A coordinated dispatching method and system for mixed passenger and freight transportation in subways

Abstract

The present invention relates to the technical field of urban rail transit operation and management, and discloses a method and system for coordinated scheduling of mixed passenger and freight transportation in subways. Dynamic coordinated scheduling of passenger and freight transportation is achieved by constructing a spatiotemporal grid network model: a coupling model of multidimensional spatial grid units and time dimensions is constructed based on real-time collected passenger and logistics data, accurately depicting the spatiotemporal occupancy status of passenger and freight paths. A scheduling strategy is generated based on a comprehensive calculation of a path conflict index based on passenger density, logistics occupancy, evacuation efficiency, and environmental impact, to coordinately schedule mixed passenger and freight transportation in subways, effectively resolving core contradictions in traditional mixed passenger and freight transportation, such as path conflict, weakened evacuation capacity, and environmental interference.

Description

Technical Field

[0001] The present invention relates to the technical field of urban rail transit operation management, and in particular to a subway passenger and freight mixed transportation coordinated dispatching method and system. Background Art

[0002] With the rapid development of urban rail transit systems, subway networks have become the core vehicle for modern urban passenger transportation. In recent years, the need for efficient utilization of urban underground space resources has become increasingly prominent. Integrating logistics and transportation functions into subway systems to create a "passenger-freight mixed transport" model has gradually become a key development direction for alleviating surface transportation pressure and improving the overall efficiency of infrastructure. However, existing subway systems, primarily designed for passenger transport during the planning and design phase, face multi-faceted operational conflicts and safety risks when implementing passenger-freight coordinated transport. Therefore, a scientific and systematic coordinated dispatching mechanism is urgently needed.

[0003] Traditional subway operating systems prioritize passenger flow in their spatial layout. The design capacity and service functions of key areas such as station halls, platforms, and passageways are configured based on peak passenger flow characteristics. The introduction of logistics and transportation functions inevitably creates overlap between the routes and operating areas of freight equipment and passenger activity spaces. This competition for spatial resources is particularly acute during peak passenger flow periods. The temporary occupation of evacuation routes by logistics equipment can create bottlenecks, reducing passenger flow efficiency and posing a serious threat to evacuation safety in emergencies. Furthermore, the vibration, noise, and exhaust emissions generated by freight equipment create new conflicts with existing environmental control systems in subway stations, directly impacting the quality of passenger service.

[0004] In terms of time, the tidal passenger flow characteristics of the subway system and the need for continuous logistics transportation are inherently conflicting. Existing dispatching methods, which often rely on fixed-time isolation, are unable to adapt to the real-time dynamics of passenger flow. Especially during sudden surges or operational plan adjustments, inflexible logistics routing can easily lead to equipment delays or secondary dispatches, exacerbating station disruptions. Furthermore, existing dispatching systems often rely on manual judgment and lack the integrated analysis of multi-source data such as space occupancy status and environmental parameters, making it difficult to predict and resolve potential conflicts in a timely manner.

[0005] Current technological exploration in the mixed passenger and freight transport sector focuses on hardware improvements, such as the design of dedicated freight cars or the construction of independent logistics corridors. While these solutions can achieve physical isolation, they are limited by the existing infrastructure and operating costs, hindering their widespread adoption. Simple rule-based time-sharing scheduling strategies, while able to mitigate conflicts during certain time periods, are unable to cope with complex and volatile real-time operational scenarios. Furthermore, a quantitative evaluation system has yet to be established to balance the multi-objective demands of transport efficiency and safety management.

[0006] Therefore, a subway passenger and freight mixed transportation coordinated scheduling method and system can maximize logistics transportation efficiency while ensuring the quality of passenger service. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a method for coordinated scheduling of mixed passenger and freight transportation in subways, comprising the following steps:

[0008] Step S1: Real-time collection of passenger flow data and logistics data at subway stations;

[0009] Step S2: constructing a spatiotemporal grid network model based on the passenger flow data and logistics data, wherein the spatiotemporal grid network model divides the functional area of ​​the station into multiple layers of grid units and superimposes a time dimension to represent the dynamic path occupancy status;

[0010] Step S3: Calculating the path conflict index of each grid cell in the spatiotemporal grid network model based on the passenger density influencing factor, the logistics occupancy influencing factor, the passenger evacuation efficiency influencing factor, and the environmental control influencing factor;

[0011] Step S4: generating a scheduling strategy according to the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway.

[0012] Furthermore, in step S2, a spatiotemporal grid network model is constructed based on the passenger flow data and logistics data, including:

[0013] Based on the spatial layout of the station hall, platform and transfer passage, each functional area is divided into multi-layer grid units;

[0014] The passenger flow data and logistics data are mapped to the corresponding grid units to generate a four-dimensional path occupancy matrix containing a timestamp as the spatiotemporal grid network model.

[0015] Furthermore, the calculation formula of the path conflict index is:

[0016] ;

[0017] Where, represents the path conflict index of the i-th grid cell at time t, represents the passenger and cargo space impact factor of the i-th grid unit at time t, represents the passenger evacuation efficiency influencing factor of the i-th grid unit at time t, represents the environmental control influencing factor of the i-th grid cell at time t, and ω1, ω2 and ω3 are weight coefficients respectively.

[0018] Furthermore, the passenger and cargo space impact factor is calculated by the passenger density impact factor, the logistics occupancy impact factor and their corresponding weights, and the formula is:

[0019] ;

[0020] Where, D passenger ( t,i ) represents the passenger density influencing factor of the i-th grid cell at time t, D logistics ( t,i ) represents the logistics occupancy impact factor of the i-th grid unit at time t, α represents the passenger density weight coefficient, and β represents the logistics occupancy weight coefficient;

[0021] The passenger density influencing factor is calculated according to the real-time number of passengers and the maximum safe carrying capacity of each grid unit using the following formula:

[0022] ;

[0023] Where, N p ( t,i ) represents the real-time number of passengers in the i-th grid cell at time t, N p max represents the maximum safe load capacity within the i-th grid unit;

[0024] The logistics occupancy impact factor is calculated based on the occupied area of ​​logistics equipment in each grid unit and the maximum allowed logistics occupied area. The calculation formula is:

[0025] ;

[0026] In the formula L f ( t,i ) represents the area occupied by logistics equipment in the i-th grid unit at time t, L f max represents the maximum allowable logistics area within the i-th grid cell.

[0027] Furthermore, the calculation of the passenger evacuation efficiency influencing factor includes the following steps:

[0028] Extract evacuation channel design data within each grid cell;

[0029] According to the length of the evacuation passage occupied by the logistics equipment and the design data of the evacuation passage, the passenger evacuation efficiency influencing factor is calculated, and the calculation formula is:

[0030] ;

[0031] Where, represents the passenger evacuation efficiency influencing factor of the i-th grid unit at time t, represents the length of the evacuation channel occupied by the logistics equipment of the i-th grid unit at time t, represents the total evacuation channel length in the evacuation channel design data within the i-th grid unit, is the correction factor.

[0032] Furthermore, the calculation of the environmental control impact factor includes the following steps:

[0033] Obtain the noise decibel value and air pollutant concentration in each grid cell in real time;

[0034] The environmental control impact factor is calculated based on the noise decibel value and the air pollutant concentration. The calculation formula is:

[0035] ;

[0036] Where, represents the environmental control influence factor of the i-th grid cell at time t, represents the real-time noise value of the i-th grid cell at time t, represents the real-time air pollutant concentration of the i-th grid cell at time t, represents the noise threshold, represents the air pollution threshold, γ is the noise weight coefficient, and δ is the pollution weight coefficient.

[0037] Furthermore, a scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation on the subway, including:

[0038] If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed;

[0039] If the path conflict index is greater than or equal to the preset conflict threshold, the logistics equipment path is dynamically adjusted, specifically:

[0040] If it is a peak passenger flow period, the logistics equipment route will be allocated to non-passenger transfer channels and underground idle areas;

[0041] During periods of low passenger flow, routes that overlap with passenger flow lines are activated and the priority of logistics equipment is increased.

[0042] Furthermore, a scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in subways, specifically:

[0043] If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed;

[0044] If the path conflict index is greater than or equal to a preset conflict threshold, the flexible transport time window is executed, including:

[0045] Based on the passenger flow forecast results within the preset time period, logistics transportation tasks are inserted into the blank periods of the train timetable;

[0046] According to the passenger flow growth rate, the occupied time of logistics routes can be shortened.

[0047] Furthermore, a scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in subways, specifically:

[0048] If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed;

[0049] If the path conflict index is greater than or equal to the preset conflict threshold, the key area logistics path is isolated, including:

[0050] Determine key areas based on the functional settings of each subway area;

[0051] The key areas are set as logistics restricted areas so that they can be used as logistics routes for logistics transportation only during non-operating periods.

[0052] Another aspect of the present invention provides a subway passenger and freight mixed transportation coordinated dispatching system, which executes any of the above subway passenger and freight mixed transportation coordinated dispatching methods, including:

[0053] Data collection module, used to collect passenger flow data and logistics data of subway stations in real time;

[0054] A spatiotemporal grid network model construction module is used to construct a spatiotemporal grid network model based on the passenger flow data and logistics data. The spatiotemporal grid network model divides the functional area of ​​the station into multiple layers of grid units and superimposes a time dimension to represent the dynamic path occupancy status;

[0055] a path conflict index calculation module, configured to calculate the path conflict index of each grid cell in the spatiotemporal grid network model based on a passenger density influencing factor, a logistics occupancy influencing factor, a passenger evacuation efficiency influencing factor, and an environmental control influencing factor;

[0056] The scheduling strategy generation module is used to generate a scheduling strategy according to the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway.

[0057] The embodiments of the present invention have the following technical effects:

[0058] The subway passenger and freight mixed transportation collaborative scheduling method provided by the present invention realizes dynamic collaborative scheduling of passenger and freight transportation by constructing a spatiotemporal grid network model: based on the passenger flow and logistics data collected in real time, a coupling model of multidimensional spatial grid units and time dimensions is constructed to accurately characterize the spatiotemporal occupancy status of passenger and freight paths, and a dynamic risk assessment system is established by comprehensively calculating the path conflict index of passenger density, logistics occupancy, evacuation efficiency and environmental impact, so that the scheduling strategy can actively adapt to the passenger flow fluctuation law, effectively resolve the core contradictions such as path conflict, weakened evacuation capacity and environmental interference in traditional passenger and freight mixed transportation, significantly improve logistics transportation efficiency while ensuring the quality of passenger service, and at the same time enhance the emergency response capability of the station operation system to sudden passenger flow changes, providing intelligent decision-making support for the coordinated transportation of passengers and freight in the subway system. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0060] Figure 1 This is a flowchart of the steps of a subway passenger and freight mixed transportation coordinated scheduling method provided by an embodiment of the present invention;

[0061] Figure 2 This is a method flow chart of a subway passenger and freight mixed transportation coordinated scheduling method provided by an embodiment of the present invention;

[0062] Figure 3 It is a schematic diagram of a spatiotemporal grid network model provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0063] To make the objectives, technical solutions, and advantages of the present invention more clear, the technical solutions of the present invention are described clearly and completely below. Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without inventive effort are also within the scope of protection of the present invention.

[0064] In order to solve the above technical problems, the present invention provides a method for coordinated scheduling of mixed passenger and freight transportation in subways. Figure 1 and Figure 2 As shown, the following steps are included:

[0065] Step S1: Real-time collection of passenger flow data and logistics data at subway stations;

[0066] For example, a sensing network covering all functional areas of a station will be established, with intelligent sensing terminals deployed at key nodes in the concourse, platform, and transfer corridors. This will capture real-time spatiotemporal data streams, including passenger flow trajectories and the operational status of logistics equipment. Passenger flow data will include dynamic information such as passenger distribution heat maps and inbound and outbound traffic fluctuations. Logistics data will include the location coordinates of freight equipment, transport task execution progress, and route planning parameters. Data collection can be updated in milliseconds through a distributed computing architecture, ensuring real-time visualization of operational status.

[0067] Step S2: constructing a spatiotemporal grid network model based on the passenger flow data and logistics data, wherein the spatiotemporal grid network model divides the functional area of ​​the station into multiple layers of grid units and superimposes a time dimension to characterize the dynamic path occupancy status.

[0068] The grid division of station functional areas can be achieved using spatial topology analysis methods. Key parameters such as the layout of concourse-level service facilities, the distribution of platform-level security gates, and the topology of transfer channel connections can be extracted based on the building information model. Concourse-level grid cells are subdivided into sub-units such as security check areas, ticketing areas, and commercial service areas based on service functions. Each sub-unit is assigned an independent spatial coordinate identifier. Platform-level grid division takes into account the characteristics of train stops and passenger boarding and alighting flows, forming evenly spaced waiting units bounded by security gates. Transfer channel grid cells are divided into diamond shapes based on channel width and direction of travel, ensuring that each unit accurately represents the state of bidirectional passenger flow.

[0069] The spatiotemporal data mapping process employs a coordinate conversion algorithm to match real-time passenger flow coordinates and logistics equipment positioning data to corresponding grid cells. Timestamp data records the state changes of each grid cell within the sampling period, forming a four-dimensional spatiotemporal grid network model encompassing spatial horizontal and vertical coordinates, time dimensions, and a path conflict index. This model transcends the limitations of traditional two-dimensional planar models and accurately reflects the spatiotemporal interaction characteristics of passenger and freight transport in three-dimensional space.

[0070] like Figure 3 As shown in the figure, the horizontal and vertical axes indicate the location in the subway, and the directions perpendicular to the horizontal and vertical axes represent the path conflict index in different time periods. The path conflict index of each subway location in each time period is displayed through a spatiotemporal grid network model. The path conflict index is represented by different colors, and is visualized in the model using color coding technology. A small path conflict index indicates mild conflict, represented by green; an intermediate path conflict index is represented by yellow; a large path conflict index indicates a severe conflict between passenger flow and logistics, represented by red, indicating a high-risk unit requiring immediate intervention. Figure 3The color bar in the upper left corner represents time. By dragging the bar, you can view the path conflict index for different time periods. The displayed color is determined by comparing the difference between the current path conflict index and the preset conflict threshold. Using different colors also provides intuitive support for dispatchers' manual decision-making.

[0071] In some implementations, in step S2, constructing a spatiotemporal grid network model based on the passenger flow data and logistics data includes:

[0072] Step S21: Divide each functional area into multi-layer grid units according to the spatial layout of the station hall, platform and transfer passage;

[0073] Step S22: Map the passenger flow data and logistics data to the corresponding grid units, and generate a four-dimensional path occupancy matrix containing time stamps as the spatiotemporal grid network model.

[0074] Step S3: Calculating the path conflict index of each grid cell in the spatiotemporal grid network model based on the passenger density influencing factor, the logistics occupancy influencing factor, the passenger evacuation efficiency influencing factor, and the environmental control influencing factor;

[0075] In some implementations, the calculation formula for the path conflict index is:

[0076] ;

[0077] Where, represents the path conflict index of the i-th grid cell at time t, represents the passenger and cargo space impact factor of the i-th grid unit at time t, represents the passenger evacuation efficiency influencing factor of the i-th grid unit at time t, represents the environmental control influencing factor of the i-th grid cell at time t, and ω1, ω2 and ω3 are weight coefficients respectively.

[0078] The formula for calculating the path conflict index adopts multi-objective optimization theory, balancing the intensity of different influencing factors through linear weighting. The passenger and freight space impact factor reflects the spatial competition intensity of passenger and freight transportation within the grid unit at the current moment, and its value is positively correlated with the degree of passenger concentration and the volume of logistics equipment. The passenger evacuation efficiency impact factor represents the blocking effect of logistics equipment on the emergency channel. The higher the channel occupancy rate, the larger the value of this factor. The environmental control impact factor quantifies the environmental disturbance caused by freight operations, comprehensively considering the combined impact of acoustic pollution and air quality changes on the passenger experience. The three sub-factors are dynamically balanced through weight coefficient adjustment. When the station is in normal operation, the focus is on optimizing space utilization efficiency. In emergency mode, the decision weight of the evacuation efficiency factor is automatically increased.

[0079] The weighting coefficients in the formula are dynamically configured based on the station's operational characteristics. Commercial hubs prioritize passenger comfort, thus increasing the weighting of environmental control factors. Transfer stations prioritize traffic efficiency, thus increasing the weighting of evacuation efficiency factors. This flexible weighting mechanism enables the conflict index assessment model to adapt to different scenarios, effectively addressing the personalized needs of different station types. The total conflict index is output.

[0080] In some implementations, the passenger and cargo space impact factor is calculated from the passenger density impact factor, the logistics occupancy impact factor, and their respective corresponding weights, using the formula:

[0081] ;

[0082] Where, D passenger ( t,i ) represents the passenger density influencing factor of the i-th grid cell at time t, D logistics ( t,i ) represents the logistics occupancy impact factor of the i-th grid unit at time t, α represents the passenger density weight coefficient, and β represents the logistics occupancy weight coefficient;

[0083] The passenger and cargo space impact factor is calculated using dual-channel data fusion technology. The passenger density impact factor uses an intelligent video analysis system to count the real-time number of passengers within a grid cell and calculates space utilization based on the maximum load capacity specified in building safety regulations. The logistics occupancy impact factor uses lidar scanning to obtain the projected area of ​​freight equipment and calculates the ratio with the logistics operation area allowed by the grid cell design. These two sub-factors respectively represent the spatial competition between passenger service capacity and logistics operation intensity. Dynamic adjustment of transportation priorities is achieved through differentiated weighting of passenger density and logistics occupancy.

[0084] During the morning rush hour, the passenger density weighting factor is automatically increased to ensure sufficient passenger service space resources. During low passenger flow periods at night, the logistics occupancy weighting factor is increased to improve cargo turnover efficiency. This dynamic weighting adjustment mechanism effectively balances the conflicting transportation demands at different times of day and avoids the resource mismatch caused by fixed weighting strategies. The influencing factor calculation results are normalized before being input into the path conflict index model to eliminate the influence of data of different dimensions on the overall evaluation results and ensure comparability and superposition of the sub-factors.

[0085] The passenger density influencing factor is calculated according to the real-time number of passengers and the maximum safe carrying capacity of each grid unit using the following formula:

[0086] ;

[0087] Where, Np ( t,i ) represents the real-time number of passengers in the i-th grid cell at time t, N p max represents the maximum safe load capacity within the i-th grid unit;

[0088] The logistics occupancy impact factor is calculated based on the occupied area of ​​logistics equipment in each grid unit and the maximum allowed logistics occupied area. The calculation formula is:

[0089] ;

[0090] In the formula L f ( t,i ) represents the area occupied by logistics equipment in the i-th grid unit at time t, L f max represents the maximum allowable logistics area within the i-th grid cell.

[0091] In some implementations, the calculation of the passenger evacuation efficiency influencing factor includes the following steps:

[0092] Extract evacuation channel design data within each grid cell;

[0093] According to the length of the evacuation passage occupied by the logistics equipment and the design data of the evacuation passage, the passenger evacuation efficiency influencing factor is calculated, and the calculation formula is:

[0094] ;

[0095] Where, represents the passenger evacuation efficiency influencing factor of the i-th grid unit at time t, represents the length of the evacuation channel occupied by the logistics equipment of the i-th grid unit at time t, represents the total evacuation channel length in the evacuation channel design data within the i-th grid unit, is the correction factor.

[0096] The calculation of factors influencing passenger evacuation efficiency relies on a digital model of the station building, extracting officially certified evacuation corridor design parameters within each grid cell, including key indicators such as total corridor length and minimum effective width. The length of the evacuation corridor occupied by logistics equipment is determined using a path trajectory matching algorithm. This algorithm analyzes the topological relationship between the real-time operating trajectory of the freight equipment and the spatial coordinates of the evacuation corridor, calculating the continuous length of the corridor occupied by the equipment itself and the safety buffer area. A correction coefficient is dynamically adjusted based on the corridor level, with a higher correction coefficient for primary evacuation corridors than for auxiliary corridors, reflecting the importance of different corridor levels in emergency evacuations.

[0097] The formula for calculating the passenger evacuation efficiency impact factor uses a ratio to reflect the degree of reduction in evacuation capacity caused by logistics occupancy. When logistics equipment completely blocks the main evacuation route, the evacuation efficiency impact factor for that grid cell reaches its maximum value. The calculated results are linked to the fire monitoring system. When the impact factor for a specific cell exceeds a safety threshold, an audible and visual alarm is automatically triggered, and emergency evacuation instructions are generated for logistics equipment. This design ensures that safety hazards are preemptively eliminated during normal operations, preventing the risk of evacuation route obstruction in emergencies.

[0098] In some embodiments, the calculation of the environmental control impact factor comprises the following steps:

[0099] Obtain the noise decibel value and air pollutant concentration in each grid cell in real time;

[0100] The environmental control impact factor is calculated based on the noise decibel value and the air pollutant concentration. The calculation formula is:

[0101] ;

[0102] Where, represents the environmental control influence factor of the i-th grid cell at time t, represents the real-time noise value of the i-th grid cell at time t, represents the real-time air pollutant concentration of the i-th grid cell at time t, represents the noise threshold, represents the air pollution threshold, γ is the noise weight coefficient, and δ is the pollution weight coefficient.

[0103] The calculation of factors influencing passenger evacuation efficiency relies on a digital model of the station building, extracting officially certified evacuation corridor design parameters within each grid cell, including key indicators such as total corridor length and minimum effective width. The length of the evacuation corridor occupied by logistics equipment is determined using a path trajectory matching algorithm. This algorithm analyzes the topological relationship between the real-time operating trajectory of the freight equipment and the spatial coordinates of the evacuation corridor, calculating the continuous length of the corridor occupied by the equipment itself and the safety buffer area. A correction coefficient is dynamically adjusted based on the corridor level, with a higher correction coefficient for primary evacuation corridors than for auxiliary corridors, reflecting the importance of different corridor levels in emergency evacuations.

[0104] The impact factor calculation formula uses a ratio to reflect the degree of reduction in evacuation capacity caused by logistics occupancy. When logistics equipment completely blocks the main evacuation route, the evacuation efficiency impact factor for that grid cell reaches its maximum value. The calculated results are linked to the fire monitoring system. When the impact factor of a specific cell exceeds a safety threshold, an audible and visual alarm is automatically triggered, and emergency evacuation instructions are generated for logistics equipment. This design ensures that safety hazards are preemptively eliminated during normal operations, preventing the risk of evacuation route obstruction in emergencies.

[0105] Step S4: generating a scheduling strategy according to the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway.

[0106] Furthermore, a scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation on the subway, including:

[0107] If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed;

[0108] If the path conflict index is greater than or equal to the preset conflict threshold, the logistics equipment path is dynamically adjusted, specifically:

[0109] If it is a peak passenger flow period, the logistics equipment route will be allocated to non-passenger transfer channels and underground idle areas;

[0110] During periods of low passenger flow, routes that overlap with passenger flow lines are activated and the priority of logistics equipment is increased.

[0111] For example, the dynamic adjustment of logistics equipment routes utilizes a two-layer path planning strategy: the base layer is a fixed logistics trunk route, and the optimization layer is a flexible path generated in real time. During peak passenger flow periods, the path optimization algorithm prioritizes underground tunnels in non-passenger flow areas as alternative routes. These tunnels are typically reserved for equipment maintenance and can be temporarily activated to form dedicated logistics channels. For transport tasks that must pass through passenger activity areas, the system automatically generates time-sharing and segmented traffic plans, breaking down long-distance transport into multiple short-distance tasks and completing key sections during peak passenger flow periods.

[0112] For example, the dynamic route adjustment process is deeply integrated with the elevator dispatch system. When logistics equipment needs to be transported across floors, freight elevators are reserved in advance and the elevator's operating time is locked. The adjusted route plan is then sent to the AGV navigation system via the logistics control center, and the onboard terminal receives the route change instructions in real time. This dynamic route management mechanism effectively reduces the frequency of intersections between passenger and freight routes, achieving optimal allocation of transportation resources in the spatial dimension.

[0113] Furthermore, a scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in subways, specifically:

[0114] If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed;

[0115] If the path conflict index is greater than or equal to a preset conflict threshold, the flexible transport time window is executed, including:

[0116] Based on the passenger flow forecast results within the preset time period, logistics transportation tasks are inserted into the blank periods of the train timetable;

[0117] According to the passenger flow growth rate, the occupied time of logistics routes can be shortened.

[0118] For example, flexible transport time window allocation utilizes a demand-responsive scheduling model, identifying low-load periods within the train timetable based on the output of a passenger flow forecasting model. High-density logistics transport tasks are inserted during these periods, creating transport waves by compressing the time intervals between multiple logistics tasks. The time window allocation algorithm considers multiple constraints, such as transport task priority and equipment endurance, and employs a heuristic algorithm to generate the optimal task sequence. When a sudden surge in passenger flow renders the scheduled time window unavailable, the system immediately initiates an emergency rescheduling process, breaking down unfinished tasks and reallocating them to alternate time windows at nearby stations.

[0119] The dynamic time window adjustment process is synchronized with the train operation monitoring system, providing real-time information on changes in train arrival and departure times. When a train delay causes a time window shift, the logistics task execution sequence is automatically adjusted and the route plan is recalculated. This flexible mechanism significantly improves the transport plan's adaptability to changes in the operating environment, ensuring a healthy synergy between logistics and passenger services.

[0120] Furthermore, a scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in subways, specifically:

[0121] If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed;

[0122] If the path conflict index is greater than or equal to the preset conflict threshold, the key area logistics path is isolated, including:

[0123] Determine key areas based on the functional settings of each subway area;

[0124] The key areas are set as logistics restricted areas so that they can be used as logistics routes for logistics transportation only during non-operating periods.

[0125] For example, logistics routes in key areas are isolated using a combination of electronic fencing and physical barriers. Dynamic electronic fencing is installed in the platform security gate area. When logistics equipment approaches the restricted area, a three-level warning mechanism is triggered: a primary warning prompts the equipment to slow down, an intermediate warning initiates a mandatory speed limit, and a high-level warning directly cuts off the drive power. The physical isolation device uses liftable isolation piles, which automatically lower to form a logistics channel during non-operating hours and raise to form a continuous isolation zone during operating hours. Dedicated logistics entrances and exits are equipped with independent access control systems, using dual authentication methods such as biometrics and RFID to ensure transportation safety.

[0126] The vertical freight elevators implement a time-sharing sharing strategy, serving as backup emergency evacuation routes during the day and converting to dedicated logistics channels at night. The elevator's operating status is linked in real time to the logistics dispatch system, automatically clearing the elevator car and locking the route before a transport task arrives. This three-dimensional isolation and control system provides all-weather protection for critical areas, fundamentally eliminating the safety hazards associated with mixed passenger and freight transport.

[0127] When coordinating the coordinated scheduling of mixed passenger and freight transportation on the subway, the specific approach is to dynamically adjust the logistics equipment routes, implement flexible transportation time windows, or isolate logistics routes in key areas. Based on the actual capacity of the current subway, the degree of conflict, and priority judgment, one or more scheduling methods can be selected to alleviate conflicts and improve both passenger and logistics capacity while ensuring safety. In some implementations, after step S4, step S5 may also be included: path simulation verification of the hierarchical scheduling strategy through a digital twin platform, and iterative optimization of the logistics equipment path allocation plan in combination with a reinforcement learning algorithm to minimize the combined delay time of passengers and goods, thereby further improving the accuracy of scheduling.

[0128] Another aspect of the present invention provides a subway passenger and freight mixed transportation coordinated dispatching system, which executes any of the above subway passenger and freight mixed transportation coordinated dispatching methods, including:

[0129] Data collection module, used to collect passenger flow data and logistics data of subway stations in real time;

[0130] A spatiotemporal grid network model construction module is used to construct a spatiotemporal grid network model based on the passenger flow data and logistics data. The spatiotemporal grid network model divides the functional area of ​​the station into multiple layers of grid units and superimposes a time dimension to represent the dynamic path occupancy status;

[0131] a path conflict index calculation module, configured to calculate the path conflict index of each grid cell in the spatiotemporal grid network model based on a passenger density influencing factor, a logistics occupancy influencing factor, a passenger evacuation efficiency influencing factor, and an environmental control influencing factor;

[0132] The scheduling strategy generation module is used to generate a scheduling strategy according to the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway.

[0133] The subway passenger and freight mixed transportation collaborative scheduling method provided by the present invention realizes dynamic collaborative scheduling of passenger and freight transportation by constructing a spatiotemporal grid network model: based on the real-time collected passenger flow and logistics data, a coupling model of multidimensional spatial grid units and time dimensions is constructed to accurately characterize the spatiotemporal occupancy status of passenger and freight paths, and a dynamic risk assessment system is established by comprehensively calculating the path conflict index of passenger density, logistics occupancy, evacuation efficiency and environmental impact, so that the scheduling strategy can actively adapt to the passenger flow fluctuation law, realize passenger and freight spatial diversion through dynamic path adjustment during peak hours, utilize the elastic time window allocation mechanism to match transportation tasks with passenger flow tidal characteristics, and form a safe buffer space in combination with isolation control of key areas, effectively resolving the core contradictions such as path conflict, weakened evacuation capacity and environmental interference in traditional passenger and freight mixed transportation, significantly improving logistics transportation efficiency while ensuring the quality of passenger service, and at the same time enhancing the emergency response capability of the station operation system to sudden passenger flow changes, providing intelligent decision-making support for the subway system passenger and freight collaborative transportation.

[0134] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the technical solutions of the embodiments of the present invention.

Claims

1. A subway passenger and freight mixed transportation coordinated scheduling method, characterized in that: The steps include: Step S1: Real-time collection of passenger flow data and logistics data at subway stations; Step S2: constructing a spatiotemporal grid network model based on the passenger flow data and logistics data, wherein the spatiotemporal grid network model divides the functional area of ​​the station into multiple layers of grid units and superimposes a time dimension to represent the dynamic path occupancy status; Step S3: Calculating the path conflict index of each grid cell in the spatiotemporal grid network model based on the passenger density influencing factor, the logistics occupancy influencing factor, the passenger evacuation efficiency influencing factor, and the environmental control influencing factor; Step S4: generating a scheduling strategy based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway; The calculation formula of the path conflict index is: ； Where, represents the path conflict index of the i-th grid cell at time t, represents the passenger and cargo space impact factor of the i-th grid unit at time t, represents the passenger evacuation efficiency influencing factor of the i-th grid unit at time t, represents the environmental control influencing factor of the i-th grid cell at time t, and ω1, ω2 and ω3 are weight coefficients respectively.

2. A subway passenger and freight mixed transportation coordinated dispatching method according to claim 1, characterized in that: In step S2, a spatiotemporal grid network model is constructed based on the passenger flow data and logistics data, including: Based on the spatial layout of the station hall, platform and transfer passage, each functional area is divided into multi-layer grid units; The passenger flow data and logistics data are mapped to the corresponding grid units to generate a four-dimensional path occupancy matrix containing time stamps as the spatiotemporal grid network model.

3. The method for coordinated scheduling of mixed passenger and freight transportation in subways according to claim 1, characterized in that: The passenger and cargo space impact factor is calculated by the passenger density impact factor, the logistics occupancy impact factor and their corresponding weights. The formula is: ； Where, D passenger ( t,i ) represents the passenger density influencing factor of the i-th grid cell at time t, D logistics ( t,i ) represents the logistics occupancy impact factor of the i-th grid unit at time t, α represents the passenger density weight coefficient, and β represents the logistics occupancy weight coefficient; The passenger density influencing factor is calculated according to the real-time number of passengers and the maximum safe carrying capacity of each grid unit using the following formula: ； Where, N p ( t,i ) represents the real-time number of passengers in the i-th grid cell at time t, N p max represents the maximum safe load capacity within the i-th grid unit; The logistics occupancy impact factor is calculated based on the occupied area of ​​logistics equipment in each grid unit and the maximum allowed logistics occupied area. The calculation formula is: ; In the formula L f ( t,i ) represents the area occupied by logistics equipment in the i-th grid unit at time t, L f max represents the maximum allowable logistics area within the i-th grid cell.

4. The method for coordinated scheduling of mixed passenger and freight transportation in subways according to claim 1, characterized in that: The calculation of the passenger evacuation efficiency influencing factor includes the following steps: Extract evacuation channel design data within each grid cell; According to the length of the evacuation passage occupied by the logistics equipment and the design data of the evacuation passage, the passenger evacuation efficiency influencing factor is calculated, and the calculation formula is: ； Where, represents the passenger evacuation efficiency influencing factor of the i-th grid unit at time t, represents the length of the evacuation channel occupied by the logistics equipment of the i-th grid unit at time t, represents the total evacuation channel length in the evacuation channel design data within the i-th grid unit, is the correction factor.

5. The method for coordinated scheduling of mixed passenger and freight transportation in subways according to claim 1, characterized in that: The calculation of the environmental control impact factor comprises the following steps: Obtain the noise decibel value and air pollutant concentration in each grid cell in real time; The environmental control impact factor is calculated based on the noise decibel value and the air pollutant concentration. The calculation formula is: ； Where, represents the environmental control influence factor of the i-th grid cell at time t, represents the real-time noise value of the i-th grid cell at time t, represents the real-time air pollutant concentration of the i-th grid cell at time t, represents the noise threshold, represents the air pollution threshold, γ is the noise weight coefficient, and δ is the pollution weight coefficient.

6. The subway passenger and freight mixed transportation coordinated scheduling method according to claim 1 is characterized in that: A scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway, including: If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed; If the path conflict index is greater than or equal to the preset conflict threshold, the logistics equipment path is dynamically adjusted, specifically: If it is a peak passenger flow period, the logistics equipment route will be allocated to non-passenger transfer channels and underground idle areas; During periods of low passenger flow, routes that overlap with passenger flow lines are activated and the priority of logistics equipment is increased.

7. The method for coordinated scheduling of mixed passenger and freight transportation in subways according to claim 1, characterized in that: A scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in subways, specifically: If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed; If the path conflict index is greater than or equal to a preset conflict threshold, the flexible transport time window is executed, including: Based on the passenger flow forecast results within the preset time period, logistics transportation tasks are inserted into the blank periods of the train timetable; According to the passenger flow growth rate, the occupied time of logistics routes can be shortened.

8. The method for coordinated scheduling of mixed passenger and freight transportation in subways according to claim 1, characterized in that: A scheduling strategy is generated based on the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in subways, specifically: If the path conflict index is less than the preset conflict threshold, the original scheduling plan is executed; If the path conflict index is greater than or equal to the preset conflict threshold, the key area logistics path is isolated, including: Determine key areas based on the functional settings of each subway area; The key areas are set as logistics restricted areas so that they can be used as logistics routes for logistics transportation only during non-operating periods.

9. A subway passenger and freight mixed transportation coordinated dispatching system, characterized in that: The method for coordinated scheduling of mixed passenger and freight transportation in subways according to any one of claims 1 to 8 comprises: Data collection module, used to collect passenger flow data and logistics data of subway stations in real time; A spatiotemporal grid network model construction module is used to construct a spatiotemporal grid network model based on the passenger flow data and logistics data. The spatiotemporal grid network model divides the functional area of ​​the station into multiple layers of grid units and superimposes a time dimension to represent the dynamic path occupancy status; a path conflict index calculation module, configured to calculate the path conflict index of each grid cell in the spatiotemporal grid network model based on a passenger density influencing factor, a logistics occupancy influencing factor, a passenger evacuation efficiency influencing factor, and an environmental control influencing factor; The scheduling strategy generation module is used to generate a scheduling strategy according to the path conflict index to coordinate the scheduling of mixed passenger and freight transportation in the subway.

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