A bus departure frequency simulation dispatching system

Abstract

The present invention provides a bus departure frequency simulation and scheduling system, comprising a calculation module for acquiring bus route information and performing bus operation simulation and emulation based on the Nasch model; a visualization module for receiving data from the calculation module and generating a visualization interface for the road grid; and a controllable module for acquiring and controlling change information of variable parameters during bus operation, and sending the control variable data to the calculation module for calculation. The bus departure frequency scheduling system can achieve dynamic scheduling of bus departure frequencies, simulate emergencies during bus operation, construct a reliability index system to measure the operating efficiency of buses at a specific departure frequency, and propose a series of measures for dynamically adjusting departure frequencies based on the reliability index. The measures can effectively alleviate various problems encountered during bus operation, achieve scientific dynamic scheduling, and improve the operational efficiency of the bus system.

Description

Technical Field

[0001] The present invention relates to the technical field of transportation, and in particular to a bus departure frequency simulation scheduling system. Background Art

[0002] Bus departure frequency scheduling refers to dynamically determining the departure frequency of a bus line in each time period based on road conditions and passenger flow at each stop, so as to achieve the purpose of reasonably controlling the operation of the bus system and improving the operational efficiency of the bus system.

[0003] Currently, most algorithms for finding the optimal bus departure frequency aim to minimize bus operating costs and passenger travel costs, using genetic algorithms. Once the optimal departure frequency is determined, existing scheduling strategies, such as developing a bus scheduling system based on a bus operation plan compilation process and using bus signal priority strategies to predict future bus operations, exist. However, in actual scheduling, given the wide variety and real-time variability of passenger demand, existing bus scheduling models exist that consider dynamic passenger demand and support immediate responsiveness.

[0004] Cellular automata can be described as any finite-dimensional discrete grid, where each grid is in a finite state. The state of each grid at time t is determined by the state of its neighboring grid at time t-1. The Nasch model uses the 184th rule of elementary cellular automata to simulate traffic flow. In the Nasch model, time, space, and speed are all discretized, and the road is divided into discrete grids (cells). Each cell is either empty or occupied by a car, and the speed of each car can be 1, 2, ..., v max As the time step increases, the model evolves according to the following rules:

[0005] Step 1. Acceleration: v→min(v+1,v max ), which means the speed is increased by 1 without exceeding the maximum speed, reflecting the characteristic that drivers tend to drive at the fastest possible speed.

[0006] Step 2. Decelerate: v → min(v, d), where d is the distance between the vehicle and the vehicle in front, to ensure that the vehicle does not collide with the vehicle in front.

[0007] Step 3. Random deceleration: With random probability p, let v→max(v-1,0). Due to uncertain factors such as the driver's driving skills and road conditions, the vehicle decelerates. The extreme condition for deceleration is that the vehicle is stationary.

[0008] Step 4. Position update: x→x+v, the vehicle continues to move forward at the updated speed.

[0009] Based on comprehensive consideration of passenger demand and bus operating costs, the use of the Nasch model can well simulate the vehicle's operating status, road conditions and various emergencies, facilitating the display of the process.

[0010] In summary, the Nasch model has advantages in bus scheduling. In addition, how to further improve the operating efficiency of the bus system based on the Nasch model is also a problem that bus operating companies need to solve. Summary of the Invention

[0011] In order to solve the problems mentioned in the prior art, the present invention provides a bus departure frequency simulation scheduling system, which simulates the actual bus operation process under the premise of dynamic and controllable operation, and can propose a scheduling strategy that effectively improves the operating efficiency of the bus system.

[0012] The present invention provides a bus departure frequency simulation scheduling system, which includes the following modules:

[0013] The calculation module obtains bus route information and performs simulation and emulation of bus operation based on the Nasch model;

[0014] The visualization module receives data from the calculation module and generates a visualization interface for the road grid;

[0015] The controllable module obtains and controls the change information of variable parameters during bus operation, and sends the control variable data to the calculation module for calculation;

[0016] The execution method of the operation module includes:

[0017] L1. Execute the following rules based on the Nasch model:

[0018] First improvement rule: Buses have unique and fixed origin and destination stations. When adding a bus to a route, always check whether the grid where the origin station is located can accommodate the new bus. If it can, add the bus. When a bus passes the destination station, release it and change the corresponding grid position of the bus route destination station to None.

[0019] The second improved rule: designate a specific grid as a fixed stop. For buses that have not passed the stop, if the sum of the vehicle's current position and current speed is greater than the stop's position, the bus can enter the stop and the vehicle's speed is adjusted to allow it to stop at the stop.

[0020] The third improved rule: When the bus passes through the grid where the station is located, the passengers get on and off the bus, and the passengers are generated using the Poisson distribution with different parameters;

[0021] L2. Define a reliability index to measure road conditions and use it as a standard for dynamically scheduling bus departure frequencies;

[0022] L3. Formulate bus frequency adjustment strategies based on the constructed reliability index system;

[0023] L4. Simulate road congestion and sudden increase in passengers based on bus departure frequency adjustment strategy.

[0024] Furthermore, the reliability indicators described in L2 include the following:

[0025] Route reliability measures whether bus routes remain unobstructed. It is specifically expressed as the number of direct and indirect congestion on the current road. Direct congestion occurs when two buses on the same route appear in adjacent grids, while indirect congestion occurs when a grid is left empty between two buses on the same route. The greater the number of congestion occurrences, the lower the route reliability.

[0026] Time reliability measures whether the bus can pick up passengers at the appropriate time. It is specifically expressed as the number of passengers waiting at each stop. The more passengers there are, the lower the time reliability.

[0027] Safety and reliability measures whether accidents or traffic incidents occur during bus operations. Specifically, it is expressed as the ratio of the average number of such accidents occurring on bus routes per year to the number of bus departures per year. The lower the safety and reliability, the more appropriate it is to reduce bus departures.

[0028] Transfer reliability measures the number of stops on a bus route that can be used to take buses on other routes. It is specifically performed by constructing a transfer matrix, assigning values to transfer behaviors using the transfer ratio as an indicator, and then obtaining the transfer reliability of a route. The result is between 0 and 1, and the closer it is to 1, the stronger the transfer capacity.

[0029] Furthermore, bus frequency adjustment strategies in L3 include:

[0030] A1. When bus route reliability decreases, bus frequency should be increased. Specifically, when direct congestion occurs on a given road at a given time, or the number of buses on a particular route exceeds a certain threshold, bus frequency should be significantly increased. When indirect congestion occurs on a given road at a given time, bus frequency should be slightly increased (by half the increase due to direct congestion). When there is no bus congestion on a given route at a given time, bus frequency should return to its initial level. The extent of the reduction in frequency should be determined based on transfer reliability; routes with high transfer reliability should have a lower reduction.

[0031] A2. When the time reliability of a bus route decreases, if the time reliability is below a certain threshold, the bus departure frequency is reduced to the minimum; otherwise, the reduction in departure frequency is a monotonic function of the time reliability, and the parameters of the monotonic function should be determined based on safety reliability.

[0032] Furthermore, to quantify the efficiency of bus operations, when a bus enters the terminal, it means that a trip is completed. At this time, the passenger volume per unit mileage of the bus is calculated and expressed as

[0033]

[0034] where p i is the passenger volume at the station, and s is the total mileage; this indicator reveals the operating efficiency of the bus.

[0035] Furthermore, the simulation of the road congestion described in L4 needs to be executed. When road congestion occurs, all vehicles with a speed greater than 1 are required to stop, and vehicles with a speed of exactly 1 can drive normally.

[0036] Furthermore, the controllable module is communicatively connected to the monitoring unit; the control of the variable parameters includes the control of the number of passengers at the station, the control of the starting departure frequency, and the control of the road status.

[0037] The beneficial effects of the present invention are as follows: the bus departure frequency simulation and scheduling system of the present invention can realize the dynamic scheduling of bus departure frequency, and use the Nasch model to simulate the normal driving of vehicles on the road. Taking into account the operating characteristics of buses such as stops at stations, passengers getting on and off the bus, etc., a series of improved rules are added on the basis of the Nasch model to realize the simultaneous operation of multiple buses. Emergencies during bus operation are simulated, a reliability index system is constructed to measure the operating efficiency of buses at a certain departure frequency, and a series of measures for dynamically adjusting the departure frequency are proposed based on the reliability index. This measure can effectively alleviate various problems encountered during bus operation, realize scientific dynamic scheduling, and improve the operational efficiency of the bus system. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following is a brief introduction to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0039] Figure 1 Provides the user interface for bus frequency simulation scheduling system;

[0040] Figure 2 The vehicle travel trajectories and station distribution of the three bus routes used in the embodiment;

[0041] Figure 3 This is the simulation result of the optimal departure frequency during the off-peak period in the embodiment;

[0042] Figure 4This is the simulation result of the optimal departure frequency during peak hours in the embodiment;

[0043] Figure 5 This is the simulation result when the road state is selected as unobstructed in the embodiment.

[0044] Figure 6 The simulation results of the embodiment in which the road state is selected as a sudden increase in passengers 1;

[0045] Figure 7 This is the simulation result of selecting the road state as the passenger sudden increase 2 in the embodiment;

[0046] Figure 8 The simulation result of selecting the road state as road congestion 1 in the embodiment;

[0047] Figure 9 This is the simulation result when the road state is selected as road congestion 2 in the embodiment. DETAILED DESCRIPTION

[0048] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. All other embodiments obtained by ordinary technicians in this field based on the embodiments of the present invention without making any creative efforts shall fall within the scope of protection of the present invention.

[0049] The present invention provides a bus departure frequency simulation scheduling system, which includes the following modules:

[0050] The calculation module obtains bus route information and performs simulation and emulation of bus operation based on the Nasch model;

[0051] The visualization module receives data from the calculation module and generates a visualization interface for the road grid;

[0052] The controllable module obtains and controls the change information of variable parameters during bus operation, and sends the control variable data to the calculation module for calculation;

[0053] The execution method of the operation module includes:

[0054] L1. Execute the following rules based on the Nasch model:

[0055] First improvement rule: Buses have unique and fixed origin and destination stations. When adding a bus to a route, always check whether the grid where the origin station is located can accommodate the new bus. If it can, add the bus. When a bus passes the destination station, release it and change the corresponding grid position of the bus route destination station to None.

[0056] The second improved rule: designate a specific grid as a fixed stop. For buses that have not passed the stop, if the sum of the vehicle's current position and current speed is greater than the stop's position, the bus can enter the stop and the vehicle's speed is adjusted to allow it to stop at the stop.

[0057] The third improved rule: When the bus passes through the grid where the station is located, the passengers get on and off the bus, and the passengers are generated using the Poisson distribution with different parameters;

[0058] L2. Define a reliability index to measure road conditions and use it as a standard for dynamically scheduling bus departure frequencies;

[0059] L3. Formulate bus frequency adjustment strategies based on the constructed reliability index system;

[0060] L4. Simulate road congestion and sudden increase in passengers based on bus departure frequency adjustment strategy.

[0061] In specific implementation, the calculation module uses Python programming to implement the bus frequency scheduling system. The visualization module uses the Matplotlib library to visualize bus operations under optimal frequency. The controllable module uses the interaction between the Matplotlib library and the Tkinter library to implement a GUI and control the bus operation process and road conditions.

[0062] The computation module simulates and emulates bus operations based on the Nasch model. The Nasch model is commonly used to simulate traffic flow and discretizes roads into grids. A list, link, is used to store road grids. If there is no vehicle in a grid, the corresponding link position is stored as None; if there is a vehicle in a grid, the corresponding link position stores the vehicle speed. The model has been improved to suit the operational characteristics of buses.

[0063] The first improvement principle implemented based on the Nasch model is that buses have unique and fixed starting and ending stations. In a cellular automaton, the initial position of a vehicle on the road is random, and the vehicle travels periodically, returning to its starting position after leaving the road. Therefore, there is no concept of a destination. However, during bus operation, the initial and final positions of all vehicles must be fixed. When adding a bus to a road, the grid containing the link's starting station is always checked to see if it can accommodate the new bus. If so, the vehicle is added. When a vehicle passes the terminal, it is released, and the corresponding grid position of the link's terminal is changed to None.

[0064] The second improved principle based on the Nasch model is that buses must pass through fixed stops. In a cellular automaton, the updated positions of vehicles on the road are random. However, during bus operation, it is necessary to set stops that must be passed. Certain grid cells are designated as stops. For buses that do not pass through these stops, if the sum of the vehicle's current position and current speed is greater than the location of the stop, the bus is allowed to enter the stop and its speed is adjusted to allow it to stop at the stop.

[0065] The third improved principle implemented on the basis of the Nasch model: When the bus passes through the grid where the station is located, the passengers get on and off the bus. Assume that the number of passengers getting on and off the bus is half of the number of passengers on the bus and at the station respectively. The number of passengers arriving at each station at each moment follows a Poisson distribution. Considering that the number of passengers at the intermediate stations is generally larger than that at the two end stations, a Poisson distribution with different parameters is used to generate passengers. If the expected number of passengers arriving at the initial station is λ, then the expected number of passengers arriving at the remaining stations is

[0066]

[0067] Where p is the total number of stops. Use the list s_passenger to store the cumulative number of passengers at a stop, and the list b_passenger to store the number of passengers on the bus. Use new_passenger to store the number of new passengers arriving at a stop at a given moment, adding each new passenger to s_passenger. When a vehicle arrives at a stop, the number of passengers in b_passenger for the corresponding vehicle is halved, indicating that a passenger has disembarked. Without exceeding the maximum passenger capacity, the number of passengers in s_passenger for the corresponding stop is halved and added to b_passenger, indicating that a passenger has boarded the bus.

[0068] L2. Define a reliability index to measure road conditions and use it as a standard for dynamically scheduling bus departure frequencies.

[0069] Route Reliability: This measures whether bus routes remain unobstructed. This is measured by the number of direct and indirect congestion events on the route. Direct congestion occurs when two buses on the same route appear in adjacent grid cells, while indirect congestion occurs when a grid cell is left empty between two buses on the same route. A higher number of congestion events indicates lower route reliability.

[0070] Time reliability: Whether a bus can pick up passengers at the appropriate time. This is measured by the number of passengers waiting at each stop. A higher number of passengers indicates lower time reliability.

[0071] Safety and reliability: Whether accidents or traffic incidents occur during bus operations. This can be expressed as the ratio of the average number of such accidents occurring on a bus route per year to the number of bus departures per year. Lower safety and reliability indicates that bus departures should be reduced appropriately.

[0072] Transfer reliability: The number of stops on a bus route that can connect to other buses. A transfer matrix is constructed, using the transfer ratio as an indicator to assign values to transfer behaviors. This yields a route's transfer reliability, which ranges from 0 to 1, with the closer to 1, the stronger the transfer capacity.

[0073] L3. Based on the reliability index system constructed in L2, a bus departure frequency adjustment strategy is formulated, which can be elaborated into two aspects:

[0074] A1. When the reliability of a route decreases, the frequency of departure should be increased. Specifically, when there is direct congestion on the road at a certain moment, or the number of buses on this route is more than M, the frequency of bus departures will be greatly increased, expressed as x. When there is indirect congestion on the road at a certain moment, the frequency of bus departures will be slightly increased, expressed as x / 2. When there is no bus congestion on this route on the road at a certain moment, the frequency of departure will return to the initial frequency. The reduction in the frequency of departures should be determined with reference to the transfer reliability H. The reduction in the frequency of departures for routes with high transfer reliability is low. Therefore, the adjustment range of the frequency of departures derived from route reliability is

[0075]

[0076] A2. When time reliability T decreases, if time reliability is lower than a certain threshold t1, the bus departure frequency is reduced to the minimum. Otherwise, the reduction in departure frequency is a monotonic function of time reliability. The parameters of the function should be determined based on safety reliability A. Therefore, the frequency adjustment range derived from time reliability is

[0077]

[0078] Where x is the number of passengers at a stop. When the number of passengers is less than b0, no adjustment is required. When the number of passengers is b1, the corresponding time reliability is t1. By dividing time into discrete points, bus operations and frequency adjustments are always made at these points in time. The bus position at the next moment is calculated by adding the previous moment's position and speed. Whenever the frequency is adjusted, the previous moment's frequency is added to σ to obtain the next moment's frequency.

[0079] To quantify the efficiency of bus operation, when a bus enters the terminal, it means that a trip is completed. At this time, the passenger volume per unit mileage of the bus is calculated and expressed as

[0080]

[0081] where p i is the passenger volume at the station, and s is the total mileage. This indicator reveals the operational efficiency of buses.

[0082] L4: Develop bus frequency adjustment strategies based on L2, simulating two types of emergencies: road congestion and sudden surges in passengers. When a road congestion occurs, all vehicles with a speed greater than 1 are stopped, while vehicles with a speed of exactly 1 can continue normally. Sudden surges in passengers primarily occur at high-traffic stops.

[0083] Based on the above-mentioned concepts, the present invention constructs a bus frequency scheduling system. It generates a road grid, visualizes bus operations, and simulates bus operations at the optimal frequency under normal circumstances. It also implements a user interface (GUI) to control bus operations and road conditions. This controllability primarily involves controlling the number of passengers at a station, the starting frequency of departures, and road conditions. Road conditions are categorized as clear, congested, and with a sudden increase in passengers. The stations experiencing sudden increases in passengers and the number of sudden increases can be controlled.

[0084] Based on the bus departure frequency dispatching system of the present invention, taking Hangzhou No. 7 bus and other three bus routes as an example, a bus is constructed. Figure 2 The vehicle driving trajectory and station distribution map shown in Figure 2 are Figure 2 It can be seen that there are three bus routes: 1, 2, and 3.

[0085] like Figure 3 The simulation results for bus operation during off-peak hours are shown, using the optimal departure frequency as the starting frequency. During off-peak hours, passenger flow is low, and there is no congestion at stops. Buses operate smoothly, with no congestion. All three bus routes operate at the optimal departure frequency. The number of passengers on each bus is moderate, significantly below the maximum capacity, ensuring a comfortable ride for passengers. Due to the low passenger count, the bus's unit operating mileage remains within a normal range.

[0086] like Figure 4 The following figure shows the simulation results of bus operations during peak hours, using the optimal departure frequency as the starting frequency. During peak hours, passenger flow is high, and stations with fewer buses, such as Station 7 and Station 9, begin to experience congestion. During this period, bus departure frequency is reduced, hoping to minimize the number of passengers waiting at stations by dispatching buses faster. At the same time, due to the excessively rapid departures, minor congestion may occur. Due to the high number of passengers, the bus's passenger volume per mile increases, improving operational efficiency but reducing passenger comfort.

[0087] like Figure 1 The following is the user interface of the bus frequency dispatching system. Enter the expected number of passengers at the station and the optimal frequency of departure according to the prompts, and click Start to generate the road grid and initial vehicles. When selecting the road status, selecting "unblocked road" means that the vehicle is operating normally, that is, according to Figure 3 or Figure 4Run the simulation results for one time period. Selecting Road Congestion means that the bus speed does not exceed 1 within Station 1-Station 3, and run the simulation for one time period. When selecting Passenger Sudden Increase, specify the sudden increase station and the number of sudden increase passengers, and run the simulation for one time period after the sudden increase in passengers occurs.

[0088] like Figure 5 As shown in Figure 2, the expected number of passengers at the station during off-peak hours and the optimal departure frequency are input, and the simulation results are selected when the road is unobstructed. The buses on the three routes all advance for one time period.

[0089] During actual bus operations, various emergencies may occur, such as traffic accidents, severe weather, and a sudden increase in passengers. In these cases, bus departure frequency needs to be quickly adjusted based on the actual situation to ensure the normal operation of the bus system. This means that the bus system needs to be able to withstand certain unknown risks.

[0090] The efficiency of bus dispatch systems will be measured through two emergencies: large-scale congestion and sudden surges in passenger numbers. Sudden surges often occur during peak travel times. A sudden surge in passengers at a particular station requires a rapid reduction in the frequency of departures on the corresponding bus route, while minimizing congestion on other routes.

[0091] like Figure 6 The following simulation results show the addition of 100 passengers to Station 3. As can be seen, the frequency of departures for all three routes dropped significantly due to the sudden increase in passengers at Station 3, with the frequency of departures for the blue and red routes dropping to almost 1. Thanks to the expedited departures, the emergency was quickly alleviated without causing congestion. Furthermore, the passenger volume per mile of buses experiencing passenger congestion increased significantly.

[0092] like Figure 7 The following simulation results show an increase of 100 passengers at Station 7. As can be seen, due to the sudden increase in passengers at Station 7, the departure frequency of the blue line drops to 1, while the departure frequencies of other lines also decrease due to the increase in passengers. This event was alleviated by the faster departure of these lines.

[0093] like Figure 8 The following figure shows the simulation results for a congested road. It can be seen that the purple bus is directly congested, while the blue bus is indirectly congested. In the event of a traffic jam, the frequency of blue and purple bus departures increases, while the number of departures decreases. Furthermore, in the event of direct congestion, the corresponding bus route does not depart to avoid further congestion. Due to congestion in the first half of the road, the number of buses in the second half decreases, and passengers begin to accumulate. Therefore, after the congestion is alleviated, the number of departures should be increased quickly to accommodate more passengers.

[0094] like Figure 9 As shown in Figure 1, after congestion is relieved, some bus routes will reduce their departure frequency to accommodate the increase in passengers. When the number of passengers returns to normal, the departure frequency returns to the optimal departure frequency, and this can be considered as completing a congestion dispatch.

[0095] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A bus departure frequency simulation scheduling system, characterized in that: Includes the following modules: The calculation module obtains bus route information and performs simulation and emulation of bus operation based on the Nasch model; The visualization module receives data from the calculation module and generates a visualization interface for the road grid; The controllable module obtains and controls the change information of variable parameters during bus operation, and sends the control variable data to the calculation module for calculation; The execution method of the operation module includes: L1. Execute the following rules based on the Nasch model: First improvement rule: Buses have unique and fixed origin and destination stations. When adding a bus to a route, always check whether the grid where the origin station is located can accommodate the new bus. If it can, add the bus. When a bus passes the destination station, release it and change the corresponding grid position of the bus route destination station to None. The second improved rule: designate a specific grid as a fixed stop. For buses that have not passed the stop, if the sum of the vehicle's current position and current speed is greater than the stop's position, the bus can enter the stop and the vehicle's speed is adjusted to allow it to stop at the stop. The third improved rule: When the bus passes through the grid where the station is located, the passengers get on and off the bus, and the passengers are generated using the Poisson distribution with different parameters; L2. Define a reliability index to measure road conditions and use it as a standard for dynamically scheduling bus departure frequencies; L3. Formulate bus frequency adjustment strategies based on the constructed reliability index system; L4. Simulate road congestion and sudden increase in passengers based on bus departure frequency adjustment strategy.

2. The bus departure frequency simulation scheduling system according to claim 1 is characterized in that: The reliability indicators described in L2 include the following: Route reliability measures whether bus routes remain unobstructed. It is specifically expressed as the number of direct and indirect congestion on the current road. Direct congestion occurs when two buses on the same route appear in adjacent grids, while indirect congestion occurs when a grid is left empty between two buses on the same route. The greater the number of congestion occurrences, the lower the route reliability. Time reliability measures whether the bus can pick up passengers at the appropriate time. It is specifically expressed as the number of passengers waiting at each stop. The more passengers there are, the lower the time reliability. Safety and reliability measures whether accidents or traffic incidents occur during bus operations. Specifically, it is expressed as the ratio of the average number of such accidents occurring on bus routes per year to the number of bus departures per year. The lower the safety and reliability, the more appropriate it is to reduce bus departures. Transfer reliability measures the number of stops on a bus route that can be used to take buses on other routes. It is specifically performed by constructing a transfer matrix, assigning values to transfer behaviors using the transfer ratio as an indicator, and then obtaining the transfer reliability of a route. The result is between 0 and 1, and the closer it is to 1, the stronger the transfer capacity.

3. The bus departure frequency simulation scheduling system according to claim 2 is characterized in that: The bus frequency adjustment strategies in L3 include: A1. When bus route reliability decreases, bus frequency should be increased. Specifically, when direct congestion occurs on a given road at a given time, or the number of buses on a particular route exceeds a certain threshold, bus frequency should be significantly increased. When indirect congestion occurs on a given road at a given time, bus frequency should be slightly increased, by half the amount of the increase in direct congestion. When there is no bus congestion on a given route at a given time, bus frequency should return to its initial frequency. The extent of the reduction in frequency should be determined based on transfer reliability, with routes with high transfer reliability corresponding to lower reductions. A2. When the time reliability of a bus route decreases, if the time reliability is below a certain threshold, the bus departure frequency is reduced to the minimum; otherwise, the reduction in departure frequency is a monotonic function of the time reliability, and the parameters of the monotonic function should be determined based on safety reliability.

4. The bus departure frequency simulation scheduling system according to claim 1, characterized in that: To quantify the efficiency of bus operation, when a bus enters the terminal, it means that a trip is completed. At this time, the passenger volume per unit mileage of the bus is calculated and expressed as in is the passenger volume of the station, is the total mileage; this indicator reveals the operating efficiency of buses.

5. The bus departure frequency simulation scheduling system according to claim 1 is characterized in that: The simulation of road congestion described in L4 needs to be executed. When road congestion occurs, all vehicles with a speed greater than 1 are required to stop, and vehicles with a speed of exactly 1 can drive normally.

6. The bus departure frequency simulation scheduling system according to claim 1, characterized in that: The controllable module is in communication connection with the monitoring unit; the control of the variable parameters includes the control of the number of passengers at the station, the control of the starting departure frequency, and the control of the road status.

Images