JP2016005294A - Collision damage reduction method and collision damage reduction system - Google Patents

Abstract

PROBLEM TO BE SOLVED: To estimate magnitude of latent collision risk with high probability as possible, for efficiently reducing collision damage.SOLUTION: A collision occurrence probability and magnitude of damage when collision occurs, considering size and weight of an obstacle on an accident occurrence place, season and time zone, are expressed by a statistic model, based on past accident data for every route, and magnitude of collision risk on a zone where a train is traveling, is estimated, and when the estimated collision risk is high, speed control is performed.

Description

  The present invention relates to a collision damage reduction method and a collision damage reduction system, and more particularly, to a method of reducing damage caused by a collision between a railway vehicle and an obstacle and a system using the method.

  In order to realize safe and reliable railway operations, how to reduce collisions between trains and obstacles (for example, animals such as cars and deer) has become an issue. Information on where and where a train has collided in the past is often recorded and stored in a database. However, such records and databases are helpful in discussing safety improvements, but there are few examples of systematic use.

  Conventionally, in order to reduce damage caused by a collision (collision damage), a driver travels while paying attention to the front in a frequent collision accident section based on past experience. In order to reduce collision damage, a special signal light emitter is installed on the ground and a protective radio is installed on the vehicle at the level crossing.

  Collision prediction technology is being developed in the automotive field. For example, Patent Document 1 discloses a technique for predicting a collision form based on a positional relationship at the time of collision between the host vehicle and another vehicle.

Japanese Patent No. 5262394 JP 2011-207353 A JP 2011-116300 A JP 2013-111247 A Japanese Patent No. 5056033

Terada, Ito, Yamakawa “3D Collision Analysis of Organized Vehicles Using Multibody Dynamics”, Proceedings of the Symposium of the Federation of Railway Technology, 2011, Vol. 18, p. 301-304 Koji Omino, 3 others “Simulation of passenger behavior during a commuter train crossing accident”, Railway Research Institute report, January 2012, Vol. 26, No. 1, p. 21-26 Yuji Nagahama “Fundamental Study on Risk of Railroad Crossing Accident”, Journal of Japan Society of Civil Engineers, 1979, No. 290, p. 99-114. Yoko Takeuchi, 4 others "Operation simulator that can be reproduced at the driving curve level" Railway Research Institute report, April 2014, Vol. 28, No. 4, p. 41-46

  When mitigation of collision damage is realized based on driver's experience and attention (visual confirmation), there are individual differences in the mitigation effect. Special signal light emitters and protective radios are intended to reduce collision damage when risks become apparent. Therefore, it is powerless against potential risks.

  Similarly, many of the existing collision prediction techniques function by detecting an obstacle with an optical sensor or the like, or by supplementing the blind spot of the sensor with wireless communication. Therefore, these technologies are also powerless against potential risks.

  Information sharing on road traffic and railways is in the process of development, and even if technology is established, it will take time to disseminate. Also, tracking wild animals is impractical except for some rare animals.

  The present invention has been made to solve these problems. By estimating the potential collision risk with the highest possible probability, it is possible to effectively reduce collision damage. Objective.

  In order to achieve the above object, the collision damage mitigation method according to the present invention is based on the type of obstacle, the speed, the mass including passengers and cargo, and the state of the train such as the number of passengers. Using the first step (estimated damage estimation step) to estimate the magnitude of total damage and past accident data, the collision probability at a certain position is estimated for each obstacle type, season, and time zone. A second step of creating a collision probability map (collision probability map creating step), and a step of looking up the collision probability map and estimating the collision probability at each point based on the running pattern during train operation Multiply the 3rd step (collision probability estimation step), the occurrence damage estimated in the 1st step, and the collision probability estimated in the 3rd step for each type of obstacle to calculate the collision risk. 4 steps (collision risk calculation step), 5th step (collision risk evaluation step) for evaluating the degree of collision risk obtained in the 4th step based on a predetermined criterion, and collision evaluated in the 5th step And a sixth step (speed control step) for giving a speed control signal to the speed control device in accordance with the degree of risk.

  In other words, the present invention is based on the past accident data for each route, and the collision occurrence probability in consideration of the size and mass of the obstacle at the location where the accident occurred, the season and the time zone, and the magnitude of damage when a collision occurs. This is expressed by a statistical model, the magnitude of the collision risk in the section where the train is running is estimated, and speed control is performed when the estimated collision risk is large. Thereby, the damage when the collision with the obstacle occurs can be reduced.

  The collision damage mitigation system that uses the above collision damage mitigation method is an occurrence damage estimation means that estimates the magnitude of equipment damage and human damage from the type of obstacle and the state of the train, and the collision probability at a certain position as an obstacle. The occurrence probability estimation means for estimating the collision probability from the traveling pattern of the train, the occurrence damage estimated by the occurrence damage estimation means, and the collision probability estimated by the occurrence probability estimation means. A collision risk evaluation means for evaluating whether the collision risk is large from the product of the above, and a speed control means for controlling the traveling speed of the train when the collision risk evaluation means evaluates that the collision risk is large. Features.

  The collision damage mitigation system has a collision probability map creation unit that creates a collision probability map by estimating a collision probability at a certain position for each obstacle type, season, and time zone using past accident data. It is preferable. And it is preferable that a collision probability estimation means estimates the collision probability in each point by looking up the said collision probability map based on a running pattern at the time of train operation.

  According to the present invention, collision damage can be reduced without installing special equipment on the ground, and the safety of railway operation is improved.

  In addition, based on past objective data, a statistical model is used to mathematically determine the collision risk, and speed control is performed to reduce the collision risk, so there is a method that depends on the experience and attention of the conventional driver. The effects of individual differences and judgment delays are eliminated, and the effects of collision avoidance / prevention and damage reduction can be obtained stably.

It is a figure which shows the whole structure of the collision damage reduction system which concerns on embodiment of this invention. It is a figure explaining the main functions of the collision damage reduction system of FIG. It is a figure which shows the structure which implement | achieves the main function of a collision damage reduction system. It is a table | surface which shows the model parameter of an obstruction. It is a figure which shows an example of a collision probability map. It is a flowchart explaining the operation | movement at the time of collision damage reduction system operation. It is a block block diagram of Example 1 of this invention. It is a block block diagram of Example 2 of this invention. It is a block block diagram of Example 3 of this invention.

  Next, embodiments of the present invention will be described with reference to the drawings. In the following, the collision damage reduction system will be described, and the collision damage reduction method will also be described in the description.

[Basic idea]
The collision damage reduction system is composed of a computer centered on a CPU (arithmetic control unit). As shown in FIG. 1, the collision damage reduction system includes an input unit 1, a display unit 2, a position / speed detection device 3, a storage unit 4, an alarm device 5, a speed control device 6, and an arithmetic control unit. 7.

  The input unit 1 is for designating conditions such as a route to which the collision damage reduction method is applied, and known input means such as a keyboard, a touch panel, and a mouse can be used. The display unit 2 is for displaying calculation results of an occurrence damage estimation unit and an occurrence probability estimation unit configured by functions of the calculation control unit 7 described later, and is configured by a liquid crystal panel, an LED panel, or the like. . The position / speed detection device 3 detects and outputs the position and speed of the train, and is composed of, for example, a speed generator and a vehicle upper element that detects a ground element for correcting a position error.

  The input unit 1, the display unit 2, and the position / speed detection device 3 are all known, and are connected to the arithmetic control unit 7 via an I / O interface (not shown). If necessary, a weight sensor for estimating the mass of the train and the number of passengers, a communication device for acquiring information from the outside of the train, and the like (both not shown) are connected to the arithmetic control unit 7.

  The storage unit 4 includes a memory such as a ROM and a RAM for storing program data and working data for realizing the object of the collision damage reduction system. In the memory, past collision accident cases are stored in a database for each route. Data constituting the database is comprehensive data related to past collision accidents, and includes the following as an example. That is, the name of the route, the location of the collision accident (km), the date and time of the collision accident, the weather, the traveling speed, the type of obstacle (car, bicycle, person, animal) and the size, the degree of damage (wrecked, Midway), deaths, injuries, etc.

  The arithmetic control unit 7 performs predetermined arithmetic processing based on data input from the input unit 1 and the position / speed detection device 3 by executing the program stored in the storage unit 4, that is, as shown in FIG. , Mainly occurrence damage estimation (S1), collision probability map creation (S2), occurrence probability estimation (S3), collision risk calculation (S4), collision risk evaluation (S5), and speed control based on collision risk evaluation (S6) I do.

  More specifically, as shown in FIG. 3, the arithmetic control unit 7 constitutes the occurrence damage estimation means 7a by the function of estimating the occurrence damage, and constitutes the occurrence probability estimation means 7b by the function of estimating the occurrence probability. It has a collision risk calculation means 7c that obtains the total collision risk from the estimated values of the occurrence damage estimation means 7a and the occurrence probability estimation means 7b, and has a collision risk evaluation means 7d that evaluates the degree of the obtained total collision risk. . In a preferred embodiment, the calculation control unit 7 is provided with a collision probability map display means 7e for causing the display unit 2 to display a collision probability map at a certain position. Below, these each means 7a-7e are explained in full detail.

  As will be described later, the occurrence damage estimation means 7a determines the magnitude of equipment damage / human damage based on the type of obstacle and the state of the train (for example, speed, mass including passengers / cargo, number of passengers, etc.). presume.

  The occurrence damage estimation may be performed using another data processing apparatus instead of the arithmetic control unit 7, and the estimation result may be stored in the storage unit 4 as a database. In that case, the occurrence damage estimation means 7a looks up the estimation result stored in the storage unit 4 and estimates the occurrence damage corresponding to the state of the train.

  One of the methods for estimating the occurrence damage is a method in which a human is inductively estimated by referring to a database of past collision accident cases. In addition, there is a method using physical simulation in order to obtain damage occurrence more quantitatively and objectively.

  In the physical simulation, the dynamic motion at the time of collision is calculated from the obstacle model and the train model. Some of the model parameters of the obstacle are shown in FIG. However, FIG. 4 is schematic and the values are not always practical. The mass need not be normally distributed.

  All parameters can be defined as random variables. However, only a parameter (for example, mass) having a large value range and a large impact on the collision risk may be defined as a random variable.

  At the time of a collision, energy dissipation occurs due to the deformation of the train and obstacles. The aspect of deformation can vary greatly depending on the location and angle of the collision. For places with deformation, finite element method (FEM) analysis is applied, and for macroscopic movements of trains, multibody dynamics (MBD) analysis is applied, and these are coupled to generate deformation. A dynamic simulation of the collision can be performed. A technique for performing a dynamic simulation of a collision by FEM analysis and MBD analysis is disclosed in Non-Patent Document 1, for example.

  Moreover, about the estimation of the secondary collision damage of the passenger in the train at the time of a collision occurrence, the technique evaluated by simulation is shown by the nonpatent literature 2, for example.

  As an indicator of the magnitude of damage, for example, an amount can be used for equipment damage. How to quantify the magnitude of the damage from the situation at the time of the collision depends on values and is not specified in the present invention (some mapping from the situation to the magnitude of the damage is defined). As long as it is). The situation of the collision itself is less dependent on the train position and time of occurrence. However, taking into consideration incidental situations (ease of securing necessary personnel and time for restoration, whether alternative transportation exists, etc.), the magnitude of damage depends on the train location and time of occurrence. Change. When considering incidental situations, the mapping may be switched according to the train position and time of occurrence.

  The occurrence probability estimation means 7b estimates the probability of occurrence of a collision from the type of obstacle, train position, season, time zone, and the like. The season and time zone are acquired from a calendar / clock (not shown) built in or connected to the arithmetic control unit 7.

  The probability of occurrence strongly depends on the train position, and is less dependent on the other train states. Using this feature, in estimating the occurrence probability, the collision probability at a certain position is determined for each condition such as the type of obstacle, season, time zone, etc. as a collision probability map as illustrated in FIG. Save to 4. Then, the occurrence probability estimation unit 7b looks up the collision probability map along the traveling pattern (time / position) of the train and estimates the collision probability of the point.

  It has been found that the occurrence situation of a collision accident in a level crossing may be correlated with the level crossing specifications, level crossing environment, and the like (for example, Non-Patent Document 3). Therefore, a method is effective in which classification is performed based on conditions such as level crossing specifications and level crossing environment, and the collision probability is complemented from level crossings based on similar conditions. The level crossing specifications, level crossing environment, etc. include the presence or absence of a breaker, the length of a crossing, the number of crossings, and the like.

  In addition, it is desirable to consider a case where there has been a possibility of a serious accident that has not led to a collision accident in the past. Therefore, based on Heinrich's law, it is also effective to estimate the probability of a collision accident from the state of occurrence of an unsafe state that did not result in a collision accident.

  The validity of the collision probability map can be relatively evaluated by obtaining the likelihood (the conditional probability that an individual collision accident case occurs under the condition given the collision probability map). For example, if the likelihood in the case of the estimated collision probability map is higher than the likelihood in the case where the collision occurrence probability is assumed to be uniform regardless of the position, it is relatively appropriate (that is, usefulness is high). It can be said.

The collision risk calculation means 7c multiplies and integrates the estimated values of the occurrence damage estimation means 7a and the occurrence probability estimation means 7b to obtain the total collision risk. That is, in the embodiment of the present invention, collision risk = occurrence damage × occurrence probability. That is, in estimating the magnitude of the collision risk, the magnitude of the occurrence damage is determined as an element having a small dependence on the train position and the occurrence time. In addition, the occurrence probability is used as an element depending on the train position and the occurrence time. Assuming that there is only one type of obstacle that can collide at a time (for example, a car and an animal will not collide at the same time), the collision risk is
Collision risk = Σ (Occurrence damage with certain obstacles x Occurrence probability with certain obstacles)
It is calculated by the following formula. Here, Σ means an operation for obtaining the sum of the types of obstacles. If an event that collides with a plurality of types of obstacles at the same time is considered, a set of obstacles (for example, “one passenger car and one bicycle”) may be independently defined as a specific obstacle type.

  Occurrence damage and collision risk are generally expressed in a probability distribution with probability distribution. However, in order to simplify the arithmetic processing, summary statistics (average value, mode value, etc.) may be used instead of the probability distribution.

  The total collision risk is obtained by integrating the collision risk by a predetermined method. Examples of the integration method include integration within a certain period of time from the current time, integration while traveling a certain distance from the current position, or a method using a combination thereof. Alternatively, the most important and most recent collision risk in space and time may be given a large weight and integrated as a weighted sum.

  The collision risk evaluation means 7d compares the total collision risk obtained from the collision risk calculation means 7c with a predetermined reference value and evaluates whether the total collision risk is high. Since the total collision risk is also generally a probability distribution, summary statistics (average value, quantile, etc.) are used for comparison. When it is evaluated that the total collision risk is high, a driving signal is given to the alarm device 5 and a speed control signal is given to the speed control device 6.

  For example, the collision risk evaluation means 7d outputs a drive signal and gives it to the alarm device 5 when the total collision risk exceeds a predetermined first threshold value. As a result, the alarm device 5 emits an alarm sound or flashing light to alert the driver of the train. Further, the collision risk evaluation means 7d outputs a speed control signal and gives it to the speed control device 6 when the total collision risk exceeds a predetermined second threshold value that is larger than the first threshold value. As a result, the speed control device 6 controls the braking device (not shown) to decelerate. When a predetermined third threshold value that is larger than the second threshold value is exceeded, the speed control device 6 performs control to stop the braking device.

  When receiving a drive signal from the collision risk evaluation means 7d of the arithmetic control unit 7, the alarm device 5 alerts the train driver about the traveling speed and the like. Further, when the speed control device 6 is given a speed control signal from the collision risk evaluation means 7d of the arithmetic control unit 7, the speed control device 6 is currently subjected to factors other than the collision risk (for example, distance to the preceding train, curve radius, gradient, etc.). The braking device is controlled to decelerate or stop the traveling speed according to the speed pattern based on the degree of collision risk.

  When the collision risk is high, it is preferable to widen the train interval by performing speed control. This will be described below. In general interval control, even when it is assumed that the preceding train stops instantaneously (deceleration infinite), the train interval is secured so as not to collide. However, considering the situation where the braking of the following train is delayed for some reason or the deceleration is insufficient, there is a small risk that the following train will collide with the preceding train. The risk of this rear-end collision is small, but increases when the preceding train collides with an obstacle. Also, when a collision occurs, the risk of multiple collisions arises because trains and obstacles interfere with the surrounding lines.

  When sudden braking is performed to avoid rear-end collisions and multiple collisions, there is an increased risk of passengers or luggage falling or colliding in the vehicle. However, by increasing the train interval, it is technically possible for the following trains or neighboring trains to take a safer stop with a smaller deceleration.

  Moreover, in a situation where the risk of collision is large, it is considered that an unsafe state that does not lead to a collision is likely to occur. Even if the train stops in an emergency due to the occurrence of an unsafe condition, it is assumed that the operation will be restarted relatively early if a collision does not occur. At this time, it is easier to recover the train operation and organize the operation by keeping the train interval wide.

  A method for increasing the train interval will be described later.

  FIG. 5 is a collision probability map showing the collision probability on the route R where three railroad crossings C1, C2, and C3 and one tunnel T exist as an example. In this collision probability map, the collision probability when the obstacle type is a passenger car is indicated by a solid line, and the collision probability when the obstacle type is a wild animal is indicated by a broken line. It is shown that the passenger car collision probability is high at the level crossings C1 and C3, and the passenger car collision probability at the level crossing C2 is relatively small. It is shown that the animal collision probability is slightly high before and after the tunnel T.

  Therefore, in the example of FIG. 5, as an example, when the train approaches the railroad crossing C <b> 1 having a high passenger car collision probability, the alarm device 5 emits an alarm sound or flashing light to alert the driver. The speed control device 6 decelerates the traveling speed of the train. Further, when the train approaches the tunnel T having a slightly higher animal collision probability, and immediately after passing through the tunnel, the alarm device 5 emits an alarm sound or flashing light to alert the driver. Further, when the train approaches the railroad crossing C2 where the passenger car collision probability and the animal collision probability are low, an alarm sound or flashing light is emitted to alert the driver, but the speed control device 6 reduces the traveling speed of the train. Do not control. When the train approaches the railroad crossing C3 having a relatively high passenger car collision probability, the alarm device 5 emits an alarm sound or flashing light to alert the driver, and the speed control device 6 decelerates the traveling speed of the train. To do. By decelerating, the estimated damage is reduced, thereby reducing the risk of collision. If the collision risk falls below a predetermined reference value, the driving of the alarm device 5 and the deceleration control of the speed control device 6 are canceled / mitigated.

  A plurality of collision probability maps are prepared for each route according to the season, time zone, and the like. The types of obstacles are not limited to passenger cars or animals. FIG. 5 is merely an example.

  The collision probability map of FIG. 5 is generated using past accident data (database). However, the probability that a collision accident actually occurs is not necessarily high, and the number of cases is limited with respect to the total length of the route. Accordingly, it is necessary to determine the location where there is no accident example by complementing the collision probability from information such as the level crossing specifications and the level crossing environment as described above.

  The collision probability map display means 7e may be provided in another data processing device instead of the arithmetic control unit 7. Instead of the collision probability, the collision risk obtained by the collision risk calculation means 7c may be output as a map. As a method for illustrating the collision probability or the collision risk, a curve graph as shown in FIG. 5 may be used, or a color or a numerical value may be used.

[Operation during operation]
Next, the operation at the time of operation of the collision damage reduction system according to the above embodiment will be described with reference to FIG. The execution of the collision damage mitigation system program starts with departure from the starting point of the train. Simultaneously, the position / speed detection is started (S21), and the collision probability estimation means 7b looks up the collision probability map at the current position (S22), and the collision probability at the current position is determined from the travel pattern (position / speed). Is estimated (S23). On the other hand, the occurrence damage estimation means 7a estimates the occurrence damage from the train state (S24). When the estimated values by the occurrence damage estimation means 7a and the occurrence probability estimation means 7b are obtained, the collision risk calculation means 7c calculates the total collision risk by integrating the estimated values by the occurrence damage estimation means 7a and the occurrence probability estimation means 7b ( S25). The total collision risk is given to the collision risk evaluation means 7d, and the collision risk evaluation means 7d compares the total collision risk with a predetermined reference value to evaluate whether the collision risk is large (S26). Depending on the degree of evaluation, a driving signal is given to the alarm device 5 or a speed control signal is given to the speed control device 6 (S27).

  Next, an embodiment in which the above basic idea of the collision damage reduction method and the collision damage reduction system is specifically applied will be described.

[Example 1]
FIG. 7 is a block diagram illustrating the configuration of the first embodiment. The collision damage reduction system includes a diagram design unit 11, an operation curve creation unit 12, an operation / collision simulation unit 13, and a collision risk evaluation unit 14.

  The diamond design unit 11 is based on an existing diamond design method described in Patent Documents 2 and 3, for example.

  When the diagram design unit 11 receives an evaluation signal from the collision risk evaluation unit 14 that the collision risk is high, the driving curve generation unit 12 generates an operation curve so that the collision risk is reduced. When a new operation curve is created in the operation curve creation unit 12, a new reference operation time is proposed to the diagram design unit 11 and a diamond correction is requested.

  The operation / collision simulation unit 13 is obtained by adding a collision simulation function to an operation simulator that can be reproduced at a driving curve level. In the operation simulator that can be reproduced at the driving curve level, the position and speed of each train are calculated. This corresponds to a state in which the position / speed of the train is acquired from the position / speed detection device 3 in FIG. In addition to position and speed, it is also possible to calculate the number of passengers. The collision simulation is based on a stochastic simulation (Monte Carlo simulation) using a statistical model possessed by the occurrence damage estimation means 7a and occurrence probability estimation means 7b of FIG.

  As the operation simulator technology that can be reproduced at the driving curve level, for example, those described in Non-Patent Document 4 or those described in Patent Document 4 as related technologies can be used.

  The collision risk evaluation unit 14 includes the above-described collision risk calculation means 7c and collision risk determination means 7d in FIG. When the collision risk is calculated by the above-mentioned collision risk = Σ (occurrence of damage caused by certain obstacles × probability of occurrence by certain obstacles) and the total collision risk exceeds a predetermined reference value, the diamond design The part 11 is notified of the magnitude of the collision risk, the location where the collision risk is high, and the time zone, and requests a timetable correction.

  That is, the basic function of the arithmetic control unit 7 that realizes the basic idea of the present invention described above is performed by the operation / collision simulation unit 13 and the collision risk evaluation unit 14. The function corresponding to the speed control device 6 is performed by the diamond design unit 11 and the operation curve creation unit 12.

  The diamond design unit 11 corrects the diamond so that the collision risk calculated by the collision risk evaluation unit 14 is reduced to an acceptable level. Then, by reducing the driving speed in a place and time zone where the collision risk is high and widening the driving time interval, a reduction in the collision risk can be expected.

  As for how much the driving speed and driving interval (train interval) are changed based on the size of the collision risk, the method of manual input by a person, the method of referring to a pre-calculated table, or random change The method of letting it be mentioned. As a method of referring to the table, a prior art that draws a temporary speed pattern according to a disaster, for example, the concept described in Patent Document 5 can be applied. Metaheuristics may be applied to automate the diamond correction.

[Example 2]
Example 2 calculates | requires the collision risk when the own train drive | operates according to a brake pattern, and brakes when a collision risk is large. As shown in FIG. 8, the collision damage reduction system in this case includes a position / speed detection device 21, a pattern generation unit 22, a speed control device 23, a braking device 24, an operation / collision simulation unit 25, a collision, And a risk evaluation unit 26.

  The pattern generation unit 22 is a function for correcting the deceleration timing and deceleration of the brake pattern according to the collision risk, in addition to the brake pattern generation function similar to the conventional automatic train stop device (ATS) or automatic train control device (ATC). Have

  The operation / collision simulation unit 25 and the collision risk evaluation unit 26 are the same as the operation / collision simulation unit 13 and the collision risk evaluation unit 14 in the first embodiment. However, the subject of simulation / evaluation is only the own train. The train operation on the simulation is deterministically determined by the brake pattern by the pattern generation unit 22.

  After correcting the brake pattern in consideration of the collision risk, the simulation is performed again to evaluate the collision risk and feed back to the pattern generation unit 22.

  The speed control device 23 and the braking device 24 are similar to those of the conventional ATS or ATC, and brake the train when the brake pattern is exceeded.

  When the collision risk evaluation unit 26 exceeds a predetermined reference value, the driver may be alerted by an alarm device (not shown).

[Example 3]
In the third embodiment, in addition to the collision risk management of the own train, information affecting the collision risk is transmitted to other trains to further reduce the collision damage. As shown in FIG. 9, the collision damage reduction system in this case includes a position detection device 31, an own train state estimation unit 32, an own train information / ground facility information transmission unit 33, an other train information reception unit 34, A ground facility information receiving unit 35, an operation / collision simulation unit 36, a collision risk evaluation unit 37, a pattern generation unit 38, a speed control device 39, and a braking device 310 are included.

  The own train information / ground equipment information transmission unit 33 transmits the own train information and the ground equipment information received by the own train to other trains. The other train information receiving unit 34 receives other train information from other trains. The ground facility information receiving unit 35 receives ground facility information from the ground facility or another train.

  The own train state estimation unit 32 estimates the position / speed of the own train at the current time based on the information from the position / speed detection device 31. In addition, the future position / speed (running pattern) of the train is predicted from the current time. Furthermore, the situation (for example, the traveling pattern of a preceding train or the state of a railroad crossing in front of the train) associated with the own train with information acquired from the other train information receiving unit 34 and the ground facility information receiving unit 35 is estimated. This estimation need not be deterministic.

  The operation / collision simulation unit 36 and the collision risk evaluation unit 37 are the same as the operation / collision simulation unit 13 and the collision risk evaluation unit 14 in the first embodiment.

  The pattern generation unit 38 generates a brake pattern that reduces the driving speed in accordance with the collision risk evaluation result of the collision risk evaluation unit 26 and that can take a wide driving interval. The speed control device 39 compares the brake pattern generated by the pattern generation unit 38 with the own train speed estimated by the own train state estimation unit 32, and if it exceeds the brake pattern, causes the braking device 310 to brake. . Unless the braking device 310 or the like breaks down, a travel pattern that greatly exceeds the brake pattern is not reached. Therefore, the information on the brake pattern is used for the prediction of the traveling pattern of the own train in the own train state estimation unit 32.

  In this embodiment, since the status information of the own train is transmitted to other trains, it is not necessary to issue a type of protection radio. Each peripheral train evaluates the risk and controls it. As in the past, the protection radio may be used when a risk becomes apparent.

  The ground equipment information is used as necessary to improve the accuracy of the collision probability. The ground facility information is, for example, the actual warning time at the level crossing, the traffic on the road around the level crossing, and the like, and is not limited to the information on the railway facilities.

  By acquiring weather conditions and the like as ground facility information, it is possible to estimate and evaluate the risk of collision classified as a natural disaster such as falling rocks and fallen trees more quantitatively.

DESCRIPTION OF SYMBOLS 1 Input part 2 Display part 3 Position / speed detection apparatus 4 Memory | storage part 5 Ground equipment or alarm device 6 Speed control apparatus 7 Operation control part (operation | collision simulation part)
7a Occurrence damage estimation means 7b Occurrence probability estimation means 7c Collision risk calculation means 7d Collision risk evaluation means 7e Collision probability map creation means 11 Diagram design part 12 Driving curve creation part 13 Operation / collision simulation part 14 Collision risk evaluation part 21 Position / Speed Detection device 22 Pattern generation unit 23 Speed control device 24 Braking device 25 Operation / collision simulation unit 26 Collision risk evaluation unit 31 Position / speed detection device 32 Own train state estimation unit 33 Own train information / ground facility information transmission unit 34 Other train information Reception unit 35 Ground equipment information reception unit 36 Operation / collision simulation unit 37 Collision risk evaluation unit 38 Pattern generation unit 39 Speed control device 310 Braking device

Claims (3)

The first step (estimated damage estimation) is based on the type of obstacles, the speed, the mass including passengers and cargo, and the train conditions such as the number of passengers. Step) and
A second step (collision probability map creation step) of creating a collision probability map by estimating the collision probability at a certain position for each obstacle type, season, and time zone using past accident data,
A third step (collision probability estimation step) of looking up the collision probability map and estimating a collision probability at each point based on a running pattern during train operation or train operation simulation;
A fourth step (collision risk calculation step) for calculating the collision risk by multiplying the occurrence damage estimated in the first step and the collision probability estimated in the third step by multiplying each type of obstacle,
A fifth step (collision risk evaluation step) for evaluating the degree of collision risk obtained in the fourth step based on a predetermined criterion;
A sixth step (speed control step) for giving a speed control signal to the speed control device in accordance with the degree of collision risk evaluated in the fifth step;
A collision damage mitigation method comprising: Damage occurrence estimation means that estimates the magnitude of equipment damage and human damage from the type of obstacles and the state of the train,
Occurrence probability estimating means for determining the collision probability at a certain position for each condition such as obstacle type, season, time zone, etc., and estimating the collision probability from the traveling pattern of the train,
A collision risk evaluation means for evaluating whether or not the collision risk is large from the multiplication / accumulation result of the occurrence damage estimated by the occurrence damage estimation means and the collision probability estimated by the occurrence probability estimation means;
A collision damage mitigation system comprising: a speed control unit that controls a traveling speed of the train when the collision risk evaluation unit evaluates that the collision risk is high.   The collision damage mitigation system according to claim 2, wherein a collision probability map is created by estimating the collision probability at a certain position for each condition such as obstacle type, season, time zone, etc. using past accident data. A collision probability map creating means for performing the collision probability estimation means for looking up the collision probability map and estimating the collision probability at each point based on a running pattern during train operation or train operation simulation. Collision damage reduction system characterized by being a thing.

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