CN112214873A - Passenger flow distribution simulation evaluation method and system under rail transit fault - Google Patents
Passenger flow distribution simulation evaluation method and system under rail transit fault Download PDFInfo
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Abstract
The invention relates to a passenger flow distribution simulation evaluation method and a passenger flow distribution simulation evaluation system under a rail transit fault, wherein the method comprises the following steps: step 1: preprocessing basic data; step 2: modeling and simulating the interactive process of passenger flow and train: for each departure event, dividing the train waiting process, the getting-on process and the getting-off process by a passenger flow and train interaction process modeling and simulation module, sequentially traversing all departure events to form dynamic simulation, and calculating a passenger flow time-space distribution index; and step 3: and (3) passenger flow distribution evaluation: based on the passenger flow distribution calculation result, the passenger service level evaluation module compares the passenger flow distribution index and the passenger travel time index related to the train and the platform in the fault scene. Compared with the prior art, the method has the advantages of providing assistant decision support for handling large passenger flow and handling vehicle dispatching in a fault and the like.
Description
Technical Field
The invention relates to a rail transit passenger flow data analysis and processing technology, in particular to a passenger flow distribution simulation evaluation method and system under rail transit faults.
Background
As a huge complex system, the operation of urban rail transit is influenced by various factors, faults are difficult to avoid and occur randomly, train operation delay and even operation interruption are caused, and therefore passenger trip experience is reduced. With the enlargement of the scale of a rail transit road network and the increase of passenger flow, faults occur more frequently and have larger and larger influence, but because the current passenger flow is difficult to predict in real time, the influence range and the influence degree of the faults on the passenger trip are difficult to quantify in dynamic operation practice.
With the accumulation and the availability of the historical operation data of the rail transit, the method for regularly mining based on the historical passenger flow data becomes a common method in recent years, and the method mainly analyzes the influence of faults on the passenger flow by comparing the difference of the space-time distribution of the passenger flow of a section under the fault condition and the normal condition. However, the reliability of the historical passenger flow data analysis result depends on the accuracy of the network passenger flow clearing method, the transport capacity and the passenger flow are dynamically changed under abnormal conditions, and the fault process is difficult to restore by the subsequent clearing result, so that the passenger flow data analysis under the fault is easy to deviate from the actual condition.
In practice, because the timely propelling movement of fault information in each city has not been popularized yet completely at present, most commuting passengers go out according to usual fixed time, and usually know the fault information after arriving at a subway station. Therefore, the passenger flow at a period of time after the fault is started is not much different from the previous day, and more passengers are detained in the train, the train is crowded in the train, the platform waits, the passengers enter the train and queue the passengers out of the train because the transportation energy is reduced and the passenger flow distribution speed is slowed down. The passenger flow analysis after the fault cannot reflect the interactive process of train operation and platform passenger flow during the fault period and the distribution condition and the supply condition of transportation energy of the passenger flow at each time-space position under the interaction.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a passenger flow distribution simulation evaluation method and a passenger flow distribution simulation evaluation system under a rail transit fault, which are used for calculating the space-time distribution of passenger flow under the fault and the meeting condition of the transportation energy to the requirements and providing auxiliary decision support for handling large passenger flow and handling vehicle dispatching under the fault.
The purpose of the invention can be realized by the following technical scheme:
according to one aspect of the invention, a passenger flow distribution simulation evaluation method under a rail transit fault is provided, which comprises the following steps:
step 1: preprocessing basic data: calling OD passenger flow grouped data obtained by a standard passenger flow calculating module, and arranging the OD passenger flow grouped data according to the ascending sequence of the station-entering time; selecting the subsequent stage starting event data obtained by the adjustment chart calculation module, and arranging the starting event data in ascending order according to the direction and the time; setting train capacity data, and taking the longest waiting time limit parameter value of passengers;
step 2: modeling and simulating the interactive process of passenger flow and train: for each departure event, dividing the train waiting process, the getting-on process and the getting-off process by a passenger flow and train interaction process modeling and simulation module, sequentially traversing all departure events to form dynamic simulation, and calculating a passenger flow time-space distribution index;
and step 3: and (3) passenger flow distribution evaluation: based on the passenger flow distribution calculation result, the passenger service level evaluation module compares the passenger flow distribution index and the passenger travel time index related to the train and the platform in the fault scene.
As a preferred technical solution, the specific process of calculating the passenger flow space-time distribution index in step 2 is as follows:
1) waiting for the vehicle: explicitly waiting for a set of passengers and a set of passengers leaving because the maximum waiting time is exceeded; considering newly inbound passengers and passengers left for riding in a preceding car; for a small-traffic-road turn-back station, if a train in front of the small-traffic-road turn-back station turns back in advance, the condition that a passenger getting off in advance enters into waiting or leaves is also considered, an attribute of getting off in advance is added to the passenger, the passenger is considered as a new 'station-entering moment', waiting or leaving is judged according to the maximum waiting time as the same as the first two classes of passengers, wherein the maximum waiting time is set as Dg；
2) The getting-on process: determining the number of available passengers based on the remaining capacity of the train and the number of waiting passengers, and if the number of available passengers is equal to the number of waiting passengers, enabling all waiting passengers to be available for getting on the train; if the number of passengers getting on the train is equal to the remaining capacity of the train, the passengers get on the train in the principle of first-come first-serve until a certain group of passengers cannot get on the train completely, and at the moment, the passengers at different destinations in the group are considered to get on the train in proportion, so that the passenger collection getting on the train, the passenger collection left to take the train and the passenger collection in the train are calculated in an accumulated mode;
3) the getting-off process comprises the following steps: and defining a set of passengers getting off, determining the passengers getting off at the station in advance according to the destination of the passengers and the starting event of the station, and distinguishing the conditions of all the passengers getting off at the turn-back station of the small traffic road.
As a preferred technical scheme, the maximum waiting time DgThe value of the time interval is set under the condition that most passengers are willing to wait more due to longer trip time in a trip habit or other modes under the condition of considering faults, and is more than or equal to two planned driving intervals;
the calculation of the remaining train capacity is to distinguish whether the current starting event is an initiating event, if so, the train has complete train capacity; otherwise, subtracting the number of the passengers on the train when the train departs from the previous station and the number of the passengers getting off the train at the current station from the capacity of the train; the number of the passengers on the train when the train departs comprises the number of the passengers on the train at the station, and the number of the passengers on the train when the train departs from the previous station is added to the non-starting event, and the number of the passengers off the train when the train arrives at the station is subtracted.
As a preferred technical solution, the passenger flow distribution index and the passenger travel time index in step 3 include:
1) the train full load rate: the number of people in each space-time position compartment can be known through the passenger set in the train corresponding to each departure event, and the space-time full load rate of each train is calculated by combining the train passenger deciding capacity;
2) station congestion situation: analyzing the distribution and evolution characteristics of passengers staying and waiting for passengers, calculating the occurrence rate of all-line passengers staying, and measuring the station congestion by combining the station capacity; .
3) Passenger exit condition: analyzing the number and distribution characteristics of passengers leaving the train, and checking the overall adaptation condition of the train service and the passenger flow demand;
4) passenger waiting time: the method comprises the time for waiting for getting on the train at a starting station and the time for waiting for the next shift of the train after being forced to get off in advance at a small traffic route return station; in the case of temporary adjustment to the folding back of the minor traffic route, the latter belongs to increased waiting time, so that a penalty coefficient larger than 1 is multiplied, and the waiting time before the passengers leave is also counted;
5) travel time of the passenger: including waiting time and ride time, and also considering both being serviced and not being serviced by departure, for a departing passenger, consider its subsequent departure time to increase, i.e., equal to the planned ride time multiplied by a penalty factor greater than 1.
As a preferred technical solution, the getting-on and getting-off attributes of each passenger group are recorded during simulation of the passenger flow and train interaction process in step 2, and include a start station getting-on time, a transfer station getting-off time, a transfer station getting-on time, and a terminal station getting-off time, so that the passenger waiting time and the riding time associated with each train departure event are calculated in step 3, and the total passenger waiting time and the total passenger riding time are calculated.
According to another aspect of the invention, a passenger flow distribution simulation evaluation system under rail transit fault is provided, which comprises:
and a standard passenger flow volume calculation module: the system is used for obtaining the standard passenger flow volume of each space-time granularity of a certain characteristic day according to the statistical analysis of historical passenger flow data of a plurality of same characteristic days under normal operation conditions;
an adjustment operation diagram calculation module: the adjustment operation diagram data is used for generating a fit plan operation diagram according to the fault information and the scheduling strategy;
the passenger flow and train interaction process modeling and simulation module comprises: the passenger flow distribution index calculation method is used for constructing a passenger flow distribution index calculation method according to the interaction state of platform passenger flow and the train operation process, loading standard passenger flow and adjusting operation diagram data, and calculating a passenger flow space-time distribution result through dynamic simulation in combination with the train capacity limit;
a passenger service level assessment module: and the passenger travel service level evaluation system is used for comparing the normal scene and evaluating the passenger travel service level index in the fault scene according to the passenger flow space-time distribution calculation result.
As a preferred technical scheme, the normal operation condition is moreThe same characteristic day refers to a week with the same practical meaning in a period of time when no abnormal event occurs; each space-time granularity refers to each OD group s and unit time t, and the corresponding standard passenger flow is expressed as
The calculation formula is as follows:
wherein Dx is a set of normal days,
for calculating the function, a clustering algorithm is adopted; when the fault date and the national holiday have been eliminated, an averaging method can be adopted.
As a preferred technical solution, the fault information includes fault time, location, cause, and estimated fault duration; and the dispatching strategy is confirmed according to the fault information, a station stopping time and interval running time adjusting strategy is adopted for slight faults, and a corresponding intersection and interval adjusting strategy is searched from the emergency plan for serious faults.
As a preferred technical scheme, the interaction state of the platform passenger flow and the train running process is divided into an waiting process, an getting-on process and a getting-off process; the passenger flow distribution indexes comprise the number of waiting persons, the number of leaving persons, the number of getting-on persons, the number of remaining persons, the number of getting-on persons and the number of getting-off persons corresponding to each train at each station.
Preferably, the passenger service level index includes a train full load rate, a platform congestion condition, a passenger leaving condition, a passenger waiting time, and a passenger travel time.
Compared with the prior art, the invention has the following advantages:
1. the standard passenger flow volume can be calculated and stored in advance, and the passenger flow demand characteristics similar to the characteristic days with the same characteristics at the beginning of the fault and the previous day are reflected, so that the quick calling and handling under the fault are facilitated, and the quick handling under the fault is facilitated.
2. And an adjusting operation diagram is quickly generated according to the scheduling experience and the emergency plan, so that the change situation of the transport capacity can be conveniently mastered, and the operation situation is comprehensively known by combining the standard passenger flow for further adjusting and optimizing reference.
3. By refining the interactive process of passenger flow and trains, the distribution condition of the demand of each station and each class of passengers is predicted, and reference is provided for traffic scheduling and passenger transport organizations.
4. The maximum waiting time is set, the change of the passenger trip behavior under the influence of faults is reflected, the value of the parameter is adjusted by combining different line conditions, and the change of the passenger waiting behavior in practice is reflected.
Drawings
FIG. 1 is a system architecture diagram of the present invention;
FIG. 2 is a schematic diagram of the interaction result between passenger flow and train according to the present invention;
FIG. 3 is a schematic diagram of the full load of the train under the normal operation scenario in the embodiment of the present invention, in which (a) is the ascending (D)g9min, and (b) is descending (D)g＝9min)；
FIG. 4 is a schematic diagram of the full load rate of the train under the fault operation scenario in the embodiment of the present invention, where (a) is uplink (D)g9min, and (b) is descending (D)g(ii) 9min), (c) is ascending (D)g15min), (D) is descending (D)g＝15min)；
Fig. 5 is a schematic diagram illustrating a sequence of the number of waiting passengers at the platform for all train services according to an embodiment of the present invention, wherein (a) is the number of waiting passengers at the platform in a normal operation scenario, and (b) is the number of waiting passengers at the platform in a fault operation scenario.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, shall fall within the scope of protection of the present invention.
The invention provides a passenger flow distribution simulation evaluation method under a rail transit fault and a corresponding system. In short, the method adjusts the operation diagram data based on normal standard passenger flow data and fault stages, and calculates and evaluates passenger flow distribution indexes and passenger travel time indexes related to the train and the platform under the fault through modeling in a sub-process and simulating the interaction process of the passenger flow and the train according to time sequence.
The invention is further illustrated below, with reference to fig. 1, and comprises the following implementation steps:
step S1: before a fault occurs, the standard passenger flow volume is calculated and stored in advance based on historical normal passenger flow data in a standard passenger flow volume calculation module.
Aiming at a certain characteristic day, selecting a week with the same actual meaning in a period of historical time without abnormal events, carrying out statistical analysis on historical passenger flow data, and calculating the standard passenger flow of each OD group s in unit time t, wherein the calculation formula is as follows:
wherein Dx is a set of normal days,
for calculating the function, a clustering algorithm is generally adopted, and when the fault date and the national holiday are eliminated, a mean value calculation method can be adopted.
Particularly, the work of the step can be carried out at any time interval of normal operation, and if the passenger flow characteristics are stable, the step can be calculated and stored at one time for standby in a subsequent period.
Step S2: after a fault occurs, in an adjustment operation diagram calculation module, according to fault information, a plan operation diagram and a scheduling strategy, adjustment operation diagram data are quickly generated, and adjustment operation diagram data of a subsequent stage are directly called during fault treatment.
The fault information comprises fault time, position, reason and estimated fault duration; and the dispatching strategy is confirmed according to the fault information, the minor fault mainly adopts a stop time and interval running time adjusting strategy, and the major fault searches a corresponding intersection and interval adjusting strategy from the emergency plan.
Step S3: and calling the standard passenger flow data obtained in the step S1, selecting the starting event data of the adjustment operation chart in the subsequent stage in the step S2, and setting the values of the limiting parameters of the train capacity and the longest waiting time of passengers.
The standard passenger flow data are grouped and arranged in ascending order according to OD and station-entering time, the adjusted departure events are arranged in ascending order according to direction and time, and parameters such as train capacity, longest waiting time of passengers and the like are respectively taken according to line conditions. Wherein the maximum waiting time is set to Dg。
Step S4: based on the data preprocessed in the step S3, for each departure event, a model is built and simulated in the passenger flow and train interaction process, the classification process, the getting-on process and the getting-off process refine the passenger flow and train interaction process, all departure events are traversed in sequence to form dynamic simulation, and the passenger flow space-time distribution index is calculated, which includes the number of waiting persons, the number of leaving persons, the number of getting-on persons, the number of remaining persons, the number of getting-on persons and the number of getting-off persons corresponding to each train at each station, and refer to fig. 2.
1) Waiting for the vehicle: an explicitly waiting passenger set and a passenger set that left because the maximum waiting time was exceeded. Consideration is generally given to newly arriving passengers and passengers who have left the lead car; for a small-traffic-road turning-back station, if a train in front of the small-traffic-road turning-back station turns back in advance, the situation that a passenger getting off in advance enters or leaves needs to be considered, an attribute of getting off in advance is added for the passenger, the new 'getting-on time' is considered, and waiting or leaving is judged according to the maximum waiting time as the first two classes of passengers, namely: when the passenger gets into the station and arrives in the maximum waiting time from the next train, the passenger waits; otherwise, the passenger leaves.
The value of the maximum waiting time influences the calculation result of the passenger flow distribution index, most passengers are willing to wait more and can bear longer waiting time due to longer trip time in the trip habit or other modes under the condition of considering the fault, and therefore DgThe value range is set to be more than or equal to two planned driving roomsAnd (4) separating.
2) The getting-on process: and accumulating and calculating the boarding passenger set, the reserved passenger set and the in-vehicle passenger set. Determining the number of available passengers based on the remaining capacity of the train and the number of waiting passengers, and if the number of available passengers is equal to the number of waiting passengers, enabling all waiting passengers to be available for getting on the train; if the number of passengers getting on the train is equal to the remaining capacity of the train, the passengers get on the train in the principle of first-come first-serve until a group of passengers arriving at the same time cannot get on the train completely, at the moment, the passengers of different destinations in the group are considered to get on the train in proportion to obtain a part of getting on the train and a part of getting on the train in the group, the total passengers getting on the train corresponding to the event are composed of all the passengers grouped in the past and the part of the passengers getting on the train in the group, and the total passengers getting on the train are composed of all the passengers grouped in the past and all the passengers grouped in.
The calculation of the remaining capacity of the train needs to distinguish whether the current starting event is an initiating event, and if so, the train has complete capacity; or subtracting the number of the passengers getting on the train when the train departs from the last station and the number of the passengers getting off the train from the current station from the capacity of the train. The number of the passengers on the train when the train departs comprises the number of the passengers on the train at the station, and the number of the passengers on the train when the train departs from the previous station is added to the non-starting event, and the number of the passengers off the train when the train arrives at the station is subtracted.
3) The getting-off process comprises the following steps: the set of alighting passengers is specified. And determining the passengers getting off at the station in advance according to the destination of the passenger and the starting event of the station, and distinguishing the conditions that all the passengers get off at the turn-back station of the small traffic route.
Step S5: based on the passenger flow distribution calculation result of step S4, the passenger service level evaluation module compares the passenger flow distribution index and the passenger travel time index related to the train and the platform in the fault scene with the normal scene.
1) The train full load rate: the number of people in each space-time position compartment can be known through the passenger set in the train corresponding to each departure event, and the space-time full load rate of each train is calculated by combining the train passenger deciding capacity;
2) station congestion situation: and analyzing the distribution and evolution characteristics of the passengers staying and waiting for passengers, calculating the occurrence rate of the whole-line passengers staying, and measuring the degree of congestion of the platform by combining the capacity of the platform.
3) Passenger exit condition: analyzing the quantity and distribution characteristics of the passengers leaving the train, and checking the overall adaptation condition of the train service and the passenger flow demand.
4) Passenger waiting time: the method comprises the time for waiting for getting on at a starting station and the time for waiting for the next shift of traffic trains after the small traffic route return station is forced to get off in advance. In the case of temporary adjustment to minor-crossing foldback, the latter is of increased latency, and is therefore multiplied by a penalty factor greater than 1, set to δ. The waiting time before the passenger leaves is also taken into account.
5) Travel time of the passenger: including waiting time and riding time, as well as being serviced and not serviced by leaving. For the leaving passenger, the subsequent travel time is considered to be increased, namely equal to the planned riding time multiplied by a penalty coefficient which is larger than 1, and is set as rho.
In step S4, the getting-on/off attributes of each passenger group are recorded during simulation of the passenger flow and train interaction process, including the getting-on time at the start station, the getting-off time at the transfer station, the getting-on time at the transfer station, and the getting-off time at the end station, so that the passenger waiting time and the riding time associated with each train departure event are calculated in step S5, and the total passenger waiting time and the total passenger riding time are calculated.
Further, as shown in fig. 1, the results of the passenger service level evaluation module can be used to further optimize and adjust the operation diagram, such as finding the space-time position where the capacity of the train or platform is not enough to meet the passenger flow demand, for the car scheduling and the passenger organization to take countermeasures in time.
Taking an actual line as an example, the system and the method of the invention are used for evaluating the passenger flow distribution under the fault. Selecting the passenger flow data under the normal operation condition, and converting the network OD passenger flow data into local line OD passenger flow data in advance to form standard passenger flow. The train passenger capacity is 840 persons, and the maximum allowable load rate of the train is calculated by 120%. The transfer latency penalty factor δ is set to 2. And (4) testing two normal and fault operation scenes by taking 8: 00-11: 00 as a research time domain. The normal scene is orderly operated according to a plan, and a plan operation diagram is used; the failure scenario is assumed to be 8:00, when a fault occurs, the operation of the partial section unilateral train is interrupted for 2h, and an adjusting operation diagram generated according to a scheduling strategy is used. Taking into account the maximum waiting time D of the passengersgAnd the penalty coefficient rho of the subsequent trip of the leaving passenger has obvious influence on the calculation of passenger flow distribution indexes, and different values are respectively set for discussion and analysis: (1) dg＝9/10/15min；(2)ρ＝1.5/2。
The train full load rate is as shown in fig. 3 and 4, and the upper and lower rows are respectively displayed in each operation scene; the platform related passenger flow distribution index statistics are shown in table 1 and fig. 5; the passenger travel time index is shown in table 2.
TABLE 1
TABLE 2
While the invention has been described with reference to specific embodiments, the invention is not limited thereto, and various equivalent modifications and substitutions can be easily made by those skilled in the art within the technical scope of the invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A passenger flow distribution simulation evaluation method under a rail transit fault is characterized by comprising the following steps:
step 1: preprocessing basic data: calling OD passenger flow grouped data obtained by a standard passenger flow calculating module, and arranging the OD passenger flow grouped data according to the ascending sequence of the station-entering time; selecting the subsequent stage starting event data obtained by the adjustment chart calculation module, and arranging the starting event data in ascending order according to the direction and the time; setting train capacity data, and taking the longest waiting time limit parameter value of passengers;
step 2: modeling and simulating the interactive process of passenger flow and train: for each departure event, dividing the train waiting process, the getting-on process and the getting-off process by a passenger flow and train interaction process modeling and simulation module, sequentially traversing all departure events to form dynamic simulation, and calculating a passenger flow time-space distribution index;
and step 3: and (3) passenger flow distribution evaluation: based on the passenger flow distribution calculation result, the passenger service level evaluation module compares the passenger flow distribution index and the passenger travel time index related to the train and the platform in the fault scene.
2. The method for simulating and evaluating the passenger flow distribution under the rail transit fault as claimed in claim 1, wherein the specific process of calculating the passenger flow space-time distribution index in the step 2 is as follows:
1) waiting for the vehicle: explicitly waiting for a set of passengers and a set of passengers leaving because the maximum waiting time is exceeded; considering newly inbound passengers and passengers left for riding in a preceding car; for a small-traffic-road turn-back station, if a train in front of the small-traffic-road turn-back station turns back in advance, the condition that a passenger getting off in advance enters into waiting or leaves is also considered, an attribute of getting off in advance is added to the passenger, the passenger is considered as a new 'station-entering moment', waiting or leaving is judged according to the maximum waiting time as the same as the first two classes of passengers, wherein the maximum waiting time is set as Dg；
2) The getting-on process: determining the number of available passengers based on the remaining capacity of the train and the number of waiting passengers, and if the number of available passengers is equal to the number of waiting passengers, enabling all waiting passengers to be available for getting on the train; if the number of passengers getting on the train is equal to the remaining capacity of the train, the passengers get on the train in the principle of first-come first-serve until a certain group of passengers cannot get on the train completely, and at the moment, the passengers at different destinations in the group are considered to get on the train in proportion, so that the passenger collection getting on the train, the passenger collection left to take the train and the passenger collection in the train are calculated in an accumulated mode;
3) the getting-off process comprises the following steps: and defining a set of passengers getting off, determining the passengers getting off at the station in advance according to the destination of the passengers and the starting event of the station, and distinguishing the conditions of all the passengers getting off at the turn-back station of the small traffic road.
3. The method as claimed in claim 2, wherein the maximum waiting time D is a maximum waiting timegThe value of the time interval is set under the condition that most passengers are willing to wait more due to longer trip time in a trip habit or other modes under the condition of considering faults, and is more than or equal to two planned driving intervals;
the calculation of the remaining train capacity is to distinguish whether the current starting event is an initiating event, if so, the train has complete train capacity; otherwise, subtracting the number of the passengers on the train when the train departs from the previous station and the number of the passengers getting off the train at the current station from the capacity of the train; the number of the passengers on the train when the train departs comprises the number of the passengers on the train at the station, and the number of the passengers on the train when the train departs from the previous station is added to the non-starting event, and the number of the passengers off the train when the train arrives at the station is subtracted.
4. The method as claimed in claim 1, wherein the passenger flow distribution index and the passenger travel time index in step 3 include:
1) the train full load rate: the number of people in each space-time position compartment can be known through the passenger set in the train corresponding to each departure event, and the space-time full load rate of each train is calculated by combining the train passenger deciding capacity;
2) station congestion situation: analyzing the distribution and evolution characteristics of passengers staying and waiting for passengers, calculating the occurrence rate of all-line passengers staying, and measuring the station congestion by combining the station capacity;
3) passenger exit condition: analyzing the number and distribution characteristics of passengers leaving the train, and checking the overall adaptation condition of the train service and the passenger flow demand;
4) passenger waiting time: the method comprises the time for waiting for getting on the train at a starting station and the time for waiting for the next shift of the train after being forced to get off in advance at a small traffic route return station; in the case of temporary adjustment to the folding back of the minor traffic route, the latter belongs to increased waiting time, so that a penalty coefficient larger than 1 is multiplied, and the waiting time before the passengers leave is also counted;
5) travel time of the passenger: including waiting time and ride time, and also considering both being serviced and not being serviced by departure, for a departing passenger, consider its subsequent departure time to increase, i.e., equal to the planned ride time multiplied by a penalty factor greater than 1.
5. The method as claimed in claim 4, wherein in the step 2, the getting-on/off attributes of each passenger group are recorded during simulation of the interaction process between the passenger flow and the train, including the getting-on time at the start station, the getting-off time at the transfer station, the getting-on time at the transfer station, and the getting-off time at the end station, so that the waiting time and the riding time of the passengers associated with each train departure event are calculated in the step 3, and the total waiting time and the total riding time of the passengers are calculated.
6. A passenger flow distribution simulation evaluation system under rail transit fault is characterized by comprising:
and a standard passenger flow volume calculation module: the system is used for obtaining the standard passenger flow volume of each space-time granularity of a certain characteristic day according to the statistical analysis of historical passenger flow data of a plurality of same characteristic days under normal operation conditions;
an adjustment operation diagram calculation module: the adjustment operation diagram data is used for generating a fit plan operation diagram according to the fault information and the scheduling strategy;
the passenger flow and train interaction process modeling and simulation module comprises: the passenger flow distribution index calculation method is used for constructing a passenger flow distribution index calculation method according to the interaction state of platform passenger flow and the train operation process, loading standard passenger flow and adjusting operation diagram data, and calculating a passenger flow space-time distribution result through dynamic simulation in combination with the train capacity limit;
a passenger service level assessment module: and the passenger travel service level evaluation system is used for comparing the normal scene and evaluating the passenger travel service level index in the fault scene according to the passenger flow space-time distribution calculation result.
7. The system as claimed in claim 6, wherein the normal operation is performed by the systemUnder the condition, a plurality of days with the same characteristics refer to weeks with the same practical meaning in a period of time without abnormal events; each space-time granularity refers to each OD group s and unit time t, and the corresponding standard passenger flow is expressed as
The calculation formula is as follows:
wherein Dx is a set of normal days,
for calculating the function, a clustering algorithm is adopted; when the fault date and the national holiday have been eliminated, an averaging method can be adopted.
8. The system for the simulation evaluation of the passenger flow distribution under the rail transit fault as claimed in claim 6, wherein the fault information comprises fault time, location, reason and estimated fault duration; and the dispatching strategy is confirmed according to the fault information, a station stopping time and interval running time adjusting strategy is adopted for slight faults, and a corresponding intersection and interval adjusting strategy is searched from the emergency plan for serious faults.
9. The passenger flow distribution simulation evaluation system under the rail transit fault according to claim 6, wherein the interaction state of the platform passenger flow and the train running process is divided into an waiting process, an getting-on process and a getting-off process; the passenger flow distribution indexes comprise the number of waiting persons, the number of leaving persons, the number of getting-on persons, the number of remaining persons, the number of getting-on persons and the number of getting-off persons corresponding to each train at each station.
10. The system of claim 6, wherein the passenger service level indicators include train occupancy, platform congestion, passenger departure, passenger waiting time, and passenger travel time.
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