Single-line and multi-line bus stringing vehicle optimization control method

Abstract

The application provides a single-line and multi-line bus string vehicle optimization control method, which firstly carries out single-line bus string vehicle prevention and treatment, carries out intersection signal adjustment by analyzing the relationship between the bus arrival intersection time and the signal execution state, and takes the bus state of the single road section bus string vehicle, signal control and road parameters as system inputs, selects the decision type through the calculation and analysis of the headway offset between stations, designs an edge computing-based decision method to solve the decision problems of optimization measure selection and optimization measure combination, and then carries out multi-road section bus string vehicle prevention and treatment, adopts a multi-road section string vehicle prevention and treatment decision method, and designs multi-road section bus string vehicle prevention and treatment optimization targets from two aspects of bus string vehicle prevention and treatment inter-station road section quantity control and road per capita delay control through historical case retrieval, similar case extraction, similar case correction and case storage.

Description

Technical Field

[0001] This invention relates to an optimized control method for single-line and multi-line bus lane merging, mainly used to solve the problem of bus lane merging prevention and operation recovery control. Background Technology

[0002] During actual operation, buses experience headway deviations due to random fluctuations. The cumulative effect of these deviations can lead to bus lane separation, which disrupts bus operation plans and easily causes a series of problems such as platform congestion, reduced operational efficiency, and decreased passenger satisfaction. Therefore, preventing bus lane separation has gradually become a research hotspot for scholars both domestically and internationally. Existing research on optimizing bus lane separation mostly uses bus stop control to adjust headway. However, this method easily leads to poor punctuality and low responsiveness to passenger demand. Therefore, relying solely on bus stop control is insufficient to improve the overall decline in bus service quality. Furthermore, adjusting departure intervals, temporarily adding backup buses, and allowing vehicles to overtake in lane separation do not effectively and sustainably improve bus lane separation; instead, they further exacerbate the problem by increasing passenger demand responsiveness and management costs for bus companies. Therefore, it is necessary to utilize proactive control methods to improve bus lane separation. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes an optimized control method for single-line and multi-line bus berths, specifically employing the following technical solution:

[0004] The method includes the following steps:

[0005] (1) Prevention of bus berthing on single-line routes

[0006] (1.1) Status Analysis of Single-Rail Bus Routes

[0007] in For the first The on-time arrival time of each platform The arrival and departure of the vehicle are respectively At the moment of the intersection, The arrival and departure of the vehicle are respectively At the time of the platform, The first Platform 1 and the first The upper and lower limits of the prescribed arrival time interval between platforms. The first From the first station to the second The first intersection and the first The intersection to the first The distance between each station For the first the bus stop time at the station, the first the red light waiting time at the intersection, the punctual arrival time section;

[0008] analyze the bus inter-station running state:

[0009] (1)

[0010] wherein the vehicle driving speed on the road section ;

[0011] analyze the relationship between the bus arrival time at the intersection and the signal execution state:

[0012] 1) if , the bus vehicle passes through the intersection during the green light period, wherein represents the first period, respectively represents the green light start time and the end time of the first period, and ;

[0013] 2) if , the bus vehicle arrives at the intersection during the red light period at the intersection, and the intersection signal adjustment threshold is combined to judge the bus intersection state, and the specific process is as follows:

[0014] the maximum green light extension time of the intersection needs to meet formula (2)

[0015] (2)

[0016] the maximum red light early break time of the intersection needs to meet formula (3)

[0017] (3)

[0018] wherein is the maximum green light and minimum green light time of the intersection;

[0019] therefore, the maximum adjustment amount of the intersection is obtained;

[0020] if , the bus can pass through the intersection without stopping by extending the green light , at this time ; otherwise, the green light extension cannot affect the vehicle intersection state, at this time ;

[0021] if , then the bus can pass the intersection without stopping by early red light breaking , at this time ; otherwise, the early red light breaking method cannot be used to reduce the intersection time consumption, at this time ;

[0022] In summary, the shortest optimized travel time between stations is

[0023] (4)

[0024] The adjusted arrival time at the station is obtained by combining formula (1) t i apn At this time, the station-to-station headway offset of the vehicle is defined as:

[0025] (5)

[0026] When , there is no station-to-station headway deviation for the vehicle, and no further correction is needed; when , the bus arrives at the bus stop early, and the bus headway is compensated by the bus stop method, and the stop time is ; when , there is a station-to-station headway deviation, and further adjustment is needed in the next section.

[0027] (1.2) Single-section bus string optimization

[0028] The single-section bus string prevention steps are as follows:

[0029] Step 1: Collect environmental state parameter set , and perform correlation analysis with the historical states in the decision library, and select The decision scheme corresponding to the historical state with the smallest difference is selected as the initialization control scheme ;

[0030] Step 2: Select scheme , , calculate the time of the scheme to arrive at the station :

[0031] (6)

[0032] If , execute Step 3, if , execute Step 4, if , execute Step 5.

[0033] Step 3: Calculate the average delay per person under this scenario. Use the HCM1985 delay model to analyze the average delay per person at the intersection, as shown below:

[0034] (7)

[0035] in For green credit ratio, For saturation, For the intersection cycle, Indicates traffic flow at the intersection;

[0036] like If the number of solutions is less than 1, then the solution set has not been fully calculated. Then proceed to Step 3; if The solution set has been calculated; proceed to Step 6.

[0037] Step 4: If the bus arrives at the bus stop earlier than expected, the headway offset between stops is: At this point, it is necessary to control the number of buses waiting at bus stops. Bus guidance speed v i Reduce speed by one unit within the constraints. The unit of speed Defined as 1 m / s; if the intersection signal adjustment amount The signal adjustment amount is reduced by one signal unit. The signal unit quantity is set to 1 second, and then Step 2 is executed;

[0038] Step 5: If the bus arrives at the bus stop later than the scheduled time, the headway offset between stops is: At this point, it is necessary to control the number of buses waiting at bus stops. Bus guidance speed v i Increase the speed unit within the constraints. The intersection signal adjustment amount increases by one signal unit within the constraint range. Then proceed to Step 2;

[0039] Step 6: Calculate the average delay per person. Choose the one with the smallest average delay per person. and will The corresponding solution As the final implementation plan, it will be issued, along with the detailed parameters of the plan. Stored in the decision database;

[0040] (2) Prevention and control of multiple bus routes running together

[0041] (2.1) Multi-line bus state analysis

[0042] Define the time when the front and rear vehicles leave the bus stop , and the adjusted travel times of the front and rear vehicles are obtained according to formula (5) , and the time table time of the front and rear vehicles at the station .

[0043] (2.1.1) If the arrival order and vehicle route order are consistent

[0044] If , the arrival order is consistent with the vehicle route order, and when the rear vehicle leaves the bus stop, the distance between the front and rear vehicles satisfies , and the front and rear vehicle distance constraints should satisfy formula (8)

[0045] (8)

[0046] where , are the real-time speeds of the front and rear vehicles on the route , which are mainly obtained by real-time vehicle-mounted GPS. It should be noted that , which means that the rear vehicle has caught up with the front vehicle at this time, and the rear vehicle speed needs to satisfy .

[0047] Therefore, the travel time under the multi-line state is:

[0048] (9)

[0049] and the arrival headway offset can be analyzed according to formula (5).

[0050] (2.1.2) If the arrival order and vehicle route order are inconsistent

[0051] If , the arrival order is inconsistent with the vehicle route order, and the rear vehicle arrives first, and the front vehicle arrives later, where the required dwell time of the front vehicle is:

[0052] (10)

[0053] where is the predicted dwell time of the front vehicle at the bus stop;

[0054] Further reduce the arrival time difference between the front and rear vehicles , i.e.

[0055] (11)​​

[0056] in Indicates a fixed component;

[0057] (2.2) Optimization of multi-segment bus service

[0058] The steps to prevent multiple bus routes from interfering with each other are as follows:

[0059] Step 1: Use The case library information is represented in the form of , where Indicates the number of cases in the case library. Indicates the first Traffic status information description for each case, and ,in Indicates the first The first case Each feature description, The number of feature attributes;

[0060] Step 2: Define the traffic state description for the new train-on-train scenario. For calculation same The similarity is calculated using a similarity evaluation algorithm based on Euclidean distance, namely:

[0061] (12)

[0062] in For the first The weights of each feature, and ;

[0063] Then process the results in descending order. Rank the relevance scores and select from them. The most similar cases, among which ;

[0064] Step 3: Define three evaluation parameters: whether the speed constraint is met, whether normal operation can be restored, and whether the required inter-station distance is appropriate. The evaluation coefficient for the effectiveness of the solution can be defined as:

[0065] (13)

[0066] like This indicates that the solution meets the requirements, at which point Step 5 is executed; if This indicates that at least one requirement of the solution is not met, and Step 4 is executed in this case;

[0067] Step 4: When At that time, the plan was revised and adjusted, firstly by... The values of the three are judged, if , the maximum bus speed is selected according to the constraint range; if , the bus vehicle guidance speed and intersection signal priority state are optimized; if , the travel time of the bus vehicle is further compressed, and the cumulative travel time in the adjustment process is:

[0068] (14);

[0069] Step 5: save the control scheme meeting the requirements to the temporary scheme set , then repeat Step 3 and Step 4 to evaluate and correct all Group control strategies, finally obtain a group of schemes meeting the correct solution requirements, and select a group of schemes with the minimum target function value as the final execution scheme, the best scheme is issued at the same time, and the scheme and its corresponding scene state are stored in the case library in the form of binary tuple , for subsequent decision-making use. BRIEF DESCRIPTION OF DRAWINGS

[0070] Figure 1 is a single shift operation state analysis diagram.

[0071] Figure 2 is a single road section bus string vehicle prevention process diagram.

[0072] Figure 3 is an intelligent agent decision-making flowchart.

[0073] Figure 4 is a diagram showing that the arrival order is consistent with the vehicle sequence.

[0074] Figure 5 is a diagram showing that the arrival order is not consistent with the vehicle sequence.

[0075] Figure 6 is a diagram showing the prevention of bus string vehicles on multiple road sections.

[0076] Figure 7 is a flowchart for solving the number of station distances.

[0077] Figure 8 is an improved CBR scheme optimization flowchart.

[0078] Figure 9 is a scheme correction flowchart.

[0079] Figure 10 is a signal adjustment conflict diagram.

[0080] Figure 11 is a bus string vehicle prevention and cooperative control flowchart.​

[0081] Figure 12 Figure 1 is a schematic diagram of interference degree screening. DETAILED DESCRIPTION

[0082] 1 Single-line bus string prevention and control

[0083] 1.1 Single-line bus state analysis

[0084] wherein is the punctual arrival time of the nthstation, are the times of the vehicle arriving at and leaving the nthintersection, respectively, are the times of the vehicle arriving at and leaving the nthstation, respectively, are the upper and lower limits of the prescribed arrival time interval between the stations and the stations , respectively, are the distances between the stations and the stations , respectively, are the distances between the stations and the intersections , and between the intersections and the stations , respectively, is the bus dwell time at the nthstation, is the red light waiting time at the intersection , is the punctual arrival time section, and is set in the present application .

[0085] Bus inter-station running state can be obtained according to the analysis: Figure 1

[0086] (1)

[0087] wherein is the vehicle driving speed on the road section .

[0088] It can be seen from the above that the adjustment of the bus inter-station driving state mainly includes four parts, namely, bus dwell control, bus off-station speed guidance, intersection bus signal priority, and bus arrival speed guidance. Among them, the off-station and arrival speed guidance are limited by the maximum speed of the road section, and the intersection signal priority is not only limited by the execution state of the intersection signal, but also by the maximum and minimum green requirements of the intersection, so for the adjustment of the intersection signal, it is necessary to analyze the relationship between the bus arrival time at the intersection and the signal execution state.

[0089] 1) If , it means that the bus vehicle is passing through the intersection during the green light period, wherein represents the nthintersection.​​ a cycle, respectively represent the green light start time and end time of the a cycle, at this time ;

[0090] 2) If , it means that the bus vehicle arrives at the intersection during the intersection red light period, at this time the intersection signal adjustment threshold needs to be combined to judge the bus intersection state, the specific process is as follows:

[0091] The maximum green light extension time of the intersection needs to meet formula (2)

[0092] (2)

[0093] The maximum red light early break time of the intersection needs to meet formula (3)

[0094] (3)

[0095] Wherein is the maximum green light and minimum green light time of the intersection.

[0096] Therefore, the maximum adjustment amount of the intersection can be obtained.

[0097] If , it means that the bus can pass through the intersection without stopping by extending the green light , at this time ; otherwise, the green light extension cannot affect the vehicle intersection state, at this time .

[0098] If , it means that the bus can pass through the intersection without stopping by extending the red light early break , at this time ; otherwise, the red light early break cannot be used to reduce the intersection time consumption, at this time .

[0099] In summary, the shortest optimized travel time between stations can be obtained as

[0100] (4)

[0101] Combined with formula (1), the arrival time at the station after adjustment can be obtained as t i apn At this time, the vehicle headway offset between stations can be defined as:

[0102] (5)

[0103] When , it means that there is no headway deviation between vehicles, and no further correction is needed;

[0104] When , it means that the bus arrives at the bus stop too early, and in this case, to simplify the scheduling difficulty, the bus headway is compensated by the means of bus stop delay, and the stop delay time is ;

[0105] When , it means that there is a headway deviation between vehicles, and the bus travel time needs to be reduced, which requires further adjustment in the next section.

[0106] 1.2 Single-section bus string optimization

[0107] Single-section bus string prevention and control mainly refers to the ability to balance the bus arrival headway and the headway designed in the timetable within the distance between two stations. Factors affecting the effectiveness of single-section bus string prevention and control include bus stop time, bus guide speed, intersection signal control, and other measures, so the problem of optimization measure selection and optimization measure combination often accompanies the process of bus string prevention and control. Based on the above, the single-section bus string prevention and control process is designed as shown in Figure 2 .

[0108] First, the bus state (position, speed, traffic flow, passenger capacity, timetable, bus stop time, etc.), signal control (cycle, green ratio, maximum green, minimum green, execution state, etc.), and road parameters (road channelization, maximum speed, minimum speed, station distribution, distance distribution, etc.) are taken as system inputs. Through the calculation and analysis of the headway deviation between stations , the decision type is selected. To solve the decision problem of optimization measure selection and optimization measure combination, an edge computing-based decision method is designed.

[0109] The vehicle state, signal control, and road parameter environment information described in the foregoing constitute a data set . The state is compared with the state analysis in the decision library, and the decision scheme corresponding to the historical state with the smallest difference is selected as the initialization control scheme . It should be noted that in the case of certain road parameters and signal control, the traffic state difference mainly comes from the dynamic traffic state, and there are already a large number of researches and achievements in the field related to traffic state, so they are not introduced here.

[0110] The computing link mainly includes two parts of decision learning and scheme evaluation. The decision learning mainly adjusts the operation scheme of the bus from three aspects of bus stop, speed guidance and intersection signal priority for different states when the scheme does not meet the needs of bus string prevention. , that is, the scheme travel time is less than the required travel time. At this time, the bus stop time is first determined as , then the bus guidance speed is reduced by one unit , and the signal priority adjustment amount is reduced by one unit within the constraint range of the maximum green and minimum green. If it is out of the constraint range of the maximum green and minimum green, the signal adjustment remains the same; if , that is, the scheme travel time is greater than the required travel time. At this time, the bus stop amount needs to be adjusted to 0, that is, . Then the speed is increased by one unit within the speed constraint range, and the signal priority adjustment amount is increased by one unit within the constraint range of the maximum green and minimum green. If it is out of the constraint range of the maximum green and minimum green, the signal adjustment remains the same. The specific process is shown in Figure 3 .

[0111] As shown in Figure 3 , the scheme meeting the requirements of bus string prevention is analyzed by using the HCM1985 delay model to analyze the intersection delay per capita, and the obtained delay is stored in the set , and the decision scheme corresponding to the minimum value is found in the set .

[0112] Based on the above, the steps of bus string prevention for a single section are as follows:

[0113] Step 1: Collect the environmental state parameter set , and perform correlation analysis on the historical states in the decision library, and select the decision scheme corresponding to the historical states with the smallest difference as the initialization control scheme according to the difference sorting;

[0114] Step 2: Select the scheme , . Calculate the time of the scheme to reach the platform :

[0115] (4)

[0116] If , execute Step 3, if , execute Step 4, if Step 5 is executed.

[0117] Step 3: It is explained that the scheme can make the bus vehicle restore the on-time state, that is, the headway offset between stations is 0, so the person delay under the improved scheme is calculated, and the HCM1985 delay model is used to analyze the intersection person delay, and the specific expression is as follows:

[0118] (5)

[0119] wherein is the green ratio, is the saturation, is the intersection cycle, represents the traffic flow at the intersection.

[0120] If , it is explained that the scheme set is not calculated, Step 3 is executed; if , it is explained that the scheme set has been calculated, and Step 6 needs to be executed;

[0121] Step 4: If the bus vehicle arrives at the bus station early, the headway offset between stations at this time is , the bus station control amount needs to be reduced, the bus guide speed v i a speed unit amount is reduced in the constraint range, wherein the speed unit amount is defined as 1 m / s; if the intersection signal adjustment amount , the signal adjustment amount is reduced by a signal unit amount , wherein the signal unit amount is defined as 1 s, and then Step 2 is executed;

[0122] Step 5: If the bus vehicle arrives at the bus station later than the required period of the timetable, the headway offset between stations at this time is , the bus station control amount needs to be increased, the bus guide speed v i a speed unit amount is increased in the constraint range, and the intersection signal adjustment amount is increased by a signal unit amount in the constraint range, and then Step 2 is executed;

[0123] Step 6: The minimum person delay is selected from the obtained person delays , and the scheme corresponding to the minimum person delay is taken as the final scheme and is executed, and the details in the scheme are Stored in the decision database.

[0124] It's important to note that in a single-segment, multi-route configuration, the only possible scenario is that the arrival order and route sequence of buses match. In this case, the speed constraints are not only... and In addition to the constraints, the speed constraints of buses in Step 4 and Step 5 need to be redefined in conjunction with formula (4).

[0125] 2. Prevention and control of multiple bus routes running together

[0126] 2.1 Status Analysis of Multiple Bus Routes

[0127] Considering that multiple bus services may affect each other during operation between bus stops, which will further impact the guidance speed of buses on the road and the priority of intersection signals, it is necessary to analyze the situation of multiple vehicles running together on the road.

[0128] Define the vehicles in front and behind as leaving the bus stop. The times are respectively And according to formula (5), the adjustment travel times of the front and rear vehicles can be obtained as follows: And the trains in front and behind are on the platform. The timetable is It should be noted that, as explained above, if the following occurs... In such cases, the bus will stop at the platform, so there is no situation where the bus has already deviated too far ahead when it leaves the platform. Therefore, the following analysis process... .

[0129] (1) The arrival order is consistent with the vehicle segment order.

[0130] like This indicates that the order of arrival at the station is consistent with the order of train connection (e.g., Figure 4 (As shown). When the following vehicle leaves the bus stop, the distance between the front and rear vehicles at this point meets the following condition. At this point, the required vehicle spacing constraint should satisfy formula (6).

[0131] (6)

[0132] in , The front and rear vehicles were on the road section respectively. Real-time vehicle speed is primarily obtained through the vehicle's onboard GPS. It is important to note that... When this happens, it means the following vehicle has caught up with the preceding vehicle, and the following vehicle's speed must then meet the following requirements. .

[0133] Therefore, the travel time in multi-line mode is:

[0134] (7)

[0135] Furthermore, the time offset of the train head at the station can be determined and analyzed according to formula (5).

[0136] (2) The order of arrival at stations is inconsistent with the order of vehicle segments.

[0137] like This indicates that the arrival order is inconsistent with the train sequence order; the following train needs to arrive at the station first, and the preceding train needs to arrive later (e.g., ...). Figure 5 (As shown). To address this situation, this paper proposes that the preceding train be on the platform... For vehicles stuck at a station, the following vehicle must leave first while the preceding vehicle is still stuck at the station. At the platform, the train sequence is adjusted. The required waiting time for the preceding train is:

[0138] (8)

[0139] in For the car in front Predicted station stay time at the platform.

[0140] The influence can be found from formula (8) The value is the same as the value of the train arriving at the platform. The moment There is a direct correlation; therefore, to minimize the impact of the preceding train being delayed at the station, it is necessary to further reduce the arrival time difference between the preceding and following trains. ,Right now

[0141] (9)

[0142] in This indicates a fixed component.

[0143] From formula (8), we can see that The value of is mainly affected by the speed of the following vehicle, so the shortest travel time scheme within the allowable scheme needs to be selected. It should be noted that this case is all for multi-segment traffic control.

[0144] 2.2 Optimization of multi-route bus service

[0145] Due to limitations in speed adjustment and signal optimization, and considering inconsistencies in arrival order and vehicle segment sequencing, single road segments often struggle to meet the requirements for preventing bus lane overlap. Adjusting multiple road segments involves the coordination of multiple agents. While minimizing the average delay per agent in a single road segment is the optimization objective, optimal control of a single segment may lead to global suboptimal control across multiple segments. For example... Figure 6As shown, scheme 1 follows the control mode of minimum delay of each section, and does not adjust the intersection The signal priority control is adopted, so scheme 1 cannot successfully correct the headway offset between bus stations in two road sections, and more than two station sections need to be adjusted to eliminate the offset; however, scheme 2 considers the efficiency of multi-section bus string prevention and control, introduces intersection signal adjustment, and can make the vehicle return to normal operation after passing through two station sections. In summary, when dealing with multi-section bus string prevention and control, the coordinated optimization between multiple sections needs to be considered, so that the multi-section bus string prevention and control is more efficient and effective.

[0146] For each multi-section bus string prevention and control scheme, the road delay per capita can be calculated according to formula (11), and the headway offset between stations at each bus station in the scheme state can be judged according to formula (1) and formula (10) . It can be known from formula (5) that the number of required inter-station distances can be judged by the number of , so the vehicle bus station state is defined as

[0147] (12)

[0148] wherein is a large enough constant value, and the present application defines . Therefore, when , the headway offset between stations is ; when , the headway offset between stations is . Figure 7 The solving process of the number of inter-station distances is shown.

[0149] On the basis of obtaining the delay per capita of the scheme and the number of required inter-station distances, in order to further consider the efficiency and effect of multi-section bus string prevention and control, the multi-section bus string prevention and control optimization target is designed from the aspects of bus string prevention and control section number control and road delay per capita control. After the sigmoid function normalization processing of the two, the multi-section bus string prevention and control optimization target can be obtained as

[0150] (13)

[0151] wherein is a weight coefficient, and in the present application, it is considered that the importance of rapid recovery is higher than that of the delay per capita, so it is defined as .

[0152] Considering that the multi-link bus string car state exceeds the single-link state in both magnitude and relevance, and considering that the bus line schedule is relatively fixed in the link, the historical knowledge reference of bus string car prevention and control measures is high, so case-based reasoning (CBR) is selected as the multi-link string car prevention and control decision method. Case-based reasoning, as an artificial intelligence technology based on past experience and knowledge to analyze and solve current similar scene problems, mainly includes four parts of historical case retrieval, similar case extraction, similar case correction and case storage. However, considering that the optimization intention is not only to find the correct solution of the case, but also to further filter out the optimal scheme, therefore, the original CBR idea is improved, and the main idea is as shown in Figure 8 .

[0153] Therefore, the multi-link bus string car prevention and control steps can be obtained as follows:

[0154] Step 1: Case base introduction. The case base information is represented in the form of , wherein represents the number of cases in the case base, represents the traffic state information description of the th case, and , wherein represents the th feature description in the th case, is the number of feature attributes;

[0155] Step 2: Historical case retrieval. The traffic state description of the new string car scene is defined as , and in order to calculate the similarity between and , a similarity evaluation algorithm based on Euclidean distance is used, that is:

[0156] (14)

[0157] wherein is the weight of the th feature, and .

[0158] Then, the obtained relevance degrees are sorted in descending order, and the most similar cases are selected therefrom, wherein .

[0159] Step 3: Scheme effect evaluation. The control strategies corresponding to the groups of similar cases obtained in Step 2 are , and verify whether the above control scheme meets the speed constraint (see Step 2.2), whether it can restore normal operation ( ), and whether the required inter-station distance is appropriate ( ). Define three evaluation parameters for the three aspects, respectively , with values of 0 (not met) and 1 (met). Therefore, the scheme effect evaluation coefficient can be defined as:

[0160] (15)

[0161] If , it means that the scheme meets the requirements, and Step 5 is executed; if , it means that at least one requirement is not met, and Step 4 is executed.

[0162] Step 4: Scheme modification. When , it means that the scheme is not a correct solution, and adjustment is needed. First, judge the values of . If , it means that the bus speed does not meet the constraint requirements, so the maximum bus speed is selected according to the constraint range; if , it means that the bus cannot eliminate the inter-station headway deviation, so the bus speed and intersection signal priority state need to be optimized; if , it means that the remaining inter-station route number cannot meet the bus inter-station headway deviation elimination, so the bus travel time needs to be further compressed, and the cumulative travel time during adjustment is:

[0163] (16)

[0164] Therefore, through formula (16), it can be found that within the constraint range, the travel time can be optimized by increasing the speed and increasing the intersection signal priority. The specific adjustment process is shown in Figure 9 , where is the maximum number of iterations to prevent the modification process from entering a dead loop and affecting the solution efficiency.

[0165] Step 5: Save the control scheme that meets the requirements to the temporary scheme set , then repeat Step 3 and Step 4 to evaluate and modify the control strategies. Finally, obtain the scheme that meets the correct solution requirements. Calculate the objective function value of the scheme according to formula (13), and select the scheme with the smallest objective function value as the final execution scheme. The best scheme is issued at the same time, and the scheme and its corresponding scene state are saved as a binary tuple The cases are stored in the case library for future decision-making.

[0166] It is important to note that as time goes on, the number of cases in the case library will gradually increase. Therefore, the later case selection and matching process will become more time-consuming and inefficient. To address this, we have set a uniform size for the case library. When the case library overflows, the oldest record will be deleted in chronological order to ensure the efficiency of case reasoning.

[0167] 3. Collaborative Control of Bus Crossing

[0168] The preceding sections described measures for preventing bus entanglement on single and multiple bus routes. However, these descriptions only considered prevention measures for a single bus route. In real-world scenarios, different bus routes may have varying entanglement prevention needs, leading to conflicting adjustment requirements between prevention schemes for different routes. This can negatively impact the effectiveness of bus entanglement prevention and reduce road traffic efficiency. Furthermore, considering the arrival time of buses, the state of bus entanglement may change from single bus to multiple buses and from single route to multiple routes, resulting in a dynamic and time-varying characteristic of bus entanglement prevention. In summary, the analysis reveals that coordinated bus entanglement prevention not only requires attention to the coordination between prevention schemes on different routes but also to the coordination of these schemes caused by changes in bus entanglement status. Therefore, an interference analysis index was constructed based on the speed and signal adjustment effects between schemes, and a coordinated control model for bus entanglement prevention was built with the goal of minimizing interference.

[0169] 3.1 Construction of Interference Index for the Scheme

[0170] Based on the analysis, we can obtain the optimal control strategy for different bus routes under different traffic conditions. Therefore, according to the order of vehicles in the inter-stop section, we define the preceding vehicle's position in the inter-stop section. The desired control scheme is The following vehicle was on the section of road between stations. The desired control scheme is Considering the speed set constraint caused by the pursuit problem in the actual process, i.e., formula (6), the following vehicle may be constrained by the speed of the preceding vehicle during actual operation. Therefore, the vehicle pursuit process is analyzed first.

[0171] (17)

[0172] Using formula (17), we can determine the time when the following vehicle catches up with the preceding vehicle. .

[0173] like This means that when a following train catches up with a preceding train within the distance between stations, the actual speed of the following train must meet the following requirements. ; otherwise, the rear vehicle cannot catch up with the front vehicle in the distance between stations, and the actual running speed of the rear vehicle between stations is . Through the above analysis, it is found that the speed influence of the front and rear vehicles is not only reflected in the difference between the actual speed and the expected speed , but also related to the duration of the speed influence , so the speed interference degree is defined as:

[0174] (18)

[0175] wherein , .

[0176] The adjustment conflict of the signal cycle mainly occurs at the beginning and end of the green light and the beginning and end of the red light at the intersection, as shown in Figure 10 , wherein represents the th execution cycle.

[0177] When the front vehicle is in the case of scheme 1 and the rear vehicle is in the case of scheme 2, the front vehicle needs to extend the green light , and the rear vehicle needs to break the red light early . According to the maximum green light and the minimum green light limit, it can be found that the actual signal adjustment of the rear vehicle will have the following four situations:

[0178] ① If and , it is indicated that the signal adjustment of the two schemes meets the intersection maximum green light constraint and minimum green light constraint requirement, and the front and rear vehicles execute the expected signal adjustment;

[0179] ② If and , it is indicated that the signal adjustment of the two schemes exceeds the intersection maximum green light constraint requirement, and the actual signal adjustment of the rear vehicle is ;

[0180] ③ If and , it is indicated that the signal adjustment of the two schemes does not meet the intersection minimum green constraint requirement, and the actual signal adjustment of the rear vehicle is ;

[0181] ④ If and , it is indicated that the signal adjustment of the two schemes does not meet the intersection maximum green and minimum green constraints, and the actual signal adjustment of the rear vehicle is ;

[0182] When the front vehicle is in the case of scheme 2 and the rear vehicle is in the case of scheme 1, the front vehicle needs to break the red light early , the rear vehicle needs green light extension According to the maximum green light and minimum green light constraints, the actual signal adjustment of the rear vehicle can be found to have the following four cases:

[0183] ① If and , it means that the signal adjustment of the two schemes meets the intersection maximum green light constraint and minimum green light constraint requirement, at this time the front and rear vehicles execute the expected signal adjustment;

[0184] ② If and , it means that the signal adjustment of the two schemes exceeds the intersection maximum green light constraint requirement, at this time the actual signal adjustment of the rear vehicle is ;

[0185] ③ If and , it means that the signal adjustment of the two schemes does not meet the intersection minimum green constraint requirement, at this time the actual signal adjustment of the rear vehicle is ;

[0186] ④ If and , it means that the signal adjustment of the two schemes does not meet the intersection maximum green and minimum green constraints, at this time the actual signal adjustment of the rear vehicle is .

[0187] The difference between the actual signal adjustment of the rear vehicle and the expected adjustment is Therefore, the signal adjustment interference degree can be defined as:

[0188] (19)

[0189] Where is the cycle of the intersection .

[0190] The speed interference degree and the signal adjustment interference degree are normalized by using the sigmiod function, and the interference degree index between the schemes can be defined as:

[0191] (20)

[0192] Where is the weight coefficient, and the present application considers that the speed interference degree and the signal adjustment interference degree have the same weight, that is .

[0193] 3.2 Public transport string vehicle cooperative control model

[0194] Bus lane coordination is mainly used to prevent buses from different routes from traveling together on the same route between stations. The number of buses traveling together on the same route between stations can be obtained in real time from the bus's onboard positioning system. Here, the route between stations is defined. The status of the bus routes is as follows To address this, a collaborative control model for preventing bus lane overlap was constructed, based on the principles of preventing and controlling bus lane overlap and collaborative optimization control, for different bus routes. Figure 11 (As shown). The specific control steps are as follows:

[0195] Step 1: Determining the Desired Solution. Based on traffic condition information, first calculate the set of solutions that can meet the requirements for preventing train congestion for all bus routes within the inter-station section. ,in Control scheme The main components include the time difference between train heads between stations, speed adjustment, and signal adjustment.

[0196] Step 2: Determine if multiple lines are needed. This indicates that there are no buses on that section of the road between the stations; if This indicates that there is a bus route between the stations. In this case, only the bus skipping prevention effect needs to be considered, and Step 3 should be executed; if This indicates that there are multiple bus lines between the stations, and it is necessary to determine whether coordinated control is needed based on the bus connection status of each line. At this time, Step 4 is executed.

[0197] Step 3: Select the optimal control scheme for a single line. Based on the different state requirements of single and multiple line segments, determine the optimal control scheme according to the content of Steps 1 and 2, and then proceed to Step 6;

[0198] Step 4: Calculate the interference degree of each option for the preceding and following trains on different routes. (The text abruptly ends here, likely due to an incomplete sentence or missing information.) Buses of the same type The interference level of a bus can be determined by content 3.1 as follows:

[0199] (twenty one)

[0200] in The number of elements in the set of solutions for the preceding vehicle. The number of elements in the set of subsequent vehicle schemes.

[0201] Step 5: Select the optimal interference combination scheme. From formula (21), we can... Buses of the same type The interference between the various bus routes is such that it's not difficult to deduce the interference corresponding to the optimal combination of routes between the two buses should be [value missing]. But in the multi-line bus state, the screening process of the best overall interference degree of the station-to-station section can actually be converted into a shortest path decision-making process, as shown in Figure 12

[0202] As can be seen from Figure 12 , the screening process of the best interference degree of the station-to-station section is the process of finding the shortest path from A to B, and we define the interference degree of the initial state A to the scheme set in the four-car scheme as 0, and the interference degree of the four-car scheme to the final state B is also 0, and each line scheme is solved according to Dijkstra's Algorithm, and finally the best interference degree of the section is determined as

[0203] (22)

[0204] wherein is the number of bus lines existing in the station-to-station section.

[0205] According to the combination of the best interference degree of the section, the control scheme corresponding to each car is selected to form the control scheme set as .

[0206] Step 6: Decision library data update. The best control scheme is added to the decision library while the scheme is being executed; in order to avoid the problems of long retrieval time and long decision-making time caused by the large sample data of the decision library, the size of the decision library is uniformly set, and when the sample of the decision library overflows, the earliest record is deleted in time sequence, thereby ensuring the efficiency of collaborative decision-making.​

Claims

1. A single-line and multi-line bus train optimization control method, characterized in that, The method comprises the following steps: (1) Single-line bus string prevention and control (1.1) Single-line bus state analysis wherein is the punctual arrival time at the th stop, are the times of arrival and departure of the vehicle at the th intersection, are the times of arrival and departure of the vehicle at the th stop, are the distances between the th stop and the th intersection and between the th intersection and the th stop, is the bus dwell time at the th stop, is the red light waiting time at the th intersection, is the punctual arrival time zone. Analysis of the inter-station running state of the bus: （1） wherein the speed of a vehicle travelling on a road segment on a road segment Analysis of the relationship between the bus arrival time at the intersection and the signal execution state: 1) if the bus vehicle is passing through the intersection during the green light, wherein denotes the th cycle, denotes the start time and the end time of the green light of the th cycle, respectively, wherein ; 2) if At this time, the bus vehicle arrives at the intersection during the red light period of the intersection. The bus intersection state is judged in combination with the intersection signal adjustment threshold. The specific process is as follows: Maximum green extension time at intersection The formula (2) needs to be satisfied （2） Intersection maximum red light early break time The formula (3) needs to be satisfied （3） wherein is the maximum green and minimum green time for the intersection; Thus the maximum adjustment amount of the intersection is obtained ; If , then the bus can pass the intersection without stopping by extending the green light , at this time ; otherwise, the extension of the green light cannot affect the state of the intersection, at this time ; If , then the bus can pass the intersection without stopping by early red light breaking , at this time ; otherwise, the early red light breaking cannot be used to reduce the intersection time, at this time ; Based on the above, the shortest optimized travel time between stations is （4） The adjusted arrival time is obtained by combining formula (1) t i apn At this time, the headway offset of the vehicle between stations is defined as （5） When , the vehicle does not exist the headway deviation between stations, and no further correction is needed; when , the bus arrives at the bus stop early, the bus headway is compensated by the bus stop delay means, and the stop delay time is ; when , the headway deviation between stations occurs, and further adjustment is made in the next section. (1.2) Single-section bus string optimization The single-section bus string prevention and control steps are as follows: Step 1: Collect the environmental state parameter set , and perform correlation analysis with the historical states in the decision library, and select the decision scheme corresponding to the historical state with the smallest difference as the initialization control scheme according to the difference ranking ; Step 2: Selecting a plan , , calculate the time for the plan to reach the station . （6） If Step 3 is performed, if Step 4 is performed, if Step 5 is performed; Step 3: Calculate the per capita delay under this scheme. The per capita delay at the intersection is analyzed using the HCM1985 delay model, which is specifically expressed as follows: （7） wherein is the green-to-red ratio, is the saturation, is the intersection cycle, denotes the traffic flow at the intersection; If then the set of solutions is not yet computed, Step 3 is performed; if the set of solutions is already computed, Step 6 is performed; Step4: If the bus arrives at the bus stop early, the headway offset between stops is At this time, the bus stop control amount is needed v The bus guidance speed i is reduced by one speed unit , where the speed unit is defined as 1 m / s; if the intersection signal adjustment amount , the signal adjustment amount is reduced by one signal unit , where the signal unit is defined as 1 s, and Step 2 is executed. Step5: If the bus arrives at the bus stop later than the required period, the headway offset between stops is At this time, the bus stop control amount , the bus guide speed v i Increase a speed unit amount in the constraint range Increase a signal unit amount in the constraint range of the intersection signal adjustment amount Then execute Step2; Step 6: Calculate the average delay per person. Choose the one with the smallest average delay per person. and will The corresponding solution As the final implementation plan, it will be issued, along with the detailed parameters of the plan. Stored in the decision database; (2) Multi-line bus string prevention and control (2.1) Multi-line bus state analysis Define the time when the front and rear buses leave the bus stop are respectively , and the adjusted travel times of the front and rear buses are respectively according to formula (5), and the time table time of the front and rear buses at the bus stop are respectively ; (2.1.1) If the arrival order and the vehicle section order are consistent If , the arrival order is consistent with the vehicle order. When the following bus departs from the bus stop, the distance between the two buses satisfies , the distance between the two buses should satisfy formula (8) （8） wherein , are the real-time vehicle speeds of the front and rear vehicles on the road segment , respectively, which are mainly obtained by the real-time vehicle GPS; it should be noted that , it indicates that the rear vehicle has caught up with the front vehicle at this time, and the rear vehicle speed needs to meet ; Therefore, the travel time under the multi-line state is: （9） And the headway offset of the arrival vehicle is analyzed according to formula (5); (2.1.2) If the arrival order and the vehicle section order are inconsistent If , the arrival order is inconsistent with the train-association order, the latter train arrives at the station first and the former train arrives at the station last, and the required dwell time of the former train is: （10） wherein is the preceding vehicle station's dwell prediction time; Further reducing headway differences between front and rear vehicles i.e. （11） wherein represents a fixed component; (2.2) Multi-section bus string optimization The multi-section bus string prevention and control steps are as follows: Step 1: Adopting the form of to express case base information, wherein represents the number of cases in the case base, represents the traffic state information description of the th case, and , wherein represents the th feature description in the th case, is the number of feature attributes; Step 2: define the new string yard scenario traffic state description as , to calculate the similarity of , the similarity evaluation algorithm based on the Euclidean distance is used, that is: （12） wherein is the weight of the th feature, and ; The obtained correlation degrees are then sorted in descending order, and the most similar cases are selected from among them, where ; and ; and ; Step 3: three evaluation parameters are defined, i.e. whether the speed constraint is met, whether the normal operation can be resumed, and whether the required distance between stations is appropriate The scheme effect evaluation coefficient is defined as: （13） If , the scheme meets the requirements, then Step 5 is executed; if , the scheme does not meet at least one requirement, then Step 4 is executed. Step 4: When , the scheme is modified and adjusted, first by judging the values of , if , the maximum bus speed is selected according to the constraint range; if , the bus vehicle guidance speed and the intersection signal priority state are optimized; if , the travel time of the bus vehicle is further compressed, and the cumulative travel time in the adjustment process is: （14）； Step5: Save the qualified control scheme to the temporary scheme set , and repeat Step3 and Step4 to evaluate and correct the group control strategy, and finally obtain a scheme meeting the correct solution requirement , select a scheme with the minimum target function value from the group as the final execution scheme, and store the scheme and the corresponding scene state in the form of a binary tuple in the case library for subsequent decision-making.

Images