CN113705902A - Traffic hub passenger transport organization evaluation method based on crowd management - Google Patents

Traffic hub passenger transport organization evaluation method based on crowd management Download PDF

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CN113705902A
CN113705902A CN202111008940.1A CN202111008940A CN113705902A CN 113705902 A CN113705902 A CN 113705902A CN 202111008940 A CN202111008940 A CN 202111008940A CN 113705902 A CN113705902 A CN 113705902A
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CN113705902B (en
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王智鹏
胡必松
陈希荣
吕颖
冯威
张明
王正邦
吴琼
宁骥龙
马海超
曲士荣
王琳
马驷
张凌
张鹏
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China Railway First Survey and Design Institute Group Ltd
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Abstract

The invention discloses a traffic hub passenger transport organization evaluation method based on crowd management. The reasonable adjustment of the traveling path of the passenger is a key measure for reducing crowd congestion at a traffic junction, and the solving speed of the existing model is limited when the existing model is oriented to large-scale crowd, so that the real-time requirement on application cannot be met. Compared with the traditional method that passenger coordination is regarded as a planning or scheduling problem, the method adopts a multi-stage dynamic coordination control method, and reasonably selects transfer targets and transfer paths for passengers by using current passenger flow information and passenger position information; when passengers enter a traffic junction and follow-up transfer and path decision are considered, the traveling behaviors of the passengers are tracked in real time, the transfer traveling travel of the passengers is dynamically and optimally designed in stages, and reasonable allocation and coordination of resources are carried out among a large number of passengers through a coordination control mechanism, so that the efficiency of the whole system is ensured.

Description

Traffic hub passenger transport organization evaluation method based on crowd management
Technical Field
The invention belongs to the technical field of comprehensive transportation hub passenger transport organization, and particularly relates to a transportation hub passenger transport organization evaluation method based on crowd management.
Background
The reasonable adjustment of the traveling path of the passenger is a key measure for reducing crowd congestion at the traffic junction, and the transfer behavior of the passenger is coordinated under the condition of considering the personal preference of the passenger, so that the people flow can be uniformly distributed in time and space. The traditional method is to regard passenger coordination as a planning or scheduling problem, establish an optimization model of passenger coordination, wherein the model belongs to NP-hard problem, although a heuristic algorithm can be used for solving, the solving speed is limited when facing large-scale crowd, and the real-time requirement on application cannot be met.
Disclosure of Invention
The invention aims to provide a traffic hub passenger transport organization evaluation method based on crowd management, which can increase the overall social benefit on the basis of not reducing the personal utility of passengers.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows:
a transportation junction passenger transport organization evaluation method based on crowd management constructs a passenger security inspection utility model and a passenger junction station transfer utility model on the basis of the passenger security inspection utility model, thereby constructing a social welfare calculation model under the pareto optimal state, and specifically comprises the following steps:
the method comprises the following steps: establishing a passenger security inspection target point selection model based on a preferred selection mechanism, and quantifying the security inspection target point selection behavior of passengers before entering a junction;
step two: establishing a passenger path selection model based on an improved Logit model, and quantifying the walking path selection behavior of passengers after entering a junction;
step three: and establishing a hub station passenger flow organization method evaluation index model based on pareto optimization.
Specifically, the first step is that the passenger total satisfaction v of any node i of the passenger j in the node list of the current time unit, which is not yet subjected to security inspection, is calculated, the next security inspection target node is selected based on the calculation result, the coordination agent can count the passenger flow going to the target node, then the passenger can dispersedly select the idle security inspection nodes according to a suboptimal selection method, and the calculation model is as follows:
Figure BDA0003237909710000011
wherein,
Figure BDA0003237909710000012
is the average of the preferences of the nodes that passenger j has not yet gone to the security check,
Figure BDA0003237909710000013
the average of the expected waiting times of the nodes that have not yet been security checked by passenger j,
Figure BDA0003237909710000021
the average value of the shortest time distances of all nodes which are not yet subjected to security inspection of the passenger j is represented by alpha, beta and gamma which are balance indexes, the total satisfaction degree of the passenger is represented, the comprehensive balance is achieved for three passenger visiting behavior characteristic elements, and according to the passenger visiting behavior characteristics, alpha and gamma take positive values, and beta takes negative values.
Specifically, the distribution rate of the O-D quantity T (r, v) of passengers on the k-th walking path in the passenger path selection model is as follows:
Figure BDA0003237909710000022
the distribution amount on the k-th walking path in the passenger path selection model is as follows:
Q(r,v,k)＝P(r,v,k)·T(r，v)
wherein stkIs the travel time of the k-th path,
Figure BDA0003237909710000023
and the average running time of each running path, sigma is an allocation parameter, and m is the number of effective running paths.
Specifically, the third step includes the following steps:
1) establishing a passenger security check utility model, wherein the passenger security check utility model is as follows:
setting the utility of the passenger at the first security inspection as a constant and the utility of the repeated security inspection as 0, and expressing the utility model of the passenger j at the security inspection point i as follows:
f(pji,vtji)＝pji·min(l,vtji)
wherein p isji∈[0,1]Indicating a transfer preference, p, for passenger j for security point ijiA larger value indicates that passenger j is more likely to arrive at security checkpoint i for a security transfer. vtjiThe number of times of passing of passenger j at the security checkpoint;
2) establishing a passenger junction station path utility model, wherein the passenger junction station path utility model is as follows:
uj＝∑f(pji,vtji)+w·∑f(pji,vtji)/(wtj+mtj)
in which wtjFor the total queuing time, mt, of passenger j during the transferjThe total travel time of the transfer period of the passenger j, w is a weight coefficient and represents the utility value of the non-transfer time;
3) establishing a social welfare calculation model, wherein the social welfare calculation model comprises the following steps:
Figure BDA0003237909710000024
wherein wjRepresents the contribution of the passenger j to social welfare as the weight value of the passenger j, and satisfies wj>0,∑wj1, different weights wjThe method of selecting a corresponding social welfare under pareto optima, where w is taken without taking into account the differences between passengersj＝1/n。
The invention has the beneficial effects that:
the invention provides a preferred selection mechanism based on passenger overall satisfaction by using a Logit model, which provides a next security inspection target point for a passenger. The method comprises the steps of reasonably selecting transfer targets and transfer paths for passengers by using current passenger flow information and passenger position information in the passenger traveling process, tracking passenger traveling behaviors in real time when the passengers enter a traffic junction and considering follow-up transfer and path decision, issuing junction passenger flow information in real time, dynamically and optimally designing passenger transfer traveling routes in stages, reasonably configuring and coordinating resources among a large number of passengers through a coordination control mechanism, ensuring the efficiency of the whole system and providing high-quality service for each passenger.
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FIG. 1 is a flow chart of a transportation junction passenger transportation organization evaluation method based on crowd management;
fig. 2 is a schematic diagram of the organization of the terminal passenger flow.
Detailed Description
The following description of the embodiments of the present invention is provided to facilitate the understanding of the present invention by those skilled in the art, but it should be understood that the present invention is not limited to the scope of the embodiments, and it will be apparent to those skilled in the art that various changes may be made without departing from the spirit and scope of the invention as defined and defined in the appended claims, and all matters produced by the invention using the inventive concept are protected.
An embodiment of the present invention is described in detail below with reference to the accompanying drawings.
The invention comprises the following steps:
s1, establishing a passenger security inspection target point selection model based on a preferred selection mechanism;
s2, establishing a passenger path selection model based on the improved Logit model;
s3, establishing a hub station passenger flow organization method evaluation index model based on pareto optimality.
Step S1, establishing a passenger security inspection target point selection model based on a preferred selection mechanism;
the passengers have mainly the following behavior characteristics when in the junction: (1) the passenger can select a security check point to complete the transfer according to the transfer preference of the passenger: (2) passengers often avoid congested security points and prefer to go to uncongested security points; (3) passengers always tend to transfer to security checkpoints close to themselves.
The transfer behavior characteristic (1) of passenger j can be determined by the preference p of the passengerjiInscription, for feature (2), define wtiFor the expected queuing time of the passenger to the security inspection point i for security inspection, which represents the time for waiting in a queue if the passenger arrives at the security inspection point i at the current moment, it reflects the current congestion condition of the node i, the characteristic (3) is described by the shortest distance from the current security inspection (gate) point of the passenger to the security inspection point i which can transfer to, and the specific calculation model is as follows:
wti＝qi·sti/ci
in each time unit, the coordination agent determines a next transfer security check node v for the passenger by calculating the passenger total satisfaction v of the passenger j in any node i which is not yet security checked in the node list of the current time unit according to the passenger flow information (including the congestion condition of each security check point and the road condition information of the passage) of the current hub and the current position of the passenger, and the calculation model is as follows:
Figure BDA0003237909710000041
Figure BDA0003237909710000042
wherein,
Figure BDA0003237909710000043
is the average value of the preference of the node that passenger j has not yet gone to security check, if
Figure BDA0003237909710000044
For the set of passenger j current time unit without security check node yet, then
Figure BDA0003237909710000045
Figure BDA0003237909710000046
Average value of expected waiting time of node which is not yet security-checked for passenger j
Figure BDA0003237909710000047
Figure BDA0003237909710000048
The average value of the shortest time distances of all the nodes which are not yet subjected to security inspection of the passenger j is
Figure BDA0003237909710000049
Alpha, beta and gamma are balance indexes which represent the total satisfaction of passengers, and are the comprehensive balance of three characteristic elements of the visiting behavior of the passengers, and the alpha and the gamma are corrected according to the visiting behavior of the passengersThe value, β, takes a negative value.
And finally, selecting a next security inspection target node for the passenger based on a preferred selection mechanism, in order to prevent the congestion of the target node caused by the aggregation effect brought by the preferred selection mechanism, the coordination agent counts the passenger flow going to the target node, and then the passenger can dispersedly select the idle security inspection nodes according to a suboptimal selection method.
Step S2 is to establish a passenger path selection model based on the improved Logit model;
after the security inspection target point is determined, a common method is to select the shortest route from the starting point r to the destination point v as a passenger traveling route, and although the method reduces the traveling time of passengers, for a comprehensive junction, if a large number of passengers are guided to travel the shortest route within a period of time, road congestion is easy to occur, and the load of the target point is increased, so that new queuing is brought. The invention uses an improved model of multi-path traffic distribution-the Logit model of path selection. The Logit model has the advantages that the shortest path factor and the random factor in the passenger path selection process can be well reflected, passengers can be uniformly distributed on an effective route, the resource allocation is more reasonable, and the Logit model is suitable for complex traffic and large networks. The Logit model for passenger flow organization crowd management allocation in a comprehensive hub is given below.
The distribution rate of the O-D quantity T (r, v) of passengers on the k-th walking path in the model of the step S2 is as follows:
Figure BDA00032379097100000410
in the formula stkIs the travel time of the kth path;
Figure BDA00032379097100000411
the average walking time of each walking path is obtained; sigma is a distribution parameter and is between 3.00 and 3.50; m is the number of effective running paths. The allocation rate of passengers on the invalid travel path is 0.
In the step S2 model, the allocation amount on the k-th travel path is:
Q(r,v,k)＝P(r,v,k)·T(r，v)
when the O-D quantity T (r, v) of the passenger is smaller, the passenger can select the shortest route more reasonably, so a critical point c is set, and the c is used as a boundary to distinguish the general crowd from the large crowd.
And when the T (r, v) belongs to (0, c), calculating the shortest travel time as the travel path of the passenger by using a Floyd algorithm.
When T (r, v) ∈ [ c, + ∞), the allocation amount on each effective travel path is determined according to the model in step S2, and the passenger flow is randomly allocated to each effective travel path according to the allocation amount, so that each passenger obtains its randomly allocated path.
In step S3, establishing a pareto-optimal-based hub station passenger flow organization method evaluation index model, including the following sub-steps:
s3.1 passenger security inspection utility model
S3.2 passenger hub station path utility model
S3.3 social welfare calculation model
The coordination of passenger flow organization in a large-scale transportation hub ensures the personal utility of passengers and simultaneously optimizes social welfare (the efficiency of the whole system) under the condition of limited resources, which is a multi-objective planning problem about how to allocate the limited resources. It is very difficult to optimize the utility of each passenger because the behavior among a large number of passengers is interfering, often at the expense of longer queue time for one passenger, and the transfer time for another passenger is extended. The pareto optimal is an important concept for expressing the resource allocation state, and social welfare can be increased on the basis of not reducing the personal utility of passengers by using the pareto optimal. This concept is introduced below and a definition of social welfare based on the pareto optimality concept is given on the basis of defining the utility of the passenger.
And S3.1, passenger security inspection utility model.
The security check utility of passengers at a security check point in a terminal is generally three: (a) the utility is constant; (b) the utility is decreased along with the increase of the number of times of the passengers staying in the security check; (c) the utility is constant in the first security check and 0 in the later security check. The utility definition of (c) is adopted, and by assuming that the repeated security inspection utility of the passenger is 0, the utility of the security inspection process of the passenger j at the security inspection point i is as follows:
f(pji,vtji)＝pji·min(l,vtji)
wherein p isji∈[0,1]Indicating a transfer preference, p, for passenger j for security point ijiA larger value indicates that passenger j is more likely to arrive at security checkpoint i for a security transfer. vtjiThe number of passes of passenger j at the security checkpoint.
Step S3.2 passenger hub station path utility model is:
uj＝∑f(pji,vtji)+w·∑f(pji,vtji)/(wtj+mtj)
in which wtjFor the total queuing time, mt, of passenger j during the transferjAnd w is a weight coefficient which represents the utility value of the non-transfer time and is the total traveling time of the transfer period of the passenger j.
Step S3.3 the social welfare calculation model is as follows:
Figure BDA0003237909710000061
wherein wjRepresents the contribution of the passenger j to social welfare as the weight value of the passenger j, and satisfies wj>0,∑wj1, different weights wjThe method of selecting a corresponding social welfare under pareto optima, where w is taken without taking into account the differences between passengersj＝1/n。
In addition, the average queuing waiting time and the average walking time of passengers during transfer also reflect the congestion condition of the junction, and the calculation model is as follows:
Figure BDA0003237909710000062
Figure BDA0003237909710000063
wherein n is the total number of passengers entering the hub for transfer.
When each passenger buys a ticket, one-to-one correspondence between the passenger ticket and AFC data and one-to-one correspondence between the ticket and a passenger communication device (such as a mobile phone) are established. Passengers go to the security points needed for transfer when entering the hub, and each security point of the hub is given a certain preference value, and a (security point, preference) list, namely (v) of each passenger is establishedi，pji) The list is not the transfer path of the passenger, and the order of the security check point is not the precedence of the transfer order.
The working principle of the invention is as follows: based on intensive crowd management, the pareto optimal is adopted to express hub resource allocation, traveling paths of passengers are reasonably evaluated and adjusted to reduce management difficulty of the intensive crowd in the traffic hub, and social benefits (overall benefits) can be increased on the basis of not reducing personal effects of the passengers. A preferred selection mechanism based on the overall satisfaction of passengers is provided by using a multi-stage dynamic coordination method, an optimal walking scheme is provided for dense crowds, and a Logit model is used for selecting a path.
Compared with the traditional method that passenger coordination is regarded as a planning or scheduling problem, and an optimization model of passenger coordination is established, the method adopts a multi-stage dynamic coordination control method, utilizes current passenger flow information and passenger position information to reasonably select transfer targets and transfer paths for passengers in the passenger traveling process, tracks passenger traveling behaviors in real time when the passengers enter a traffic junction to consider subsequent transfer and path decision, releases junction passenger flow information in real time, dynamically optimizes and designs passenger transfer traveling routes in stages, reasonably configures and coordinates resources among a large number of passengers through a coordination control mechanism, ensures the efficiency of the whole system, and provides high-quality service for each passenger.
The invention is not limited to the examples, and any equivalent changes to the technical solution of the invention by a person skilled in the art after reading the description of the invention are covered by the claims of the invention.

Claims (4)

1. A traffic hub passenger transport organization evaluation method based on crowd management is characterized by comprising the following steps: the passenger safety inspection utility model is built, and a passenger terminal transfer utility model is built on the basis of the passenger safety inspection utility model, so that a social welfare calculation model in the pareto optimal state is built, and the method specifically comprises the following steps:
the method comprises the following steps: establishing a passenger security inspection target point selection model based on a preferred selection mechanism, and quantifying the security inspection target point selection behavior of passengers before entering a junction;
step two: establishing a passenger path selection model based on an improved Logit model, and quantifying the walking path selection behavior of passengers after entering a junction;
step three: and establishing a hub station passenger flow organization method evaluation index model based on pareto optimization.
2. The transportation junction passenger transport organization evaluation method based on crowd management as claimed in claim 1, wherein: the first step is that the passenger total satisfaction v of any node i of the passenger j in the node list of the current time unit, which is not yet subjected to security inspection, is calculated, the next security inspection target node is selected based on the calculation result, the coordination agent can count the passenger flow going to the target node, then the passenger can dispersedly select the idle security inspection nodes according to a suboptimal selection method, and the calculation model is as follows:
Figure FDA0003237909700000011
Figure FDA0003237909700000012
wherein,
Figure FDA0003237909700000013
is the average of the preferences of the nodes that passenger j has not yet gone to the security check,
Figure FDA0003237909700000014
the average of the expected waiting times of the nodes that have not yet been security checked by passenger j,
Figure FDA0003237909700000015
the average value of the shortest time distances of all nodes which are not yet subjected to security inspection of the passenger j is represented by alpha, beta and gamma which are balance indexes, the total satisfaction degree of the passenger is represented, the comprehensive balance is achieved for three passenger visiting behavior characteristic elements, and according to the passenger visiting behavior characteristics, alpha and gamma take positive values, and beta takes negative values.
3. The transportation junction passenger transport organization evaluation method based on crowd management as claimed in claim 2, wherein: the distribution rate of O-D quantity T (r, v) of passengers on the k-th walking path in the passenger path selection model is as follows:
Figure FDA0003237909700000016
the distribution amount on the k-th walking path in the passenger path selection model is as follows:
Q(r,v,k)＝P(r,v,k)·T(T，v)
wherein stkIs the travel time of the k-th path,
Figure FDA0003237909700000017
and the average running time of each running path, sigma is an allocation parameter, and m is the number of effective running paths.
4. The transportation junction passenger transport organization evaluation method based on crowd management as claimed in claim 3, wherein: the third step comprises the following steps:
1) establishing a passenger security check utility model, wherein the passenger security check utility model is as follows:
setting the utility of the passenger at the first security inspection as a constant and the utility of the repeated security inspection as 0, and expressing the utility model of the passenger j at the security inspection point i as follows:
f(pji,vtji)＝pji·min(l,vtji)
wherein p isji∈[0,1]Indicating a transfer preference, p, for passenger j for security point ijiA larger value indicates that passenger j is more likely to arrive at security checkpoint i for a security transfer. vtjiThe number of times of passing of passenger j at the security checkpoint;
2) establishing a passenger junction station path utility model, wherein the passenger junction station path utility model is as follows:
uj＝∑f(pji,vtji)+w·∑f(pji,vtji)/(wtj+mtj) In which wtjFor the total queuing time, mt, of passenger j during the transferjThe total travel time of the transfer period of the passenger j, w is a weight coefficient and represents the utility value of the non-transfer time;
3) establishing a social welfare calculation model, wherein the social welfare calculation model comprises the following steps:
Figure FDA0003237909700000021
wherein wjRepresents the contribution of the passenger j to social welfare as the weight value of the passenger j, and satisfies wj>0,∑wj1, different weights wjThe method of selecting a corresponding social welfare under pareto optima, where w is taken without taking into account the differences between passengersj＝1/n。
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