JP3510865B2 - Transportation planning support method and transportation planning support device - Google Patents

Description

Detailed Description of the Invention

[0001]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a transportation plan support method and apparatus for determining a distribution state of transportation targets in a transportation network and preparing a transportation plan for transportation targets, particularly a transportation plan at the time of disaster.

[0002]

2. Description of the Related Art There is a conventional technique for simulating and predicting the state of a transportation network in order to prepare a transportation plan for transporting transportation targets such as goods and personnel.

Japanese Patent Laid-Open No. 11-
Japanese Patent No. 144182 discloses a traffic flow simulation system. This traffic flow simulation system performs a micro traffic flow simulation for each narrow road range of a wide area road network to obtain highly accurate macro parameters, and based on the macro parameters for all narrow road ranges, Predict the total traffic volume.

As a similar prior art, Japanese Patent Laid-Open No. 10-
The traffic condition prediction device disclosed in Japanese Patent No. 312497 discloses
Divide a certain section of the highway into multiple small sections,
Vehicle detectors that measure traffic conditions such as traffic volume and traffic density are installed in each small section, and the measured traffic conditions in the upstream and downstream sections of the prediction target section and the measured traffic status in the prediction target section The traffic condition is predicted by expressing the relationship with the neural network.

As a similar conventional technique, Japanese Patent Laid-Open No. 7-
The traffic volume predicting apparatus disclosed in Japanese Patent No. 29087 determines the current traffic volume by measuring the number of vehicles inflowing and the number of vehicle outflowing to and from the intersection at the intersection of roads, and calculates a neural network based on the current traffic volume. Use to predict traffic volume.

[0006]

In an emergency such as when a disaster occurs over a wide area, a comprehensive disaster countermeasure plan including transportation of relief supplies is required. Therefore, the applicant is
In the disaster countermeasure evaluation device disclosed in Japanese Unexamined Patent Publication No. 10-116023, a method for easily grasping road conditions and determining a coping action of an emergency vehicle that transports relief supplies and personnel is proposed. Furthermore, in order to quickly and efficiently determine such coping actions, there is a method to create a transportation plan for relief supplies and personnel based on the road conditions grasped by the disaster countermeasures evaluation device, more quickly and efficiently. Is desired.

However, the traffic flow simulation system disclosed in Japanese Patent Laid-Open No. 11-144182 discloses a wide area road based on macro parameters obtained by performing a micro traffic flow simulation for each narrow road range of a wide area road network. Since the traffic volume of the entire network is predicted, a huge amount of calculation is required to obtain macro parameters for all narrow road ranges, and it is necessary to predict the traffic volume of the entire wide area road network. It is necessary to use a specific large-scale high-speed computing device that stores all the calculation methods that are stored in advance, and in the event of a disaster, it is possible to quickly grasp the distribution state of transportation targets in response to the situation that changes moment by moment. Have difficulty.

Further, the traffic condition predicting apparatus disclosed in Japanese Patent Laid-Open No. 10-312497 discloses the traffic condition predicting section upstream and downstream of a prediction target section measured by a vehicle sensor installed in each small section in a specific section of the road. The relationship between the traffic condition of the section and the measured traffic condition of the prediction target section is expressed by a neural network to predict the traffic condition, so the vehicle detector may be damaged in the event of a disaster and the traffic condition cannot be measured. Then, the traffic situation cannot be predicted.
Moreover, the calculation by the neural network is very complicated, requires a huge amount of calculation, and it is difficult to grasp the distribution state of the transportation target quickly in response to the situation that changes moment by moment in the event of a disaster. is there.

Further, the traffic volume predicting apparatus disclosed in Japanese Patent Laid-Open No. 7-29087 obtains the current traffic volume by measuring the number of vehicles flowing into and out of the intersection at the intersection of roads and calculating the present traffic volume. Since the traffic volume is predicted using a neural network based on the traffic volume, it is difficult to grasp the current traffic volume at the time of a disaster, and it is impossible to predict the macro traffic volume. Moreover, the calculation by the neural network is very complicated, requires a huge amount of calculation, and it is difficult to grasp the distribution state of the transportation target quickly in response to the situation that changes moment by moment in the event of a disaster. is there.

Therefore, an object of the present invention is to provide a transportation plan support method and transportation plan capable of grasping a distribution state of transportation objects at a predetermined time in a transportation network in order to easily and quickly create a transportation plan for transportation objects. It is to provide a support device.

[0011]

According to a first aspect of the present invention, there is provided a method for obtaining a distribution state of a transportation object by using a computer having an input means, a setting means, a storage means, a computing means and an output means, the input means. Input the actual distribution state, which is the number of actual transport targets existing at multiple reference points, which are the starting point, the reaching point, and the waypoint, which are measured in advance in the actual transport network. Set the route that connects the routes, and the transportation rate that indicates the ratio of transportation targets that move to other reference points after a unit time out of the entire transportation targets that exist at each reference point It is set so that it can be changed for each reference point based on the situation of each route based on the distribution state, and the transportation pair existing at each reference point at the initial time input by the input means by the calculation means. By multiplying the transport rate of the number of,
A matrix operation for obtaining the number of transport objects existing at each reference point at a time after a unit time is repeated to obtain a distribution state of the transport objects at a time when a predetermined time has elapsed from the changeable set initial time, and outputting means It is a transportation planning support method characterized by outputting the distribution state according to.

According to the present invention, the actual distribution state, which is the number of actual transportation objects existing at a plurality of reference points, which are the starting point, the reaching point, and the transit point, which are measured in advance in the actual transportation network, is input and the transportation is performed. The transport network that transports the object is modeled as a simple model by setting the transport rate for each reference point based on the situation of each route using the reference points and routes, Matrix calculation that sets the number of transport objects existing at the reference point, multiplies the number of transport objects at each reference point by the transportation rate, and obtains the number of transport objects existing at each reference point at the time after a unit time By repeating the above, it is possible to obtain the distribution state of the transportation target at the time when a predetermined time has elapsed from the initial time. With this, it is possible to easily and quickly grasp the distribution state of the transportation target at a time when a predetermined time set so as to be changeable from the initial time by a simple matrix calculation.
Based on the distribution state of the transportation object obtained in this way,
It is possible to create a transportation plan that transports the transportation target from the starting point to the reaching point. Also, when the situation of the transportation route changes, simply change the setting of the transportation rate according to the change and calculate the distribution state easily and quickly without changing the setting of the reference point and the route. You can figure it out.

The present invention according to claim 2 shows the actual distribution state, which is the number of actual transportation objects existing at a plurality of reference points which are the starting point, the reaching point and the waypoint, which are measured in advance in the actual transportation network. Set the route connecting the input means and each reference point, and set the transportation rate that indicates the ratio of the transportation objects that move to other reference points after a unit time of the entire transportation objects that exist at each reference point. , Setting means for setting changeable for each reference point based on the situation of each route based on the actual distribution state, storage means for storing the transportation rate, and the number of transportation objects existing at each reference point at the initial time. By repeating the matrix calculation for multiplying the transportation rate and obtaining the number of transportation objects existing at each reference point at the time after a unit time, the transportation at the time when a predetermined time has elapsed from the initial time set to be changeable. Arithmetic means for obtaining the distribution state of the subject, a transportation planning support apparatus which comprises an output means for outputting the obtained distribution.

According to the present invention, the actual distribution state, which is the number of actual transportation objects existing at a plurality of reference points, which are the starting point, the reaching point, and the waypoint, which are measured in advance in the actual transportation network, is input and the transportation is performed. The transport network that transports the object is modeled as a simple model by setting the transport rate for each reference point based on the situation of each route using the reference points and routes, Matrix calculation that sets the number of transport objects existing at the reference point, multiplies the number of transport objects at each reference point by the transportation rate, and obtains the number of transport objects existing at each reference point at the time after a unit time By repeating the above, it is possible to obtain the distribution state of the transportation target at the time when a predetermined time has elapsed from the initial time. With this, it is possible to easily and quickly grasp the distribution state of the transportation target at a time when a predetermined time set so as to be changeable from the initial time by a simple matrix calculation.
Based on the distribution state of the transportation object obtained in this way,
It is possible to create a transportation plan that transports the transportation target from the starting point to the reaching point. Also, when the situation of the transportation route changes, simply change the setting of the transportation rate according to the change and calculate the distribution state easily and quickly without changing the setting of the reference point and the route. You can figure it out.

[0015]

1 is a flow chart showing the procedure of a transportation planning support method according to an embodiment of the present invention.
FIG. 2 is a perspective view showing a transportation planning support device (may be referred to as “support device”) 20 according to the embodiment of the present invention. The support device 20 is realized by a computing device such as a personal computer (abbreviation: PC), and the arithmetic processing unit 21, the storage unit 22, the input operation unit 23, and the display unit 24.
It is configured to include.

The arithmetic processing unit 21 which is a setting means and an arithmetic means is realized by, for example, a central arithmetic processing unit (abbreviation: CPU), sets a transportation rate described later, and calculates the distribution state of the transportation medium. The storage unit 22 that is a storage unit is, for example, a hard disk drive (abbreviation: HD).
D) and other storage devices and CD-ROM and other storage media, and provides information about the transportation network related to the target area, the transportation rate to be described later, the distribution status of transportation media and transportation targets, and software necessary for calculation. Remembered. The input operation unit 23 is realized by an input device such as a keyboard and a mouse, and is operated by an operator of the support device 20 to input a command to the support device 20. Display 24
Is realized by a display device such as a liquid crystal display device (abbreviation: LCD), and the obtained distribution state and the like are displayed.

In the flow chart shown in FIG.
In step s0, the transportation planning support method is started, and the process proceeds to step s1. In step s1, the arithmetic processing unit 21 of the support device 20 determines a target area for which a transportation plan is created, and based on the information of the transportation network stored in the storage unit 22 of the support device 20, the transportation in the target area. Multiple reference points such as target departure point, arrival point and waypoint,
A route connecting the respective reference points is set to determine a transportation network for transporting the transportation target, the transportation network is modeled into a simple network model described later, and the process proceeds to step s2.

In step s2, the arithmetic processing unit 21 sets the transportation rate indicating the ratio of the transportation target moving to another reference point after a unit time to the entire transportation target existing at each reference point, and the status of each route. Set for each reference point based on
Go to step s3. In step s3, the arithmetic processing unit 2
In step 1, the distribution state of the transportation target at a predetermined time is calculated and obtained, and the process proceeds to step s4.

In step s4, the arithmetic processing section 21 compares the distribution state at the predetermined time obtained in step s3 with the actual distribution state measured in advance in the actual transportation network to determine whether it is appropriate or not. For example, it is determined whether or not the error between the distribution state obtained in step s3 and the actual distribution state is about 1 to 5%, and if it is determined to be valid, the process proceeds to step s5. If step s
If it is determined that the error between the distribution state obtained in 3 and the actual distribution state exceeds 5%, the process returns to step s2 to reset the transport rate.

In step s4, when it is determined that the distribution state at the predetermined time obtained in step s3 is appropriate and the process proceeds to step s5, the arithmetic processing unit 21 stores the transportation rate in the storage unit 22 in step s5. At the same time, a transportation plan for transporting the transportation target from the departure point to the arrival point is created, and the process proceeds to step s6 to end all the procedures.

FIG. 3 is a diagram showing a network model 3 in the transportation planning support method according to the embodiment of the present invention. In the present embodiment, the actual transportation network is simplified by using a node which is a reference point which is one of a starting point, an arrival point and a waypoint in the actual transportation network and an arc which is a route connecting the nodes. Model into a simple network model. The transportation medium that transports the transportation target moves between the nodes along the arc. The transportation target is, for example, goods and personnel, and the transportation medium is a vehicle such as a truck and a bus.

The arc connecting one node and the other node has two directions: a direction from one node to the other node and a direction from the other node to the one node. There are also arcs that have a direction out of a node and back to the same node. A transportation rate is set for each arc connected to each node. The transportation rate indicates the ratio of the transportation medium, that is, the transportation target, which moves to the same node and another node via the arc after a unit time out of the entire transportation medium existing in each node, that is, the entire transportation target.

In the node a of the network model 3, the node a is connected to the nodes b and c.
The transport medium is the movement from node a to node a, node a
From the node to the node b and the time from the node a to the node c are unit time Δt. The movement of the transportation medium from the node a to the node a means that the transportation medium stays at the node a. The transport rate p (ab) for the arc ab directed from the node a to the node b set to the node a is 0.5, the transport rate p (ac) for the arc ac directed from the node a to the node c is 0.2, and the node a.
Transport rate p (a
a) is 0.3. The transport rate p (aa) regarding the arc aa traveling from the node a to the node a indicates the proportion of the transport medium existing in the node a, which remains in the node a after a unit time. In FIG. 3, in order to simplify the description, the arrow mark in the direction toward the node a of the arc connecting the node a and the nodes b and c and the transportation rate set in the nodes b and c are omitted. In addition, like the arc ab, the codes indicating the arcs are arranged in order of the code of the starting node and the code of the ending node. The transport rates p (aa), p (ab), and p (ac) are determined by the transport rates p (aa), p (ab), and p (a) as shown in the following equation (1).
The sum P (a) of c) is set to 1. P (a) = p (aa) + p (ab) + p (ac) = 0.3 + 0.5 + 0.2 = 1 (1)

In the network model 3, when the state of the transportation network changes, the transportation medium moves only through the arc ab from the node a to the node b.
Arc set from node a to node b
The transport rate p (ab) for b is 1, the transport rate p (ac) for the arc a from the node a to the node c is 0, and the transport rate p (aa) for the arc aa from the node a to the node a is 0. . In this case as well, the transport rate p (aa),
p (ab) and p (ac) are the sum P of transport rates p (aa), p (ab), and p (ac) as shown in the following equation (2).
(A) is set to 1. P (a) = p (aa) + p (ab) + p (ac) = 0 + 1 + 0 = 1 (2)

Further, the situation of the transportation network changes, and in the network model 3, the transportation medium does not move via the arc ab from the node a to the node b but via the arc ac from the node a to the node c. It is assumed that the ratios of the transport mediums that perform the two movements and the movements from the node a to the node a via the arc aa are the same. In this case, the transport rate p for the arc ab set from the node a to the node b and set to the node a
(Ab) is 0, arc a from node a to node c
The transport rate p (ac) of c is 0.5, from node a to node a
The transport rate p (aa) of the arc aa heading for becomes 0.5. In this case also, the transport rates p (aa), p (ab), p (a
c) is the transport rate p (aa), p as shown in the following equation (3).
The sum P (a) of (ab) and p (ac) is set to 1. P (a) = p (aa) + p (ab) + p (ac) = 0.5 + 0 + 0.5 = 1 (3)

In this way, each transportation rate is set so that the total transportation rate when moving from a certain node via the arc connected to the node is always 1.

The transportation medium moves according to the transportation rate set for each arc connected to the node in which the transportation medium exists. As the transportation medium moves every unit time, the transportation medium in the network model 3, in other words, the distribution state of the transportation target changes every unit time.

If the numbers of transport media existing in the nodes a, b, and c at a certain time t in the network model 3 are set as a (t), b (t), and c (t), respectively, a certain time t
The number a (t + Δt) of transport media existing in the node a at a time t + Δt after a unit time Δt from is the number p (a of transport media remaining at the node a after a unit time Δt from the time t.
a) a (t), the number of transport media moving from node b to node a p (ba) b (t), and node c to node a
By adding the number p (ca) c (t) of the transport mediums moving to, the following equation (4) is obtained. a (t + Δt) = p (aa) a (t) + p (ba) b (t) + p (ca) c (t) (4)

Similarly, the numbers b (t + Δt) and c (t of transport media existing in the nodes b and c at time t + Δt.
+ Δt) is expressed by the following equations (5) and (6). b (t + Δt) = p (ab) a (t) + p (bb) b (t) + p (cb) c (t) (5) c (t + Δt) = p (ac) a (t) + p (bc) b (t) + p (cc) c (t) (6)

The above equations (4) to (6) are summarized as follows.
It is expressed as the following equation (7).

[Equation 1]

The distribution state Q (t) of the transport medium at the time t in the network model 3 is given by the following equation (8).
In Expression (8), T represents a transposed matrix. Q (t) = [a (t), b (t), c (t)] ^T (8)

If the matrix on the right side of the equation (7) in which all the transport rates in the network model 3 are elements is the total transport rate matrix P, the equation (7) is expressed by the following equation (9). Q (t + Δt) = P × Q (t) (9)

Therefore, the initial time t = 0 (that is, n =
0) from the initial time t = 0 by integrating the distribution state Q (0) and the total transport rate matrix P.
After that, that is, the distribution state Q (Δt) at time t = Δt
Can be obtained by the following equation (10). Q (Δt) = P × Q (0) (10)

Similarly, time t = 2Δt, t = 3Δ
The distribution state Q (2Δt), Q at t, ..., T = nΔt
(3Δt), ..., Q (nΔt) can be obtained by the following equations (11) to (13). n is a natural number. Q (2Δt) = P × Q (Δt) (11) Q (3Δt) = P × Q (2Δt) (12) Q (nΔt) = P × Q ((n−1) Δt) (13)

In order to apply the network model as described above to a transportation network for transporting relief goods and personnel to be transported by a transportation medium in an emergency such as when a disaster occurs over a wide area, it is connected to each node. The method of setting the transportation rate set for each arc is shown below.

FIG. 4 is a diagram showing an example of setting the transport rate of the node a in the network model 4 in normal times. Normal times refer to times when there is no emergency such as a disaster. Like the node a in the network model 4, a plurality of arcs a
When a, arc ab, arc ac, and arc ad are connected, each arc aa, ab, ac, ad of node a
The normal transportation rate for each arc is aa, ab, a
It is set according to the situation of the actual route and the reference point in the actual transportation network in normal times corresponding to c and ad.

The actual route situation is, for example, the allowable traffic volume of the roads constituting the route, the average traffic speed, the number of lanes, the number of traffic signal installations, and safety. The transport rate of each node is set based on the actual route situation and the reference point, and is stored in a database and stored in the storage unit 22 of the support device 20.
Memorized in. In this way, the actual transportation network in normal times can be modeled as a network model that closely resembles the actual transportation network.

In the network model 4 shown in FIG. 4, based on the situation of each actual route, for example, the arc ac has a very large allowable traffic volume, and therefore the transport rate p (ac) of the arc ac of the node a is the highest. Since it is set to a high value of 0.6 and the arc aa is not used at all, the transport rate p (aa) for the arc aa of the node a is set to the lowest value of 0,
Since the arcs ab and ad have the same actual route situation, the transport rate p (a
b) and p (ad) are each set to 0.2. Also in this case, the transport rates p (aa), p (ab), p (ac), p (a
d) is the transport rate p (aa), as shown in the following equation (14).
The sum P (a) of p (ab), p (ac), and p (ad) is set to 1. P (a) = p (aa) + p (ab) + p (ac) + p (ad) = 0 + 0.2 + 0.6 + 0.2 = 1 (14)

In the event of an emergency such as a disaster, which is different from normal times, when the route of the transportation network is broken or the broken route is restored, the transportation rate of each node is changed and set. For example, when a certain route in the transportation network is cut off, the transportation rate for the arc of the nodes at both ends connected to the arc corresponding to the route is set to 0. If the route that has become incomplete is in the incompletely restored state, the nodes at both ends connected to the arc corresponding to that route,
The transportation rate for the arc is set higher than 0 and lower than the transportation rate in normal times, and the transportation rate is changed according to the restoration status. Further, when the route that has become incomplete is completely restored, the transport rate for the arc of the nodes at both ends connected to the arc corresponding to the route is set to the normal transport rate.

In such an emergency, when the transport rate changes, each arc connected to the node is set so that the total transport rate set in the node becomes 1 even if the transport rate changes. Change the shipping rate for. For example, when the arc ac in FIG. 4 is cut off, the transportation rate for the arc ac of the node a is set to 0, and the transportation rate for the arc aa is set to 0.6. In this way, when the transport rate for the interrupted arc and incompletely restored arc at a node is lower than normal, the transport rates for other nodes connected to that node are increased to Set the sum of the transportation rates of 1 to 1.

In order to increase the transportation rate for arcs other than the non-cut and incompletely restored arcs, the transportation rate for arcs returning from a certain node to the same node, such as the arc aa in FIG. 4, should be changed. By doing so, it is possible to easily change the transport rate for arcs other than the arcs that are in the interrupted state and the incompletely restored state.

In this way, by using the network model that closely resembles the actual transport network, by changing the transport rate of the node in an emergency, it is possible to change the transport rate in the network model that closely resembles the actual transport network in an emergency. The transport rate in this emergency can be used to determine the accurate distribution state of the transport target.

FIG. 5 is a diagram showing a network model 5 having an arc that takes 2 unit time to move the transportation medium. The above-mentioned transportation rate is the transportation medium that is present in each node, that is, the transportation medium that moves to the same node and another node through the arc after a unit time in the entire transportation target,
That is, since the ratio of the transportation target is shown, for example, as shown in FIG. 5 (1), when the distance of the route is long and movement between nodes requires, for example, 2 unit time 2Δt,
As shown in FIG. 5 (2), the network model 5 includes a node a, a node b, a dummy node a ′, an arc aa ′ directed from the node a to the node a ′, and an arc a′b directed from the node a ′ to the node b. To the network model 5A.

The time required for the transportation medium to move from the node a to the node a ′ is the unit time Δt, and the time required for the node a ′ is
The time required to move from node to node b is unit time Δt
Is. In this way, the dummy node a ′ is added, and the movement from the node a to be transported to the node b is set as the movement from the node a to the node b via the node a ′.

In the network model 5 shown in FIG. 5 (1), the transport rate per 2 unit time for the arc ab of the node a is p (ab), and the arc of the node a in the network model 5A shown in FIG. 5 (2). The transport rate per unit time for aa ′ is p (aa ′), and the transport rate per unit time for the arc a′b of the node a ′ is p (a′b). In the network model 5A, the transportation medium existing in the node a moves to the node a ′ after a unit time,
Considering that the transport medium that has moved to the node a ′ always moves to the node b after a unit time, it is the same as that the transport medium existing in the node a in the network model 5 moves to the node b after two unit time. Can be considered That is, in the network model 5A, the transport rate p (a'b) for the arc a'b of the node a'is 1
And the transport rates p (ab), p (a'a),
There is a relationship represented by the following expression (15) between p (a'b). p (ab) = p (aa ′) × p (a′b) = p (aa ′) × 1 = p (aa ′) (15)

As described above, the movement that requires a plurality of unit times can be regarded as the movement that takes a unit time a plurality of times via one or a plurality of dummy nodes.

FIG. 6 is a diagram showing a network model 6 modeled by applying the transportation planning support method of this embodiment to a specific transportation network. Network model 6
Is a model of a transportation network that transports goods to be transported in normal times, as described above, into a network model that closely resembles a simple and actual transportation network. In the network model 6, node a is an accumulation point where materials are accumulated, nodes b, node c, nodes d, e and f are transit points, and nodes g, h, i, and j and node k are material supply points which are the starting points of the material.
In the network model 6, the time required for the transportation medium to move between the nodes via the arc is the unit time Δt.
Is.

If it is set that the transportation medium existing at the node a, which is the accumulation point, does not move to another node, the node a
Transport rates p (ab), p (ae), p (ah) of node a for arcs ab, ae, ah, ai connected to
The transport rate p (aa) for the arc aa is set to 1 in order to set the sum of the transport rates of the node a related to the arc connected to the node a to 1 with all p (ai) set to 0.

Further, the transportation mediums connected to the node a, which is the accumulation point, by one arc, and the nodes, which are the transit points adjacent to the node a, such as the nodes b and e, always move to the node a after a unit time. Then, if set, the transport rate p (ba) for the arc ba of the node b and the transport rate p (ea) for the arc ea of the node e are both 1.
And all other transportation rates are set to 0.

Further, in the case of a node which is connected to the node a, which is an accumulation point, by one arc, and which is a material supply point adjacent to the node a, for example, nodes h and i, the transport rate p (ha) for the arc ha of the node h. ), And the transport rate p (ia) of the arc ia of the node i are set to be high. In addition, for example, nodes a and j, which are not connected by arcs, have a transport rate of 0 for arcs that are not connected. In this way, each transportation rate is set according to the situation of the route and the situation of the reference point in the actual transportation network.

The following equations (16) to (26) show the transport rate of each arc set in each node and the total transport rate of each node.

[0052]

[Equation 2]

Using the transport rates shown in the equations (16) to (26), the total transport rate matrix Pn in normal time is calculated by the following equation as shown in the above equations (4) to (9). It is defined as shown in (27).

[0054]

[Equation 3]

Table 1 is a table showing the normal-time transportation rate for each arc of each node, which is arranged based on the normal-time total transportation rate matrix Pn shown in the equation (27).

[0056]

[Table 1]

Distribution Q of transport medium at time t
(T) is represented by the following equation (28). Q (t) = [a (t), b (t), c (t), d (t), e (t), f (t), g (t), h (t), i (t) , j (t), k (t)] ^T … (28)

In equation (28), a (t) to k (t)
Is the number of transport media at each node a to k at time t.

FIG. 7 is a diagram showing a distribution state in the network model 6A at the initial time t = 0. Initial time t
= 0, the nodes g, h, i, which are the material supply points,
The distribution state Q0 = Q (0) at the initial time t = 0 is represented by the following equation (29), assuming that there are 100 transport media in j and k in 500 in the entire network model. Q0 = Q (0) = [0,0,0, 0,0,0,100,100,100,100,100] ^T (29)

FIG. 8 is a diagram showing a distribution state in the network model 6B at time t = Δt. Time t = Δt
The distribution state Q1 = Q (Δt) in is obtained by integrating the distribution state Q0 at the initial time t = 0 and the total transport rate matrix Pn in normal time as shown in the following expression (30).

[0061]

[Equation 4]

FIG. 9 is a diagram showing a distribution state in the network model 6C at time t = 2Δt. Time t = 2
The distribution state Q2 = Q (2Δt) at Δt is expressed by the following equation (3
As shown in 1), it is obtained by integrating the distribution state Q1 at time t = Δt and the total transport rate matrix Pn in normal times.

[0063]

[Equation 5]

FIG. 10 is a diagram showing a distribution state in the network model 6D at time t = 3Δt. Time t =
The distribution state Q3 = Q (3Δt) at 3Δt is obtained by integrating the distribution state Q2 at time t = 2Δt and the total transport rate matrix Pn in normal time as shown in the following expression (32).
Desired.

[0065]

[Equation 6]

The distribution state after time t = 4Δt can be obtained in the same manner as described above.

Table 2 shows time t = 0, Δt, 2Δt, 3Δ.
6 is a table showing distribution states at t, 4Δt, 5Δt, 6Δt, and 7Δt. As shown in Table 2, the transportation medium reaches node a, which is an accumulation point, at about 60% of the entire transportation medium at time 2Δt, about 90% of the entire transportation medium at time 3Δt, and all of the transportation medium at time 7Δt. The result is that is reached.

[0068]

[Table 2]

FIG. 11 is a diagram showing a network model 7 at the time of disaster when a part of the route is cut off by the occurrence of the disaster. The disaster network model 7 includes arcs ah and ha connecting the nodes a and h and arcs ai and ia connecting the nodes a and i of the network model 6 shown in FIG. This is a network model in which arcs eh and he connecting the node h and the node h are cut off. It is necessary to change the transportation rate of the nodes e, h, and i connected to the shredded arc with respect to the shredded arc from the normal transportation rate. Node a
With respect to, since the transportation medium does not move through the arcs ai and ah, it is not necessary to change the transportation rate. Regarding the node e, the arcs ae and ea connecting the node a and the node e are not broken, and the transport medium existing in the node e always moves to the node a after a unit time.
There is no need to change the shipping rate.

Regarding the node h, since the arcs ha and ah and the arcs he and eh connected to the node h are cut off, the transport rate p for the arc ha of the node h is p.
(Ha) is changed from 0.8 to 0, and the transport rate p (he) regarding the arc he is changed from 0.1 to 0. In this case, in order to set the total of the transportation rates of the node h to 1, an arc hh connecting from the node h to the node h is provided, and the transportation rate of the node h with respect to the arc hh is set to 0.9.

Regarding the node i, since the arcs ia and ai connected to the node i are cut off, the transport rate p (ia) for the arc ia of the node i is changed from 0.7 to 0. In this case, the sum of the transport rates of node i is 1
For this reason, an arc ii connecting the node i to the node i is provided, and the transportation rate of the arc ii of the node i is set to 0.7. For shipping rates that do not need to be changed,
The transportation rate will be the same as the normal transportation rate.

Using the transportation rates set in this way, the total transportation rate matrix Pe at the time of a disaster is defined as shown in the following equation (33).

[0073]

[Equation 7]

Table 3 is a table showing the transport rates at the time of disaster regarding the arcs of each node, which are arranged based on the total transport rate matrix Pe at the time of the disaster shown in the equation (33).

[0075]

[Table 3]

The distribution state Q (t) of the transport medium at time t in the disaster time network model 7 is calculated by the above equation (28).
Shall be represented by. As shown in FIG. 11, the distribution state Q0 = Q (0) of the transportation medium in the disaster time network model 7 at the initial time t = 0 is transported to the nodes g, h, i, j, k which are the material supply points. Assuming that there are 100 media each and 500 in the disaster network model 7 as a whole, the distribution state Q0 = Q (0) is expressed by the above equation (29).
It is represented by.

FIG. 12 is a diagram showing a distribution state in the network model 7A at time t = Δt. Time t = Δ
The distribution state Q1 = Q (Δt) at t is expressed by the following equation (34).
As shown in, it is obtained by integrating the distribution state Q0 at the initial time t = 0 and the total transportation rate matrix Pe at the time of disaster.

[0078]

[Equation 8]

FIG. 13 is a diagram showing a distribution state in the network model 7B at time t = 2Δt. Time t =
The distribution state Q2 = Q (2Δt) at 2Δt is obtained by integrating the distribution state Q1 at time t = Δt and the total transportation rate matrix Pe at the time of disaster as shown in the following expression (35).

[0080]

[Equation 9]

The distribution state after time t = 3Δt can be obtained in the same manner as described above.

Table 4 shows time t = 0, Δt, 2Δt, 3Δ.
t, 4Δt, 5Δt, 6Δt, 7Δt, 8Δt, 9Δ
9 is a table showing distribution states at t, 10Δt, 11Δt, and 12Δt. As shown in Table 4, the transportation medium reaches the node a, which is an accumulation point, at about 20% of the entire transportation medium at time 2Δt and about 5% of the entire transportation medium at time 3Δt.
The result is that about 80% of the entire transport medium arrives at time 10Δt.

[0083]

[Table 4]

As described above, at the time of a disaster, the transportation rate matrix Pe at the time of disaster can be easily created based on the situation of the route at the time of the disaster and the transportation rate of the transportation rate matrix Pn in the normal time stored in the storage device 22. The distribution state of the transportation medium can be obtained. Therefore, in order to transport the transportation medium to the collection point as quickly as possible, it is necessary to consider which route should be preferentially restored, in other words, which node should have a higher transportation rate. it can. Further, it is possible to consider which route should be used as the priority route, in other words, which arc of the node should have the transport rate of 1.

Since the distribution state of the entire transportation network can be obtained by the calculation of the simple matrix as described above, such a calculation can be performed by the support device 20 in which the spreadsheet software is stored in the storage unit 22 at the time of a disaster. It can be easily calculated using a small portable PC. Such a small PC
Can be easily obtained, so the distribution state can be calculated at any place during a disaster. In addition, since the amount of calculation is significantly smaller than that of the conventional technique, the calculation can be performed more quickly.

According to the transportation plan support method and the transportation plan support apparatus 20 of the present embodiment, the transportation network for transporting the transportation target is determined by using the nodes and the arcs and determining the transportation rate for each node based on the situation of each route. By setting to, the transportation network can be modeled into a simple network model, and the distribution state of transportation objects at a predetermined time can be calculated and obtained. This makes it possible to grasp the distribution state of the transportation target at a predetermined time and easily and quickly create a transportation plan for transporting the transportation target from the departure point to the arrival point. Also, when the situation of the transportation route changes, it is possible to create a transportation plan easily and quickly without changing the setting of the reference point and the route simply by changing the setting of the transportation rate according to the change. .

[0087]

According to the present invention as set forth in claim 1, it is the number of actual transportation objects existing at a plurality of reference points which are preliminarily measured starting points, reaching points and transit points in an actual transportation network. Model the transportation network that inputs the distribution state of the transportation target and transports the transportation target by setting the transportation rate for each reference point based on the situation of each route using the reference points and routes. And set the number of transport objects existing at each reference point at the initial time, multiply the number of transport objects at each reference point by the transportation rate, and transport existing at each reference point at the time after a unit time. By repeating the matrix calculation for obtaining the number of objects, it is possible to obtain the distribution state of the objects to be transported at the time when a predetermined time has elapsed from the initial time. With this, it is possible to easily and quickly grasp the distribution state of the transportation target at a time when a predetermined time set so as to be changeable from the initial time by a simple matrix calculation. A transportation plan for transporting the transportation target from the departure point to the arrival point can be created based on the distribution state of the transportation target thus obtained. Also, when the situation of the transportation route changes, simply change the setting of the transportation rate according to the change and calculate the distribution state easily and quickly without changing the setting of the reference point and the route. You can figure it out.

According to the second aspect of the present invention, the actual distribution which is the number of actual transportation objects existing at a plurality of reference points which are the starting point, the reaching point and the waypoint measured in advance in the actual transportation network. The transportation network that inputs the state and transports the transportation target is modeled as a simple model by using the reference points and routes and setting the transportation rate for each reference point based on the situation of each route. , Set the number of transportation objects existing at each reference point at the initial time, multiply the number of transportation objects at each reference point by the transportation rate, and calculate the number of transportation objects at each reference point at the time after a unit time. By repeating the matrix operation for obtaining the number, it is possible to obtain the distribution state of the transportation target at the time when a predetermined time has elapsed from the initial time. With this, it is possible to easily and quickly grasp the distribution state of the transportation target at a time when a predetermined time set so as to be changeable from the initial time by a simple matrix calculation. A transportation plan for transporting the transportation target from the departure point to the arrival point can be created based on the distribution state of the transportation target thus obtained. Also, when the situation of the transportation route changes, simply change the setting of the transportation rate according to the change and calculate the distribution state easily and quickly without changing the setting of the reference point and the route. You can figure it out.

[Brief description of drawings]

FIG. 1 is a flowchart showing a procedure of a transportation planning support method according to an embodiment of the present invention.

FIG. 2 is a transportation plan support device 20 according to an embodiment of the present invention.
FIG.

FIG. 3 is a diagram showing a network model 3 in the transportation planning support method according to the embodiment of the present invention.

FIG. 4 is a diagram showing an example of setting a transportation rate of a node a in the network model 4 in normal times.

FIG. 5 is a diagram showing a network model 5 having an arc that takes 2 unit hours to move a transportation medium.

FIG. 6 is a network model 6 modeled by applying the transportation planning support method of the present embodiment to a specific transportation network.
FIG.

FIG. 7 is a diagram showing a distribution state in a network model 6A at an initial time t = 0.

FIG. 8 is a diagram showing a distribution state in the network model 6B at time t = Δt.

FIG. 9 is a diagram showing a distribution state in the network model 6C at time t = 2Δt.

FIG. 10 is a diagram showing a distribution state in the network model 6D at time t = 3Δt.

FIG. 11 is a diagram showing a network model 7 at the time of a disaster when a part of the route is cut off due to the occurrence of the disaster.

FIG. 12 is a diagram showing a distribution state in the network model 7A at time t = Δt.

FIG. 13 is a diagram showing a distribution state in the network model 7B at time t = 2Δt.

[Explanation of symbols]

20 Transportation planning support device 21 arithmetic processing unit 22 Memory

Front page continuation (72) Kenichiro Matsui, 1-1 Kawasaki-cho, Akashi-shi, Hyogo Kawasaki Heavy Industries Ltd. Akashi factory (72) Inventor, Kiji Tsutsumi, Kawasaki-cho, Kakamigahara-shi, Gifu Kawasaki Heavy Industries, Ltd. Gifu (72) Inventor Keiji Kurita 1 Kawasaki-cho, Kakamigahara-shi, Gifu Kawasaki Heavy Industries, Ltd. Gifu factory (72) Inventor Shinpei, Kawasaki-cho, Kakamigahara, Gifu Prefecture Kawasaki Heavy Industries, Ltd. Gifu factory (56 ) Reference JP-A-9-73563 (JP, A) (58) Fields investigated (Int.Cl. ⁷ , DB name) G08G 1/00 B65G 61/00 544 G06F 17/60 114

Claims (2)

(57) [Claims] 1. A method for obtaining a distribution state of a transportation object using a computer having an input means, a setting means, a storage means, a calculation means and an output means, wherein a starting point measured in advance in an actual transportation network by the input means, Enter the actual distribution state, which is the number of actual transport objects existing at multiple reference points that are the arrival point and the waypoint, and set the route connecting each reference point by the setting means, and set the route to each reference point. Based on the situation of each route based on the actual distribution state input by the input means, the transportation rate that indicates the ratio of transportation objects that move to other reference points after a unit time of the existing transportation objects The number of transportation objects existing at each reference point at the initial time input by the input means is multiplied by the transportation rate by the calculation means, and the unit time is set. By repeating the matrix calculation for obtaining the number of transport objects existing at each reference point at a later time, the distribution state of the transport objects at a time when a predetermined time has elapsed from the initial time set to be changeable is obtained, and by the output means, A transportation planning support method characterized by outputting a distribution state. 2. Input means for inputting an actual distribution state, which is the number of actual transportation objects existing at a plurality of reference points which are a starting point, an reaching point and a waypoint, which are measured in advance in an actual transportation network, Based on the actual distribution state, set the route that connects the reference points and calculate the transportation rate that indicates the ratio of the transportation objects that move to other reference points after a unit time in the entire transportation objects that exist at each reference point. Setting means for setting changeable for each reference point based on the situation of each route, storage means for storing the transportation rate, and multiplying the transportation rate by the number of transportation objects existing at each reference point at the initial time. , Repeat the matrix operation to obtain the number of transport objects existing at each reference point at the time after the unit time, and obtain the distribution state of the transport objects at the time when a predetermined time has passed from the initial time that can be changed. A transportation planning support apparatus comprising: a calculation unit that outputs the calculated distribution state; and an output unit that outputs the calculated distribution state.