Signal vehicle integrated control system based on rail transit

Abstract

The invention discloses a signal vehicle integrated control system based on rail transit, and the system comprises a time determination unit which is used for determining a predicted arrival time point when a target train enters a target station; the congestion coefficient acquisition unit is used for acquiring congestion coefficients of N continuous future time points before and after the positioning time point; the graph construction unit is used for constructing a congestion event graph according to the congestion coefficients of the N continuous future time points; the time interval determination unit is used for determining a recommended arrival time interval of the target train in the congestion event graph; the speed interval determining unit is used for determining a recommended driving speed interval of the target train according to the recommended arrival time interval; according to the station entering feasibility index, the two key indexes including the average congestion coefficient and the maximum curve slope in the station entering time window are fused, the current congestion degree of the station and the change trend of future congestion can be reflected at the same time, and the congestion pressure of the station can be effectively relieved.

Description

Technical Field

[0001] The present invention relates to a rail transit control system, in particular to a signal vehicle integrated control system based on rail transit. Background Art

[0002] In rail transit systems, train dispatching and signal control are the core links to ensure the efficiency of system operation. With the continuous expansion of the scale of urban rail transit networks and the increase in train density, the traditional control method based on fixed timetables or static signal priority rules has become difficult to adapt to the increasingly complex operating environment. Especially during peak hours or in the case of temporary sudden scheduling changes, static scheduling schemes are often unable to respond dynamically according to real-time status, which can easily lead to problems such as train congestion, scheduling conflicts or waste of resources. Patent document CN105882695A discloses a forward-looking correlation control method for urban rail transit network passenger flow congestion. It formulates a network collaborative flow limiting scheme, reasonably sets the flow limiting stations, flow limiting time and flow limiting for congested related stations, and avoids the phenomenon of urban rail transit network passenger flow congestion in a forward-looking control manner.

[0003] However, existing scheduling strategies generally ignore the impact of changes in track resource occupancy at the station level on train scheduling, and lack predictions of congestion evolution trends in future time periods, making it difficult to dynamically adjust train operating speeds to avoid possible future congestion. Summary of the Invention

[0004] In response to the shortcomings of the existing technology, the present invention provides an integrated signal vehicle control system based on rail transit, which solves the technical problems raised in the background technology by constructing several entry feasibility indexes for the target train before and after the expected entry time point, and determining the recommended driving speed range based on the entry feasibility index.

[0005] To achieve the above objectives, the present invention is implemented through the following technical solutions: A signal vehicle integrated control system based on rail transit, the control system comprising: A time determination unit is used to determine the estimated time point of arrival of the target train into the target station; A congestion coefficient acquisition unit is used to use the expected arrival time as a reference time point for congestion coefficient collection, and extract the congestion coefficients of N consecutive future time points before and after the expected arrival time point; A graph construction unit, configured to construct a congestion event graph based on congestion coefficients at N consecutive future time points; A time interval determination unit, used to determine the recommended time interval for the target train to enter the station in the congestion event map; The speed interval determination unit is used to determine the recommended travel speed interval of the target train according to the recommended entry time interval.

[0006] In some specific embodiments, the step of determining the estimated arrival time by the time determination unit includes: S1-1, mark the passing sub-path of the target train; S1-2. Obtain the distance to be traveled by the target train in the pass sub-path; S1-3. Determine the estimated arrival time of the target train at the target station based on the distance to be traveled.

[0007] In some specific embodiments, marking the passing sub-path of the target train includes: S1-1-1. Obtain a track path diagram of a target train; S1-1-2. Mark the starting point and the end point of the target train on the track path diagram, as well as one or more candidate travel paths connecting the starting point and the end point; wherein each candidate travel path consists of a starting point, an end point, and a plurality of sequentially arranged stations therebetween; The track path diagram is a track network diagram in a two-dimensional coordinate system, wherein each station is calibrated by two-dimensional coordinates in the two-dimensional coordinate system; S1-1-3. In each candidate travel path, extract the travel track segments between adjacent stations and mark them as travel sub-paths.

[0008] In some specific embodiments, obtaining the distance to be traveled by the target train in the pass sub-path includes: S1-2-1, anchor the real-time position of the target train in the passage sub-path and the two-dimensional coordinates of the target station; S1-2-2, marking the remaining path of the target train in the transit sub-path according to the real-time position and the two-dimensional coordinates of the target station; S1-2-3. Obtain M two-dimensional coordinates covered by the remaining path; S1-2-4. Calculate the Euclidean distance between M-1 adjacent coordinates in the M two-dimensional coordinates; S1-2-5. Accumulate the M-1 Euclidean distances to obtain the distance to be traveled by the target train in the pass sub-path.

[0009] In some specific embodiments, determining the estimated arrival time of the target train at the target station includes: S1-3-1. Obtain the real-time running speed of the target train; S1-3-2. Determine the theoretical travel time for the target train to reach the target station based on the target train's real-time running speed and the distance to be traveled; S1-3-3. Anchor the current time point on the time axis, and starting from the current time point, extend the theoretical travel time to determine the estimated arrival time of the target train at the target station.

[0010] In some specific embodiments, the step of the congestion coefficient obtaining unit obtaining the congestion coefficient includes: S2-1. Using the expected arrival time as the base time, extend forward and backward by N consecutive future time points with equal amplitude; S2-2. Obtaining traffic status parameters of the target site at N consecutive future time points; The traffic status parameters include: the number of trains scheduled to arrive at each time point, the number of trains scheduled to stop, the planned duration of each stop, and the number of trains scheduled to depart at each time point; S2-3. Calculate the congestion coefficients at N consecutive future time points based on the traffic state parameters at N consecutive future time points; The calculation formula of the congestion coefficient is: ; in, represents the congestion coefficient at the i-th future time point, represents the number of trains scheduled to arrive at the i-th future time point, Indicates the standard arrival train dwell time. represents the number of trains scheduled to stop at the i-th future time point, represents the planned stopover time of the jth train at the i-th future time point, represents the expected number of departing trains at the i-th future time point, Indicates the standard departure time. represents normalization; In some specific embodiments, the step of constructing the congestion event graph by the graph construction unit includes: S3-1. Establish a two-dimensional coordinate system with continuous future time points as the horizontal axis and the congestion coefficient as the vertical axis; S3-2. Mark the congestion coefficients corresponding to N consecutive future time points in the two-dimensional coordinate system. S3-3. The congestion coefficient corresponding to each consecutive future time point in the two-dimensional coordinate system is defined as a congestion event; S3-4. Connect N adjacent congestion events to form a congestion event graph.

[0011] In some specific embodiments, the step of determining the recommended arrival time interval of the target train by the time interval determination unit includes: S4-1. On the horizontal axis of the congestion event graph, a fixed-length entry time window is constructed; wherein the length of the entry time window is the standard stop time of the target train at the target station; S4-2, using a single future time point as a sliding step, sliding fixed-length entry time windows one by one on the horizontal axis of the congestion event graph; S4-3. Calculate the average congestion coefficient and maximum curve slope of the curve within the entry time window after sliding one by one; S4-4. Determine an entry feasibility index for the entry time window based on the average congestion coefficient and the slope of the curve within the entry time window; The calculation formula of the pit stop feasibility index is: ; in, represents the pit stop feasibility index, It represents the average congestion coefficient of the curve within the entry time window after sliding; Indicates the maximum slope of the curve within the sliding stop time window, The weight representing the maximum curve slope; S4-5. If the entry feasibility index is less than the set threshold, the entry time window corresponding to the entry feasibility index is defined as the recommended entry time interval; otherwise, the fixed-length entry time windows are continuously slid one by one; wherein the recommended entry time interval includes several recommended entry time points.

[0012] In some specific embodiments, the step of the speed interval determining unit determining the recommended speed interval of the target train includes: S5-1. Determine whether the recommended stop-in time interval covers the expected stop-in time point; S5-2. If the estimated arrival time is covered, the real-time running speed of the target train is maintained; otherwise, the distance to be traveled by the target train is recalculated; S5-3, obtaining the ideal driving time between several recommended stop-in time points and the current time point; S5-4, determining the recommended travel speeds of the target train corresponding to the plurality of recommended station entry time points based on the ideal travel times and the recalculated distance to be traveled at the plurality of recommended station entry time points; S5-5. Sort the recommended driving speeds for the multiple recommended entry time points to obtain a recommended driving speed range; S5-6. Adjust the real-time running speed of the target train to keep it within the recommended running speed range.

[0013] The present invention provides a signal vehicle integrated control system based on rail transit, which has the following beneficial effects: The present invention realizes the quantitative evaluation of the feasibility of the train entry window by constructing the entry feasibility index. The entry feasibility index integrates two key indicators: the average congestion coefficient within the entry time window and the maximum slope of the curve. It can simultaneously reflect the current congestion level of the station and the changing trend of future congestion. In addition, the present invention provides a scheduling scheme based on real-time traffic status, train position and target station congestion by combining the congestion event graph, the sliding time window of the entry time window and dynamic speed adjustment. It can effectively avoid high congestion risks and realize efficient and stable operation of the rail transit system through optimized driving speed range. This method can not only dynamically adapt to the traffic conditions of different stations, but also accurately adjust the operation of the train according to the real-time conditions, thereby improving the utilization efficiency of track resources, reducing delays, ensuring that the train enters the station on time, and effectively alleviating the congestion pressure of the station. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 This is a structural block diagram of a signal vehicle integrated control system based on rail transit of the present invention; Figure 2 This is a control flow diagram of a rail transit-based signal vehicle integrated control system according to the present invention; Figure 3 This is a schematic diagram of the congestion coefficient calculation process of the present invention; Figure 4 This is a schematic diagram of the station entry feasibility index comparison process described in the present invention. DETAILED DESCRIPTION

[0015] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0016] See also Figures 1 to 4 The present invention provides a signal vehicle integrated control system based on rail transit, the control system comprising: A time determination unit is used to determine the estimated time point of arrival of the target train into the target station; Exemplarily, in this embodiment, the step of determining the estimated time point of entering the station by the time determination unit includes: S1-1, mark the passing sub-path of the target train; S1-2. Obtain the distance to be traveled by the target train in the pass sub-path; S1-3. Determine the estimated arrival time of the target train at the target station based on the distance to be traveled.

[0017] It's important to note that the estimated arrival time is calculated based on the target train's current real-time status and the remaining distance. By combining the remaining distance and the target train's real-time speed, we can predict when the train will arrive at the target station at its current speed, thereby calculating the estimated arrival time.

[0018] Furthermore, the step S1-1 specifically includes: S1-1-1. Obtain a track path diagram of a target train; S1-1-2. Mark the starting point and the end point of the target train on the track path diagram, as well as one or more candidate travel paths connecting the starting point and the end point; wherein each candidate travel path consists of a starting point, an end point, and a plurality of sequentially arranged stations therebetween; The track path diagram is a track network diagram in a two-dimensional coordinate system, wherein each station is calibrated by two-dimensional coordinates in the two-dimensional coordinate system; It should be noted that the marking objects of the starting point, end point and station described in this embodiment are their two-dimensional coordinates in the track path diagram. For example, the two-dimensional coordinates can be selected longitude and latitude coordinates.

[0019] S1-1-3. In each candidate travel path, extract the travel track segments between adjacent stations and mark them as travel sub-paths.

[0020] It's important to note that marking the target train's travel sub-path involves explicitly marking the target train's entire trajectory on the track map. First, by obtaining the target train's track map, the starting and ending points are defined, and candidate travel paths for the train are identified. On these candidate paths, the starting and ending points are connected by multiple adjacent stations to form a complete path. The track segments between these "adjacent stations" on each path are the travel sub-paths.

[0021] Among them, each sub-path has a clear spatial coordinate position in the track map. These positions are calibrated based on a two-dimensional coordinate system (such as longitude and latitude coordinates) to ensure that each station and path segment can be accurately mapped to the actual track network.

[0022] Furthermore, the step S1-2 specifically includes: S1-2-1, anchor the real-time position of the target train in the passage sub-path and the two-dimensional coordinates of the target station; S1-2-2, marking the remaining path of the target train in the transit sub-path according to the real-time position and the two-dimensional coordinates of the target station; S1-2-3. Obtain M two-dimensional coordinates covered by the remaining path; S1-2-4. Calculate the Euclidean distance between M-1 adjacent coordinates in the M two-dimensional coordinates; S1-2-5. Accumulate the M-1 Euclidean distances to obtain the distance to be traveled by the target train in the pass sub-path.

[0023] Specifically, by anchoring the target train's real-time position with the 2D coordinates of the target station, the remaining path segment (i.e., the remaining path) can be identified. This remaining path is typically represented in a track diagram as a set of continuous 2D coordinate points, which, based on spatial points on the track line, form the track trajectory that the train still needs to traverse.

[0024] On this basis, by calculating the Euclidean distance between these coordinate points, that is, the straight-line distance between every two adjacent coordinate points, and accumulating the distances between all adjacent points, the remaining physical travel length of the train on the current sub-path can be obtained.

[0025] It should be emphasized that since the actual rail transit lines may have a certain degree of curvature, the density and accuracy of the two-dimensional coordinate sequence are crucial to the accuracy of the remaining path calculation; during deployment, it is usually necessary to rely on the refined line coordinate point data provided by the rail transit operator or to update the track path in real time through a high-frequency positioning system.

[0026] Furthermore, the step S1-3 specifically includes: S1-3-1. Obtain the real-time running speed of the target train; S1-3-2. Determine the theoretical travel time for the target train to reach the target station based on the target train's real-time running speed and the distance to be traveled; S1-3-3. Anchor the current time point on the time axis, and starting from the current time point, extend the theoretical travel time to determine the estimated arrival time of the target train at the target station.

[0027] It should be noted that the estimated arrival time in this embodiment is determined based on the train's current operating status, the physical distance it still needs to travel, and its current speed. Specifically, the real-time speed is first collected and divided by the length of the route to be traveled to determine the theoretical travel time required for the train to reach the destination station.

[0028] Next, the theoretical travel time will be used as a linear time extension factor, calculated backward from the current system time (that is, the time when the train obtains positioning and speed information), so as to calculate the time when the train is expected to arrive at the target station, which is the "estimated arrival time".

[0029] Furthermore, the control system further includes: A congestion coefficient acquisition unit is used to use the expected arrival time as a reference time point for congestion coefficient collection, and extract the congestion coefficients of N consecutive future time points before and after the expected arrival time point; Illustratively, in this embodiment, the step of the congestion coefficient obtaining unit obtaining the congestion coefficient includes: S2-1. Using the expected arrival time as the base time, extend forward and backward by N consecutive future time points with equal amplitude; S2-2. Obtaining traffic status parameters of the target site at N consecutive future time points; The traffic status parameters include: the number of trains scheduled to arrive at each time point, the number of trains scheduled to stop, the planned duration of each stop, and the number of trains scheduled to depart at each time point; It should be noted that the traffic status parameters described in this embodiment are all preset or predictable data items, typically derived from train timetables, scheduling plans, or historical data. For example, the number of planned arriving trains and the number of planned stopping trains can be set in advance based on the established timetable; the planned dwell time of each stopping train can also be estimated based on the type of train and the station's function; and the expected number of departing trains is typically deduced based on station scheduling logic and the operating status of the preceding trains.

[0030] S2-3. Calculate the congestion coefficients at N consecutive future time points based on the traffic state parameters at N consecutive future time points; The calculation formula of the congestion coefficient is: ; in, represents the congestion coefficient at the i-th future time point, represents the number of trains scheduled to arrive at the i-th future time point, meaning that the more trains arrive, the higher the occupancy; Indicates the standard arrival train dwell time, used to estimate the time the arrival train occupies the track (based on the average calculation of the historical data period). represents the number of trains scheduled to stop at the i-th future time point, represents the planned stopover time of the jth train at the i-th future time point, represents the number of trains expected to depart at the i-th future time point. More trains departing means freeing up track resources and reducing congestion. It represents the standard departure time, which means the average time unit released by each departing train. The more time is released, the more obvious the congestion relief effect is. Represents normalization; specifically, each calculated original congestion coefficient can be subjected to maximum and minimum normalization calculation with the maximum and minimum congestion coefficients within N future time points to generate a normalized congestion coefficient corresponding to the original congestion coefficient at the time point.

[0031] Specifically, Predict how many new trains will arrive at the station in the future and estimate how long they will take. Considering that there are trains still occupying the track, sum up all the remaining occupancy times, This means that deducting the trains that will release track resources can alleviate congestion. In short, the congestion coefficient expresses the amount of congestion at a point in time by estimating the total track occupancy time.

[0032] In this embodiment, the congestion coefficient is calculated based on the planned number of arriving trains, the number of stopping trains, the duration of the stops, and the expected number of departing trains. The core calculation logic is to estimate the congestion level of the station at each time point through the dynamic occupation and release behavior of track resources.

[0033] Furthermore, the control system further includes: A graph construction unit, configured to construct a congestion event graph based on congestion coefficients at N consecutive future time points; Exemplarily, in this embodiment, the step of the graph construction unit constructing a congestion event graph includes: S3-1. Establish a two-dimensional coordinate system with continuous future time points as the horizontal axis and the congestion coefficient as the vertical axis; S3-2. Mark the congestion coefficients corresponding to N consecutive future time points in the two-dimensional coordinate system. S3-3. The congestion coefficient corresponding to each consecutive future time point in the two-dimensional coordinate system is defined as a congestion event; S3-4. Connect N adjacent congestion events to form a congestion event graph.

[0034] It should be noted that the congestion event graph constructed in this embodiment is based on the two-dimensional mapping result of future time points and their corresponding congestion coefficients. The congestion coefficient at each time point is marked as a "congestion event" and adjacent points are connected in chronological order to form a curve trajectory. The originally discrete congestion coefficient is presented in the form of a curve so that the slope of the curve can represent the speed and trend of congestion changes at the station in the future time period, that is, the rate of increase and decrease and direction of congestion. The larger the slope, the faster the congestion level increases; a negative slope indicates that congestion is decreasing; a slope approaching zero indicates that the congestion level is stabilizing.

[0035] The congestion event graph includes a curve trajectory with continuous future time points as the horizontal axis and the corresponding congestion coefficient as the vertical axis, reflecting the congestion change trend of the target station on the future time axis; Furthermore, the control system further includes: A time interval determination unit, used to determine the recommended time interval for the target train to enter the station in the congestion event map; Exemplarily, in this embodiment, the step of the time interval determining unit determining the recommended arrival time interval of the target train includes: S4-1. On the horizontal axis of the congestion event graph, a fixed-length entry time window is constructed; wherein the length of the entry time window is the standard stop time of the target train at the target station; The length of the station entry time window is equal to the standard travel cycle of the train at the station, including the total time required for entering the station, stopping, boarding and disembarking passengers, and exiting the station; S4-2, using a single future time point as a sliding step, sliding fixed-length entry time windows one by one on the horizontal axis of the congestion event graph; S4-3. Calculate the average congestion coefficient and maximum curve slope of the curve within the entry time window after sliding one by one; S4-4. Determine an entry feasibility index for the entry time window based on the average congestion coefficient and the slope of the curve within the entry time window; The calculation formula of the pit stop feasibility index is: ; in, Indicates the feasibility index of the pit stop (the higher the better), It represents the average congestion coefficient of the curve within the entry time window after sliding; Indicates the maximum slope of the curve within the sliding stop time window, The weight representing the maximum curve slope; Specifically, the denominator of this formula represents the product of the congestion and volatility risk penalties. The greater the average congestion coefficient or the maximum curve slope, the lower the entry feasibility index. In other words, both the average congestion coefficient and the maximum curve slope significantly lower the entry feasibility index.

[0036] S4-5. If the entry feasibility index is less than the set threshold, the entry time window corresponding to the entry feasibility index is defined as the recommended entry time interval; otherwise, the fixed-length entry time windows are continuously slid one by one; wherein the recommended entry time interval includes several recommended entry time points.

[0037] It should be noted that this embodiment combines a sliding window with the dynamic curve changes of the congestion event graph to achieve a comprehensive assessment of congestion conditions at different time periods in the future. The introduction of the station entry feasibility index not only considers the overall congestion level within the station entry window (average congestion coefficient) but also quantifies the volatility of congestion trends (maximum curve slope), effectively avoiding the risk of misjudging complex scenarios such as "low congestion but a sharp increase" or "high congestion but easing." The resulting recommended station entry time interval features low congestion risk and high stability, helping to guide trains into stations at more optimal times.

[0038] Furthermore, the control system further includes: The speed interval determination unit is used to determine the recommended travel speed interval of the target train according to the recommended entry time interval.

[0039] Exemplarily, in this embodiment, the step of the speed interval determining unit determining the recommended travel speed interval of the target train includes: S5-1. Determine whether the recommended stop-in time interval covers the expected stop-in time point; S5-2. If the estimated arrival time is covered, the real-time running speed of the target train is maintained; otherwise, the distance to be traveled by the target train is recalculated; S5-3, obtaining the ideal driving time between several recommended stop-in time points and the current time point; S5-4, determining the recommended travel speeds of the target train corresponding to the plurality of recommended station entry time points based on the ideal travel times and the recalculated distance to be traveled at the plurality of recommended station entry time points; S5-5. Sort the recommended driving speeds for the multiple recommended entry time points to obtain a recommended driving speed range; S5-6. Adjust the real-time running speed of the target train to keep it within the recommended running speed range.

[0040] It should be noted that in this embodiment, by matching and calculating the recommended entry time point with the length to be traveled between the current position of the train, a set of ideal travel speeds corresponding to the time points are generated, and a recommended travel speed interval is formed accordingly. The recommended travel speed interval provides multiple feasible speed options to adapt to the scheduling requirements corresponding to multiple recommended entry time points. By judging whether the expected entry time point has been covered by the recommended entry time interval, the system can decide whether to maintain the current speed or recalculate a better speed based on the real-time path and the recommended time point, thereby realizing dynamic adjustment of the train's operating status. This dynamic adjustment strategy emphasizes the linkage between speed control and congestion windows, effectively avoiding the waste of track resources and scheduling conflicts caused by blind speed increases or lagging operations.

[0041] It should be noted that the recommended driving speed range refers to the range of possible driving speeds obtained by time reverse calculation, based on the known remaining path length between the current position of the target train and the target station, combined with the earliest and latest entry time points allowed by the recommended entry time range.

[0042] In summary, the present invention provides a scheduling solution based on real-time traffic status, train location, and target station congestion by combining a congestion event graph, a sliding time window of the arrival time window, and dynamic speed adjustment. By predicting the arrival time of the target train and controlling the speed in real time, the system can effectively avoid the risk of high congestion and achieve efficient and stable operation of the rail transit system through optimized driving speed ranges. This method can not only dynamically adapt to the traffic conditions of different stations, but also accurately adjust the operation of the train according to the real-time conditions, thereby improving the efficiency of track resource utilization, reducing delays, ensuring that the train arrives at the station on time, and effectively alleviating the congestion pressure at the station.

[0043] The above embodiments can be implemented in whole or in part by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer program are loaded or executed on a computer, the process or function described in the embodiments of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via a wired method (e.g., infrared, wireless, microwave, etc.).

[0044] The computer-readable storage medium can be any available medium that can be accessed by a computer, or a data storage device such as a server or data center that contains one or more available media. The available medium can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. The semiconductor media can be a solid-state drive.

[0045] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices, and methods can be implemented in other ways. For example, the device embodiments described above are merely illustrative, and for example, multiple units or components can be combined or integrated into another system, or some features can be omitted or not implemented. In addition, the coupling or direct coupling or communication connection shown or discussed can be through some interface, indirect coupling or communication connection of devices or units, and can be electrical, mechanical, or other forms.

[0046] The above is only a specific implementation method of the present application, but the scope of protection of the present application is not limited thereto. Any technician familiar with this technical field can easily think of changes or replacements within the technical scope disclosed in this application, which should be covered by the scope of protection of the present application.

Claims

1. A signal vehicle integrated control system based on rail transit, characterized in that: include: A time determination unit is used to determine the estimated time point of arrival of the target train into the target station; A congestion coefficient acquisition unit is used to use the expected arrival time as a reference time point for congestion coefficient collection, and extract the congestion coefficients of N consecutive future time points before and after the expected arrival time point; A graph construction unit, configured to construct a congestion event graph based on congestion coefficients at N consecutive future time points; A time interval determination unit, used to determine the recommended time interval for the target train to enter the station in the congestion event map; The speed interval determination unit is used to determine the recommended travel speed interval of the target train according to the recommended entry time interval.

2. The integrated signal vehicle control system based on rail transit according to claim 1, characterized in that: The step of determining the estimated arrival time by the time determination unit includes: S1-1, mark the passing sub-path of the target train; S1-2. Obtain the distance to be traveled by the target train in the pass sub-path; S1-3. Determine the estimated arrival time of the target train at the target station based on the distance to be traveled.

3. The integrated signal vehicle control system based on rail transit according to claim 2, characterized in that: Mark the target train's travel subpath, including: S1-1-1. Obtain a track path diagram of a target train; S1-1-2. Mark the starting point and the end point of the target train on the track path diagram, as well as one or more candidate travel paths connecting the starting point and the end point; wherein each candidate travel path consists of a starting point, an end point, and a plurality of sequentially arranged stations therebetween; The track path diagram is a track network diagram in a two-dimensional coordinate system, wherein each station is calibrated by two-dimensional coordinates in the two-dimensional coordinate system; S1-1-3. In each candidate travel path, extract the travel track segments between adjacent stations and mark them as travel sub-paths.

4. The integrated signal vehicle control system based on rail transit according to claim 2, characterized in that: Obtain the target train's remaining travel distance in the passable sub-path, including: S1-2-1, anchor the real-time position of the target train in the passage sub-path and the two-dimensional coordinates of the target station; S1-2-2, marking the remaining path of the target train in the transit sub-path according to the real-time position and the two-dimensional coordinates of the target station; S1-2-3. Obtain M two-dimensional coordinates covered by the remaining path; S1-2-4. Calculate the Euclidean distance between M-1 adjacent coordinates in the M two-dimensional coordinates; S1-2-5. Accumulate the M-1 Euclidean distances to obtain the distance to be traveled by the target train in the pass sub-path.

5. The integrated signal vehicle control system based on rail transit according to claim 2, characterized in that: Determine the estimated arrival time of the target train at the target station, including: S1-3-1. Obtain the real-time running speed of the target train; S1-3-2. Determine the theoretical travel time for the target train to reach the target station based on the target train's real-time running speed and the distance to be traveled; S1-3-3. Anchor the current time point on the time axis, and starting from the current time point, extend the theoretical travel time to determine the estimated arrival time of the target train at the target station.

6. The integrated signal vehicle control system based on rail transit according to claim 2, characterized in that: The step of the congestion coefficient obtaining unit obtaining the congestion coefficient includes: S2-1. Using the expected arrival time as the base time, extend forward and backward by N consecutive future time points with equal amplitude; S2-2. Obtaining traffic status parameters of the target site at N consecutive future time points; The traffic status parameters include: the number of trains scheduled to arrive at each time point, the number of trains scheduled to stop, the planned duration of each stop, and the number of trains scheduled to depart at each time point; S2-3. Calculate the congestion coefficients at N consecutive future time points based on the traffic state parameters at N consecutive future time points; The calculation formula of the congestion coefficient is: ； in, represents the congestion coefficient at the i-th future time point, represents the number of trains scheduled to arrive at the i-th future time point, Indicates the standard arrival train dwell time. represents the number of trains scheduled to stop at the i-th future time point, represents the planned stopover time of the jth train at the i-th future time point, represents the expected number of departing trains at the i-th future time point, Indicates the standard departure time. Indicates normalization.

7. The integrated signal vehicle control system based on rail transit according to claim 6, characterized in that: The step of constructing a congestion event graph by the graph construction unit includes: S3-1. Establish a two-dimensional coordinate system with continuous future time points as the horizontal axis and the congestion coefficient as the vertical axis; S3-2. Mark the congestion coefficients corresponding to N consecutive future time points in the two-dimensional coordinate system. S3-3. The congestion coefficient corresponding to each consecutive future time point in the two-dimensional coordinate system is defined as a congestion event; S3-4. Connect N adjacent congestion events to form a congestion event graph.

8. The integrated signal vehicle control system based on rail transit according to claim 7, characterized in that: The step of determining the recommended arrival time interval of the target train by the time interval determination unit includes: S4-1. On the horizontal axis of the congestion event graph, a fixed-length entry time window is constructed; wherein the length of the entry time window is the standard stop time of the target train at the target station; S4-2, using a single future time point as a sliding step, sliding fixed-length entry time windows one by one on the horizontal axis of the congestion event graph; S4-3. Calculate the average congestion coefficient and maximum curve slope of the curve within the entry time window after sliding one by one; S4-4. Determine an entry feasibility index for the entry time window based on the average congestion coefficient and the slope of the curve within the entry time window; The calculation formula of the pit stop feasibility index is: ； in, represents the pit stop feasibility index, It represents the average congestion coefficient of the curve within the entry time window after sliding; Indicates the maximum slope of the curve within the sliding stop time window, The weight representing the maximum curve slope; S4-5. If the pit stop feasibility index is less than the set threshold, defining the pit stop time window corresponding to the pit stop feasibility index as the recommended pit stop time interval; otherwise, continuing to slide the pit stop time windows of fixed length one by one; The recommended entry time interval includes several recommended entry time points.

9. The integrated signal vehicle control system based on rail transit according to claim 8, characterized in that: The step of determining the recommended travel speed interval of the target train by the speed interval determination unit includes: S5-1. Determine whether the recommended stop-in time interval covers the expected stop-in time point; S5-2. If the estimated arrival time is covered, the real-time running speed of the target train is maintained; otherwise, the distance to be traveled by the target train is recalculated; S5-3, obtaining the ideal driving time between several recommended stop-in time points and the current time point; S5-4, determining the recommended travel speeds of the target train corresponding to the plurality of recommended station entry time points based on the ideal travel times and the recalculated distance to be traveled at the plurality of recommended station entry time points; S5-5. Sort the recommended driving speeds for the multiple recommended entry time points to obtain a recommended driving speed range; S5-6. Adjust the real-time running speed of the target train to keep it within the recommended running speed range.

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