CN114065611A - In-station passenger evacuation method and device suitable for urban rail transit - Google Patents
In-station passenger evacuation method and device suitable for urban rail transit Download PDFInfo
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Abstract
The embodiment of the disclosure provides an in-station passenger evacuation method and device suitable for urban rail transit. The method comprises the steps of obtaining emergency evacuation factors; inputting the emergency evacuation factor into a pre-trained target passenger evacuation model to obtain a passenger evacuation scheme; evacuating passengers in the station according to the passenger evacuation scheme; wherein the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the stations, and central emergency instructions of the urban rail transit. In this way, can be when the emergency situation appears can be intelligent and in time guide the passenger to evacuate, avoid when the emergency situation appears, can't in time provide sparse guide for the passenger and lead to the unable quick evacuation of passenger.
Description
Technical Field
The present disclosure relates to the field of vehicle technology, and in particular to the field of urban rail transit technology.
Background
Since urban rail transit brings great convenience to users, urban rail transit is introduced into many cities or the number of urban rail transit is increased, but emergency treatment of urban rail transit is still insufficient.
Disclosure of Invention
The present disclosure provides an in-station passenger evacuation method, apparatus, device, and storage medium suitable for urban rail transit.
According to a first aspect of the present disclosure, an in-station passenger evacuation method suitable for urban rail transit is provided. The method comprises the following steps:
acquiring emergency evacuation factors;
inputting the emergency evacuation factor into a pre-trained target passenger evacuation model to obtain a passenger evacuation scheme;
evacuating passengers in the station according to the passenger evacuation scheme; wherein,
the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the station, and central emergency instructions of the urban rail transit.
The above-mentioned aspects and any possible implementation further provide an implementation, and the emergency evacuation factor further includes:
system equipment information of the urban rail transit; and/or the presence of a gas in the gas,
passenger information.
The above aspect and any possible implementation further provide an implementation that evacuates the on-board passengers according to the passenger evacuation scheme, including:
according to the passenger evacuation scheme, at least one of the following controls is carried out on the urban rail transit and/or the station so as to evacuate passengers in the station:
controlling a vertical ladder in the station;
controlling the escalator in the station;
controlling an AFC system within the station;
controlling a PIS system in the station;
starting a standby battery of the urban rail transit;
controlling a ventilation system of the urban rail transit;
and controlling the operation scheduling scheme of the urban rail transit.
The above-described aspects and any possible implementations further provide an implementation, the method further comprising:
generating a power decision according to the emergency evacuation factor;
inputting the power decision to the target passenger evacuation model.
The above-described aspects and any possible implementations further provide an implementation, the method further comprising:
inputting the emergency evacuation factor into an initial passenger evacuation model to obtain a current evacuation scheme;
and adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme to obtain the target passenger evacuation model.
The above-described aspects and any possible implementations further provide an implementation, the method further comprising:
calculating the density of regional passenger flow according to the emergency evacuation factors; the regional passenger flow density comprises: the passenger flow density of the indoor area and/or the passenger flow density of the indoor area of the carriage;
and calculating the passenger evacuation time corresponding to the current evacuation scheme according to the regional passenger flow density.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where the evacuation time of the passenger corresponding to the current evacuation scheme includes at least one of:
the passenger evacuation time required for the passengers to evacuate upwards in the station;
the passenger evacuation time required for the passengers in the station to evacuate by using the elevator;
the passenger evacuation time required for the evacuation of passengers at the flat floor;
passenger evacuation time required for the in-station passenger evacuation using the urban rail transit to the station.
The above-mentioned aspect and any possible implementation manner further provide an implementation manner, where the adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme to obtain the target passenger evacuation model includes:
and adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme and the evacuation exit information in the station to obtain the target passenger evacuation model.
According to a second aspect of the present disclosure, there is provided an in-station passenger evacuation device suitable for urban rail transit, comprising:
the first acquisition module is used for acquiring emergency evacuation factors;
the second acquisition module is used for inputting the emergency evacuation factor into a pre-trained target passenger evacuation model to obtain a passenger evacuation scheme;
the evacuation module is used for evacuating passengers in the station according to the passenger evacuation scheme; wherein,
the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the station, and central emergency instructions of the urban rail transit.
According to a third aspect of the present disclosure, an electronic device is provided. The electronic device includes: a memory having a computer program stored thereon and a processor implementing the method as described above when executing the program.
According to a fourth aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method as according to the first and/or second aspects of the present disclosure.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become readily apparent from the following description.
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The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. The accompanying drawings, which are included to provide a further understanding of the present disclosure and are incorporated in and constitute a part of this disclosure, illustrate embodiment(s) of the disclosure and together with the description serve to explain the principles of the disclosure:
fig. 1 shows a flow chart of an on-station passenger dispersion method suitable for urban rail transit according to an embodiment of the present disclosure;
fig. 2 shows a block diagram of an in-station passenger evacuation system suitable for urban rail transit, in accordance with an embodiment of the present disclosure;
fig. 3 illustrates a block diagram of another in-station passenger evacuation system suitable for urban rail transit in accordance with an embodiment of the present disclosure;
fig. 4 illustrates a station model diagram of urban rail transit according to an embodiment of the present disclosure;
fig. 5 shows a distribution diagram of a station area of urban rail transit according to an embodiment of the present disclosure;
fig. 6 shows a block diagram of yet another in-station passenger evacuation system suitable for urban rail transit, in accordance with an embodiment of the present disclosure;
fig. 7 shows a schematic diagram of a calculation principle of passenger evacuation time corresponding to a current evacuation scenario according to an embodiment of the present disclosure;
FIG. 8 shows a block diagram of an in-station passenger dispersion device suitable for urban rail transit, in accordance with an embodiment of the present disclosure;
FIG. 9 illustrates a block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
In addition, the term "and/or" herein is merely an association relationship describing an associated object, and means that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
In this disclosure, through in inputing emergent evacuation factor to the sparse model of target passenger who has trained, can obtain accurate passenger evacuation scheme to intelligence and guide the passenger in time to evacuate, avoid when the emergency situation appears, can't in time provide evacuation guide for the passenger and lead to the passenger can't evacuate fast.
Fig. 1 shows a flow chart of an in-station passenger evacuation method 100 suitable for urban rail transit according to an embodiment of the disclosure. The urban rail transit can be subway, high-speed rail, light rail and the like.
As shown in fig. 1, the method 100 includes:
the target passenger evacuation model may be a deep learning model, such as a Convolutional Neural Network (CNN), and the target CNN model is obtained as the target passenger evacuation model through training of the initial CNN model.
The passenger evacuation scheme can be that the PIS system in the control station is opened, the gate of the card swiping exit in the station is opened, the vertical elevator is controlled to normally operate, and the passenger evacuation path of each region is given (taking the example that the passenger evacuation path of the region 4 shown in fig. 3 is moved from the region 4 to the region 6 and then rides the vertical elevator to two floors, and then leaves from the exit A and the exit C respectively), the passenger evacuation path can be displayed and broadcasted through the PIS system, and meanwhile, the vertical elevator between the first floor and the second floor is controlled to normally operate and the card swiping gates corresponding to the exit A and the exit C are opened, so that passengers in the region 4 on one floor can be rapidly evacuated in the station.
the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the station, and central emergency instructions of the urban rail transit.
Through inputting emergent evacuation factor to the target passenger evacuation model that has trained, can obtain accurate passenger evacuation scheme, then utilize this passenger evacuation scheme to control urban rail transit and/or in-station equipment to can intelligently and in time guide the passenger to evacuate when emergency situation appears, avoid when emergency situation appears, can't in time provide evacuation guide for the passenger and lead to the unable quick evacuation of passenger.
The central emergency command may be a command to halt a station, a fire alarm command, a warning command to encounter heavy water, etc.
In some embodiments, the emergency evacuation factor further comprises:
system equipment information of the urban rail transit; and/or the presence of a gas in the gas,
passenger information.
The system device information includes, but is not limited to, what, how, the location of the operational devices are, whether the operational devices are malfunctioning, etc. within the station.
The passenger information includes, but is not limited to, passenger location, passenger number, passenger type, passenger distribution area, area of the area where the passenger is located, and the like, wherein the passenger type includes passenger age, gender, and the like, and the passenger may be an on-station passenger, and may also include a passenger on urban rail transit.
The accuracy of the passenger evacuation scheme output by the target passenger evacuation model can be improved by enriching emergency evacuation factors, so that passengers are more accurately and rapidly evacuated, and the evacuation timeliness of the passengers is improved.
In some embodiments, said evacuating said on-board passengers according to said passenger evacuation plan comprises:
according to the passenger evacuation scheme, at least one of the following controls is carried out on the urban rail transit and/or the station so as to evacuate passengers in the station:
controlling a vertical ladder in the station;
controlling the escalator in the station;
controlling an AFC system within the station; an AFC System (Automatic Fare Collection System), which is an Automatic ticket selling and checking System for urban rail transit, is a gate in a station.
Controlling a PIS system in the station; the PIS System (Passenger Information System) is a display System in a station, and devices capable of seeing screens in the station are all attached to the PIS System and used for prompting Passenger evacuation paths in a text mode, an audio mode and the like, namely the PIS System in the station is controlled to be used for controlling and prompting the Passenger evacuation paths.
Starting a standby battery of the urban rail transit;
controlling a ventilation system of the urban rail transit;
and controlling the operation scheduling scheme of the urban rail transit. The operation scheduling scheme is used for controlling whether the urban rail transit stops at the station or not and whether the urban rail transit carries people or not, adjusting departure time and the like. One or more items of intelligent control can be carried out on the urban rail transit and/or the in-station system/equipment according to the passenger dispersion scheme, so that timely evacuation of passengers in the station is realized through various coordination and flexible scheduling.
Among these, it is to be emphasized: whether urban rail transit or in-station control or both control is in practice carried out, and whether one or more controls are carried out, depends on the content of the passenger evacuation plan. The contents of the passenger evacuation plan include one or more of the control commands and the passenger evacuation path, and some necessary prompts (such as some equipment or system failure).
In some embodiments, the method further comprises:
generating a power decision according to the emergency evacuation factor;
the power decision may be used to indicate whether the backup battery is normal, whether to enable the backup battery within the station, whether to enable the backup battery on urban rail transit, when to enable, how long to enable, etc.
And generating an electric power influence decision accurately according to whether the emergency evacuation factor is related to the electric power or not and whether the electric power utilization in the station and/or the urban rail transit is influenced. For example: the emergency evacuation factor is that the central emergency command is that the power failure occurs in several minutes in the station, and then in order not to influence the normal work in the station, a power decision for starting a standby battery in the station for a plurality of times is generated in several minutes; another example is: the emergency evacuation factor is that the urban rail transit suffers from the influence of fire so that a part of an original power system is paralyzed, and in order to ensure the normal operation of the urban rail transit and avoid influencing passengers, a power decision for starting a backup battery of the urban rail transit is generated until the original power system is recovered to be normally used.
Inputting the power decision to the target passenger evacuation model.
According to the emergency evacuation factors, the power decision can be automatically generated and then automatically input to the target passenger evacuation model, so that when the target passenger evacuation model generates the passenger evacuation scheme, the power decision is combined with the emergency evacuation factors, and the accuracy of the passenger evacuation scheme is improved.
Before the power decision is input into the target passenger evacuation model, the power utilization in the default station of the target passenger evacuation model and the urban rail transit is normal, and the output passenger evacuation scheme comprises control instructions for various power utilization systems and/or equipment; after the power decision is input into the target passenger evacuation model, the target passenger evacuation model can further determine whether the current power consumption of the station and the urban rail transit is normal, whether the standby battery is used and how long the standby battery can supply power if the standby battery is used, and the input factors of the target passenger evacuation model are enriched, so that the output passenger evacuation scheme is more accurate. For example: the target passenger evacuation model can determine whether the standby battery is abnormal or not, so that the output passenger evacuation scheme does not contain opening instructions for the PIS system and the gate but contains information for prompting the PIS system and the gate to be abnormal when the standby battery is abnormal, so that staff in the station can prompt the evacuation path of the passengers and open the gate manually in time, and the passengers are ensured to be evacuated in time.
In some embodiments, the method further comprises:
inputting the emergency evacuation factor into an initial passenger evacuation model to obtain a current evacuation scheme;
and adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme to obtain the target passenger evacuation model.
The method comprises the steps of inputting emergency evacuation factors into an initial passenger evacuation model to obtain a current evacuation scheme, then intelligently adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme, such as adjusting internal personnel distribution weight and the like, and adjusting coefficients in a passenger flow density calculation formula and a speed calculation formula, so as to ensure that the passenger evacuation time corresponding to the evacuation scheme output by the model is shortest, and taking the model as a target passenger evacuation model.
In addition, when the initial passenger evacuation model is adjusted according to the passenger evacuation time corresponding to the current evacuation scheme, the initial passenger evacuation model can be continuously adjusted according to the passenger evacuation time corresponding to the current evacuation scheme and the preset shortest passenger evacuation time; or
The passenger evacuation time corresponding to the current evacuation scheme can be compared with the passenger evacuation time corresponding to other possible evacuation schemes to judge whether the passenger evacuation time corresponding to the current evacuation scheme is the current evacuation scheme with the shortest time, and if the passenger evacuation time corresponding to the current evacuation scheme is not the current evacuation scheme with the shortest time, the initial passenger evacuation model is adjusted according to the time difference; or
The passenger evacuation time corresponding to the current evacuation scheme is the theoretical passenger evacuation time, so that the real evacuation time corresponding to the current evacuation scheme can be counted and compared, and if the real evacuation time is inconsistent with the real evacuation time, the initial passenger evacuation model is adjusted according to the time difference; or
And determining whether to continue to iteratively adjust the initial passenger evacuation model according to whether the current adjustment times reach preset times.
In some embodiments, the method further comprises:
calculating the density of regional passenger flow according to the emergency evacuation factors; the regional passenger flow density comprises: the passenger flow density of the indoor area and/or the passenger flow density of the indoor area of the carriage;
and calculating the passenger evacuation time corresponding to the current evacuation scheme according to the regional passenger flow density.
When the passengers are evacuated, the passenger evacuation time can be automatically and intelligently calculated by combining the distance, the speed formula and the like of the passengers moving from the positions to the specified positions in addition to the regional passenger flow density, so that the accuracy of the passenger evacuation time is ensured.
The principle of calculating the density of regional passenger flow is as follows:
the passenger flow density of the in-station area can be calculated according to the number of passengers in the in-station area and the area of the in-station area of the passengers;
the passenger flow density of the area in the carriage can be calculated according to the number of passengers in the carriage and the area of the carriage where the passengers are. In some embodiments, the evacuation time of the passengers corresponding to the current evacuation plan includes at least one of:
the passenger evacuation time required for the passengers to evacuate upwards in the station; the passengers in the station are evacuated upwards, and the passengers in the station are evacuated from the lower layer to the upper layer by using a straight ladder, an escalator or a step ladder.
The passenger evacuation time required for the passengers in the station to evacuate by using the elevator; the evacuation of passengers in the station by using the elevator can be the evacuation of passengers in the station by using a straight ladder and/or the evacuation of passengers in the station by using a staircase.
The passenger evacuation time required for the evacuation of passengers at the flat floor;
passenger evacuation time required for the in-station passenger evacuation using the urban rail transit to the station.
The passenger evacuation time corresponding to the current evacuation scheme includes, but is not limited to, one or more of the above-mentioned passenger evacuation times of different schemes, and when multiple schemes are included, the passenger evacuation time corresponding to the current evacuation scheme is the sum of the passenger evacuation times of the multiple schemes or the longest passenger evacuation time in the passenger evacuation times of the multiple schemes, that is, the sum of the passenger evacuation times required by passengers in the station to evacuate by using different evacuation schemes or the longest passenger evacuation time in the passenger evacuation times of the multiple schemes, so as to ensure that the counted passenger evacuation time corresponding to the current evacuation scheme is accurate no matter there is one or more sub-schemes in the current evacuation scheme. For example: a, B, C areas are arranged on a certain floor in a station, the current evacuation scheme is that passengers in the area A evacuate by adopting a plane layer, passengers in the area B evacuate by adopting a straight ladder, and passengers in the area C evacuate by adopting a step ladder, so that the passenger evacuation time corresponding to the current evacuation scheme is the sum of the passenger evacuation time required by the passengers in the area A evacuating by adopting the plane layer, the passenger evacuation time required by the passengers in the area B evacuating by adopting the straight ladder and the passenger evacuation time required by the passengers in the area C evacuating by adopting the step ladder, or the longest passenger evacuation time in the area A, the area B and the area C.
Of course, the current evacuation scenario output by the model may also indicate that different passengers located in the same area employ different evacuation scenarios.
In some embodiments, the adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation plan to obtain the target passenger evacuation model includes:
and adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme and the evacuation exit information in the station to obtain the target passenger evacuation model.
The initial passenger evacuation model can be intelligently and accurately adjusted by combining the passenger evacuation time corresponding to the current evacuation scheme and the evacuation exit information in the station, so that the target passenger evacuation model can be self-adaptive to different stations and is not limited to being only suitable for one type of station, and the evacuation scheme for evacuating passengers at the fastest speed can be always output no matter how many exits and positions of the stations are.
The evacuation exit information may be the location, number, etc. of the station exits.
The technical solution of the present disclosure will be further explained in detail with reference to fig. 2 to 7:
as shown in fig. 2, the overall system architecture of the station passenger evacuation scheme in the emergency state is divided into three layers. The system comprises an input layer, an algorithm layer and an output layer. An input layer, which takes the emergency evacuation command, the line vehicle-mounted equipment fault, the signal system fault sent by the center, and other data such as the inelegability according to the natural disaster such as the weather condition, and the fire, the human factor caused by the system fault as the input, and inputs the input into an emergency evacuation algorithm (target passenger evacuation model), as shown in fig. 3; the algorithm layer adopts a deep learning method, station personnel are randomly used as input, evaluation scores are input into the algorithm layer and station division algorithm, the fastest evacuation mode of passengers in the shortest time is used as a target, optimal algorithm parameters are obtained, and an algorithm model is continuously optimized. And (3) outputting an analysis suggestion obtained by the algorithm model to each system of the station, and dynamically adjusting the state of the system equipment through a specified system linkage scheme to enable passengers to evacuate the station most quickly as shown in figure 3.
Among these, the factors of the input layer in fig. 2 and 3 can be refined as:
1. internal and external factors influencing passenger evacuation in emergency state
1.1 external factors that generate an emergency condition:
(1) natural disasters such as fire, flood, snow storm, epidemic situation, etc.;
(2) under the condition of human beings, dangerous articles such as fire, toxic and harmful substances and the like in the station are released to harm the waiting safety in the passenger station.
1.2 internal factors that generate an emergency situation:
(1) the conditions of failure of basic equipment in the station, smoke release, fire hazard and the like are met;
(2) and the carrying function of the train at the station fails to evacuate personnel in the station.
2. Factors affecting evacuation within a passenger station:
2.1 internal factors affecting evacuation in passenger stations
(1) Design factors of infrastructure type in the station;
(2) system state factors of operating basic equipment in the station and system linkage among systems;
(3) the type of the emergency and the location factor of the emergency;
(4) the number of people in each area of the station.
2.2 external factors influencing evacuation in passenger stations
(1) Station operation time interval and station form under emergency state
(2) Location of train
(3) Device states of other system devices of station electric power system
Further, the system framework of fig. 2 and 3 may be applied to a standard station model as shown in fig. 4 and 5, which sets up three exits of ABC, and the station has uplink and downlink vehicle travel lines, which may be used as an evacuation exit. Meanwhile, an emergency mode controller can be added at the front end of the algorithm by combining the emergency state type (namely emergency evacuation factors) of the station, and data and output variables are controlled as shown in fig. 6. Finally, the passengers can safely evacuate according to the own positions by adopting a nearby principle and a dynamic indication mark above the screen. Specifically, evacuation is performed according to a fixed evacuation plan set up as indicated by the numbered zones (1,2,3,4,5,6,7,8,9,10) in fig. 5.
The emergency state controller in fig. 6 is used for inputting a power indication into the algorithm model according to the power influence decision (output according to the emergency state type), so that the algorithm model outputs a passenger evacuation scheme by combining the power indication and the emergency type (emergency evacuation factor of the input floor in fig. 2), and thus, the PIS system, the AFC system, the escalator and the like are intelligently controlled, and passengers in the station can be evacuated at the fastest speed.
For example: if the disaster is an external irresistible natural disaster, the straight ladder is directly controlled to stop running; the power impact decision may be that the power terminal system starts a backup power supply, and if the backup power supply fails, the whole power system fails and is broken down.
Another example is: the operation scheduling scheme can be adjusted according to natural disasters, vehicle system faults, human hazard safety, center emergency prompts and equipment faults, and is sent to a large subway management center to control whether a subway arrives at a station and stops or carries people or not, adjust the departure time of the subway and the like.
Another example is:
in a general emergency state, an AFC system (automatic fare collection system), a PIS system (passenger information system) and a ventilation system are controlled to be automatically started, and the AFC system is automatically started. Of course, it is also possible to control the AFC system to turn off if a fighting situation occurs at the outbound port.
Of course, the calculation principle of the passenger evacuation time corresponding to the current evacuation scheme may be as shown in fig. 7, and the passenger evacuation time corresponding to the current evacuation scheme may be any time output in fig. 7, or the sum of any two or three times output in fig. 7, or the longest time among the multiple times output in fig. 7, wherein the emergency state may determine which time algorithm in fig. 7 is used, that is, which time in fig. 7 is output, so as to perform intelligent adjustment on the passenger evacuation model according to the passenger evacuation time.
The calculation principle of the area density and the speed in fig. 7 is as follows:
generally, the passenger occupies an area of about 0.28 square meter per capita during evacuation, and when the passenger occupies an area of 0.25 square meter per capita, the passengers push each other closely in front of and behind the human body. All must be controlled to occupy an area of 0.28 square meters. When the distance between the passenger and the passenger is more than 1.5 square meters, the moving speed of the pedestrian is not limited, if the distance is less than 1.5 meters, the speed is rapidly reduced, and when the distance is reduced to 0.3 meters, the speed is reduced to 0.
(1) Passenger density is D is passenger flow density, M is number of people, S is area:
D＝M/S
(2) through station practical observation, the average moving speed is VL, D is the people flow density, and the moving speed on the straight passage is:
v1＝0.005 7D++0.074 4D3-0.274 5D2
-0.014 2D+1.567
(3) moving up the stairs, D is the density of the human stream, and the speed of moving Vu up is as follows:
vv＝-0.221D+0.939。
of course, when adjusting the passenger evacuation model, the coefficients in the velocity formula can also be adjusted, and the actual situation is more complicated, such as: it may also be desirable to adjust the maximum number of passengers corresponding to each region in the passenger evacuation model, adjust the population ratio coefficient for each region in the passenger evacuation model using different evacuation schemes, and so on.
Through the technical scheme shown in fig. 2 to 7, the emergency state (namely, emergency evacuation factors), the emergency state position, the number of people and the like can be used as the input of the passenger evacuation model, and the algorithm model is optimized by taking the minimum output time as the judgment basis, so that the fastest passenger evacuation scheme can be provided for passengers in the emergency state, and the operation safety of a station is ensured.
It should be noted that for simplicity of description, the above-mentioned method embodiments are described as a series of acts or combination of acts, but those skilled in the art will recognize that the present disclosure is not limited by the order of acts, as some steps may occur in other orders or concurrently in accordance with the disclosure. Further, those skilled in the art should also appreciate that the embodiments described in the specification are exemplary embodiments and that the acts and modules referred to are not necessarily required for the disclosure.
The above is a description of embodiments of the method, and the following is a further description of the embodiments of the apparatus.
Fig. 8 shows a block diagram of an on-board passenger dispersion device 800 suitable for urban rail transit, according to an embodiment of the present disclosure. As shown in fig. 8, the apparatus 800 includes:
a first obtaining module 810, configured to obtain an emergency evacuation factor;
a second obtaining module 820, configured to input the emergency evacuation factor into a pre-trained target passenger evacuation model, so as to obtain a passenger evacuation scheme;
an evacuation module 830, configured to evacuate passengers in the station according to the passenger evacuation scheme; wherein,
the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the stations, and central emergency instructions of the urban rail transit.
It can be clearly understood by those skilled in the art that, for convenience and brevity of description, the specific working process of the described module may refer to the corresponding process in the foregoing method embodiment, and is not described herein again.
The present disclosure also provides an electronic device and a non-transitory computer-readable storage medium according to an embodiment of the present disclosure.
FIG. 9 illustrates a schematic block diagram of an electronic device 900 that may be used to implement embodiments of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not intended to limit implementations of the disclosure described and/or claimed herein.
The apparatus 900 includes a computing unit 901, which can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)902 or a computer program loaded from a storage unit 909 into a Random Access Memory (RAM) 903. In the RAM 903, various programs and data required for the operation of the device 900 can also be stored. The calculation unit 901, ROM 902, and RAM 903 are connected to each other via a bus 904. An input/output (I/O) interface 905 is also connected to bus 904.
A number of components in the device 900 are connected to the I/O interface 905, including: an input unit 906 such as a keyboard, a mouse, and the like; an output unit 907 such as various types of displays, speakers, and the like; a storage unit 908 such as a magnetic disk, optical disk, or the like; and a communication unit 909 such as a network card, a modem, a wireless communication transceiver, and the like. The communication unit 909 allows the device 900 to exchange information/data with other devices through a computer network such as the internet and/or various telecommunication networks.
The computing unit 901 may be a variety of general and/or special purpose processing components having processing and computing capabilities. Some examples of the computing unit 901 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and so forth. The computing unit 901 performs the respective methods and processes described above, such as the method 100. For example, in some embodiments, the method 100 may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 908. In some embodiments, part or all of the computer program may be loaded and/or installed onto device 900 via ROM 902 and/or communications unit 909. One or more steps of the method 100 described above may be performed when the computer program is loaded into the RAM 903 and executed by the computing unit 901. Alternatively, in other embodiments, the computing unit 901 may be configured to perform the method 100 in any other suitable manner (e.g., by means of firmware).
Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.
Program code for implementing the methods of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable data processing apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.
In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user may provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.
The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), and the Internet.
The computing system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The server may be a cloud server, a server of a distributed system, or a server combining a blockchain.
It should be understood that various forms of the flows shown above may be used, with steps reordered, added, or deleted. For example, the steps described in the present disclosure may be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in the present disclosure can be achieved, and the present disclosure is not limited herein.
The above detailed description should not be construed as limiting the scope of the disclosure. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions are possible, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present disclosure should be included in the scope of protection of the present disclosure.
Claims (11)
1. An in-station passenger evacuation method suitable for urban rail transit is characterized by comprising the following steps:
acquiring emergency evacuation factors;
inputting the emergency evacuation factor into a pre-trained target passenger evacuation model to obtain a passenger evacuation scheme;
evacuating passengers in the station according to the passenger evacuation scheme; wherein,
the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the stations, and central emergency instructions of the urban rail transit.
2. The method of claim 1,
the emergency evacuation factors further include:
system equipment information of the urban rail transit; and/or the presence of a gas in the gas,
passenger information.
3. The method of claim 1,
the evacuating the passengers in the station according to the passenger evacuating scheme comprises the following steps:
according to the passenger evacuation scheme, at least one of the following controls is carried out on the urban rail transit and/or the station so as to evacuate passengers in the station:
controlling a vertical ladder in the station;
controlling the escalator in the station;
controlling an AFC system within the station;
controlling a PIS system in the station;
starting a standby battery of the urban rail transit;
controlling a ventilation system of the urban rail transit;
and controlling the operation scheduling scheme of the urban rail transit.
4. The method of claim 1, further comprising:
generating a power decision according to the emergency evacuation factor;
inputting the power decision to the target passenger evacuation model.
5. The method according to any one of claims 1 to 4, further comprising:
inputting the emergency evacuation factor into an initial passenger evacuation model to obtain a current evacuation scheme;
and adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme to obtain the target passenger evacuation model.
6. The method of claim 5, further comprising:
calculating the density of regional passenger flow according to the emergency evacuation factors; the regional passenger flow density comprises: the passenger flow density of the indoor area and/or the passenger flow density of the indoor area of the carriage;
and calculating the passenger evacuation time corresponding to the current evacuation scheme according to the regional passenger flow density.
7. The method of claim 6,
the evacuation time of the passengers corresponding to the current evacuation scheme comprises at least one of the following items:
the passenger evacuation time required for the passengers to evacuate upwards in the station;
the passenger evacuation time required for the passengers in the station to evacuate by using the elevator;
the passenger evacuation time required for the evacuation of passengers at the flat floor;
passenger evacuation time required for the in-station passenger evacuation using the urban rail transit to the station.
8. The method of claim 5,
the adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme to obtain the target passenger evacuation model includes:
and adjusting the initial passenger evacuation model according to the passenger evacuation time corresponding to the current evacuation scheme and the evacuation exit information in the station to obtain the target passenger evacuation model.
9. An in-station passenger evacuation device suitable for urban rail transit, comprising:
the first acquisition module is used for acquiring emergency evacuation factors;
the second acquisition module is used for inputting the emergency evacuation factor into a pre-trained target passenger evacuation model to obtain a passenger evacuation scheme;
the evacuation module is used for evacuating passengers in the station according to the passenger evacuation scheme; wherein,
the emergency evacuation factors include: one or more of natural disaster conditions, human events, vehicle faults of the urban rail transit, system equipment faults in the stations, and central emergency instructions of the urban rail transit.
10. An electronic device, comprising:
at least one processor; and
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-8.
11. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-8.
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Cited By (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114715221A (en) * | 2022-05-06 | 2022-07-08 | 上海电气泰雷兹交通自动化系统有限公司 | ZC safety protection method for evacuating passengers when unmanned train opens door abnormally |
| CN114919621A (en) * | 2022-03-14 | 2022-08-19 | 上海工程技术大学 | Bidirectional feedback mechanism-based emergency evacuation guiding method in subway carriage |
| CN115394023A (en) * | 2022-09-14 | 2022-11-25 | 中国铁道科学研究院集团有限公司 | Passenger station emergency evacuation system and emergency evacuation platform |
| CN115709750A (en) * | 2022-09-27 | 2023-02-24 | 卡斯柯信号有限公司 | Passenger evacuation management method and device for TACS system |
| CN117455073A (en) * | 2023-11-22 | 2024-01-26 | 青岛理工大学 | Prediction method for passenger evacuation efficiency in carriage type transportation means under flood scene |
| CN117541083A (en) * | 2024-01-09 | 2024-02-09 | 青岛理工大学 | Evacuation platform evacuation capability prediction method and device |
| CN117575109A (en) * | 2024-01-16 | 2024-02-20 | 青岛理工大学 | Method and device for predicting underground station personnel capacity in flood scene |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103927591A (en) * | 2014-03-24 | 2014-07-16 | 北京交通大学 | Urban rail transit emergency evacuation optimization method and system |
| CN105760966A (en) * | 2016-03-16 | 2016-07-13 | 深圳市嘉泰智能科技有限公司 | Intelligent fire emergency evacuation method and system |
| CN109598076A (en) * | 2018-12-10 | 2019-04-09 | 北京交通大学 | A kind of urban track traffic emergency evacuation analogue system and method |
| CN110737989A (en) * | 2019-10-18 | 2020-01-31 | 中国科学院深圳先进技术研究院 | parallel intelligent emergency cooperation method, system and electronic equipment |
| CN110992233A (en) * | 2019-12-13 | 2020-04-10 | 中国科学院深圳先进技术研究院 | Emergency evacuation method and system for urban gathering event |
| CN111767789A (en) * | 2020-05-13 | 2020-10-13 | 北京交通大学 | Crowd evacuation method and system based on multi-carrier intelligent guidance |
| CN112257896A (en) * | 2020-09-14 | 2021-01-22 | 广州地铁集团有限公司 | Rail transit crowd evacuation method and device based on Internet of things |
-
2021
- 2021-10-26 CN CN202111248188.8A patent/CN114065611A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103927591A (en) * | 2014-03-24 | 2014-07-16 | 北京交通大学 | Urban rail transit emergency evacuation optimization method and system |
| CN105760966A (en) * | 2016-03-16 | 2016-07-13 | 深圳市嘉泰智能科技有限公司 | Intelligent fire emergency evacuation method and system |
| CN109598076A (en) * | 2018-12-10 | 2019-04-09 | 北京交通大学 | A kind of urban track traffic emergency evacuation analogue system and method |
| CN110737989A (en) * | 2019-10-18 | 2020-01-31 | 中国科学院深圳先进技术研究院 | parallel intelligent emergency cooperation method, system and electronic equipment |
| CN110992233A (en) * | 2019-12-13 | 2020-04-10 | 中国科学院深圳先进技术研究院 | Emergency evacuation method and system for urban gathering event |
| CN111767789A (en) * | 2020-05-13 | 2020-10-13 | 北京交通大学 | Crowd evacuation method and system based on multi-carrier intelligent guidance |
| CN112257896A (en) * | 2020-09-14 | 2021-01-22 | 广州地铁集团有限公司 | Rail transit crowd evacuation method and device based on Internet of things |
Non-Patent Citations (1)
| Title |
|---|
| 张越: ""基于ACP方法的城市轨道交通枢纽应急疏散若干问题研究"", 《中国优秀硕士学位论文全文数据库工程科技Ⅱ辑》, no. 2, 15 February 2014 (2014-02-15), pages 033 - 122 * |
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114919621A (en) * | 2022-03-14 | 2022-08-19 | 上海工程技术大学 | Bidirectional feedback mechanism-based emergency evacuation guiding method in subway carriage |
| CN114715221A (en) * | 2022-05-06 | 2022-07-08 | 上海电气泰雷兹交通自动化系统有限公司 | ZC safety protection method for evacuating passengers when unmanned train opens door abnormally |
| CN115394023A (en) * | 2022-09-14 | 2022-11-25 | 中国铁道科学研究院集团有限公司 | Passenger station emergency evacuation system and emergency evacuation platform |
| CN115709750A (en) * | 2022-09-27 | 2023-02-24 | 卡斯柯信号有限公司 | Passenger evacuation management method and device for TACS system |
| CN117455073A (en) * | 2023-11-22 | 2024-01-26 | 青岛理工大学 | Prediction method for passenger evacuation efficiency in carriage type transportation means under flood scene |
| CN117455073B (en) * | 2023-11-22 | 2024-05-10 | 青岛理工大学 | Prediction method for passenger evacuation efficiency in carriage type transportation means under flood scene |
| CN117541083A (en) * | 2024-01-09 | 2024-02-09 | 青岛理工大学 | Evacuation platform evacuation capability prediction method and device |
| CN117541083B (en) * | 2024-01-09 | 2024-05-28 | 青岛理工大学 | Evacuation platform evacuation capability prediction method and device |
| CN117575109A (en) * | 2024-01-16 | 2024-02-20 | 青岛理工大学 | Method and device for predicting underground station personnel capacity in flood scene |
| CN117575109B (en) * | 2024-01-16 | 2024-05-28 | 青岛理工大学 | Method and device for predicting underground station personnel capacity in flood scene |
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