ES2372945A1 - Method and intelligent system for the management of emergencies in road tunnels (Machine-translation by Google Translate, not legally binding) - Google Patents

Abstract

Method for the management of an emergency by means of support for making safety decisions in a road tunnel, which includes the steps of: identifying a scenario of the road tunnel through a first evacuation area and a second evacuation area, where the first is the area where the vehicles and people directly involved in the emergency situation and the people in imminent danger are located; and the second is adjacent to the first, where the trapped vehicles are found; identify the possibility of bidirectionality (a ' bidirec) in the evacuation process of the first area; calculate: the distance (dsi) from the upstream mouth of the tunnel to the place of occurrence of the incident; the distance (d ' i1) from the countercurrent mouth of the tunnel to the first area; the distance (d ' i2) from the countercurrent mouth of the tunnel to the end of the first area; calculate the number of people to evacuate; calculate the evacuation time of one; propose an appropriate decision. Intelligent integrated and automated system. (Machine-translation by Google Translate, not legally binding)

Description

Smart method and system for managing road tunnel emergencies.

Field of the Invention

The present invention belongs to the field of Industrial Engineering, and more specifically to the development of methods and intelligent systems for emergency management.

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Background of the invention

Currently there are Intelligent Systems applied to different areas of society (irrigation systems or washing, lighting systems ....), understanding these as systems that try to emulate the characteristics and behaviors similar to those of human or artificial intelligence.

Within the field of transport, these systems have been applied to improve operability and safety in urban, rural roads, railways ..., offering solutions technology for automatic toll collection and even the automatic surveillance of infractions.

It is possible to find in the literature not very extensive statistical information related to accidents in road tunnels worldwide. The World Tunnel Disasters since 1970 from the Institute of Advanced Motorists (IAM), 2008 and The Future of Tunnel Testing: Serious Tunnel Accidents since 1970 , from EuroTAP , collect information about the most important incidents in road tunnels since the 1970s .

Regarding evacuation systems, after a review of the existing computer evacuation models of their capabilities, applications and functionalities based on the review carried out by the NIST ( National Institute of Standards and Technology ) (Kuligowski, ED and Peacock, RD , 2005. Review of Building Evacuation Models, Technical Note 1471, Natl. Inst. Stand. Technol., Gaithersburg, MD), it was concluded that there is currently no evacuation model that represents the specific characteristics of evacuation in a tunnel from
highway.

As for decision making, it is not known no smart system that applies to road tunnels optimizing the decisions to be made by the person in charge of Manage a certain emergency.

On the other hand, in 2006 it was approved in Spain, Royal Decree 635/2006 (BOE No. 126 of May 27, 2006), on minimum safety requirements in road tunnels of the State. Regarding the management of situations of emergency, the regulations prescribe the development of a manual of holding specifying the necessary measures to guarantee user safety, but without specifying the action protocols integrated in the response plans to emergency situations.

Despite the advances in the means of prevention and protection installed in the tunnels, decision making in the necessary actions in case of emergency is a critical task for the safety of users and can cause in the person responsible for managing these actions, a stress situation that does not allow you to make the most optimal decisions or in time in the that would act in a normal situation.

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Summary of the Invention

The present invention seeks to solve the drawbacks mentioned above by a method and intelligent system, through which the personnel in charge of manage security in a road tunnel has a intelligent system that working in real time, offers proposals appropriate decision depending on the emergency detected.

In addition to the proposal for decisions, the system performs an analysis of similar preceding events, based on statistical analysis of the accident in road tunnels offering under a given probability, an estimate of the scope and consequences of the incident recorded, in relation to the number and Injury of people involved in the accident, in addition to the trapped in the tunnel

In the case of decreeing the need to evacuate the tunnel by the severity of the event, the method and system performs a prognosis about the total time needed to proceed to the total evacuation of the tunnel.

The system comprises three subsystems independent: a subsystem of incidents, a subsystem of evacuation and a decision making subsystem.

Specifically, in a first aspect of the present invention, an automated method of management is provided of the emergency by supporting decision making security in an emergency situation in a tunnel highway.

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The method comprises the steps of: identifying a road tunnel scenario through a first evacuation area (Evacuation Area I) and a second evacuation area (Evacuation Area II), where said first evacuation area is the zone where the vehicles are located and therefore the people directly involved in the accident, as well as the people who are in imminent danger due to the occurrence of fire or spillage of dangerous substances; and said second evacuation area is an area adjacent to the first evacuation area, where vehicles are trapped in the traffic jam caused by the accident; identify the possibility of bidirectionality in the evacuation process of the first evacuation area; calculate the distance from the countercurrent mouth of the tunnel to the place of occurrence of the incident; calculate the distance from the countercurrent mouth of the tunnel to the beginning of the first evacuation area (Evacuation Area
I).

Calculate distance from mouth tunnel countercurrent until the end of the first area of evacuation (Evacuation Area I); calculate the number of people to evacuate in the first evacuation area and in the second area of evacuation; calculate the evacuation time of each person; propose an appropriate decision based on the emergency detected

In another aspect of the invention, it is provided an integrated intelligent system for emergency management for an incident in a road tunnel, which comprises: a incident subsystem, configured to perform an analysis predictive of the possible development and consequences of an emergency, where said event is any accident, caused by one or several motor vehicles that pass through the tunnel, which cause real or potential harm to people who find inside and eventually advise the evacuation of these; an evacuation subsystem; and a subsystem making decisions. The integrated intelligent system is configured to carry out the steps of the method described above.

The advantages of the invention will become apparent. in the following description.

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Brief description of the figures

In order to help a better understanding of the characteristics of the invention, according to an example preferred practical implementation thereof, and to complement This description is accompanied as an integral part of it, a game of drawings, whose character is illustrative and not limiting. In these drawings:

Figure 1 shows a possible characterization of a road tunnel, according to an implementation of the invention.

Figure 2 shows a diagram of the dead zone of the CCTV camera (Closed Circuit Television) within a tunnel, according to an implementation of the invention.

Figure 3 shows a decision tree for notice to operating personnel in accordance with one embodiment of the present invention.

Figure 4 shows a decision tree for emergency services prevention, according to a embodiment of the present invention.

Figure 5 shows a decision tree for the activation of emergency services, according to a embodiment of the present invention.

Figure 6 shows a decision tree for the need for evacuation, according to an embodiment of the present invention

Figure 7 shows a decision tree for the bidirectionality of the first evacuation area, according with an embodiment of the present invention.

Figure 8 shows a decision tree for the number of lanes to close, according to an embodiment of The present invention.

Figure 9 shows a decision tree for the closure of the tunnel, in accordance with an embodiment of the present invention.

Figure 10 shows a decision tree for the activation of the maximum level of illumination, according to a embodiment of the present invention.

Figure 11 shows a decision tree for inform users, according to an embodiment of the present invention

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Figure 12 shows an example of implementation of a tunnel data file that provides the data that introduce the geometry and characteristics of the tunnel application concrete of the integrated main system.

Figure 13 shows an example of implementation of the introduction of a series of variables of entrance that define a detected emergency situation.

Figure 14 shows an example of implementation of the proposed decisions to be taken by the operator of the tunnel control center depending on the severity and conditions of the incident.

Figure 15 shows an example of implementation and introduction of additional information from event.

Figure 16 shows an example of implementation and introduction of additional event information, specifically the input variables for the models of evacuation.

Figure 17 shows an example of results of the evacuation analysis in the first evacuation area.

Figure 18 shows an example of results of the evacuation analysis in the second evacuation area.

Figures 19 and 20 show two examples of layout of two possible scenarios.

Figures 21 to 24 show the results obtained from the exemplified execution in figures 19 and 20, both in the first and second evacuation areas.

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Detailed description of the invention

In this text, the term "comprises" and its variants should not be understood in an exclusive sense, that is, These terms are not intended to exclude other technical characteristics, additives, components or steps.

In addition, the terms "approximately", "substantially", "around", "ones", etc. must understood as indicating values close to which said terms accompany, since due to calculation or measurement errors, it results impossible to get those values with total accuracy.

The following preferred embodiments will be provided by way of illustration, and are not intended to be Limitations of the present invention. In addition, the present invention covers all possible combinations of particular embodiments and preferred here indicated.

For those skilled in the art, other objects, advantages and features of the invention will be partly detached of the description and in part of the practice of the invention.

The method and system are detailed below. intelligent for the management of an emergency in tunnels of road by supporting decision making, and specifically, of the stages and different subsystems that form it: a subsystem of incidents, an evacuation subsystem and a subsystem of decisions. The integration of the subsystems in The intelligent system.

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1 Incident Subsystem

This subsystem allows analysis predictive of the possible development and consequences of an incident, understanding this as any accident, caused by one or several motor vehicles that pass through the tunnel, which cause real or potential harm to people who find inside and eventually advise the evacuation of these.

The subsystem offers results working based on the data obtained about the accidents recorded in the literature that occurred in road tunnels at an international level, in relation to the number of people killed due to the accident, number of minor (minor) injuries, number of seriously injured and summarized in the
Table 1.

TABLE 1 List of victims of Tunnel Accidents Road between 1979 and 2007. (Source: World Tunnel Disasters since 1970. Institute of Advanced Motorists (IAM). 2008 and EuroTAP - The Future of Tunnel Testing: Serious Tunnel Accidents since 1970)

one

To obtain the incident subsystem, a mathematical algorithm consisting of a set of expressions that relate a series of variables of Enter and exit. These expressions are based on the Protocols of Pre-established actions for Control Center Operators of tunnels.

First, a scenario of the road tunnel as follows (see figure 1):

?

Definition or identification of a first evacuation area (Evacuation Area I) or area where vehicles are found and therefore people directly involved in the accident as well as the people who are in imminent danger from the emergence of fire or discharge of dangerous substances.

?

Definition or identification of a second evacuation area (Evacuation Area II) or zone adjacent to the first evacuation area, to the entrance mouth of the tunnel, where vehicles are trapped in the traffic jam caused by its closure due to accident.

Figure 1 illustrates these two evacuation areas. Figure 1 also shows the distance from the countercurrent mouth of the tunnel to the approximate (center) place of occurrence of the incident d _ {\ mathit {SI}}, the distance from the countercurrent mouth of the tunnel to the end of the second evacuation area d '_ {\ mathit {I} 1} and the distance from the countercurrent mouth of the tunnel to the end of the first evacuation area d ' _ {\ mathit {I} 2}. The expressions that comprise the mathematical algorithm of the incident subsystem are the following:

1. The number of tunnel lanes that are closed to traffic m _ {\ mathit {CAR}} must be equal to the number of obstructed lanes resulting from the accident m '_ {\ mathit {CAR}}:

2

2. The need to notify operating personnel to go to the site of the event, represented by the expression a '_ {\ mathit {APE}}, must be conditioned by the very occurrence of an incident, represented by the expression a _ {\ mathit {SI}}:

3

3. The need to prevent the emergency services, represented by the expression '_ {\ mathit {PSE}}, defined by the closure of at least one rail tunnel, if the tunnel has more than one channel:

4

where m _ {\ mathit {MAX}} represents the maximum number of lanes in the tunnel and m _ {\ mathit {CAR}} is the number of lanes in the tunnel that are closed to traffic.

4. The need to activate emergency services, represented by the expression a '_ {\ mathit {ASE}}, is conditioned by the total closure of the tunnel (when the number of tunnel lanes that are closed to traffic m _ {\ mathit {CAR}} is equal to the maximum number of lanes in the tunnel m _ {\ mathit {MAX}}, the detection of a fire in it (represented by the expression a _ {\ mathit {FIRE} }), or a spill (escape) of a hazardous substance (represented by the expression a _ {\ mathit {VSP}}) or the suspicion that there is at least one injured product of the accident (represented by the expression n _ { \ mathit {HER}}):

5

5. The need for immediate evacuation of the tunnel, represented by the expression a '_ {\ mathit {EVAC}}, is determined by the emergence of a fire in the tunnel (represented by the expression a _ {\ mathit {FIRE}} ) or the discharge or escape of a hazardous substance (represented by the expression a {{mathit {VSP}})), as a result of the incident:

6

6. The bidirectionality of the possible immediate evacuation of the tunnel, represented by the expression a '_ {\ mathit {BIDIREC}} (Boolean variable that indicates the possibility of bidirectionality in the evacuation process), is defined by the total or partial obstruction of the same. If the obstruction is total (when the number of tunnel lanes that are closed to the traffic m _ {\ mathit {CAR}} is equal to the maximum number of tunnel lanes m _ {\ mathit {MAX}}) the bidirectionality it is false:

7

7. The distance from the mouth tunnel countercurrent until the beginning of the first area of evacuation can be calculated using a series of expressions that we detail to continuation:

Initially, the distance from the tunnel countercurrent mouth to the approximate (center) place of accident occurrence d _ {\ mathit {SI}} is calculated:

8

where:

d _ {\ mathit {SI}} - As can be seen in Figure 1, it is the distance from the countercurrent mouth of the tunnel to the approximate location of the incident;

d _ {\ mathit {CAM}} ( n _ {\ mathit {CCTV}}) - distance from the tunnel entrance to the CCTV camera (Closed Circuit Television) number n _ {\ mathit {CCTV}} (the camera number that detects the incident automatically in the Control Center);

\ delta _ {\ mathit {ZM}} - distance from the zone dead of the camera;

\ delta _ {\ mathit {CCTV}} - approximate place of the tunnel sector captured by the CCTV camera where it has The incident happened. This sector is commonly less than or equal to 150 m and is known for each tunnel. If for example \ delta _ {\ mathit {CCTV}} = 1, the event occurred in the first half of the tunnel

\ Delta_ {CAM} - distance between cameras.

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The distances from the countercurrent mouth until each of the tunnel chambers can be calculated by The expression:

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9

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where:

d {{mathit {CAM} 1} - distance between the countercurrent mouth of the tunnel to the first CCTV camera;

\ Delta _ {\ mathit {CAM}} - distance between tunnel chambers

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Figure 2 shows a diagram of the dead zone of the CCTV camera (CCTV) within the tunnel. From figure 2 it follows:

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10

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where:

h {{mathit {CAM}} - the height of the chambers from the plane of the roadway inside the tunnel;

β {{mathit {EF}} - focal axis angle of the camera with respect to the horizontal plane;

a _ {\ mathit {VIS}} - camera viewing angle.

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eleven

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as far as I know gets:

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12

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where:

h {{mathit {CAM}} - height of the chambers from the plane of the road inside the tunnel;

β {{mathit {EF}} - focal axis angle of the camera with respect to the horizontal plane;

a {{mathit {VIS}} - camera angle of view;

γ-angle of the dead zone of the camera;

\ delta _ {\ mathit {ZM}} - distance from the zone dead of the camera;

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Then the distance d '_ {\ mathit {I} 1} from the countercurrent mouth of the tunnel to the end of the second evacuation area (distance from the countercurrent mouth of the tunnel to the beginning of the first evacuation area):

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13

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where:

d _ {\ mathit {GALi}} - distance from the countercurrent tunnel entrance to the ith gallery;

d _ {\ mathit {GALj}} - distance from the countercurrent entrance of the tunnel to the jth gallery;

d _ {\ mathit {SI}} - distance from the countercurrent mouth of the tunnel to the approximate (center) place of occurrence of the incident;

A _ {\ mathit {G}} - variable that indicates if there is a gallery before gallery i.

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The previous expression indicates that the distance d '_ {\ mathit {I} 1} must be chosen equal to the distance to the immediate previous gallery countercurrent to the place of occurrence of the incident, if it exists. Otherwise, this distance is assumed equal to zero (tunnel entrance).

The distances to the different galleries of tunnel is calculated as:

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14

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where:

d {{mathit {GAL} 1} - distance from the countercurrent mouth of the tunnel to the first gallery;

\ Delta _ {\ mathit {GAL}} - distance between tunnel galleries;

m _ {\ mathit {GAL}} - total number of tunnel galleries.

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8. The distance from the countercurrent mouth of the tunnel to the end of the first evacuation area is calculated by the expression d '_ {\ mathit {I} 2}:

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fifteen

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where:

16

Y where:

d _ {\ mathit {GAL_ {k}}} - distance from the countercurrent entrance of the tunnel to the k-th gallery;

L \ mathit {T} - tunnel length;

d _ {\ mathit {SI}} - distance from the countercurrent mouth of the tunnel to the approximate (center) place of occurrence of the incident;

\ Delta_ {CAM} - distance between cameras of the tunnel;

A_ {G1} - indicates the existence of a gallery post incident;

a '_ {\ mathit {BIDIREC}} - bidirectionality of tunnel evacuation.

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The expression reflects that the distance d '_ {\ mathit {I} 2} is, for the cases of possibility of bidirectional evacuation, equal to the distance to the immediate subsequent countercurrent gallery of the place of occurrence of the event, if such gallery exists, or equal to the length of the tunnel otherwise. If the evacuation has to be unidirectional, the distance d '_ {\ mathit {I} 2} equal to the distance to the accident is assumed plus a spatial margin equal to one third of the distance between cameras of the
CCTV

9. The total number of people to evacuate from the first evacuation area n '_ {\ mathit {IT}} is preferably a pessimistic estimate to be made based on the number of vehicles directly involved in the accident and their types .

The pessimistic nature of this estimate assumes assume reasonable maximum values that imply times of Simulated evacuation equally reasonable maximums. Therefore the Expression of this variable can be:

17

where:

k _ {\ mathit {VL}} - passenger occupancy assumed by light vehicle;

k _ {mathit {VP} P} - passenger occupation assumed by heavy vehicle;

k _ {\ mathit {VA}} - passenger occupancy assumed by coach;

n _ {\ mathit {VLDI}} - number of light vehicles directly involved in the incident;

n _ {\ mathit {VPDI}} - number of heavy vehicles directly involved in the incident;

n _ {\ mathit {VADI}} - number of coaches directly involved in the incident.

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10. The numbers of people to evacuate with different types of mobility in the first evacuation area They are also preferably based on pessimistic estimates. Be Two situations differ: if an incident is serious or if it is not. But this can be assumed with Bayesian probabilities. For him case of serious event:

18

where:

n '_ {\ mathit {IMN}} - number of people with normal mobility;

n '_ {\ mathit {IMR}} - number of people with reduced mobility;

n '_ {\ mathit {IMA}} - number of people with assisted mobility;

P ( MN | A {{mathit {GSI}}) - probability that after a serious incident, a person's mobility is normal;

P ( MR | A {{mathit {GSI}}) - probability that after the occurrence of a serious incident, a person's mobility will be reduced;

P ( MA | A {{mathit {GSI}}) - probability that following the occurrence of a serious incident, a person's mobility will be assisted;

n '_ {\ mathit {IT}} - total number of people trapped in Evacuation Area I.

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If the gravity hypothesis is considered false of the incident, which by definition presumes the absence of injuries serious, the previous expression takes the following form:

19

where:

P ( MN | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - the probability that a person's mobility is normal in case the incident is not serious;

P ( MR | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - the likelihood of a person's mobility being reduced if the incident is not serious;

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On the other hand, the conditional probabilities used are related to the probabilities of occurrence of minor, serious and deceased injuries when a serious accident occurs in a road tunnel. This means
that:

twenty

where:

P ( MR | A {{mathit {GSI}}) - probability that following the occurrence of a Serious Incident, a person's mobility will be reduced;

P ( HL | A _ {\ mathit {GSI})) is the probability that those involved in an accident suffer minor injuries if the hypothesis that the event was serious.

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Similarly:

twenty-one

where:

P ( MA | A {{mathit {GSI}}) - probability that following the occurrence of a Serious Incident, the mobility of a person will be assisted;

P ( HG | A {{mathit {GSI}}) - probability that those involved in an accident suffer serious injuries if the hypothesis that the event was serious is true;

P ( F | A _ {\ mathit {GSI}}) - the probability that those involved in an accident will die if the hypothesis that the event was serious is true.

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In the previous expression, the pessimistic approach to the model from the point of view of the evacuation, since we consider that both the seriously injured and the deceased are included in the category of evacuated potentials with assisted mobility. In consecuense:

22

where:

P ( MN | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - Probability that a person's mobility is normal in case the incident is not serious;

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On the other hand:

2. 3

where:

P ( MR | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - The likelihood that a person's mobility will be reduced if the incident is not serious;

P ( HL | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - is the probability that those involved in an accident suffer minor injuries if the hypothesis that the event was serious is false.

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And finally:

24

where:

P ( MN | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - Probability that a person's mobility is normal in case the incident is not serious;

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11. The distance from the countercurrent mouth of the tunnel until the end of the Evacuation Area II is assumed equal to the distance to the CCTV camera that has captured the incident, that is to say:

25

where:

d _ {\ mathit {CAM}} ( n _ {\ mathit {CCTV}}) - represents the distance to the CCTV camera that has captured the incident.

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12. The number of vehicles in the second evacuation area (evacuation area II) whose drivers and passengers must be evacuated n '_ {\ mathit {IIV}} can be calculated simply, subtracting the amount of vehicles trapped in the tunnel since the occurrence of the event n _ {\ mathit {VAT}}, the total number of vehicles directly involved in the accident n _ {\ mathit {VDI}}:

26

13. The delay time in the detection of the incident obviously equals the input variable homologue:

27

In Table 2, the parameters are described used in the expressions described above.

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TABLE 2 Summary of the Subsystem parameters of Incidents

28

29

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2 Evacuation Subsystem

Road tunnel incidents involve such severity and risk that it is often advised to decree the immediate evacuation of people in your inside. As indicated in the previous section, they differ two scenarios in a road tunnel: a first area of evacuation (Evacuation Area I) and a second evacuation area (Evacuation Area II). For the intrinsic differences to each of the areas considered, a mathematical algorithm has been built for each of the scenarios, as described in continuation.

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2.1 Subsystem for Evacuation Area I

For the definition of the evacuation subsystem (SE) for the first evacuation area, the different variables that define the mathematical algorithm.

The SE depends directly on the results of the Incident Subsystem (SSI) previously developed, so that some SSI output variables serve as input to the SE, as they are:

?

a '_ {\ mathit {BIDIREC}} - Boolean variable that indicates the possibility of bidirectionality in the evacuation process of the first evacuation area.

?

d '_ {\ mathit {I} 1} - distance from the countercurrent mouth of the tunnel to the beginning of the first evacuation area. Recall that it is defined as the distance from the mouth to the gallery immediately preceding the place of occurrence of the incident, in case that gallery existed or, otherwise, would be equal to zero.

?

d '_ {\ mathit {I} 2} - distance from the countercurrent mouth of the tunnel to the end of the first evacuation area, assumed equally, for the case in which the bidirectionality of the evacuation was false, at the distance to the incident center ( d _ {\ mathit {SI}}) plus one third of the distance between CCTV cameras (\ Delta_ {CAM}).

?

n '_ {\ mathit {IT}} - total number of people to evacuate from the first evacuation area that corresponds to the sum of people with normal mobility ( n ' _ {\ mathit {IMN}}), with mobility reduced ( n '_ {mathit {IMR}}) and with assisted mobility ( n ' _ {\ mathit {IMA}}), directly involved in the incident.

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As the mathematical algorithm was defined detailing the operation of the SE, the need for Define new input variables.

The scenario defined as the first area of evacuation, it turns out for the analysis that a extremely complex and highly uncertain scenario for the following reasons:

?

Location Ignorance of people to evacuate within this first evacuation area. SSI development assumes predictable knowledge of the amount of light, heavy vehicles and buses within the first area of evacuation, but it is extraordinarily difficult to know the distribution of them as well as the exact amount and location of people on stage.

?

Ignorance of lengths and characteristics of possible evacuation routes. He ignorance of the position of people on stage makes practically impossible to know the distances to travel as well as the complexities of evacuation routes.

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Due to these uncertainties in the study of the evacuation process, the algorithm developed is presented as a stochastic and simple character. The stochastic approach allows to cover the multiple and unpredictable situations that may be found in the first evacuation area, while a simple approach allows to avoid the great diversity of possible situations that may arise with respect to human behaviors.
nas.

The subsystem is responsible for performing a estimation of the evacuation process with respect to the maximum time necessary for all people trapped on stage reach a safe place from the moment of occurrence of the event, so that additional information on the consequences of the event The subsystem uses the following expression for the calculation of the evacuation time of each person:

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30

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where:

t _ {\ mathit {EI_ {i}}} - evacuation time of the first evacuation area of the ith person;

t _ {\ mathit {pm_ {i}}} - pre-movement time of the ith person, corresponding to the time elapsed between the moment the accident occurs until this person begins the movement;

d _ {\ mathit {mov_ {i}}} - distance traveled by the i-th person from their original position on stage to leave it;

v _ {\ mathit {mov_ {i}}} - average speed of movement of the ith person during his departure from the first evacuation area.

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The evacuation time of the i-th person, t _ {\ mathit {EI_ {i}}}, is a random variable due to the randomness of the parameters on which it depends according to the previous expression. It is logical to assume that pre-movement times and average travel speeds have different probability distribution functions for different mobility groups. Although the type of distribution function is the same, the parameters that characterize it (mathematical hope, standard deviation) are different for people with normal, reduced mobility or
assisted.

The same does not happen with the distance traveled by the i-th person since regardless of their mobility can be initially in any position on stage and travel an escape route from it that is independent of the mobility.

Knowing the distribution functions or probability density functions of the variables t _ {\ mathit {pm_ {i}}} and v _ {\ mathit {mov_ {i}}} for each of the mobility groups, and the Unique function for the variable d _ {\ mathit {mov_ {i}}}, as well as the number of people in each group on the stage, can be simulated using the Monte Carlo methods, each hypothetical case of evacuation of all those involved in this process. Selecting the longest resulting in each case corresponds to simulated total evacuation time of the first evacuation area (T {\ mathit TEI {}}).

Repeating this process n _ {\ mathit {iter}} times provides a sample of volume n _ {\ mathit {iter}} of T _ {\ mathit {TEI}} and its statistical processing allows its adjustment to a function of known distribution or its estimation by the histogram, as well as the calculation of its main quantitative characteristics. We will consider that the main output variable of the model will be the percentile for a given probability p (usually greater than or equal to 0.9) of the total evacuation time of the first evacuation area.

This has a total evacuation time value such that the real value in any case, with a probability p , will be less than or equal to it. For the reasons explained above, a mathematical algorithm was developed as follows:

31

where:

T _ {\ mathit {TEI_ {j}}} - Total Evacuation Time of Scenario I (first evacuation area) for the j-th embodiment;

t ^ {(\ mathit {MN})} _ {\ mathit {EI_ {ij}}} - evacuation time of the ith person with normal mobility in the jth embodiment;

t ^ {(\ mathit {MR})} _ {\ mathit {EI_ {ij}}} - evacuation time of the ith person with reduced mobility in the jth embodiment;

t ^ {(\ mathit {MA})} _ {\ mathit {EI_ {ij}}} - evacuation time of the ith person with assisted mobility in the jth embodiment;

max {...} - maximum value of the set.

Likewise:

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32

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where:

t ^ {(\ mathit {MN})} _ {\ mathit {pm_ {ij}}} - pre-movement time of the ith person with normal mobility in the jth iteration;

t ^ {(\ mathit {MR})} _ {\ mathit {pm_ {ij}}} - pre-movement time of the ith person with reduced mobility in the jth iteration;

t ^ {(\ mathit {MA})} _ {\ mathit {pm_ {ij}}} - pre-movement time of the ith person with assisted mobility in the jth iteration;

d _ {\ mathit {mov_ {ij}}} - distance traveled by the i-th person in the j-th iteration;

v ^ {(\ mathit {MN})} _ {\ mathit {mov_ {ij}}} - average speed of movement of the ith person with normal mobility in the jth iteration;

v ^ {(\ mathit {MR})} _ {\ mathit {mov_ {ij}}} - average speed of movement of the ith person with reduced mobility in the jth iteration;

v ^ {(\ mathit {MA})} _ {\ mathit {mov_ {ij}}} - average speed of movement of the ith person with assisted mobility in the jth iteration.

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From the defined input variables, corresponding to the SSI output variables, as well as considering as input the distribution laws that define the corresponding random variables with the different times of pre-movement, distances traveled and speeds of displacement, the subsystem generates four time samples evacuation maxima each of equal volume number of iterations selected, three of the samples correspond to the maximum evacuation times by type of mobility and the fourth collect the maximum evacuation time in each iteration. Every Sample is statistically processed using the following methodology:

one)

Be calculate the main quantitative characteristics of the sample.

2)

Adjustment or estimation of the distributions of the random variable T _ {mathit {TEI}} is made. This initially involves adjusting the sample to the normal, normal logarithmic or uniform distributions. D'Agostino's K2 tests were used for the first two (previously calculating the natural logarithm of the sample elements in the case of checking the normal logarithmic law) and the modified Anderson-Darling test for the case of the uniform distribution If none of the three distributions is satisfied, the distribution is estimated using its histogram, using the Freedman and Diaconis rule to calculate the width of the sample interval.

3)

The percentile is calculated for a probability of confidence p that can be represented by the following generic formula:

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33

       \ vskip1.000000 \ baselineskip
    

where:

F <-1} _ {\ mathit {TEI} ( p ) - inverse distribution function of T {\ mathit {TEI}) evaluated for the probability of confidence p .

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2.2 Subsystem for Evacuation Area II

As was the case for the first area of evacuation, this subsystem is dependent on the SSI, so that certain input variables of the SEII, correspond to some SSI output variables:

one)

d '_ {\ mathit {II}} - distance from the countercurrent mouth of the tunnel to the end of the second evacuation area.

2)

n '_ {\ mathit {IIV}} - total number of vehicles in the second evacuation area whose drivers and passengers must be evacuated.

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In the evacuation analysis in this scenario assumes that the mobility of trapped people is not is affected by the event, so continuing with the methodology followed for the first evacuation area, the algorithm mathematician who defines the evacuation subsystem for this scenario is:

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3. 4

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where:

T {{mathit {TEII_ {j}}} - Total Evacuation Time of Evacuation Area II (second evacuation area) for the jth embodiment;

t {{mathit {TEII_ {ij}}} - evacuation time of the ith person in the jth embodiment;

q {{mathit {j}} - number of people to evacuate in the j-th embodiment;

n _ {\ mathit {iter}} - number of iterations (realizations);

max {...} - maximum value of the set.

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The number of people to evacuate in each embodiment q _ {\ mathit {j}} is defined by the expression:

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35

       \ vskip1.000000 \ baselineskip
    

where:

n '_ {\ mathit {IIVL}} - number of light vehicles in the second evacuation area (Evacuation Area II);

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36

       \ vskip1.000000 \ baselineskip
    

- number of coaches on the Stage (second evacuation area);

37

- amount of heavy vehicles on the Stage (second evacuation area);

P ( AVPA ) - probability that a vehicle, from the set of heavy vehicles and coaches that usually travel through the tunnel, is a coach;

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Evidently:

38

\ tilde {\ mathit {k}} _ {\ mathit {VL_ {j}}} - coefficient of occupation of a light vehicle in the jth iteration, which is assumed as a random integer uniformly distributed between 1 and 5;

\ tilde {\ mathit {k}} _ {\ mathit {VP_ {j}}} - coefficient of occupation of a heavy vehicle in the jth iteration, which is assumed as a random integer uniformly distributed between 1 and 2;

\ tilde {\ mathit {k}} _ {\ mathit {VA_ {j}}} - coefficient of occupation of a coach in the j-th iteration, which it is assumed as a random integer uniformly distributed between 20 and 40.

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The evacuation time of each person in each iteration is calculated using the formula:

39

3. Decision Making Subsystem

Considering the decisions to be taken by the operator of the tunnel control center, a algorithm based on decision trees for Expert Systems such as expressed below:

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3.1 Notice to Exploitation Personnel

This decision is conditioned by the operator's finding of the occurrence of a incident:

40

That is, the variable a _ {\ mathit {SI}} is true. Figure 3 shows a decision tree for notification to operating personnel. The logical expression expressed by the notice to operating personnel is as follows:

41

3.2 Emergency Services Prevention (112)

According to the protocols (records) of action of Control center operators, prevention of services emergency is subject to the closing of at least one lane of the tunnel as long as the tunnel has more than one lane, or what it is the same:

42

Figure 4 shows a decision tree for Emergency services prevention.

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3.3 Activation of Emergency Services

There are a number of events that lead to activation of emergency services and their personification in the tunnel: the total closing of the tunnel, the occurrence of a fire in its inside, a spillage of dangerous substance or suspicion of existence of at least one injured due to the accident. Figure 5 shows a decision tree for the activation of services of emergencies, in accordance with an embodiment of the present invention. The expression that indicates the need to make the decision to activate emergency services is the following:

43

3.4 Need for immediate evacuation

The decree of the need to evacuate tunnel is determined by the emergence of a fire or the discharge or escape of dangerous substances. Figure 6 shows a decision tree for the need for evacuation, according to An embodiment of the present invention.

44

3.5 Bidirectionality of Scenario I (first area of evacuation) for evacuation

The possibility of evacuation in both directions (bidirectionality of Evacuation Area I) is given by the total or partial obstruction of the tunnel. Figure 7 shows a tree of decisions for the bidirectionality of the first area of evacuation, according to an embodiment of the present invention. Figure 7 shows the decision tree to which the mathematical expression of the possibility of bidirectionality.

Four. Five

3.6 Number of tunnel lanes that close to the circulation

It is assumed that the operator is able to determine the number of lanes blocked by CCTV images.

Figure 8 shows a decision tree for the number of lanes to close, according to an embodiment of The present invention. The number of lanes to close is equal to number of clogged lanes as indicated by the expression:

46

3.7 Total tunnel closure

In the event that the total number of lanes clogged equals the total number of lanes in the tunnel is due decree the total closure of the tunnel, as indicated by the expression:

47

Figure 9 shows a decision tree for the closure of the tunnel, in accordance with an embodiment of the present invention.

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3.8 Maximum lighting in the tunnel

The maximum lighting sequence is activated in case of fire inside the tunnel or substance spill dangerous, as the expression indicates:

48

Figure 10 shows a decision tree for the activation of the maximum level of illumination, according to a embodiment of the present invention.

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3.9 Information to Users

The need to inform users in case of the occurrence of an incident is conditioned by the detection and confirmation by the operator of an incident, what is coming defined by the expression:

49

Figure 11 shows a decision tree for inform users, according to an embodiment of the present invention

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4. Integrated System

From the method and the three subsystems, has implemented an intelligent system for the management of emergency, which is accompanied by a secondary system that generates and / or modify the data files that introduce the geometry and characteristics of the concrete tunnel of application of the system main integrated. An example of a generation tool This data is illustrated in Figure 12. Figure 13 shows a implementation example of the introduction of a series of input variables that define an emergency situation detected

The integrated system allows you to enter a series of input variables that define the emergency situation detected An example of a tool that allows you to enter These input variables are illustrated in Figure 13. First place, for the system to work properly, it must be select the data file that defines the geometry and tunnel characteristics (generated with the secondary system). He System user must indicate using five Boolean variables, the veracity of the occurrence of an Incident, of a Fire, of Poured, of Injured (s) and if it is an incident classified as serious. Enter another group of variables Numerical

?

Number of lanes clogged

?

Camera number showing the incident.

?

Approximate location of the incident in the sector.

?

Amount of light vehicles involved in the incident.

?

Amount of heavy vehicles involved in the incident.

?

Number of coaches involved in the incident

?

Total number of vehicles trapped inside the tunnel.

?

Amount of heavy vehicles and Buses trapped inside the tunnel.

?

Delay time in incident detection.

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Once the input variables have been introduced, firstly, by clicking on the Decisions button of the exemplified tool, the system generates the proposal for decisions to be made by the operator of the tunnel control center depending on the severity and conditions of the incident , among the following, which are exemplified in Figure 14:

?

Notice to staff of exploitation.

?

Prevention of the services of emergency.

?

Activation of the services of emergency.

?

Evacuation need immediate.

?

Tunnel closure

?

Maximum level of illumination.

?

Inform the users.

?

Bidirectionality of the first evacuation area

?

Number of lanes a close.

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In any case, the system allows, through the button Additional information of the event , to display information that can be useful when analyzing the scope and severity of the incident, as shown in Figure 15 and offering a series of numerical results.

?

Distance to the beginning of Evacuation Area I.

?

Distance to the end of the Area of Evacuation II.

?

Total number of people to evacuate in Evacuation Area I.

?

Number of people with normal mobility in the Evacuation Area I.

?

Number of people with reduced mobility in the Evacuation Area I.

?

Number of people with assisted mobility in the Evacuation Area I.

?

Distance to the end of the Area of Evacuation II.

?

Number of vehicles to evacuate of the Evacuation Area II.

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On the other hand, in the event that the need for immediate evacuation is activated in the decision proposal, the system allows the option of obtaining a prognosis on the evacuation time for each of the evacuation areas considered. By clicking on the Evacuation Analysis button , the evacuation subsystem starts working, requiring the user to enter a series of Input Variables for evacuation models , as shown in Figure 16. These variables can be divided into three groups :

?

General variables of the models : Number of iterations generated by the Monte Carlo Method, level of confidence or significance for adjusting the distribution (to choose between 0.1 0.05 and 0.01) and level of confidence for the calculation of the percentile (a choose between 0.9, 0.95 and 0.99).

?

Variables typical of the Evacuation Area I : It allows the user to introduce the behavioral variables corresponding to the persons trapped in what has been defined as the first evacuation area according to their mobility. Mean ( M ) and standard deviation ( Sigma ) for pre-movement times and travel speeds for normal, reduced and assisted mobility.

?

Variables typical of Evacuation Area II : In the same way as for the first evacuation area, the program allows you to enter the values for the behavioral variables of people trapped in the second evacuation area (Mean M and standard sigma deviation for time of pre movement and speed of movement of the users to evacuate). The value of the response time ( tpm0 ) and travel speed ( vmov0 ) of the person initiating the evacuation (sender) is entered. This block also defines the occupancy coefficients by type of vehicle (light VL, heavy VP and VA coaches) through a range of values, as well as the probability that the coach and heavy vehicle set is a coach.

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Once all the variables of Own entry for evacuation models, by clicking on the button continue evacuation subsystem shows so consecutive results obtained on the analysis of the evacuation, as shown in figures 17 and 18 (first and second evacuation areas, respectively). Analyzing the samples obtained, the system obtains as the main output data the percentile of total evacuation time, in addition to the type of law of probability distribution to which the sample fits corresponding, mathematical hope, standard deviation and range of values

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Example of embodiment of the invention

The intelligent system was applied to the tunnel of Lantueno of the A-67 Highway (Cantabria - La Meseta), defining the data file with the characteristics of the tunnel. Be they assumed the following two types of scenarios (Scenario A and Scenario B), whose layout is illustrated, respectively, in the Figures 19 and 20.

Scenario A corresponds to an accident occurred in the area near the exit, being caught the largest possible number of vehicles. They are considered a series of cases.

?

Case 1.1. - Accident with fire (no spillage). Considering the location of the accident in zone 3, two obstructed lanes and the existence of injuries, the following scenario variants were considered:

\ circ

Case 1.1.1. Accident between two Light vehicles.

\ circ

Case 1.1.2 Accident between a Light vehicle and a heavy vehicle.

\ circ

Case 1.1.3. Accident between two Heavy vehicles.

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?

Case 1.2. - Accident with fire (with spillage). Considering the other values indicated above in addition to the following variants:

\ circ

Case 1.2.1. Accident between two Light vehicles.

\ circ

Case 1.2.2. Accident between a Light vehicle and a heavy vehicle.

\ circ

Case 1.2.3. Accident between two Heavy vehicles.

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?

Case 1.3 .- Accident without fire (with spillage). Considering the other values indicated above in addition to the following variants:

\ circ

Case 1.3.1. Accident between two Light vehicles.

\ circ

Case 1.3.2. Accident between a Light vehicle and a heavy vehicle.

\ circ

Case 1.3.3. Accident between two Heavy vehicles.

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?

Case 1.4. - Accident with fire (with spillage). Considering the other values indicated above in addition to the following variants:

\ circ

Case 1.4.1. Accident between three Light vehicles and a heavy vehicle.

\ circ

Case 1.4.2. Accident between a Light vehicle and three heavy vehicles.

\ circ

Case 1.4.3. Accident between three heavy vehicles and three light vehicles.

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Scenario B corresponds to the occurrence of an incident in the intermediate zone of the tunnel, considering the cases most likely according to the tunnel incident log. Be They considered a series of cases.

?

Case 2.1 . Accident with fire (with spillage).

\ circ

Case 2.1.1. Vehicle light.

\ circ

Case 2.1.2. Vehicle heavy.

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?

Case 2.2 . Accident with fire (no spillage).

\ circ

Case 2.2.1. Vehicle light.

\ circ

Case 2.2.2. Vehicle heavy.

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?

Case 2.3 . Accident without fire (with spillage).

\ circ

Case 2.3.1. Vehicle light.

\ circ

Case 2.3.2. Vehicle heavy.

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Input Data

In Table 3, the input data is collected of the system.

TABLE 3 Input data for the Intelligent System integrated

fifty

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51

Results on the proposed decisions

The system offers the recommended decisions to undertake by the operator of the tunnel control center (Tables 4 and 5), coinciding with those included in the protocols (action sheets) according to the emergency situation considered:

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TABLE 4 Decisions to be taken by the operator: Scenario TO

52

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TABLE 5 Decisions to be taken by the operator: Scenario B

53

54

Results on additional incident information

Regarding the numerical results on the incident, the system allows the option to display information additional that may be useful when communicating with external services when estimating the scope of events

The results are shown in Tables 6 and 7 on the estimation of people involved and their affectations

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TABLE 6 Numerical results of the incident: Scenario TO

55

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TABLE 7 Numerical results of the incident: Scenario B

56

Regarding the additional information of the incident, are results that vary in each of the cases due because it is a random variable that depends on a probability of occurrence obtained. The characteristics of the event They are decisive when estimating the number of people involved and their involvement.

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Results on evacuation in Scenario A and B

In Figures 21-24, it They show the results obtained. For the cases of Scenario B, Due to the severity assumed, the estimate reflects that No user will have normal mobility. Observing the results obtained in both Scenarios, it is verified that for the Scenario A cases, the percentile of Total Evacuation Time is superior to the cases of Scenario B, due to the assumption of a greater number of vehicles trapped in Evacuation Area II.

In summary regarding the systems Conventional: There are currently some intelligent systems applied to different areas including transport but oriented to favor operability, as in the case of automatic toll systems, but none have been applied to Safety study in road tunnels. As for the incident subsystem, no literature is included in the literature similar system that performs an analysis of the recorded accident offering an estimate of the possible consequences of same.

On the other hand, in relation to subsystems of evacuation, for the first time an evacuation model has been proposed which represents the specific characteristics of evacuation in A road tunnel. The same goes for the subsystem of decisions, since no system or subsystem of decision that applies to environments such as tunnels highway.

Although in the present report only represented and described particular embodiments of the invention, the person skilled in the art will know how to introduce modifications and replace some technical characteristics for other equivalents, depending on the requirements of each case, without departing from the scope of protection defined by the appended claims.

Claims (15)

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1. A method for emergency management by supporting security decision making in a Road tunnel, which includes the stages of:

?

Identify a scenario of road tunnel through a first evacuation area (Area of Evacuation I) and a second evacuation area (Area of Evacuation II), where the first evacuation area is the area where vehicles and people directly involved are found in the emergency situation, as well as the people who are in imminent danger from the emergence of fire or discharge of dangerous substances; and the second evacuation area is an area adjacent to the first evacuation area, where find the vehicles trapped in the traffic jam produced for the emergency situation;

?

Identify the possibility of bidirectionality ( a '_ {\ mathit {BIDIREC}}) in the evacuation process of the first evacuation area;

?

Calculate:

-

The distance ( d _ {\ mathit {SI}}) from the countercurrent mouth of the tunnel to the place of occurrence of the incident;

-

The distance ( d '_ {\ mathit {I} 1}) from the countercurrent mouth of the tunnel to the beginning of the first evacuation area (Evacuation Area I);

-

The distance ( d '_ {\ mathit {I} 2}) from the countercurrent mouth of the tunnel to the end of the first evacuation area (Evacuation Area I);

?

Calculate the number of people to evacuate;

?

Calculate evacuation time from each person;

?

Propose an appropriate decision depending on the emergency detected.

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2. The method of claim 1, wherein said step of calculating the distance from the countercurrent mouth of the tunnel to the place of occurrence of the incident ( d {{mathit {SI}}) is performed by the following expression: 57 where: d _ {\ mathit {SI}} - is the distance from the countercurrent mouth of the tunnel to the approximate place of occurrence of the incident; d _ {\ mathit {CAM}} ( n _ {\ mathit {CCTV}}) - distance from the countercurrent mouth of the tunnel to the CCTV camera number n _ {\ mathit {CCVT}} (the camera number it detects the incident automatically in the Control Center); \ delta _ {\ mathit {ZM}} - distance from the zone dead of the camera; \ delta _ {\ mathit {CCTV}} - place of tunnel sector captured by the CCTV camera where the incident. This sector is commonly less than or equal to 150 m and is known for each tunnel. If for example \ delta _ {\ mathit {CCTV}} = 1, the event occurred in the first half of the tunnel; \ Delta_ {CAM} - distance between cameras.

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3. The method of claim 2, wherein the distances to each of the tunnel chambers from the mouth of input can be calculated using the expression: 58 where: d {\ mathit {CAM} 1} - represents the distance between the countercurrent mouth of the tunnel to the first CCTV camera; \ Delta _ {\ mathit {CAM}} - distance between tunnel chambers

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4. The method of any one of the preceding claims, wherein said step of calculating the distance ( d 'I1) from the countercurrent mouth of the tunnel to the beginning of the first evacuation area is performed by the following expression:

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59

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where: d _ {\ mathit {GAL_ {i}}} - the distance from the countercurrent entrance of the tunnel to the ith gallery; d _ {\ mathit {GAL_ {j}}} - the distance from the countercurrent entrance of the tunnel to the jth gallery; d _ {\ mathit {SI}} - the distance from the countercurrent mouth of the tunnel to the approximate (center) place of occurrence of the incident; A _ {\ mathit {G}} - variable that indicates if there is a gallery before gallery i.

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5. The method of claim 4, wherein the distances to the different tunnel galleries are calculated through the expression: 60 where: d {{mathit {GAL} 1} is the distance from the countercurrent mouth of the tunnel to the first gallery; \ Delta _ {\ mathit {GAL}} is the distance between the tunnel galleries; m _ {\ mathit {GAL}} is the total number of tunnel galleries.

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6. The method of any of the preceding claims, wherein said step of calculating the distance ( d '_ {\ mathit {I} 2)) from the countercurrent mouth of the tunnel to the end of the first evacuation area (Evacuation Area I) is calculated by the expression: 61 where: 62 Y where: d _ {\ mathit {GAL_ {k}}} - is the distance from the countercurrent entrance of the tunnel to the k-th gallery; L {mathit {T}) - is the length of the tunnel;

         \ newpage
      

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d _ {\ mathit {SI}} - is the distance from the countercurrent mouth of the tunnel to the approximate (center) place of occurrence of the incident; \ Delta_ {CAM} - represents the distance between the tunnel chambers; A_ {GI} - indicates the existence of a gallery post incident; a '_ {\ mathit {BIDIREC}} - bidirectionality of tunnel evacuation.

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7. The method of any of the previous claims, wherein said number of people to evacuate comprises the number of people to evacuate in the first area of evacuation and the number of people to evacuate in the second area of evacuation. 8. The method of claim 7, wherein the number of people to be evacuated in the first evacuation area ( n '_ {mathit {IT}}) is calculated by the expression: 63 where: k _ {\ mathit {VL}} - is the passenger occupation assumed by light vehicle; k {{mathit {VP} P}) is the passenger occupation assumed by heavy vehicle; k {{mathit {VA}} is the passenger occupancy assumed by coach; n _ {\ mathit {VLDI}} - number of light vehicles directly involved in the incident; n _ {\ mathit {VPDI}} - number of heavy vehicles directly involved in the incident; n _ {\ mathit {VADI}} - number of coaches directly involved in the incident.

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9. The method of claim 7, wherein the number of people to evacuate in the first evacuation area ( n '_ {\ mathit {IT}}) is the sum of the people to evacuate with normal mobility ( n ' _ { \ mathit {IMN}}, people with reduced mobility ( n '_ {\ mathit {IMR}}) and people with assisted mobility ( n ' _ {\ mathit {IMA}}). 10. The method of claim 9, wherein the number of people to be evacuated with normal mobility mobility ( n '_ {mathit {IMN}), persons with reduced mobility ( n ' _ {\ mathit {IMR}}) and people with assisted mobility ( n '_ {\ mathit {IMA}}) is calculated as follows:

?

In case of event serious:

64

where:

n '_ {\ mathit {IMN}} - number of people with normal mobility;

n '_ {\ mathit {IMR}} - number of people with reduced mobility;

n '_ {\ mathit {IMA}} - number of people with assisted mobility;

P ( MN | A {{mathit {GSI}}) - probability that after the occurrence of a Serious Incident, a person's mobility is normal;

P ( MR | A {{mathit {GSI}}) - probability that following the occurrence of a Serious Incident, a person's mobility will be reduced;

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P ( MA | A {{mathit {GSI}}) - probability that following the occurrence of a Serious Incident, the mobility of a person will be assisted;

n '_ {\ mathit {IT}} - total number of people trapped in Evacuation Area I.

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?

In case the event is not serious:

65

where:

P ( MN | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - Probability that a person's mobility is normal in case the incident is not serious;

P ( MR | \ bar {\ mathit {A}} _ {\ mathit {GSI}}) - The likelihood that a person's mobility will be reduced if the incident is not serious;

and where

66

where:

P ( MR | A {{mathit {GSI}}) - probability that following the occurrence of a Serious Incident, a person's mobility will be reduced;

P ( HL | A _ {\ mathit {GSI})) is the probability that those involved in an accident suffer minor injuries if the hypothesis that the event was serious.

Y:

67

where

P ( MA | A {{mathit {GSI}}) - probability that following the occurrence of a Serious Incident, the mobility of a person will be assisted;

P ( HG | A {{mathit {GSI}}) - probability that those involved in an accident suffer serious injuries if the hypothesis that the event was serious is true;

P ( F | A _ {\ mathit {GSI}}) - the probability that those involved in an accident will die if the hypothesis that the event was serious is true.

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11. The method of any of the preceding claims, wherein said evacuation time of each person ( t _ {\ mathit {EI_ {i}})) is calculated by the following expression: 68 where: t _ {\ mathit {EI_ {i}}} - evacuation time of the first evacuation area of the ith person; t _ {\ mathit {pm_ {i}}} - distribution function or probability density function representing the pre-movement time of the ith person, corresponding to the time elapsed between the moment the accident occurs until that this person begins the movement; d _ {\ mathit {mov_ {i}}} - distance traveled by the i-th person from their original position on stage to leave it; v _ {\ mathit {mov_ {i}}} - distribution function or probability density function that represents the average speed of movement of the ith person during his departure from the first evacuation area.

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12. The method of claim 11, wherein said evacuation time of each person is calculated statistically according to the following expression: 69 where: T _ {\ mathit {TEI_ {j}}} - Total Evacuation Time of Scenario I (first evacuation area) for the j-th embodiment; t ^ {(\ mathit {MN})} _ {\ mathit {EI_ {ij}}} - evacuation time of the ith person with normal mobility in the jth embodiment; t ^ {(\ mathit {MR})} _ {\ mathit {EI_ {ij}}} - evacuation time of the ith person with reduced mobility in the jth embodiment; t ^ {(\ mathit {MA})} _ {\ mathit {EI_ {ij}}} - evacuation time of the ith person with assisted mobility in the jth embodiment; max {...} - maximum value of the set. Y: 70 where: t ^ {(\ mathit {MN})} _ {\ mathit {pm_ {ij}}} - pre-movement time of the ith person with normal mobility in the jth iteration; t ^ {(\ mathit {MR})} _ {\ mathit {pm_ {ij}}} - pre-movement time of the ith person with reduced mobility in the jth iteration; t ^ {(\ mathit {MA})} _ {\ mathit {pm_ {ij}}} - pre-movement time of the ith person with assisted mobility in the jth iteration; d _ {\ mathit {mov_ {ij}}} - distance traveled by the i-th person in the j-th iteration; v ^ {(\ mathit {MN})} _ {\ mathit {mov_ {ij}}} - average speed of movement of the ith person with normal mobility in the jth iteration; v ^ {(\ mathit {MR})} _ {\ mathit {mov_ {ij}}} - average speed of movement of the ith person with reduced mobility in the jth iteration; v ^ {(\ mathit {MA})} _ {\ mathit {mov_ {ij}}} - average speed of movement of the ith person with assisted mobility in the jth iteration.

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13. The method of claim 7, wherein the number of people to evacuate in the second evacuation area will Calculate by expression: 71 where: T {{mathit {TEII_ {j}}} - Total Evacuation Time of Evacuation Area II (second evacuation area) for the jth embodiment; t {{mathit {TEII_ {ij}}} - evacuation time of the ith person in the jth embodiment; q {{mathit {j}} - number of people to evacuate in the j-th embodiment; n _ {\ mathit {iter}} - number of iterations (realizations); max {...} - maximum value of the set.

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where the number of people to evacuate in each embodiment q _ {\ mathit {j}} is defined by the expression: 72 where: n '_ {\ mathit {IIVL}} - number of light vehicles in the second evacuation area (Evacuation Area II); n '_ {\ mathit {IIVA}} = P ( AVPA ) \ cdot n ' _ {\ mathit {IIVPA}} is the number of coaches on the Stage (second evacuation area); n '_ {\ mathit {IIVP}} = n ' _ {\ mathit {IIVPA}} - n '_ {\ mathit {IIVA}} is the amount of heavy vehicles on the Stage (second evacuation area); P ( AVPA ) - probability that a vehicle, from the set of heavy vehicles and coaches that usually travel through the tunnel, is a coach; \ tilde {\ mathit {k}} _ {\ mathit {VL_ {j}}} - coefficient of occupation of a light vehicle in the jth iteration, which is assumed as a random integer uniformly distributed between 1 and 5; \ tilde {\ mathit {k}} _ {\ mathit {VP_ {j}}} - coefficient of occupation of a heavy vehicle in the jth iteration, which is assumed as a random integer uniformly distributed between 1 and 2; \ tilde {\ mathit {k}} _ {\ mathit {VA_ {j}}} - coefficient of occupation of a coach in the j-th iteration, which it is assumed as a random integer uniformly distributed between 20 and 40.

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14. The method of claim 13, wherein the evacuation time of each person in each iteration is calculated by the formula: 73

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15. An integrated and automated intelligent system for the management of an emergency in a road tunnel, characterized in that it comprises:

?

A subsystem of incidents, configured to perform a predictive analysis of the possible development and consequences of an incident, where said event is any accident, caused by one or several vehicles motor vehicles that pass through the tunnel, causing real damage or potential over people inside and eventually advise their evacuation;

?

An evacuation subsystem; Y

?

A subsystem making decisions;

said intelligent system being integrated and automated configured to carry out the steps of the method of according to any of claims 1 to 14.