Method and system for determining starting points between entities

Abstract

The invention relates to a method for determining a starting point (M) between entities (E), in which each of the entities (E) is configured to measure its own position and to communicate via a communication interface, characterized in that the positions (A, A*) of the entities (E) are identified in a cartographical material (1), a circle (2) surrounding all the entities (E) is identified, an optimal position of the starting point (M) is determined iteratively, the starting point (M) is initially coincident with the circle center (3) of the circle (2) surrounding the entities (E), in order to find the optimal position of the starting point (M) for each entity (E), a route (R) consisting of at least two route points connected by a respective route section is determined between each location (A) and the starting point (M), in order to move the position of the starting point (M) such that the sum of all the time or spatial distances of the route (R) between the entities (E) and the starting point (M) is below a specified maximum distance and / or the difference in time or spatial distance between the shortest route (R) and the longest route (R) is below a specified maximum difference.

Description

Technical Field

[0001] The present invention relates to a method for determining a starting point between entities and a system for determining such starting point, according to a pattern defined in detail in the preamble of claim 1.

Background Art

[0002] For example, entities such as humans often try to gather at a certain place to drink coffee or take a walk. Also, in the daily operations of a delivery service, items are delivered to various locations. For this purpose, the delivery service operates a transportation means to transport the items from a certain starting point to various delivery locations.

[0003] Here, the problem arises as to where humans should gather so that the distance from each person to the meeting place is approximately the same, or where to choose the starting point for delivery so that it is possible to reach each delivery location from the starting point at about the same speed. This enables gathering at the meeting place as quickly as possible or delivering the items as quickly as possible. Also, it is particularly fair that each person moves to a meeting place that is located in the middle of their respective locations in terms of time and / or space, because no one's movement will be significantly longer than another's.

[0004] Hereinafter, an entity may be understood to be, for example, a human, a mobile terminal such as a smartphone, a laptop, a tablet computer, a wearable, etc. The said human or arithmetic processing device may be assigned to a transportation means. As the transportation means, all transportation devices on roads, railways, water, and in the air can be considered. In some cases, an arithmetic processing device may be incorporated into the transportation means.

[0005] According to Patent Document 1, a search method and a search device for finding a meeting point are known. This meeting point corresponds to the midpoint between two entities that meet at the meeting point. In order to identify an appropriate meeting point located approximately in the middle between entities, a Point-Of-Interest (POI) near the midpoint is searched and examined whether it is suitable for the meeting. Therein, the distance between two entities is obtained from map data, and this distance is halved for the identification of the midpoint.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0007] The problem of the present invention is to provide an improved method and system for determining a starting point between such a large number of entities, whereby the position of the starting point between entities can be specified particularly fairly and accurately in various starting situations.

Means for Solving the Problems

[0008] According to the present invention, this problem is solved by a method for determining a starting point between entities having the features of claim 1 and a corresponding system having the features of claim 10. Advantageous configurations and developments can be obtained from its dependent claims.

[0009] In a method for determining a starting point between entities, those entities can identify their respective locations and communicate with each other via a communication interface. According to the present invention, the locations of each entity are identified in map data, a circle surrounding all the entities is identified, the optimal position of the starting point is determined iteratively, the starting point initially coincides with the center of the circle surrounding each entity, and in order to find the optimal position of the starting point for each entity, a route composed of at least two route points connected by respective route sections is identified between the location of each entity and the starting point. To move the position of the starting point, the sum of all the temporal or spatial distances of the routes between each entity and the starting point is less than a specified maximum distance, and / or the difference in the temporal or spatial distance between the shortest route and the longest route is less than a specified maximum difference.

[0010] By the method according to the present invention, the starting point between entities can be specified particularly fairly. In this way, each entity moves the same path to reach the starting point and / or takes the same time to reach the starting point. Here, the influence of the means of transportation used by each entity on the travel time or route is considered. For example, when the first entity moves by car and the second entity moves by bicycle, since a car generally moves faster than a bicycle, the route that the first entity moves may be longer than the route that the second entity moves. Therefore, the route that the car moves and the route that the bicycle moves can move in the same time for each means of transportation. Here, the same time or path is understood as the same time or path ± a specified tolerance range.

[0011] Therefore, at least one entity may be located on the circumference. In this way, a first approximation of the optimal position of the center of the circle can be obtained by creating a circle such that the two entities farthest from each other are located on the circumference and the straight line connecting these two entities passes through the center of the circle.

[0012] When the starting point is arranged between the locations of each entity such that the sum of all the temporal or spatial distances of each selected route from each entity to the starting point is less than the specified maximum distance, the time required for all entities to reach the starting point is shortened. There, it is also possible to minimize the sum of the temporal or spatial distances to the smallest possible value. If the sum of the spatial distances is the shortest, the fuel consumption of those entities will be the least, the emission of pollutants will also be the least, and there is also a possibility of reaching the destination particularly inexpensively. By a special coincidence, when the starting point is arranged such that the sum of the spatial distances of the routes of each entity to the starting point is minimized, it may also happen that the sum of the temporal distances is minimized at the same time.

[0013] On the other hand, when the position of the starting point is selected such that the difference between the temporal or spatial distances is less than the specified maximum difference, each entity can reach the starting point as simultaneously as possible. This is particularly fair because the lengths of the movements of each entity become almost the same. There, it is also possible to minimize the difference between the temporal or spatial distances between the movement routes of each entity to the starting point. It is also possible that the sum of the temporal or spatial distances is less than the specified maximum distance and the difference between the temporal or spatial distances is less than the specified maximum difference.

[0014] However, it may not be possible to arrange the starting point between each entity so that at least one of the criteria that the sum of the temporal or spatial distances is less than the specified maximum distance or the difference between the temporal or spatial distances is less than the specified maximum difference is satisfied. In this case, the determination of the starting point ends. In that case, for example, an alternative starting point for each entity arranged at an arbitrary position between the entities can be proposed.

[0015] Similar to the prior art, in order to identify the position of the starting point, a Point-Of-Interest (POI) near the route can be considered. In this way, for example, if there are interesting destinations for each entity such as a café, a library, a park, etc., the starting point can be brought closer to, for example, one of the entities.

[0016] In order to identify the location of an entity, the entity can have any position measuring device such as a receiver of a global navigation satellite system. The entity can also transmit additional information via a communication interface in addition to its own location. There, the communication can be carried out directly between the entities or indirectly via a third processing device such as a central processing unit (which may be fixed in some cases). Any proven communication technology is possible as the communication technology. For example, it is possible to communicate wirelessly, in particular by mobile phone communication, Wifi, Bluetooth, NFC, etc.

[0017] The operation of calculating the route and finding the starting point within the circle surrounding each entity is carried out, by choice, by the central processing unit and / or at least one entity. For this purpose, each entity transmits its own location via a communication interface to the central processing unit and / or other entities.

[0018] If the determined starting point is within a predefined tolerance range, it may be necessary for each entity to agree to the position of the determined starting point and the extent of the tolerance range before starting to move towards the starting point. However, in this way, the starting point will not get too close to one entity unfairly. Due to the existence of the tolerance range, even if an entity arrives at the starting point at a time later than the agreed time due to delays caused by traffic congestion or schedule deviations, it can be compensated. The tolerance range takes the form of, for example, an additional circle centered on the starting point, and the additional circle has a diameter smaller than the diameter of the circle surrounding each entity.

[0019] In an advantageous development of the present invention, each entity starts from its respective location and meets at a starting point. As already mentioned, the starting point is, for example, a café, a library, a park, etc., from where each entity starts a joint activity. In this example, the starting point can also be interpreted as a gathering point or a meeting point.

[0020] According to a further advantageous configuration of the method, the deliverer starts from the starting point and moves to the location of each entity along a route extending from the location of each entity to the starting point. In this way, the method according to the present invention can also be used to optimize the route along which the transport means of the delivery service moves to reach the customer, or the time required therefor. In this way, the delivery service can send the delivery transport means to the starting point, which includes drones, in particular self-controlled drones, and then the drones move to the location of the respective entity along their respective routes. For this purpose, since it is preferably required that the same time is required for the movement of the route, it is particularly reliably possible for the drones to arrive at the delivery transport means again at the same time after delivering the goods to the customer. Thereby, the efficiency of the goods delivery of the delivery service can be improved. There, it is also possible for a person to move by the delivery transport means and then for the person to move from the starting point to the location of each entity by, for example, the same or different means of transportation. The delivery service is, for example, a parcel delivery operator, a food delivery service, etc. There, other map information such as no-fly zones for unmanned drones can also be read from map materials in addition to POIs such as the optimal stopping positions of the delivery transport means.

[0021] Furthermore, in a further advantageous configuration of the present method, the location of each entity is identified by map data provided by at least two map providers, and the locations of each entity measured by different map data are compared with each other. By using map data provided by different map providers, it is possible to more accurately identify the location of each entity and ultimately the location of the starting point within the circle surrounding each entity. By comparing the map data of different providers, it is possible to discover and correct position displacements and inaccurately identified entity positions. The map data of different map providers may contain different POIs and map information. This increases the amount of information used to execute the method according to the present invention. Thereby, the method can be used with higher reliability.

[0022] According to a further advantageous configuration of the present method, current traffic information is taken into account when calculating the route between the location of each entity and the starting point. For example, when an entity moves by car, there may be traffic congestion on the route where the entity moves. This increases the time required to move along the route. For example, when other entities move by public transportation such as subway, tram, suburban railway, city bus, etc., there may also be delays here. Information on the possibility of traffic congestion and timetable changes can be obtained from reliable third-party information sources. It is advantageous to take these delays into account when determining the starting point. For example, if the time required to move along a certain route is increased by such a delay, the starting point is moved so that each entity can still reach the starting point at the same time ± the specified tolerance threshold, or so that the deliverer departing from the starting point can reach the location of each entity, i.e., the customer, at the same time. This ensures that the location of the starting point is specified particularly fairly and accurately even in a realistic traffic situation.

[0023] Furthermore, in a further advantageous configuration of the present method, at least one entity is the following means of transportation - on foot, - a bicycle, - an electric scooter, - public transportation, in particular buses and / or trains, - motor vehicles, in particular passenger cars, trucks and / or lorries, - an airplane, or - an autonomously controllable means of transport, in particular a drone, preferably a flying drone, moves along its own route by means of one of the above.

[0024] There, in general, it is also conceivable that an entity changes its means of transport while moving along a route. Thus, for example, an entity can move on foot in a first route section, then change to a bicycle and move, for example, by bus in a last route section. An entity can also use, for example, an electric scooter. This makes it possible to use the method according to the invention in a wider variety of movement situations.

[0025] For example, when an entity moves by train, stations within a circle with a specified radius around the location point of the entity concerned are identified in the map data for that entity, connections from each station to the station near the starting point (including possible transfer options) are identified, and their travel times are investigated. There, in order to determine the total travel time of an entity, for example, the distance and / or time that the entity concerned has to move to the station, for example on foot, is also taken into account. It is also possible to identify a station or a point near a station as the starting point. There, it is also conceivable that different entities move by different means of transport. For example, some entities move by train and electric scooter, some entities move by car and on foot, and some entities move exclusively by bicycle.

[0026] Therein, in order to identify the optimal position of the starting point, it is preferable that the average moving speed of each entity is assumed. Further, the moving speed of each entity can be learned according to the means of transportation selected by each entity. In this way, the moving behavior of a specific entity can be observed over a long period of time, and from this, a moving speed dependent on time and / or distance can be obtained. For example, when an entity moves a specific route at a specific time by subway, the time required for the movement may become longer, for example, when a large number of people get on and off during rush hour. For example, when another entity moves by bicycle, the time required for the entity to move a specific route section may become shorter or longer. For example, when the entity has to move uphill or downhill, or when, for example, it moves slowly after lunch when full.

[0027] According to a further advantageous configuration of the method, the algorithm for identifying the position of the starting point within the circle surrounding each entity is at least the following - identifying the optimal position of the center of the circle and the minimum diameter of the circle such that all entities are located within the circle or on the circumference - placing the position of the starting point at the position of the center of the circle - for each entity, identifying the route from the location of each entity to the starting point - moving the position of the starting point such that the sum of all the temporal or spatial distances of the routes between each entity and the starting point is less than a specified maximum distance and / or the difference in the temporal or spatial distance between the shortest route and the longest route is less than a specified maximum difference is executed.

[0028] Placing the starting point at the center of the circle is a first approximation for finding the optimal position of the starting point among entities, which enables each entity to reach the starting point simultaneously as fast as possible and / or fairly. Specifying the circle is simple and quick. For this purpose, according to an exemplary embodiment, among all entities, two entities that are farthest from each other are selected, and the circle is expanded so that these entities are located on the circumference. And the center of the circle is located on the straight line connecting these entities. Then, the starting point is moved from the center of the circle until the sum of all the temporal or spatial distances of the routes between each entity and the starting point is less than a specified maximum distance and / or until the difference in the temporal or spatial distances between the shortest route and the longest route is less than a specified maximum difference. Other procedures for expanding the circle surrounding each entity are also conceivable.

[0029] Also, in a further advantageous configuration of the method, the starting point is recalculated considering the current location of at least one entity. For example, if a delay occurs when at least one entity is moving along the route, each entity will not reach the starting point simultaneously. Similarly, in the example of a delivery service, the items may not arrive at each entity, i.e., the customers, simultaneously, or the drones delivering the items may not return to the delivery means simultaneously. However, by monitoring the current positions of the respective entities while they are moving along the route, the position of the starting point within the circle surrounding each entity can be adaptively moved. This can enable each entity to reach the starting point simultaneously or the items to reach the original locations of each entity. Also, when a drone returns to the delivery means, if it takes more time than expected, the delivery means can also move towards that drone.

[0030] Preferably, in order to specify the position of the starting point within the circle, the following criteria - fairness, - The amount of pollutants generated by moving at least one means of transportation along a route, in particular the amount of CO2, - The amount of energy required for at least one means of transportation to move along a route, and / or - The cost incurred to move at least one means of transportation along a route, at least one of which is further considered.

[0031] By considering at least one of the above criteria, the movement of the starting point within the circle surrounding each entity can be adjusted according to the customer's preferences. For example, according to the first scenario, the starting point can be arranged within the circle so that each entity reaches the starting point after the shortest possible time. For example, one entity moves to the starting point by car, while another entity has to change means of transportation several times to reach the starting point. This will impose a heavy burden on that other entity. Considering fairness, the starting point within the circle can also be moved so that all entities take a long time to reach the starting point, but each entity has to overcome a similar burden to reach the starting point. Therefore, for example, the starting point can be set at a stop of public transportation, and then many entities move to the starting point by public transportation. And for that purpose, each entity also has to transfer equally frequently.

[0032] The implementation of the method according to the present invention becomes more acceptable by considering the amount of pollutants generated by environmentally conscious people.

[0033] Similarly, the amount of energy required to move along a route and / or the cost for determining the position of the starting point within the circle generated therewith can also be considered.

[0034] In particular, the customer can decide for themselves which of the above criteria should be further considered to identify the starting point location. This results in particularly high levels of comfort and satisfaction when using the method according to the invention.

[0035] According to the invention, in a system for determining a starting point between entities, including at least three entities, each of which is set to identify its own location and share that location via a communication interface, at least three of those entities are set to execute the above method.

[0036] An entity is, for example, a human or a computing device, and the computing device is in the form of a mobile terminal such as a smartphone, tablet computer, laptop, wearable, etc. A human and / or a computing device can move by means of transportation such as a car, truck, transporter, bus, railway, bicycle, on foot, etc. Furthermore, it is also possible to change the means of transportation while the entity is moving. Also, at least one entity may be incorporated into the corresponding means of transportation. Thus, for example, an entity may be formed by a computing device in a vehicle.

[0037] Each entity can also communicate indirectly via a central processing unit. The central processing unit can also determine a starting point for each entity. To do this, the central computing device receives the location of each entity and uses the method according to the invention to determine a starting point for a meeting or for the departure of a drone.

[0038] A further advantageous configuration of the method for determining a starting point between entities according to the invention can also be obtained from the embodiments described in detail below with reference to the drawings.

Brief Description of the Drawings

[0039]

Figure 1

Figure 2

Figure 3

Mode for Carrying Out the Invention

[0040] FIG. 1 shows map data 1, which is in the form of a digital road map here. In the example of FIG. 1, the digital road map includes a part of a metropolitan area, for example, a metropolis. In the metropolis, a plurality of entities E are at their respective locations A. Only one entity E that is at the current location A* and is moving along the route R is shown. Each entity E has agreed to meet. The starting point M is specified by the method according to the present invention, and each entity E can reach the starting point M at the same time and / or along the same route. There, the entity E moves to the starting point M along the route R determined for itself. By doing so, the time until all entities E related to the meeting reach the starting point M is minimized, and / or the arrival of those entities E is ensured to be particularly fair because the lengths of the movements of each entity E are the same.

[0041] The entity E is, for example, a human or a computing device, and the computing device is in the form of a mobile terminal such as a smartphone, a tablet computer, a laptop, or a wearable. Such a computing device may be incorporated into a means of transportation. In that case, as the computing device, for example, a central on-board computer of the means of transportation, a subsystem control device of the means of transportation, a telematics unit, etc. can be considered.

[0042] Each entity E moves to the metropolis by means of transportation. Each entity E moves, for example, on foot, by bicycle, by electric scooter, by local public transportation, by private automobile such as a passenger car, a truck, a transporter, and / or by an autonomous transportation means such as a drone. There, it is also possible to change the means of transportation one or more times while moving from the original location A to the starting point M. For example, a certain entity E who is a human can move from their place of residence to a stop of the local public transportation by an electric scooter, and then, for example, move to a stop near the starting point M by bus, and reach the starting point M on foot from that stop.

[0043] According to the present invention, the position of the starting point M on the map data 1 is specified such that the sum of all the temporal distances or spatial distances between the original location A of each entity E and the starting point M is less than a specified maximum distance, and / or the difference in the temporal distance or spatial distance between the shortest route R and the longest route R is less than a specified maximum difference. Different moving speeds corresponding to the selected means of transportation are considered in specifying the position of the starting point M.

[0044] To identify the starting point M, each entity E measures its own location A, and then each entity E transmits its location to an arithmetic processing unit that identifies at least the location of the starting point M. This arithmetic processing unit can be formed by at least one entity E and / or the central processing unit 8 shown in FIG. 3. The corresponding arithmetic processing unit identifies a circle 2 that encloses all the entities E related to the meeting. For example, the circle 2 can be determined by identifying the two entities E that are farthest apart from each other and arranging the circle 2 so that these entities E are located on the circumference U of the circle 2. There, the straight line connecting these two entities E can pass through the center 3 of the circle 2. The circle 2 preferably has the smallest possible diameter. In a first approximation, the starting point M is placed at the center 3 of the circle 2, and the sum of all the temporal or spatial distances of the route R between each entity E and the starting point M is repeatedly moved within the circle 2 until it is below a specified maximum distance and / or until the difference between the temporal or spatial distance of the shortest route R and the longest route R is below a specified maximum difference.

[0045] There, each entity E can record its current location A*. According to an embodiment of the method according to the invention, each current location A* can be used for the adaptive movement of the starting point M. For example, if one entity E is stuck in traffic, the starting point M can be brought closer to that entity E. This ensures that each entity E reaches the starting point M simultaneously as planned, despite the time delay of at least one entity E.

[0046] Also, one or more POIs 6 are near the starting point M, and it is also possible to place the starting point M near one of those POIs 6. The POI 6 is, for example, a café, a library, a park, etc. That is, each entity E plans to meet at one of the POIs 6.

[0047] In order to improve the measurement accuracy of each location A, A*, according to an embodiment of the method according to the present invention, map data 1 provided by different map providers can be used.

[0048] FIG. 1 further shows a circular tolerance range 4. In this way, the criterion for each entity E to reach the starting point M defined above is considered to be satisfied when each entity is within the tolerance range 4 at the specified time. The radius of the tolerance range 4 may be, for example, just a few meters, or several hundred meters or kilometers. It is advantageous for the entities E related to the meeting to determine how large to choose the radius of the tolerance range 4 before starting to move along their respective routes R. This makes the movement to the starting point M seem fair to each entity E.

[0049] In order to more accurately determine the distance and / or time required for the movement of the route R, at least one route R can also be divided into several route sections. There, information such as the distance, the applicable speed limit, the route for running through the route section (for example, the subway), and the time required for the movement of the route section is associated with each route section. For higher accuracy, the route section can be repeatedly divided into even smaller route sections.

[0050] According to an embodiment of the method according to the present invention, the delivery transport means 7 shown in FIG. 3 can move to the starting point M, and it is also possible for a delivery entity LE, for example, a drone, to move from the delivery transport means 7 to the location A or A* of each entity E. The drone can, for example, deliver an article to each entity E. The article is, for example, a package or food.

[0051] FIG. 2 reveals that the method according to the present invention is not limited to a specific distance. In this way, the method according to the present invention can also be used to identify the starting point M for a plurality of entities E at both ends of a certain country 5.

[0052] Figure 3 shows a flowchart 300 of the method according to the present invention. In optional method step 301, each entity E can determine whether additional criteria should be considered to identify the starting point M. The additional criteria may be, for example, fairness, the amount of pollutants (especially in the form of CO2) generated by moving at least one means of transportation along route R, the amount of energy required for at least one means of transportation to move along route R, and / or the cost incurred therefor.

[0053] In method step 302, each entity E agrees to meet at the starting point M. In method step 303, each entity E identifies its original location A and further transmits it in method step 304. In the example of Figure 3, each location A is transmitted to a central processing unit 8, such as a cloud server or the backend of a service provider. Then, the starting point M is identified by the central processing unit 8. For this purpose, an algorithm 9 is executed on the central processing unit 8. Algorithm 9 includes five steps 901, 902, 903, 904, and 905.

[0054] In step 901, with the map data 1, a circle 2 surrounding each entity E and its position are determined. In step 902, the starting point M is placed at the center 3 of the circle 2 as a first approximation. In step 903, for each entity E, a route R from their original location A to the starting point M is determined. And in step 904, the position of the starting point M within the circle 2 is moved until the sum of all the temporal or spatial distances of the route R between each entity E and the starting point M is less than a specified maximum distance, and / or until the difference between the temporal or spatial distances of the shortest route R and the longest route R is less than a specified maximum difference. Accordingly, a new route R for each entity E is calculated. In this way, finally, in step 905, the optimal position of the starting point M within the circle 2 is found. Thereafter, this position is returned to each entity E, whereby each entity E can start moving towards the starting point M.

[0055] Also, it is possible to transmit the position of the starting point M and / or other information related thereto to the delivery transport means 7. The delivery transport means 7 includes a delivery entity LE. This may be, for example, an individual, or an autonomous drone that delivers articles, food, etc. to each entity E, for example, a flyable drone. When the delivery entity LE departs from the delivery transport means 7, if the delivery transport means 7 is at the starting point M, the deliverer LE can reach each entity E simultaneously, and preferably, can also return to the delivery transport means 7 simultaneously. Thereby, the delivery service can deliver articles to customers particularly effectively and efficiently. There, for example, in order to prevent the remaining energy of the drone from running out before the drone reaches the destination entity E or before returning to the delivery transport means 7, the radius or diameter of the circle 2 can be determined in consideration of the possible reach of the delivery entity LE.

[0056] Generally, it is also possible for each entity E to transmit its own location A to each other and eliminate data transmission to the central processing unit 8. In that way, for example, the algorithm 9 can be executed by one or all of the entities E. Accordingly, one entity E returns the starting point M specified by the same entity E to other entities.

Claims

1. A method for a computer to determine a starting point (M) between entities (E), wherein each of the entities (E) is set to identify its own location (A, A*) and communicate via a communication interface, the method comprising: wherein the location (A) of the entity (E) is specified in map data (1), a circle (2) surrounding all the entities (E) is specified, an optimal position of the starting point (M) is repeatedly determined, the starting point (M) initially coincides with the center (3) of the circle (2) surrounding the entity (E), and to find an optimal position of the starting point (M) for each entity (E), a route (R) composed of at least two route points connected by respective route sections is specified between the respective locations (A) and the starting point (M), and in order to move the position of the starting point (M), the sum of all the temporal distances of the route (R) between the entity (E) and the starting point (M) is less than a specified maximum distance, and the spatial distance difference between the shortest route (R) and the longest route (R) is less than a specified maximum difference, characterized in that it is a method.

2. The method according to claim 1, characterized in that the entities (E) start from their respective locations (A) and meet at the starting point (M).

3. The method according to claim 1, characterized in that a delivery entity (LE) starts from the starting point (M) and moves to the location (A) of the entity (E).

4. The location (A) of the entity (E) is measured in map data (1) provided by at least two map providers, and the locations (A) of the respective entities (E) measured in the different map data are compared with each other, characterized in that it is a method according to any one of claims 1 to 3.

5. The method according to any one of claims 1 to 4, characterized in that current traffic information is taken into account when calculating the route (R) between the location (A) and the starting point (M).

6. At least one entity is the following means of transportation, - walking, - bicycle, - electric scooter, - public transportation, especially buses and / or railways, - motor vehicles, especially passenger cars, trucks and / or transport vehicles, or - A transport means capable of autonomous control, in particular a drone, preferably a flying drone, The method according to any one of claims 1 to 5, characterized in that it moves along its own route (R) by one of them.

7. In order to determine the starting point (M), the average moving speed of each of the entities (E) is assumed, and the assumed average moving speed of each of the entities (E) is learned according to the means of transportation selected by each of the entities (E). The method according to any one of claims 1 to 6, characterized in that.

8. An algorithm (9) for determining the position of the starting point (M) has at least the following, - Determining the optimal position of the center (3) of the circle (2) and the minimum diameter of the circle (2) such that all entities (E) are located inside and / or on the circumference (U) of the circle (2); - Placing the position of the starting point (M) at the position of the center (3) of the circle (2); - For each entity (E), determining a route from the location (A) of each entity (E) to the starting point (M); - Moving the position of the starting point (M) such that the sum of all temporal distances of the route (R) between the entity (E) and the starting point (M) is less than a specified maximum distance, and the spatial distance difference between the shortest route (R) and the longest route (R) is less than a specified maximum difference; The method according to any one of claims 1 to 7, characterized in that it executes.

9. The method according to any one of claims 1 to 8, characterized in that the starting point (M) is recalculated taking into account the current location (A*) of at least one of the entities (E).

10. For determining the optimal position of the starting point (M), the following criteria, - The amount of pollutants generated, in particular the amount of CO2, by moving at least one means of transportation along the route (R); - The amount of energy required for at least one means of transportation to move along the route (R), and / or - The cost incurred for moving at least one means of transportation along the route (R), The method according to any one of claims 1 to 9, characterized in that at least one of them is further considered.

11. A system for determining, by the computer, a starting point (M) between entities (E) including at least three entities (E), wherein each of the entities (E) is configured to measure its own location and share the own location via a communication interface. The system, characterized in that the at least three entities (E) are configured to execute the method according to any one of claims 1 to 10.

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