CN115795861A - Simulation system and method applied to intelligent bus road resistance scheduling - Google Patents
Simulation system and method applied to intelligent bus road resistance scheduling Download PDFInfo
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Abstract
The invention belongs to the technical field of traffic, and discloses a simulation system and a simulation method applied to intelligent bus road resistance scheduling, wherein the simulation system comprises the following steps: the dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to the bus lines and the driving plans in the dispatching management platform; the dispatching management platform decomposes the working condition of the road resistance dispatching scene according to the vehicle operation data and the driving plan; the dispatching simulation platform works out input conditions and expected results of all working conditions according to the decomposed working conditions; the dispatching simulation platform sets bus departure rules and vehicle section movement plans in the intelligent road resistance dispatching algorithm simulation process; introducing three objective functions for comparison and evaluation; and simulating the intelligent road resistance scheduling algorithm. The invention solves the problem that a simulation scheme aiming at the intelligent bus road resistance dispatching function is lacked in the bus industry.
Description
Technical Field
The invention belongs to the technical field of traffic, and particularly relates to a simulation system and method applied to intelligent bus road resistance scheduling.
Background
The intelligent bus road congestion scheduling is to detect road congestion in real time and send road congestion warning to a scheduling system administrator when a road congestion situation occurs in the bus operation process and the bus scheduling system needs means such as driver information reporting and vehicle-mounted state feedback. And the administrator reassigns the driving route for the vehicle related to the road block section by calling the road block real-time scheduling algorithm interface. Therefore, the influence of road congestion on bus operation efficiency and passenger trip experience is relieved.
Therefore, the road block real-time scheduling algorithm is a key core of the function, whether the road block real-time scheduling algorithm is fast, efficient and accurate or not is determined, and the success of road block real-time scheduling is determined, so that the bus operation efficiency and safety are determined.
Therefore, a simulation means or mode is adopted, algorithm development and practical application requirements are oriented on the basis of the road resistance scheduling scene in the intelligent bus, algorithm scheme design under the scene is perfected, and a simulation model is established by referring to practical application scene data and parameter configuration. Furthermore, the feasibility and superiority of the algorithm under different scenes and working conditions are analyzed, the benefit indexes of each scheme and the optimized scheme are analyzed in a comparison mode, a model and method support is provided for algorithm development, and parameter configuration scheme reference is provided for practical application. Has great practical significance.
At present, in the industry of public transport, a simulation test method or a simulation test system for public transport operation is mainly limited to the simulation of a public transport network, and a simulation scheme and a simulation system for an intelligent public transport road block dispatching function are not provided.
Therefore, the scheme provides a simulation test system and method applied to intelligent bus road resistance scheduling, aims to solve the problems and fills the blank of the field.
Disclosure of Invention
Aiming at the technical problems, the invention provides a simulation system and a simulation method applied to intelligent bus road resistance scheduling, aims to provide a simulation scheme aiming at an intelligent bus road resistance scheduling function, and fills the blank of the field.
In a first aspect, the invention provides a simulation method applied to intelligent bus road resistance scheduling, which comprises the following steps:
the method comprises the following steps that 1, a dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to a bus line and a driving plan in a dispatching management platform;
step 2, the dispatching management platform carries out working condition decomposition on a road resistance dispatching scene according to the vehicle operation data and the driving plan;
step 3, the dispatching simulation platform works out input conditions and expected results of all working conditions according to the working conditions decomposed in the step 2;
step 4, the dispatching simulation platform sets bus departure rules and vehicle section movement plans in the intelligent road resistance dispatching algorithm simulation process;
step 5, three objective functions are introduced for comparison and evaluation, the objective function 1 only considers the maximum operation income of the bus, the objective function 2 only considers the minimum waiting time of passengers, the objective function 3 simultaneously considers the maximum operation income and the minimum waiting time of the bus, the operation benefits of the bus and the travel experience of the passengers under the three objective functions are respectively compared,
wherein the objective function 1 is
Wherein f is the number of the characteristic time interval of the arrival rate of the passenger flow on the day, T f Time span of f characteristic period, r k，f Passenger arrival rate at kth station for f characteristic time period, P is unified fare, C t Is the unit operation cost of the t-type bus, L is the average mileage of the operation,
in order to make a decision on a variable,
an objective function 2 of
Wherein λ is i，k The number of passengers boarding the ith shift at the k-th station, w i，k For the maximum waiting time of a passenger on the i-th shift at the k-station, the objective function 3 is min = w 2 f 2 ’-w 1 f 1 ', wherein w 1 、w 2 As weighting coefficient, f 1 ’、f 2 ' are each f 1 And f 2 Normalized objective function value, normalized formula is
Step 6, setting parameters based on the simulation conditions from step 1 to step 5, and simulating the intelligent road resistance scheduling algorithm;
and 7, counting according to the simulation result of the step 6, recording the average running time of the shift under the normal running condition, determining the expected arrival time of the shift according to the departure time of the shift and the average running time of the shift, comparing the expected arrival time with the actual arrival time of the shift, and adjusting the parameters of the intelligent road resistance scheduling algorithm when the delay time exceeds 8 minutes to enable the shift to arrive at the station at the expected arrival time, wherein the normal running condition is no road resistance.
Specifically, step 1 comprises:
step 11, selecting a bus route from a database of a scheduling management platform, dividing the bus route into road sections, and setting alternative driving routes at a specific intersection to avoid the road resistance phenomenon of a certain road section;
and step 12, setting simulation parameters of a road resistance scheduling scene from three aspects of bus lines, buses and road resistance configuration based on a road resistance scheduling simulation line layout diagram.
Specifically, step 2 comprises:
step 21, working condition 1 is the dispatching of subsequent buses, the current bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the dispatching management platform monitors that the current bus running road section is blocked, road block position information is issued to an operating vehicle on an affected line, the subsequent operating vehicle is appointed to go to the next bus stop according to the road block position information and the line information and the optimal path planned by an intelligent bus road block dispatching algorithm, and the bus returns to a fixed line to run after the blocked road section is avoided;
step 22, the working condition 2 is scheduling of the current blocked bus, the current blocked bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the scheduling management platform monitors that the current blocked bus running road section is blocked, the current blocked bus is set to enter a road block scheduling mode, a running path is changed according to the result planned by the intelligent bus road block scheduling algorithm, when the blockage is removed, the road block scheduling mode of the current blocked bus is cancelled, and the original route running is recovered.
Specifically, step 3 includes:
step 31, according to the working condition 1, formulating input conditions and expected results based on the dispatching working conditions of subsequent vehicles;
and step 32, according to the working condition 2, making an input condition and an expected result based on the dispatching working condition of the current blocked bus.
Specifically, step 4 comprises:
step 41, setting bus departure rules, and according to the calculated departure interval of each shift and corresponding bus allocation, the departure time of shift j is
When time is
Then, the corresponding vehicle allocation of shift j is sent from the originating station;
step 42, setting a vehicle section movement plan, specifically comprising the following steps:
step 421, the driving speed is set, the bus runs at the average driving speed,
wherein v is j (t + 1) travel of bus j at time tSpeed;
step 422, location update, x j (t+1)＝x j (t)+v j (t + 1) in which x j (t) represents the location of the bus on the bus route at time t, shift j;
step 423, judging whether the station is stopped, if x j (t+1)＝x stati on (t), then v j (t + 1) =0 in which x station (t) represents the location of the bus stop at which the bus of shift j will stop in the forward direction at time t.
Specifically, the bus-mounted system collects the position information and the operation state information of the bus in real time and counts the number of passengers getting on or off the bus in real time;
the bus station system counts station passenger flow data and passenger waiting time of a bus station through video monitoring equipment;
the bus station system counts bus departure interval data and bus departure times through the video monitoring equipment;
the bus dispatching simulation system comprises a dispatching management platform and a dispatching simulation platform, wherein the dispatching management platform records real-time passenger flow data, manages historical passenger flow data and vehicle operation data, runs an intelligent road resistance dispatching algorithm and outputs a driving plan, and the dispatching simulation platform is a simulation environment of the intelligent road resistance dispatching algorithm, wherein the driving plan comprises a schedule, buses and personnel arrangement.
In a second aspect, the invention also provides a simulation system applied to intelligent bus road resistance scheduling, which comprises a bus-mounted system, a bus scheduling simulation system, a bus platform system, a bus station system and a 4G/5G mobile communication network;
the bus-mounted system comprises a vehicle-mounted mobile communication terminal, a camera and a passenger flow data acquisition device, and is used for acquiring vehicle position information and vehicle operation state information in real time and counting the number of passengers getting on or off the bus in real time;
the bus dispatching simulation system comprises a dispatching management platform and a dispatching simulation platform, wherein the dispatching management platform records real-time passenger flow data, manages historical passenger flow data and vehicle operation data, runs an intelligent road resistance dispatching algorithm and outputs a bus running plan, and the dispatching simulation platform is a simulation environment of the intelligent road resistance dispatching algorithm, wherein the running plan comprises a schedule, buses and personnel arrangement;
the bus station system counts station passenger flow data and passenger waiting time of a bus station through the video monitoring equipment;
the bus station system counts bus departure interval data and bus departure times through the video monitoring equipment;
the 4G/5G mobile communication network provides communication connection for a bus-mounted system, a bus dispatching simulation system, a bus station system and a bus station system.
The simulation flow of the intelligent bus road resistance scheduling is as follows:
the method comprises the following steps that 1, a dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to a bus line and a driving plan in a dispatching management platform;
step 2, the dispatching management platform decomposes the working condition of the road resistance dispatching scene according to the vehicle operation data and the driving plan;
step 3, the dispatching simulation platform works out input conditions and expected results of all working conditions according to the working conditions decomposed in the step 2;
step 4, the dispatching simulation platform sets bus departure rules and vehicle section movement plans in the intelligent road resistance dispatching algorithm simulation process;
step 5, three objective functions are introduced for comparison and evaluation, the objective function 1 only considers the maximum operation income of the bus, the objective function 2 only considers the minimum waiting time of passengers, the objective function 3 simultaneously considers the maximum operation income and the minimum waiting time of the bus, the operation benefits of the bus and the travel experience of the passengers under the three objective functions are respectively compared,
wherein the objective function 1 is
Wherein f is the number of the characteristic time interval of the arrival rate of the passenger flow on the day, T f Is the time span of the f-th characteristic period, r k，f Passenger arrival rate at the k-th stop for the f-th characteristic period, P is the uniform fare, C t Is the unit operation cost of the t-type public transport vehicle, L is the average mileage of the operation,
in order to make a decision on a variable,
the objective function 2 is
Wherein λ is i，k The number of passengers boarding the ith shift at the k-th station, w i，k For the maximum waiting time of passengers boarding the ith shift at k stations, the objective function 3 is min = w 2 f 2 ’-w 1 f 1 ', wherein w 1 、w 2 As weighting coefficient, f 1 ’、f 2 ' are each f 1 And f 2 Normalized objective function value, normalized formula is
Step 6, setting parameters based on the simulation conditions from step 1 to step 5, and simulating the intelligent road resistance scheduling algorithm;
and 7, counting according to the simulation result of the step 6, recording the average running time of the shift under the normal running condition, determining the expected arrival time of the shift according to the departure time of the shift and the average running time of the shift, comparing the expected arrival time with the actual arrival time of the shift, and adjusting the parameters of the intelligent road resistance scheduling algorithm when the delay time exceeds 8 minutes to enable the shift to arrive at the station at the expected arrival time, wherein the normal running condition is no road resistance.
Specifically, step 1 comprises:
step 11, selecting a bus route from a database of a dispatching management platform, dividing the bus route into road sections, and setting alternative driving routes at specific intersections to avoid the road resistance phenomenon of a certain road section;
and step 12, setting simulation parameters of a road resistance scheduling scene from three aspects of bus lines, buses and road resistance configuration based on a road resistance scheduling simulation line layout diagram.
Specifically, step 2 comprises:
step 21, working condition 1 is the dispatching of subsequent buses, the current bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the dispatching management platform monitors that the current bus running road section is blocked, road block position information is issued to an operating vehicle on an affected line, the subsequent operating vehicle is appointed to go to the next bus stop according to the road block position information and the line information and the optimal path planned by an intelligent bus road block dispatching algorithm, and the bus returns to a fixed line to run after the blocked road section is avoided;
step 22, the working condition 2 is scheduling of the current blocked bus, the current blocked bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the scheduling management platform monitors that the current blocked bus running road section is blocked, the current blocked bus is set to enter a road block scheduling mode, a running path is changed according to the result planned by the intelligent bus road block scheduling algorithm, when the blockage is removed, the road block scheduling mode of the current blocked bus is cancelled, and the original route running is recovered.
Specifically, step 3 specifically includes:
step 31, according to the working condition 1, formulating input conditions and expected results based on the dispatching working conditions of subsequent vehicles;
and step 32, according to the working condition 2, making an input condition and an expected result based on the dispatching working condition of the current blocked bus.
The invention discloses a simulation system and a method applied to intelligent bus road resistance scheduling, aiming at the problem of road resistance scheduling simulation in actual bus operation, a simulation model is established by referring to actual application scene data and parameter configuration, the feasibility and superiority of an intelligent bus road resistance scheduling algorithm under different scenes and working conditions are simulated and analyzed, the benefit indexes of each scheduling optimization scheme are contrastively analyzed, the intelligent bus road resistance scheduling algorithm is adjusted according to an operation expectation mode, model and method support is provided, and parameter configuration scheme reference is provided for actual application, so that the intelligent bus road resistance scheduling algorithm can be applied to actual operation, and the aim of respective requirements of operated passengers and operation units is fulfilled.
Drawings
FIG. 1 is a flow chart of a simulation method applied to intelligent bus road resistance scheduling according to the present invention;
FIG. 2 is a layout diagram of a road resistance scheduling simulation circuit according to the present invention;
fig. 3 is a schematic structural diagram of a simulation system applied to intelligent common impedance scheduling according to the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are intended to be a subset of the embodiments of the invention rather than a complete embodiment. All other embodiments, which can be obtained by a person skilled in the art without making creative efforts based on the embodiments in the present invention, belong to the protection scope of the present invention.
Fig. 1 is a flowchart illustrating a simulation method applied to intelligent common blocking scheduling according to an embodiment of the present invention. As shown in fig. 1, the method comprises the following steps:
step 1, the dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to the bus lines and the driving plans in the dispatching management platform.
Specifically, step 1 comprises:
and 11, selecting a bus route from a database of the dispatching management platform, dividing the bus route into road sections, and setting alternative driving routes at specific intersections to avoid the road resistance phenomenon of a certain road section.
The road resistance scheduling simulation layout is shown in fig. 2.
Specifically, the travel distance of each road section is obtained by ranging from a high-grade map.
And step 12, setting simulation parameters of a road resistance scheduling scene from three aspects of bus lines, buses and road resistance configuration based on a road resistance scheduling simulation line layout diagram.
The simulation parameters of the road resistance scheduling scenario are shown in table 1.
TABLE 1
And 2, the dispatching management platform decomposes the working condition of the road resistance dispatching scene according to the vehicle operation data and the driving plan.
Specifically, step 2 comprises:
step 21, working condition 1 is the dispatching of subsequent buses, the current bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the dispatching management platform monitors that the current bus running road section is blocked, road block position information is issued to an operating vehicle on an affected line, the subsequent operating vehicle is appointed to go to the next bus stop according to the road block position information and the line information and the optimal path planned by an intelligent bus road block dispatching algorithm, and the bus returns to a fixed line to run after the blocked road section is avoided.
Step 22, the working condition 2 is scheduling of the current blocked bus, the current blocked bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the scheduling management platform monitors that the current blocked bus running road section is blocked, the current blocked bus is set to enter a road block scheduling mode, a running path is changed according to the result planned by the intelligent bus road block scheduling algorithm, when the blockage is removed, the road block scheduling mode of the current blocked bus is cancelled, and the original route running is recovered.
And 3, the dispatching simulation platform works out the input conditions and expected results of all the working conditions according to the working conditions decomposed in the step 2.
Specifically, step 3 specifically includes:
and step 31, formulating input conditions and expected results based on the dispatching working conditions of the subsequent vehicles according to the working conditions 1.
The input conditions and expected results based on the scheduled operating conditions of the following vehicle are shown in table 2.
TABLE 2
And step 32, according to the working condition 2, making an input condition and an expected result based on the dispatching working condition of the current blocked bus. The input conditions and expected results based on the scheduled conditions of the current blocked buses are shown in table 3.
TABLE 3
And 4, setting a bus departure rule and a vehicle section movement plan in the intelligent road resistance scheduling algorithm simulation process by the scheduling simulation platform.
Specifically, step 4 includes:
step 41, setting bus departure rules, and according to the calculated departure interval of each shift and corresponding bus allocation, the departure time of shift j is
When time is
Then the corresponding car allocation for shift j is sent from the originating site.
Step 42, setting a vehicle section movement plan, specifically comprising the following steps:
step 421, setting the running speed, the bus running at the average running speed,
wherein v is j And (t + 1) is the running speed of the bus at the time of t, the shift j. (ii) a
Step 422, location update, x j (t+1)＝x j (t)+v j (t + 1) in which x j (t) represents the location of the bus on the bus route at time t, shift j.
Step 423, judging whether the station is stopped, if x j (t+1)＝x station (t), then v j (t + 1) =0 in which x station (t) represents the location of the bus stop at which the bus of shift j will stop in the forward direction at time t.
Step 5, three objective functions are introduced for comparison and evaluation, the objective function 1 only considers the maximum operation income of the bus, the objective function 2 only considers the minimum waiting time of passengers, the objective function 3 simultaneously considers the maximum operation income and the minimum waiting time of the bus, the operation benefits of the bus and the travel experience of the passengers under the three objective functions are respectively compared,
wherein the objective function 1 is
Wherein f is the number of characteristic time interval of the passenger flow arrival rate on the day, T f Is the time span of the f-th characteristic period, r k，f Passenger arrival rate at the k-th stop for the f-th characteristic period, P is the uniform fare, C t Is the unit operation cost of the t-type public transport vehicle, L is the average mileage of the operation,
in order to make a decision on a variable,
the objective function 2 is
Wherein λ is i，k The number of passengers boarding the ith shift at the k-th station, w i，k For the maximum waiting time of passengers boarding the ith shift at k stations, the objective function 3 is min = w 2 f 2 ’-w 1 f 1 ', wherein w 1 、w 2 As weighting coefficient, f 1 ’、f 2 ' are each f 1 And f 2 Normalized objective function value, normalized formula is
Specifically, the descriptions and units of the variables of the objective function 1 are shown in table 4.
TABLE 4
Specifically, in the normalization formula, f is the objective function value, f max The maximum possible value of the objective function is obtained, the operation income of the bus can be calculated by considering that all passengers get on the bus and all the shifts are normally executed, the waiting time of the passengers can be defaulted to be the maximum departure interval, f min The value is the minimum possible value of the objective function, and 0,f' can be taken as the normalized objective function value for the operation income of the bus and the waiting time of passengers.
Specifically, in the objective function 3, w 1 、w 2 Is 0.5, and the ratio of the two represents the specific gravity of the two optimization objectives.
And 6, setting parameters based on the simulation conditions from the step 1 to the step 5, and simulating the intelligent road resistance scheduling algorithm.
The road resistance phenomenon of the running road section of the bus route can obviously slow down the running speed of the bus, cause the late time of the next shift, and lead the bus to miss the departure time of the next shift in serious cases, thereby influencing the normal operation of the subsequent shifts of the bus route. In order to verify the effect of the active line change strategy, the scheme is compared with a scheme of no-path-resistance scheduling.
Preferably, simulation result statistics is completed according to the data of the relevant indexes of bus shifts and passenger trips under different working conditions and different scheduling strategies. The relative indexes and the benefit pairs of the road resistance scheduling strategy are shown in table 5, and all shown in table 5 are road resistance influence time periods (i.e. the road resistance data extends for 30min before and after).
TABLE 5
And 7, counting according to the simulation result of the step 6, recording the average running time of the shift under the normal running condition, determining the expected arrival time of the shift according to the departure time of the shift and the average running time of the shift, comparing the expected arrival time with the actual arrival time of the shift, and adjusting the parameters of the intelligent road resistance scheduling algorithm when the delay time exceeds 8 minutes to enable the shift to arrive at the station at the expected arrival time, wherein the normal running condition is no road resistance.
When the delay exceeds 8 minutes, the shift is considered to be delayed, and the passenger waits for the bus overtime.
Specifically, the bus-mounted system collects the position information and the operation state information of the bus in real time and counts the number of passengers getting on or off the bus in real time.
The bus station system counts station passenger flow data and passenger waiting time of the bus station through the video monitoring equipment.
The bus station system counts bus departure interval data and bus departure times through the video monitoring equipment.
The bus dispatching simulation system comprises a dispatching management platform and a dispatching simulation platform, wherein the dispatching management platform records real-time passenger flow data, manages historical passenger flow data and vehicle operation data, runs an intelligent road resistance dispatching algorithm and outputs a driving plan, and the dispatching simulation platform is a simulation environment of the intelligent road resistance dispatching algorithm, wherein the driving plan comprises a schedule, buses and personnel arrangement.
The real-time passenger flow data comprises station passenger flow data and riding passenger flow data.
Preferably, the simulation environment of the intelligent bus shift scheduling algorithm is realized by using MATLABR2021a in Windows10 environment, and the lowest hardware requirement is the running memory of Intel (R) Core (TM) i5-7200U CPU,8G of the processor.
Fig. 3 is a schematic structural diagram of a simulation system applied to intelligent bus road block scheduling provided by the invention, which comprises a bus-mounted system, a bus scheduling simulation system, a bus platform system, a bus station system and a 4G/5G mobile communication network.
The bus-mounted system comprises a bus-mounted mobile communication terminal, a camera and a passenger flow data acquisition device, and is used for acquiring the position information and the operation state information of a bus in real time and counting the number of passengers getting on or off the bus in real time;
the bus dispatching simulation system comprises a dispatching management platform and a dispatching simulation platform, wherein the dispatching management platform records real-time passenger flow data, manages historical passenger flow data and vehicle operation data, runs an intelligent road resistance dispatching algorithm and outputs a bus running plan, and the dispatching simulation platform is a simulation environment of the intelligent road resistance dispatching algorithm, wherein the running plan comprises a schedule, buses and personnel arrangement;
the bus station system counts station passenger flow data and passenger waiting time of a bus station through the video monitoring equipment;
the bus station system counts bus departure interval data and the number of bus departures through the video monitoring equipment;
the 4G/5G mobile communication network provides communication connection for a bus-mounted system, a bus dispatching simulation system, a bus station system and a bus station system.
The simulation flow of the intelligent bus road resistance scheduling is as follows:
the method comprises the following steps that 1, a dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to a bus line and a driving plan in a dispatching management platform;
step 2, the dispatching management platform decomposes the working condition of the road resistance dispatching scene according to the vehicle operation data and the driving plan;
step 3, the dispatching simulation platform works out input conditions and expected results of all working conditions according to the working conditions decomposed in the step 2;
step 4, the dispatching simulation platform sets bus departure rules and vehicle section movement plans in the intelligent road resistance dispatching algorithm simulation process;
step 5, three objective functions are introduced for comparison and evaluation, the objective function 1 only considers the maximum operation income of the bus, the objective function 2 only considers the minimum waiting time of passengers, the objective function 3 simultaneously considers the maximum operation income and the minimum waiting time of the bus, the operation benefits of the bus and the travel experience of the passengers under the three objective functions are respectively compared,
wherein the objective function 1 is
Wherein f is the number of the characteristic time interval of the arrival rate of the passenger flow on the day, T f Is the time span of the f-th characteristic period, r k，f Passenger arrival rate at the k-th stop for the f-th characteristic period, P is the uniform fare, C t Is the unit operation cost of the t-type public transport vehicle, L is the average mileage of the operation,
in order to make a decision on a variable,
the objective function 2 is
Wherein λ is i，k Number of passengers boarding the ith shift at the k station, w i，k For the maximum waiting time of passengers boarding the ith shift at k stations, the objective function 3 is min = w 2 f 2 ’-w 1 f 1 ', wherein w 1 、w 2 As weighting coefficient, f 1 ’、f 2 ' are each f 1 And f 2 Normalized objective function value, normalized formula is
Step 6, setting parameters based on the simulation conditions from step 1 to step 5, and simulating the intelligent road resistance scheduling algorithm;
and 7, counting according to the simulation result of the step 6, recording the average running time of the shift under the normal running condition, determining the expected arrival time of the shift according to the departure time of the shift and the average running time of the shift, comparing the expected arrival time with the actual arrival time of the shift, and adjusting the parameters of the intelligent road resistance scheduling algorithm when the delay time exceeds 8 minutes to enable the shift to arrive at the station at the expected arrival time, wherein the normal running condition is no road resistance.
Specifically, step 1 comprises:
step 11, selecting a bus route from a database of a dispatching management platform, dividing the bus route into road sections, and setting alternative driving routes at specific intersections to avoid the road resistance phenomenon of a certain road section;
and step 12, setting simulation parameters of a road resistance scheduling scene from three aspects of bus lines, buses and road resistance configuration based on a road resistance scheduling simulation line layout diagram.
Specifically, step 2 comprises:
step 21, working condition 1 is the dispatching of subsequent buses, the current bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the dispatching management platform monitors that the current bus running road section is blocked, road block position information is issued to an operating vehicle on an affected line, the subsequent operating vehicle is appointed to go to the next bus stop according to the road block position information and the line information and the optimal path planned by an intelligent bus road block dispatching algorithm, and the bus returns to a fixed line to run after the blocked road section is avoided;
step 22, the working condition 2 is scheduling of the current blocked bus, the current blocked bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the scheduling management platform monitors that the current blocked bus running road section is blocked, the current blocked bus is set to enter a road block scheduling mode, a running path is changed according to the result planned by the intelligent bus road block scheduling algorithm, when the blockage is removed, the road block scheduling mode of the current blocked bus is cancelled, and the original route running is recovered.
Specifically, step 3 specifically includes:
step 31, formulating input conditions and expected results based on the dispatching working conditions of the subsequent vehicles according to the working condition 1;
and step 32, according to the working condition 2, making an input condition and an expected result based on the dispatching working condition of the current blocked bus.
The above-mentioned embodiments only express the preferable mode of the invention, and the description is more specific and detailed, but not to be understood as the limitation of the patent scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. A simulation method applied to intelligent bus road resistance scheduling is characterized by comprising the following steps:
the method comprises the following steps that 1, a dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to a bus line and a driving plan in a dispatching management platform; the step 1 comprises the following steps:
step 11, selecting a bus route from a database of the dispatching management platform, dividing the bus route into road sections, and setting alternative driving routes at a specific intersection to avoid the road resistance phenomenon of a certain road section;
12, setting simulation parameters of a road resistance scheduling scene from three aspects of the bus route, the buses and the road resistance configuration based on the road resistance scheduling simulation route layout;
step 2, the dispatching management platform decomposes the working condition of the road resistance dispatching scene according to vehicle operation data and the driving plan;
step 3, the dispatching simulation platform works out input conditions and expected results of all working conditions according to the working conditions decomposed in the step 2;
step 4, the dispatching simulation platform sets bus departure rules and vehicle section movement plans in the intelligent road resistance dispatching algorithm simulation process; the step 4 specifically includes:
step 41, setting the bus departure rule, and according to the calculated departure interval of each shift and the corresponding bus allocation, the departure time of shift j is
When time comes
Then, the corresponding allocated vehicle for the shift j is sent from the originating station;
step 42, setting the vehicle section movement plan;
step 5, three objective functions are introduced for comparison and evaluation, the objective function 1 only considers that the operation income of the bus is maximum, the objective function 2 only considers that the waiting time of passengers is minimum, the objective function 3 simultaneously considers that the operation income of the bus is maximum and the waiting time of the passengers is minimum, and the operation benefit of the bus and the travel experience of the passengers under the three objective functions are respectively compared;
step 6, setting parameters based on the simulation conditions from the step 1 to the step 5, and simulating the intelligent road resistance scheduling algorithm;
and 7, counting according to the simulation result of the step 6, recording the average running time of the shift under the normal running condition, determining the estimated arrival time of the shift according to the departure time of the shift and the average running time of the shift, comparing the estimated arrival time with the actual arrival time of the shift, and adjusting the parameters of the intelligent road resistance scheduling algorithm when the delay time exceeds 8 minutes to enable the shift to arrive at the station at the estimated arrival time, wherein the normal running condition is no road resistance.
2. Application of the composition according to claim 1The simulation method for intelligent bus road resistance dispatching is characterized in that in the step 5, the objective function 1 is
Wherein f is the number of the characteristic time interval of the arrival rate of the passenger flow on the day, T f Time span of f characteristic period, r k,f Passenger arrival rate at the k-th stop for the f-th characteristic period, P is the uniform fare, C t Is the unit operation cost of the t-type public transport vehicle, L is the average mileage of the operation,
in order to make a decision on the variable,
the objective function 2 is
Wherein λ is i,k The number of passengers boarding the ith shift at the k-th station, w i,k For the maximum waiting time of passengers boarding the i-th shift at the k-station, the objective function 3 is Minf = w 2 f 2 ’-w 1 f 1 ', wherein w 1 、w 2 As weighting coefficient, f 1 ’、f 2 ' are respectively said f 1 And f is 2 Normalized objective function value, normalized formula is
3. The simulation method applied to intelligent bus road resistance scheduling according to claim 1, wherein the step 2 comprises:
step 21, working condition 1 is the dispatching of subsequent buses, the current bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the dispatching management platform monitors that the current bus running road section is blocked, road block position information is issued to an operating vehicle on an affected line, the subsequent operating vehicle is appointed to go to the next bus stop according to the road block position information and the line information and the optimal path planned by the intelligent bus road block dispatching algorithm, and the bus returns to a fixed line to run after the blocked road section is avoided;
step 22, the working condition 2 is scheduling of the current blocked bus, the current blocked bus runs according to the initial driving plan, the traffic flow condition of the current road section is reported in real time, when the scheduling management platform monitors that the current blocked bus running road section is blocked, the current blocked bus is set to enter a road blocking scheduling mode, a running path is changed according to a result planned by the intelligent bus road blocking scheduling algorithm, and when the blockage is removed, the road blocking scheduling mode of the current blocked bus is cancelled, and running of the original route is recovered.
4. The simulation method applied to intelligent bus road resistance scheduling according to claim 3, wherein the step 3 specifically comprises:
step 31, according to the working condition 1, formulating input conditions and expected results based on the dispatching working conditions of subsequent vehicles;
and step 32, according to the working condition 2, formulating an input condition and an expected result based on the dispatching working condition of the current blocked bus.
5. The simulation method applied to intelligent bus road resistance scheduling according to claim 1, wherein the step 42 comprises:
step 421, setting the running speed, wherein the bus runs at the average running speed,
wherein v is j (t + 1) is the travel speed of the bus at time t, shift j;
step 422, location update, x j (t+1)＝ j (t)+ j (t + 1) in which x j (t) represents the location of the bus on the bus route for shift j at time t;
step 423, judging whether the station is stopped, if x j (t+1)＝ station (t), then v j (t + 1) =0, wherein x station (t) represents the location of the bus stop at which the bus of shift j will stop in the forward direction at time t.
6. The simulation method applied to intelligent bus road block scheduling according to claim 1, wherein a bus-mounted system collects vehicle position information and vehicle operation state information in real time and counts the number of passengers getting on and off the bus in real time;
the bus station system counts station passenger flow data and passenger waiting time of a bus station through video monitoring equipment;
the bus station system counts bus departure interval data and bus departure times through the video monitoring equipment;
the bus dispatching simulation system comprises the dispatching management platform and the dispatching simulation platform, wherein the dispatching management platform records real-time passenger flow data, manages historical passenger flow data and vehicle operation data, runs the intelligent road resistance dispatching algorithm and outputs the driving plan, and the dispatching simulation platform is a simulation environment of the intelligent road resistance dispatching algorithm, wherein the driving plan comprises a timetable, buses and personnel arrangement.
7. A simulation system applied to intelligent bus road resistance scheduling is characterized by comprising a bus-mounted system, a bus scheduling simulation system, a bus platform system, a bus station system and a 4G/5G mobile communication network;
the bus-mounted system comprises a vehicle-mounted mobile communication terminal, a camera and a passenger flow data acquisition device, and is used for acquiring vehicle position information and vehicle operation state information in real time and counting the number of passengers getting on or off the bus in real time;
the bus dispatching simulation system comprises a dispatching management platform and a dispatching simulation platform, wherein the dispatching management platform records real-time passenger flow data, manages historical passenger flow data and vehicle operation data, runs an intelligent road resistance dispatching algorithm and outputs a bus running plan, and the dispatching simulation platform is a simulation environment of the intelligent road resistance dispatching algorithm, wherein the running plan comprises a timetable, buses and personnel arrangement;
the bus station system counts station passenger flow data and passenger waiting time of a bus station through video monitoring equipment;
the bus station system counts bus departure interval data and bus departure times through the video monitoring equipment;
the 4G/5G mobile communication network provides communication connection for the bus-mounted system, the bus dispatching simulation system, the bus station system and the bus station system;
the simulation process of the intelligent bus road resistance scheduling is as follows:
step 1, the dispatching simulation platform constructs a road resistance dispatching simulation line layout diagram and sets simulation parameters of a road resistance dispatching scene according to the bus lines and the driving plans in the dispatching management platform;
step 2, the dispatching management platform decomposes the working condition of the road resistance dispatching scene according to the vehicle operation data and the driving plan;
step 3, the dispatching simulation platform works out input conditions and expected results of all working conditions according to the working conditions decomposed in the step 2;
step 4, the dispatching simulation platform sets bus departure rules and vehicle section movement plans in the intelligent road resistance dispatching algorithm simulation process;
step 5, three objective functions are introduced for comparison and evaluation, the objective function 1 only considers that the operation income of the bus is maximum, the objective function 2 only considers that the waiting time of passengers is minimum, the objective function 3 simultaneously considers that the operation income of the bus is maximum and the waiting time of the passengers is minimum, the operation benefit of the bus and the travel experience of the passengers under the three objective functions are respectively compared,
wherein the objective function 1 is
Wherein f is the number of the characteristic time interval of the arrival rate of the passenger flow on the day, T f Time span of f characteristic period, r k,f Passenger arrival rate at the k-th stop for the f-th characteristic period, P is the uniform fare, C t Is the unit operation cost of the t-type public transport vehicle, L is the average mileage of the operation,
in order to make a decision on a variable,
the objective function 2 is
Wherein λ is i,k The number of passengers boarding the ith shift at the k-th station, w i,k For the maximum waiting time of passengers boarding the i-th shift at the k-station, the objective function 3 is Minf = w 2 f 2 ’w 1 f 1 ', wherein, w 1 、w 2 As weighting coefficient, f 1 ’、f 2 ' are respectively said f 1 And said f 2 Normalized objective function value, normalized formula is
Step 6, setting parameters based on the simulation conditions from the step 1 to the step 5, and simulating the intelligent road resistance scheduling algorithm;
and 7, counting according to the simulation result of the step 6, recording the average running time of the shift under the normal running condition, determining the estimated arrival time of the shift according to the departure time of the shift and the average running time of the shift, comparing the estimated arrival time with the actual arrival time of the shift, and adjusting the parameters of the intelligent road resistance scheduling algorithm when the delay time exceeds 8 minutes to enable the shift to arrive at the station at the estimated arrival time, wherein the normal running condition is no road resistance.
8. The simulation system applied to intelligent bus road resistance scheduling according to claim 7, wherein the step 1 comprises:
step 11, selecting a bus route from a database of the dispatching management platform, dividing the bus route into road sections, and setting alternative driving routes at a specific intersection to avoid the road resistance phenomenon of a certain road section;
and 12, setting simulation parameters of the road resistance scheduling scene from three aspects of the bus route, the bus and the road resistance configuration based on the road resistance scheduling simulation route layout diagram.
9. The simulation system applied to intelligent bus road resistance scheduling according to claim 8, wherein the step 2 comprises:
step 21, a working condition 1 is dispatching of subsequent buses, the current bus runs according to an initial driving plan, the traffic flow condition of the current road section is reported in real time, when the dispatching management platform monitors that the current bus running road section is blocked, road block position information is issued to an operating vehicle on an affected line, the subsequent operating vehicle is appointed to go to the next bus stop according to the road block position information and the line information and the optimal path planned by the intelligent bus road block dispatching algorithm, and the bus returns to a fixed line to run after the blocked road section is avoided;
step 22, working condition 2 is scheduling of the current blocked bus, the current blocked bus runs according to the initial driving plan, the traffic flow condition of the current road section is reported in real time, when the scheduling management platform monitors that the current blocked bus running road section is blocked, the current blocked bus is set to enter a road blocking scheduling mode, a running path is changed according to a result planned by the intelligent bus road blocking scheduling algorithm, and when the blockage is removed, the road blocking scheduling mode of the current blocked bus is cancelled, and running of the original route is recovered.
10. The simulation system applied to intelligent bus road block scheduling according to claim 9, wherein the step 3 specifically comprises:
step 31, according to the working condition 1, formulating input conditions and expected results based on the dispatching working conditions of subsequent vehicles;
and step 32, according to the working condition 2, formulating input conditions and expected results based on the dispatching working condition of the current blocked bus.
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| CN116504089B (en) * | 2023-06-27 | 2023-09-12 | 东风悦享科技有限公司 | Unmanned public transport cluster flexible scheduling system based on road surface damage factors |
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