CN115034622A - Public transportation system input and output risk quantitative evaluation method - Google Patents
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Abstract
The invention provides a quantitative evaluation method for input and output risks of a bus system. The invention considers the waiting process and the riding process of passengers in the bus trip process, considers the input and output relation of a community-bus system-community taking bus stops as an import and export link, establishes a bus system input and output risk assessment model, comprehensively considers the influence factors of the input and output risk assessment model, and proposes departure interval and station jumping strategy optimization, thereby being beneficial to reducing the input and output risks of the bus system and ensuring the normal trip of residents and the normal running of cities.
Description
Technical Field
The invention relates to a quantitative evaluation method for input and output risks of a public transport system, which is a method for establishing a 'community-public transport system-community' input and output relationship by using passenger card swiping data, bus geographic information data and bus station and line data and taking bus stations as import and export links to describe and evaluate the input and output risks of the public transport system.
Background
Emergency management and disposal capabilities for public health events are extremely important. The research on the public transportation system transmission and the infection risk is an important premise and basis for ensuring the normal travel of residents, maintaining the normal operation of transportation infrastructure and ensuring the normal operation of cities.
The current research on the public transportation system transmission and infection risk mainly focuses on two aspects: the method comprises the following steps of firstly, researching based on bus operation strategy optimization; and secondly, research based on the propagation tracking of the public transportation system. 1. The research based on the bus operation strategy mainly aims at: the method has the advantages that the supply and demand of the public transport, social economy and propagation prevention and control are balanced, the factors of the prevention and control strategy assignment needing to be additionally considered are analyzed, various strategy optimization models and methods are provided based on the factors, theoretical support is provided for the prevention and control strategy optimization, most of researches are considered by taking the public transport line as a unit, and a key propagation link of a public transport station is ignored in many researches; 2. the propagation tracking based on the public transportation system mainly focuses on: based on space-time big data and an artificial intelligence technology, the space-time rules and the relation maps of residents are excavated, the infection characteristics of infectious diseases are combined, the individual infection risk probability and other aspects are calculated, the overlapping of the passengers and the space-time tracks of the infected persons in the bus trip process is researched, and the dynamic reconfiguration of the relation network caused by the dynamic space-time characteristics and the individual space-time behaviors of the passengers in the bus trip process is not considered. In addition, the current research ignores that in actual situations, the states of passengers entering and exiting the public transportation system are unknown, and according to the current strategy means of body temperature measurement, green-code-holding riding and the like, the passengers entering the public transportation system are in a healthy state by default, so that how to effectively make a public transportation management strategy under the condition of unknown infected persons is one of the problems to be solved urgently.
The existing research on the public transport system transmission and infection risk obtains certain effect, but has the following problems:
1. a key propagation link of ignoring bus stops
The bus trip process of the passenger mainly comprises two stages: a riding stage and a waiting stage. The existing research mainly focuses on the infection risk of passengers in the process of taking a car and ignores the infection risk of passengers in the process of waiting for the car.
2. Ignoring relationships between public transportation systems and surrounding community risks
The existing research mainly focuses on infection risk transmission in the public transportation system caused by the passenger riding process, and ignores the input-output relationship between the public transportation system and the surrounding community.
3. Neglecting the fact that the passengers entering the public transportation system are all in a healthy state by default
When the existing research is used for making public transport management strategies (such as optimizing departure intervals, station jumping and the like), the premise needs to assume that infected persons (generally 1 infected case) exist in a public transport system, the existing research is ignored, the states of passengers entering and leaving the public transport system are unknown in the actual situation, and the passengers entering the public transport system are in a healthy state by default according to the existing strategy means of measuring body temperature, holding green codes for taking a bus and the like.
Disclosure of Invention
The invention aims to provide an input and output risk assessment method for a public transport system, which provides a new idea for infection risk assessment, prevention and control and emergency response mechanisms of the public transport system under sudden public health events.
The present invention is first proposed in the field of the invention,
1. by referring to the input and output risk concepts of country-country, province-province and region-region, the input and output relation of community-public transport system-community taking bus stops as import and export links is proposed;
2. the concept of input and output risks of the public transport system is put forward; wherein, the input risk refers to the possibility that the passengers getting on the bus are infected to enter the public transportation system, and describes the influence degree of different bus stations on the whole public transportation system; the output risk refers to the possibility that the getting-off passenger is infected and affects the communities around the getting-off passenger, and is used for evaluating the risk of each bus stop on the surrounding communities;
3. establishing a community-public transport system-community input and output relationship by taking a public transport station as an import and export link, and establishing a public transport system input and output risk evaluation model; wherein, the input risk is embodied by: the personal risk carried by passengers getting on the bus from a bus stop after waiting for the bus is mainly related to factors such as stop requirements, departure intervals, passenger arrival rates and the like; the output risk is embodied by: the passenger waiting process and the passenger taking process are carried by the passengers getting off the bus from the bus station, and the output risk consists of an input risk and a riding risk output risk; besides the influence factors of the input risk, the output risk is mainly related to the passenger origin-destination point, the station demand, the bus travel time and other factors.
The technical scheme adopted by the invention for solving the technical problem is that,
a quantitative evaluation method for input and output risks of a bus system is based on passenger OD data and bus GPS data and evaluates the input and output risks of the bus system through the following procedures: the method comprises the following steps of obtaining OD data and bus travel time data of passengers according to card swiping data, bus GPS data and bus station and line data of the passengers, establishing an input and output risk assessment model based on the data and in combination with a bus trip process of the passengers, and calculating input and output risks of a bus system at different time periods, wherein the method comprises the following specific steps:
1) according to the obtained data, passenger OD data and travel time data of the bus at each station are constructed;
2) based on the definition of the input and output risks of the public transport system, the input and output risks are associated with the traveling process (including the waiting process and the riding process) of passengers;
3) establishing the accumulated contact time of each passenger with other passengers in the waiting process according to the random arrival assumption of the passengers in the waiting process, and taking the accumulated contact time of the passengers getting on the bus as an input risk at the moment that the bus arrives at a bus stop;
4) according to the passenger OD data and the travel time data of the bus, establishing the accumulated contact time of each passenger with other passengers in the bus taking process, and combining the input risks, wherein the accumulated contact time of the passengers of the bus at the time when the bus arrives at the bus stop is used as the output risk;
5) and optimizing the bus dispatching strategy according to the input and output risks evaluated by each station of the bus system by combining the established input and output risk model.
In the above technical solution, further, based on the obtained passenger card swiping data, bus GPS data, and bus station and line data in step 1), the obtained data is subjected to data processing and matching to obtain bus IC card passenger boarding station data including a card number, a card swiping date, a card swiping time, a line number, a bus arrival time, a boarding station number/name, and station longitude and latitude; the passenger transfer behavior can be identified through the data, meanwhile, the passenger can be subjected to getting-off station calculation based on a trip chain, and finally, passenger OD identification is realized; this can be determined by existing methods such as probabilistic models, Markov chain methods, iterative proportional fitting methods, etc.
Further, the input risk in step 2) is embodied by: the carried risk of passengers getting on the bus from the bus stop after waiting for the bus, namely the possibility that the passengers getting on the bus are infected to enter the public transportation system, describes the influence degree of different bus stops on the whole bus system; the output risk is embodied by: the risk of everyone carried by the get-off passengers when getting off from the bus station after the waiting process and the riding process, namely the possibility that the get-off passengers are infected and influence the communities around the get-off station, is used for evaluating the risk of each bus station on the surrounding communities.
Further, in the step 3), assuming that the arrival of passengers at the bus stop is a batch poisson arrival process, determining the accumulated contact time between the passengers by the passengers arriving at the bus stop later, and modeling an input risk evaluation model according to passenger OD data and the batch poisson process; input risk is primarily related to factors such as station demand, departure intervals, and passenger arrival rates.
Further, in the step 4), based on the accumulated contact time of the passengers with other passengers in the riding process as the riding risk of the passengers in the riding process, an output risk model is established according to different boarding stations of the passengers when the passengers get off, namely the difference of input risks; the output risk consists of an input risk and a riding risk; besides the influence factors of the input risk, the output risk is mainly related to the passenger origin-destination point, the station demand, the bus travel time and other factors.
Further, in the step 5), the input and output risks of the public transport system are calculated based on passenger OD data, bus GPS data and an input and output risk quantitative evaluation model, and the input and output risks can be effectively reduced by presetting an optimized departure interval and a station jump strategy according to influence factors of the model.
The invention has the beneficial effects that:
by adopting the method, the input and output risk condition of the public transport system under the sudden public health event can be evaluated, and an idea is provided for optimizing a public transport scheduling scheme. Compared to the existing studies, the present invention focuses on: 1. combining a passenger traveling process: namely waiting for the vehicle and taking the vehicle; 2. evaluating the input and output risks of the bus system by combining bus stops and bus route propagation risks; 3. the study of the actual situation that the passengers entering the public transportation system are all in a healthy state is combined, and the mutual influence situation of the public transportation system and the risks of the surrounding communities is considered more comprehensively.
How to evaluate the input and output risks of the bus stop has not been proposed at present. Therefore, the invention provides two risk quantitative evaluation indexes, namely input risk and output risk, aiming at the public transportation system. The input-output risk assessment modeling is based primarily on the number of passengers and sustained contact time that the commuter is in contact, taking into account cumulative contingencies between commuters. Wherein, the input risk refers to the possibility that the passengers getting on the bus are infected to enter the public transportation system, and describes the influence degree of different bus stations on the whole public transportation system; the output risk refers to the possibility that the getting-off passengers are infected and influence the adjacent communities of the getting-off stations, and is used for evaluating the risk of each bus station to the adjacent communities; the two risk indexes fully reflect the input and output relations between the public transportation system taking the bus stop as an import and export link and the infection risk of the surrounding communities, and both are influenced by many factors, such as the number of passengers contacted by a commuter in the public transportation system, the origin and destination points and the travel chain of the commuter, a bus travel time table, road conditions and the like. The invention can provide reference for formulating the public transport emergency response mechanism, thereby not only enhancing the trust of passengers on public transport, but also increasing the trust of public transport enterprises.
Drawings
FIG. 1 input output Risk propagation schematic
FIG. 2 is a schematic diagram of the relationship between the trip process and the input/output risk
FIG. 3 is a schematic diagram of the process of waiting passengers and the situation of infection
FIG. 4 is a schematic diagram illustrating the calculation of the contact time of passengers in the same batch
FIG. 5 is a schematic diagram illustrating the calculation of the contact time of passengers in different batches
FIG. 6 schematic diagram of ride risk assessment
FIG. 7 is a schematic diagram of an input risk model, taking site 3 as an example
FIG. 8 input output Risk impact factor graph
FIG. 9 impact of departure intervals on input Risk
FIG. 10 input risk versus peak and mean time
Detailed Description
The present invention will be described in further detail below with reference to the accompanying drawings.
Fig. 1 is a schematic diagram showing propagation of input and output risks, which mainly embodies a "community-public transportation system-community" input and output relationship with a bus stop as an import and export link, and further illustrates that input risks refer to the possibility that passengers getting on a bus are infected to enter a public transportation system, and describes the degree of influence of different bus stops on the whole public transportation system; the output risk refers to the likelihood that the alighting passenger is infected and affects the neighborhood of the alighting site for assessing the risk imposed by each bus site on the neighborhood.
Fig. 2 is a schematic diagram illustrating a relationship between an outgoing process and an input/output risk, which mainly reflects a relationship between the input/output risk and a waiting process and a preceding riding process in the outgoing process. The input risk is embodied by: the carried risk of passengers getting on the bus from the bus stop after waiting for the bus, namely the possibility that the passengers getting on the bus are infected to enter the public transportation system, describes the influence degree of different bus stops on the whole bus system; the output risk is embodied by: the risk of passengers getting off the bus from the bus station after waiting and taking a bus is the risk of the passengers getting off the bus, namely the possibility that the passengers getting off the bus are infected and influence the communities around the bus station, and is used for evaluating the risk of each bus station to the surrounding communities.
Fig. 3 is a schematic diagram showing the process of waiting for passengers and the infection situation immediately after the passengers arrive in batches. Based on the assumption that the arrival of passengers at the bus stop is a batch poisson arrival process, the accumulated contact time between the passengers is determined by the passengers arriving at the bus stop later, and an input risk assessment model is modeled according to passenger OD data and the batch poisson process; input risk is mainly related to factors such as station demand, departure intervals, and passenger arrival rates. For the target passenger, the cumulative contact duration may consist of three parts: 1. for the same batch of passengers (see fig. 4 for details), 2 for the case of a first arrival (see fig. 5 for details) and 3 for the case of a later arrival (see fig. 5 for details).
The method specifically comprises the following steps:
for each bus stop j, if the passenger batch arrival rate is assumed to be b j The number of arriving passengers per batch is
The arrival time of each batch of passengers is
The arrival rate of the bus is lambda, and the interval time between the front bus and the rear bus is G j (mainly depending on the departure interval of the bus
And bus delays between stops).
1. For the same batch of passengers, the cumulative contact time of the target passenger with other passengers is:
2. for the first arrival case, the cumulative contact time of the target passenger with other passengers is:
3. for the case of a rear arrival, the cumulative contact time of the target passenger with the other passengers is:
to sum up, the risk RI is input j As shown:
fig. 6 is a schematic diagram illustrating ride risk assessment. In the riding process, the accumulated time between passengers is mainly related to the factors such as the origin-destination point of the passengers, the station demand, the bus travel time and the like. The method specifically comprises the following steps:
aiming at the accumulated contact time length among different bus stops in the bus taking process among passengers, if the number of passengers getting on the bus at the bus stop j and the number of passengers getting off the bus at the bus stop j are respectively assumed to be O j And D j The travel time of the bus between stops is tau j,j+1 Risk RB of passenger riding between bus stop x and bus stop y x,y Comprises the following steps:
fig. 7 is a schematic diagram of an input risk model taking site 3 as an example. The output risk defined by the invention refers to the per-capita risk carried by the getting-off passenger when getting off from the bus stop after waiting and taking a bus, so that the output risk not only pays attention to the demand of the passenger on the bus stop but also pays attention to the passenger exchange condition of the bus stop along the way during the traveling of the passenger in the modeling process; for example, taking the bus stop 3 as an example, a passenger getting off at the bus stop 3 may get on the bus at the bus stop 1 or get on the bus at the bus stop 2, and based on the definition of the input risk in the present invention, the input risk and the riding risk of the two parts of passengers are different, and details can be explained with reference to fig. 7, which specifically include the following:
if assume a 1,3 For the number of passengers getting on from bus stop 1 to bus stop 3, RE 1,3 For the part of the output risk from the passenger getting on the bus stop 1 to the passenger getting off the bus stop 3, RE 2,3 In the same way, the rest parameters are the same as the above, and the input risk consists of an input risk and a riding risk, so the RE 1,3 And RE 2,3 Comprises the following steps:
then the output risk RE of the bus stop 3 3 Comprises the following steps:
similarly, the risk RE is output j Comprises the following steps:
fig. 8 is a graph showing input-output risk impact factors. According to the input and output risk model, the input risk mainly related to the factors such as station requirements, departure intervals, passenger arrival rates and the like can be obtained; besides the influence factors of the input risk, the output risk is mainly related to the passenger origin-destination point, the station demand, the bus travel time and other factors. Based on this, fig. 9 and fig. 10 compare the variation of the input risk in different departure intervals and the comparison of the output risk in the peak period and the flat period respectively based on an example, and the specific analysis is as follows:
fig. 9 shows the variation of the input risk under different departure intervals, where different broken lines represent different bus stations, and the graphical result shows that the input risk is in a fluctuating state under different departure intervals, and for example only, under the departure interval within the virtual circle, the output risk is minimal, and thus, the input risk can be dynamically evaluated to determine the optimal departure interval;
fig. 10 shows a comparison of the output risk during the peak period and the peak period, which often causes congestion and delays of the bus due to a large passenger flow demand and poor road conditions during the peak period, and the graphical result shows that the output risk during the peak period is higher than the output risk during the peak period.
Claims (6)
1. A bus system input and output risk quantitative evaluation method is characterized in that according to card swiping data of passengers, bus geographic information data and bus station and line data, the method calculates the accumulated travel time length between passengers who arrive at random in the bus travel process including the waiting process and the riding process, takes the bus station as an import and export link, models the random input and output risk of a bus system based on the accumulated contact time length between the passengers, and is used for quantitatively evaluating the risk; the input risk refers to the possibility that the passengers getting on the bus are infected to enter the public transportation system in the process of waiting for the bus, and is used for describing the influence degree of different bus stations on the whole public transportation system; the output risk refers to the possibility that the passengers of the getting-off bus are infected in the waiting process and the taking process and influence the adjacent community of the getting-off bus station, and is used for evaluating the risk of each bus station to the adjacent community.
2. The quantitative assessment method for the input and output risks of the bus system according to claim 1, characterized in that the method comprises the following steps:
1) according to the obtained card swiping data of the passengers, the geographic information data of the bus and the data of the bus stations and lines, passenger OD data and travel time data of the bus at each station are constructed;
2) establishing a relation between the input and output risks and a waiting process and a taking process of passengers based on the definition of the input and output risks of the bus system, wherein the input risks are the average risk carried by passengers getting on the bus from a bus station after the passengers getting on the bus experience the waiting process, and the output risks are the average risk carried by passengers getting off the bus from the bus station after the passengers getting off the bus experience the waiting process and the taking process;
3) establishing the accumulated contact time of each passenger with other passengers in the waiting process according to the random arrival assumption of the passengers in the waiting process, and establishing an input risk model based on the accumulated contact time of the passengers on board at the moment that the bus arrives at the bus stop;
4) establishing the accumulated contact time of each passenger with other passengers in the bus taking process according to the passenger OD data and the travel time data of the bus, and establishing an output risk model according to the accumulated contact time of the passengers at the bus arrival time of the bus and the accumulated contact time of the passengers on the basis of the passengers on the bus;
5) and optimizing the bus dispatching strategy according to the input and output risks evaluated by each station of the bus system by combining the established input and output risk model.
3. The quantitative evaluation method for the input and output risks of the bus system according to claim 2, wherein the obtaining of the OD data and the bus travel time data of the passenger according to the obtained card swiping data of the passenger, the bus GPS data, the bus station and line data specifically comprises:
based on the acquired passenger card swiping data, bus GPS data and bus station and line data, the acquired data is subjected to data processing and matching to obtain bus IC card passenger boarding station data comprising card number, card swiping date, card swiping time, line taking number, bus arrival time, boarding station number/name and station longitude and latitude;
the bus travel time data can be determined through the data, the passenger transfer behavior can be identified, meanwhile, the passenger can be subjected to getting-off station calculation based on the trip chain, and finally, the passenger OD identification is realized.
4. The bus system input and output risk quantitative evaluation method according to claim 2, wherein the step 3) specifically comprises:
assuming that the arrival of passengers at a bus stop is a batch poisson arrival process, the accumulated contact time between the passengers is determined by the passengers arriving at the bus stop later, and modeling input risks according to passenger OD data and the batch poisson process; input risk RI for bus stop j j As follows:
wherein N is the total batch that the passengers of the station arrive in batches,
for each batch, k is {1,2, …, N },
for each batch of passengers arrival time, G j The interval time of the front bus and the rear bus is r which is the belonged batch of the target passenger arriving at the station j, and the value range of r is [1, k) U (k, N)]。
5. The bus system input and output risk quantitative evaluation method according to claim 1, wherein the step 4) specifically comprises:
establishing an output risk model based on the accumulated contact duration of the passenger and other passengers in the riding process as the riding risk of the passenger in the riding process, and combining different boarding stations of the passengers when the passenger gets off the bus, namely the difference of input risks; the output risk consists of an input risk and a riding risk; the method specifically comprises the following steps:
output risk RE of bus stop j j Comprises the following steps:
wherein RE v,j The output risk is the part of the passengers getting on the bus from the bus stop v to get off the bus stop j, and because the output risk consists of two parts, namely the input risk and the riding risk, RE v，j ＝RI v +RB v，j ，RB v,j Risk of taking bus for bus stops v to j, a v,j Number of passengers getting on from bus stop v and getting off at bus stop j, D j The number of passengers getting off at bus stop j and the riding risk RB of the passengers between the bus stop x and the bus stop y x,y Comprises the following steps:
O u for the number of passengers getting on the bus at bus stop u, tau j-1,j Travel time of buses between stops.
6. The bus system input and output risk quantitative evaluation method according to claim 1, wherein the optimizing of the bus scheduling policy specifically comprises:
and calculating to obtain the input and output risks of the public transport system based on the passenger OD data, the bus GPS data and the input and output risk quantitative evaluation model, and presetting an optimized departure interval and a station jump strategy to reduce the input and output risks by combining the influence factors of the model.
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