obtain the origin coordinates, destination coordinates and travel volume of each time period of passenger travel, and classify them as OD demand data; Obtain the static data of bus line network and historical operation data of the current passenger's city from the city traffic big data platform; Obtain the road grade, time-based congestion coefficient and congestion period division standard of the route passing road section from the city traffic monitoring platform, and classify them as road characteristic data; Preprocess the initial data to obtain preprocessed data, take the minimum total travel cost of passengers as the target, determine the optimal route based on the preprocessed data, obtain the baseline route, calculate the time spent by the baseline route, and obtain the first time length.

4. The method of claim 1, wherein, The method of obtaining constraint condition data and operation data of the route, planning a candidate route set based on the constraint condition data, and filtering the candidate route set based on the operation data of the route to obtain a filtered route set comprises the following steps: Obtain constraint condition data, construct an integer programming model based on the constraint condition data, generate candidate routes that meet the constraint condition data, integrate the candidate routes and the candidate route time length to obtain a candidate route set, Obtain operation data of the route, filter the routes in the candidate route set in combination with the operation data of the route and the candidate route set, and filter the routes from three aspects of route repetition rate, transfer node carrying capacity and route operation cost to obtain a filtered route set.

5. The method of claim 4, wherein, The operation data of the combined line is screened with the candidate line set, and the line of the candidate line set is screened, and the screening process specifically includes the following steps: Calculate the repetition rate of any two candidate lines, eliminate the line with longer total duration, and keep the line with shorter total duration to obtain the line with shorter time consumption; For the line with shorter time consumption, query the historical maximum passenger flow data of the transfer node, eliminate the line involving the transfer node with historical maximum passenger flow greater than the preset rated carrying capacity, and obtain the line with less carrying capacity; Calculate the unit mileage operation cost of the candidate line, eliminate the line with average operation cost higher than the preset cost, and obtain the screened line.

6. The method of claim 1, wherein, The passenger selects a line from the screened line set to take, and real-time parameter data is obtained at a preset time before the passenger reaches the transfer node, the remaining time of each line in the screened line set is calculated based on the real-time parameter data, the shortest line is selected from the lines with the shortest remaining time and the preset number of backup lines, and the real-time recommended line and the backup line are obtained, specifically including the following steps: An optimal line is selected from the screened line set and pushed to the passenger for taking, and the passenger takes the bus, collects real-time position, road condition and passenger flow data at a preset time before reaching the transfer node, and obtains real-time parameter data; According to the real-time parameter data, the estimated arrival time at the terminal is calculated, the arrival time of the transfer line is corrected, the passenger flow condition of the transfer node is obtained according to the passenger flow data, the congestion degree is classified, and the transfer node with excess passenger flow is marked, and the real-time constraint condition is obtained; The real-time constraint condition includes the estimated arrival time, the corrected arrival time of the transfer line, and the passenger flow excess data. According to the real-time constraint condition, the screened line set is screened, the lines meeting the requirements are calculated, the time spent on the remaining distance is calculated, and the lines are sorted according to the time spent, and the shortest line is selected as the real-time recommended line, and the lines in the front are selected as the backup lines.

7. The method of claim 6, wherein, According to the real-time constraint condition, the screened line set is screened, the lines meeting the real-time constraint condition are calculated, the time spent on the remaining distance is calculated, and the lines are sorted according to the time spent, and the shortest line is selected as the real-time recommended line, and the lines in the front are selected as the backup lines, specifically including the following steps: From the screened line, all lines passing through the current transfer node or the backup transfer node are extracted as candidate lines; According to the optimization target formula, the remaining time of each candidate line is calculated one by one, and the transfer waiting time and the congestion degree of each candidate line are recorded; Eliminate the candidate line with transfer waiting time greater than the first preset time or the congestion degree of the transfer node greater than the first preset threshold, and keep the compliant line; In the compliant line, the line with the smallest remaining time is selected as the real-time recommended line, and the first preset number of suboptimal lines are kept as backup lines.

8. A bus interchange network configuration system characterized by comprising: The bus transfer line network construction method of any one of claims 1-7.

9. An electronic device, comprising: The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims 1-7. The bus transfer line network construction method of any one of claims A processor for implementing the steps of the method of claim 1-7 when executing a program stored on a memory.

10. A storage medium having stored thereon a computer program, characterized in that The computer program for implementing the steps of the method of claim 1-7 when executed by a processor.

Images