Navigation for spatio-temporal change events

Abstract

The invention relates to a navigation method in which a navigation device calculates a navigation route (20) from a starting point to a destination. The navigation method according to the invention is characterized in that: the computing unit acquires information about at least one spatio-temporal change event (1); -the computing unit estimates the spatio-temporal course of the event (1) over a future time range and stores it as a dynamic region of interest (2); -the navigation device sets a departure point and a departure time, receives the dynamic region of interest (2), and calculates the navigation route (20) from the departure point to the destination, where the destination is located within the dynamic region of interest (2), or sets a point of view (3) from which the event (1) can be observed as the destination.

Description

Technical Field

[0001] The present invention relates to a navigation method of a type more detailed as defined in the preamble of claim 1, and a navigation system of a type more detailed as defined in the preamble of claim 7. Background Technology

[0002] Navigation devices make it easier for users to orient themselves, especially in unfamiliar environments. This allows for the determination of a navigation route from the point of origin to the destination, instructing the user on the path to follow. Navigation devices can be permanently integrated into vehicles or designed to be mobile, such as as dedicated mobile devices or as applications running on smartphones.

[0003] Here, users can manually set their destination. To further support users, navigation devices can also automatically suggest destinations. For this, the device can access a list of Points of Interest (POIs), which enumerates frequently visited locations in daily life. Examples of POIs include public parking lots, doctors' offices, shopping malls, gas stations, restaurants, etc. A POI can also be designed to cover a large area with multiple specific entry points, which can be set as navigation destinations.

[0004] A navigation device with time-dependent POI display is known in DE 10 2008 007 642 A1. This navigation device is capable of assigning open times to corresponding POIs and determining whether a POI is open and therefore available or unavailable, taking into account the current time or the time of arrival at the POI. Unavailable POIs can be hidden on the navigation device's map display, thereby improving clarity.

[0005] Furthermore, it is known to update the list of available Points of Interest (POIs) in an area. This allows for the removal of POIs that no longer exist, such as adjusting the opening hours of existing POIs, and the addition of new POIs to the list. Navigation devices can obtain the relevant information from external sources, such as via the internet or a portable computer-readable storage medium connected to the navigation device. Updates can be performed on demand or simultaneously with updates to the map data used. Temporary but location-fixed events, such as sporting events or festivals, can be temporarily queried as POIs and set as destinations.

[0006] Moreover, navigation devices can obtain current traffic information and take into account current road closures, detours, and / or congestion when calculating navigation routes.

[0007] However, there is still untapped potential in determining navigation routes for users.

[0008] Furthermore, US 2020 / 0408545 A1 discloses navigation to a moving target. The target transmits its current location, current time, and direction of movement via a navigation device. Based on paths to multiple locations of the target and contextual information, the target's future location is estimated, and a navigation route is determined to arrive at that future location simultaneously with the target.

[0009] Furthermore, DE 10 2023 004 236 A1 discloses a method for vehicle navigation. The vehicle is navigated to a moving target. The geographic coordinates of the target are transmitted via a navigation interface.

[0010] Furthermore, WO 2010 / 086680 A1 discloses a navigation system for determining a navigation route to a moving target. In this system, a server receives information about the changing location of the moving target. The server sends this information to a GPS transmitter / receiver. The navigation route from the location of the GPS transmitter / receiver to the moving target is calculated.

[0011] In addition, US 2012 / 0239584 A1 discloses navigation to a dynamic destination.

[0012] In addition, US 2022 / 0113721 A1 disclosed collaborative travel.

[0013] Furthermore, US 2007 / 0100539 A1 also discloses a method for setting a destination based on the identification features of a moving object and a method for providing location information. Summary of the Invention

[0014] The purpose of this invention is to provide an improved navigation method that further enhances user interaction compared to existing technologies.

[0015] According to the invention, this objective is achieved by a navigation method having the features of claim 1. Advantageous designs and improvements, as well as a navigation system for performing the method, are derived from the relevant claims.

[0016] A general navigation method in which the navigation device calculates a navigation route from the origin to the destination, configured as follows:

[0017] - The computing unit acquires information about at least one spatiotemporal change event;

[0018] - The computing unit estimates the spatiotemporal trajectory of the event within a future timeframe and stores it as a dynamic region of interest;

[0019] The navigation device receives the dynamic region of interest, sets the departure point and departure time, and calculates the navigation route from the departure point to the destination, where the destination is located within the dynamic region of interest, or sets an observation point where the event can be observed as the destination.

[0020] The computing unit divides the digital street map into multiple polygons, each of which is assigned map information, so that these polygons represent the digital street map in the form of a dynamic graph. The computing unit then maps the dynamic region of interest onto the dynamic graph, which includes multiple nodes, with each polygon assigned one node.

[0021] According to the present invention, height information is assigned as map information to nodes of the map, wherein the height information describes the topographic height of the terrain and / or the geodesic height of objects located within the corresponding polygons, and the calculation unit calculates the height difference between each node of the map and its respective neighboring nodes, wherein when the height relative to a neighboring node remains constant or decreases, the line of sight to that neighboring node is considered unobstructed / free line of sight; and wherein

[0022] The computing unit determines a node chain that starts from the dynamic region of interest and has a free line of sight to the dynamic region of interest, and sets one node of the node chain as the observation point.

[0023] Compared to existing technologies, the navigation method according to the present invention, for the first time, allows dynamic events to be set as destinations for navigation routes, in addition to considering static events. The difference between dynamic and static events is that the location of the event changes over time. Therefore, this is a particularly complex scenario for navigation route calculation because the navigation route must be determined over time due to the changing destination. Furthermore, the navigation method according to the present invention not only enables travel to a dynamic area of ​​interest (AOI) but also makes it possible to observe that AOI. For this purpose, the navigation device can calculate navigation routes to observation points (i.e., points that are far from the actual destination). This opens up entirely new design possibilities for providing route suggestions to users of the navigation device. In the broadest sense, an observation point can also refer to an area, i.e., an observation line or observation surface.

[0024] The computing unit can be integrated into the navigation device or implemented externally, such as as a cloud server. The computing unit can acquire information about spatiotemporal change events from various sources, which will be explained in more detail below.

[0025] A wide variety of spatiotemporal events can be considered. This specifically includes periodically recurring events such as sunrise, sunset, solar eclipse, moonrise, moonset, low tide, and high tide. Additionally, events occurring within specific time windows are also included, such as the aurora borealis, whale watching, algal blooms, bioluminescent plankton, and elephant herds crossing specific areas.

[0026] Here, the computing unit has several ways to estimate the spatiotemporal trajectory of a given event over a future timeframe. The future timeframe is specific to each event and corresponds to a specific period of occurrence. For example, daily sunrises and sunsets occur at different times depending on the date and the latitude and longitude of the Earth's surface. The occurrence of the aurora borealis is particularly dependent on the season and solar activity. The possibility of whale watching depends on whale migration and is therefore also seasonal. The spatiotemporal trajectory can be read from the information acquired by the computing unit itself, provided that this information contains the spatiotemporal trajectory. However, the computing unit can also determine the spatiotemporal trajectory itself, for example, by taking into account historical data or based on mathematical calculations. Some events, such as the aforementioned whale migration, are seasonal and therefore follow specific, identifiable patterns. Periodic events, in particular, such as sunrises, eclipses, or tides, can be calculated using deterministic equations. Conversely, events that occur specifically can change unpredictably, thus requiring separate measures to estimate their spatiotemporal trajectory, which will be explained in more detail below.

[0027] The navigation device receives the corresponding dynamic regions of interest (ROIs) from the computing unit. Specifically, a comprehensive list of all currently available ROIs can be transmitted to the navigation device, and the navigation device can also proactively output the corresponding ROIs to provide route suggestions to the user. This can occur, for example, when the user uses the navigation device. Here, the departure point specifically corresponds to the current location of the navigation device, which can be determined using established methods, such as using global navigation satellite systems like GPS and Galileo. Similarly, location can be determined using triangulation, for example, by assessing the mobile signal strength of at least three mobile communication network base stations within the communication range. Likewise, the navigation device can have the ability to identify characteristic terrain features, which can be provided, for example, by corresponding camera images from the vehicle's environmental cameras. In this case, the departure time corresponds to the current time.

[0028] Alternatively, users can pre-plan navigation routes for the navigation device, such as for the next day, the following week, or another future day. They can then select a point in time within the corresponding time window as the departure time. For example, a user might be on vacation and planning activities for that evening or the next day. In this case, the navigation device can suggest visiting or participating in spatiotemporally changing events or dynamic areas of interest. If the user plans a navigation route for a future day, the navigation device can also specifically query information about spatiotemporally changing events from its computing unit for that time window. This enables efficient storage utilization within the navigation device, as only relevant information needs to be retrieved and stored locally.

[0029] Typically, users can also manually specify the departure point, which further simplifies the planning of future trips. That is, the user knows, for example, that they will be in another location a few days later. Navigation devices can also set their own departure point and departure time; for example, the navigation device can access the user's digital calendar for this purpose and determine the navigation route based on the calendar entries read. Here, dynamic areas of interest can also be suggested as intermediate destinations on the navigation route determined to reach other destinations, and dynamic areas of interest or observation points can be selected as new (intermediate) destinations.

[0030] Here, the navigation device only needs to receive and suggest areas of interest that are accessible along the route initially planned by the user or based on the departure point and departure time. Therefore, the communication requirements with the computing unit can be further reduced, thereby making the method flow according to the invention more efficient.

[0031] Various methods can be used to calculate observation points, which will be explained below.

[0032] As previously mentioned, the configuration here involves the computing unit dividing the digital street map into multiple polygons, particularly symmetrical polygons, each assigned map information. This allows the computing unit to represent the digital street map as a dynamic graph, and the computing unit maps the dynamic region of interest onto this dynamic graph. Therefore, it is feasible to discretize the digital street map as a dynamic graph. This makes it possible to provide further functionality, which will be explained in more detail below. In this context, "street map" refers to any form of map existing in digital form, preferably including the orientation of road networks.

[0033] Polygons can have any imaginable shape and size. Polygons can be asymmetrical or symmetrical, for example. They can be triangles, rectangles, or other shapes that fill a plane. Different shapes can also be combined. Preferably, they are simply squares. The resolution or size of the polygons can also depend on the location. That is, the resolution can be increased in inhabited areas such as cities, and decreased in uninhabited rural areas. As map information, information such as POIs, AOIs, roads or road types, traffic rules, weather, visibility conditions, etc., can be stored (i.e., assigned) in the corresponding polygons.

[0034] A graph is an ordered pair of sets of nodes and sets of edges. Various types of graphs are known, such as: undirected graphs without multiple edges, directed graphs without multiple edges, undirected graphs with merged multiple edges, directed graphs with merged multiple edges, directed graphs with independent multiple edges, and so-called hypergraphs. Polygons in a street map represent the nodes of the graph. Adjacent polygons are connected by edges. Dynamic regions of interest are labeled on the nodes. Similarly, navigation routes can be represented on the graph through additional labels.

[0035] A dynamic graph is a graph that changes over time. Here, the topology and / or labels of the corresponding components of the graph can change. The changes associated with dynamic graphs are also called "evolution." By implementing digital street maps as dynamic graphs, it is possible to map dynamic regions of interest on the digital street maps mathematically and particularly efficiently. In particular, this makes it possible to use computational models known in graph theory to provide various functionalities associated with dynamic regions of interest.

[0036] Here, as previously described, height information is assigned as map information to each node of the map, where this height information describes the topographic height of the terrain and / or the geodesic height of objects located within the corresponding polygon. The calculation unit calculates the height difference between each node of the map and its corresponding neighboring node, where a free line of sight to a neighboring node exists when the height relative to that neighboring node remains constant or decreases. The corresponding height information may already be included in the topographic map, or it may be obtained from other external sources. Taking into account the terrain height, the calculation unit can thus determine, for example, whether hills or mountains obstruct the line of sight to the dynamic region of interest. Similarly, objects that can obstruct the line of sight may exist within the corresponding polygon, such as exceptionally tall trees, high-rise buildings, walls, etc.

[0037] If multiple tall objects exist within a polygon, the average height of all objects can be used as the height information, or the height of the tallest object within the polygon can be used. Alternatively, the extent of an object's line of sight on the plane can be used as a reference value to determine when to start considering the object's height. This extent can be determined as an absolute value or as a percentage of the corresponding polygon's total area. That is, if a user's line of sight can pass unobstructed through a thin tree or a tall lamppost, there is no need to consider the obstruction of such objects.

[0038] Specifically, information about tall objects can be collected and provided by the vehicles in the convoy. Thus, the height of the object and its extent on a plane can be estimated from camera images generated by one or more environmental cameras. For this purpose, information acquired using stereo cameras or by comparing camera images with a reference object can be utilized. Furthermore, the object can be scanned using sensors that enable the generation of depth information, such as LiDARe.

[0039] The computational unit identifies a chain of nodes originating from the dynamic region of interest (ROI) that allows free / unobstructed viewing of the ROI, and designates one node of this chain as the observation point. Therefore, the computational unit starts from the ROI and examines which node chains allow free / unobstructed viewing of the ROI. For this purpose, the height difference between the corresponding adjacent nodes is evaluated. A chain of nodes extending radially outward from the ROI can then be formed on the graph, with the perimeter of the chain formed by a first pair of nodes where the height increases in the direction toward the ROI. The observation point can then be located within the plane thus formed.

[0040] This process can be repeated at different points in time when the dynamic region of interest (POI) is further moved, allowing for the identification of different observation points at different times. This also makes it possible to find observation points that are inconsistent with the regular POI. For example, a point on a rural road that offers a view of a bay can be selected as an observation point. This, for example, makes whale watching possible. Here, an observation point is also understood as an observation line or observation surface. Thus, a dynamic POI can be a section of a rural road that can be observed within a certain time period. For elephant herds, it is also feasible to define a specific area as an observation surface, because, for example, in a savanna, elephants can be observed from different points in the distance.

[0041] To calculate the navigation route to be output, the spatiotemporal intersection between the trajectory of the dynamic region of interest and the possible navigation routes is calculated. The intersection of this set constitutes a set of nodes representing possible observation points.

[0042] An advantageous improvement to the navigation method according to the invention is further provided that the computing unit stores information about spatiotemporal change events in an event database, wherein at least the following information is stored for each event:

[0043] - Whether it is possible to travel to and / or observe the event; and

[0044] - When and where did the event occur?

[0045] Using an event database, it is feasible to store information about spatiotemporal change events and the resulting dynamic regions of interest (ROIs) within the computing unit, so that this information does not need to be retrieved from external sources with each request. The computing unit can also predict the spatiotemporal trajectory of events as described above and supplement the event database accordingly. In this way, more information about a specific event can be gradually collected and aggregated. Based on information about whether it is possible to reach and / or observe the event, the navigation device can be notified whether the ROI itself and / or the observation point should be designated as the destination. If both are possible, a query can be sent to the user of the navigation device, who can then decide whether they want to go to the ROI or observe it from an observation point far away from it. Thus, for example, one observation point can be used to observe sunrises, lunar eclipses, or auroras, while another can be used to observe passing elephant herds or bioluminescent plankton.

[0046] As observation points, regular points of interest (i.e., POIs) can be specifically suggested as destinations, but these POIs are determined taking into account the spatiotemporal trajectory of changing events. Thus, for example, a sunrise or whale pod can be seen particularly clearly from a viewpoint. Therefore, in a particularly simple embodiment of the method according to the invention, regular points of interest (such as parking lots) near a dynamic area of ​​interest can be identified, and, for example, the nearest point of interest can be designated as an observation point.

[0047] If the dynamic region of interest (POI) itself is defined as the destination, then any point within the POI, such as a point along a road or outside a road, can be precisely designated as the destination. For example, the geometric center of the POI could be chosen as the destination. If the event is, for example, bioluminescent plankton, then any location on the coastline where bioluminescent plankton appears could be suggested as the destination. However, mature POIs could also be considered, so that if there is a parking lot nearby, that parking lot itself could be set as the destination.

[0048] The event database may also store more information, such as event categories, preferably divided into periodic events and events with specific occurrence windows; methods for identifying events from information obtained from external sources; methods for calculating or estimating the time evolution of events or observation points or observation surfaces; mapping methods on maps; or other information, such as whether swimwear is required, which, for example, allows users to immerse themselves in self-luminous plankton.

[0049] In another advantageous design of the navigation method according to the invention, the computing unit obtains current information about spatiotemporal change events from at least one of the following sources:

[0050] - Vehicles in a connected fleet;

[0051] -A satellite, which provides aerial photographs that at least partially show dynamic areas of interest;

[0052] - A social network, in which articles about the event are shared; and / or

[0053] - Service provider.

[0054] Information about periodically occurring spatiotemporal change events can preferably be stored locally in the navigation device or computing unit. In this way, the navigation device can autonomously determine, for example, when and where a sunset can be observed, based on deterministic rules. As mentioned above, however, further measures may be needed to be taken to observe or travel to spatiotemporal change events with specific occurrence windows. This may require current information, which can be obtained, in particular, from the aforementioned sources.

[0055] In this way, specifically, the vehicles in the convoy can form a mobile sensor that collects information about spatiotemporal changing events. For this purpose, each vehicle can use internal and external sensors to record environmental information and transmit it to a central location for evaluation. Thus, vehicles can use environmental cameras to capture camera images of their surroundings and use external microphones to record sound.

[0056] For example, parked vehicles can be used to detect the passage of parades (such as carnival parades). A cloud server (which analyzes the information provided by the vehicles) then determines the current location of a particular parade float. Simultaneously, parade routes can be obtained from external service providers (such as parade organizers), and the location of a specific float within the parade route can be estimated by considering the floats' speed.

[0057] Therefore, the method according to the invention enables the following functionality: in an input interface, such as displayed on a navigation device or a vehicle-mounted navigation device with a touch-sensitive display, a user can select a single float in the parade, and suggestions on when and where the user must stop on the parade route to view the desired float are displayed. Specifically, the possibility of nearby free parking and the corresponding walking routes from the parking lot to the parade route can be considered, allowing the user to reach the corresponding location in a timely manner.

[0058] Furthermore, by considering satellite imagery, specific events, such as the passing of elephant herds, can be analyzed with particular reliability and ease. This allows for the identification of elephants in satellite images and the determination of their current location. Corresponding aerial photographs can also be automatically evaluated, for example, using known image recognition algorithms, preferably artificial intelligence. This also enables the estimation of the spatiotemporal trajectory of the resulting dynamic regions of interest. Thus, aerial photographs taken chronologically can be compared, and the direction and speed of movement of individual elephants can be estimated by tracking them. This information can be used to predict the future location of elephants, thereby also determining their future location.

[0059] Furthermore, information about specific events can be obtained from social networks. That is, users of social networks can be present at the scene of a spatiotemporally changing event and share related articles. These articles can be further enriched with photos (e.g., taken with a smartphone). The corresponding posts can also include the geographic coordinates of the event, particularly the geographic coordinates of camera images. This makes it possible to determine and estimate the current location or region of the spatiotemporal event, taking into account the corresponding geographic coordinates of the posts, which change over time. This information can be obtained from social networks in sophisticated ways. In particular, so-called web crawlers can be used for this purpose. The corresponding programs can also be based on the use of artificial intelligence, particularly through the use of artificial neural networks.

[0060] Information about spatiotemporal events can also be obtained from service providers, such as meteorological services or space agencies. This allows for information, for example, about solar storms and the resulting auroras. This enables estimations of when and where the auroras will appear. For instance, if a navigation device user is on holiday in northern Sweden during the winter and goes shopping by car at midday, the device can display a prompt informing the user that due to peak sunspot activity, the auroras will appear in the evening or at night. The navigation device then suggests corresponding observation points near the user's holiday location as destinations. This allows the user to plan a new activity for the evening that they were completely unaware of before. It might suggest observation points with particularly clear views of the aurora borealis and / or those relatively close to the user's travel distance.

[0061] Data exchange between external sources and the computing unit can be conducted in a proven and reliable manner, particularly through the use of standard interfaces such as APIs. If the computing unit is a cloud server, the relevant information can be obtained via the Internet. If the computing unit is part of a navigation device, the navigation device can have an Internet connection, particularly through the use of a mobile network, and therefore can also obtain information from external sources. The computing unit can also be another in-vehicle computing unit. The vehicle can have a telecommunications unit, through which a connection to the Internet can also be established via mobile communication or, if a Wi-Fi hotspot is available within range, via a WLAN connection.

[0062] In another advantageous design of the navigation method according to the invention, the computing unit identifies multiple potential observation points, and the user manually selects or the computing unit automatically selects the observation point determined as the destination, thereby minimizing the travel time and / or distance from the departure point to the destination, particularly by considering the observation point as an intermediate target. Therefore, the user can actively allow the navigation device to suggest dynamic regions of interest (ROIs) and select them as destinations. The user can freely choose the departure point and departure time, thus enabling the determination of a large number of destinations. Therefore, the user can manually choose when and where to travel to or observe spatiotemporal changes. However, the computing unit can also make this selection automatically. This is particularly true when the user programs other navigation routes into the navigation device, and the navigation device then suggests corresponding ROIs as intermediate targets. Here, ROIs accessible along the original route during travel can be suggested as intermediate targets. If different observation points are available, the computing unit or navigation device selects the point with the shortest travel distance and / or travel time, or suggests such a point individually. This enables particularly rapid access to ROIs or observation points.

[0063] Another advantageous design of this navigation method is that the navigation device recalculates the navigation route during the journey to the destination, particularly by considering the updated dynamic region of interest. The recalculation of the navigation route is well known from the prior art. Thus, alternative routes can be calculated, for example, due to road closures or congestion. However, this is always a static boundary condition. According to the invention, the dynamic region of interest, however, is in motion, which makes the recalculation of the navigation route correspondingly challenging. Therefore, not only the current traffic conditions or the boundary conditions of the navigation route planning must be considered, but also the temporal changes in the location of the dynamic region of interest. According to the invention, both boundary conditions are considered equally, which makes it possible to determine the navigation route with particular reliability.

[0064] In another advantageous design of the navigation method according to the invention, the navigation device proactively suggests to the user travel to or observe spatiotemporally changing events represented by dynamic regions of interest, particularly by considering user preferences, where user preferences describe the user's preferred event categories. As previously mentioned, this allows for the suggestion of activities the user would not otherwise consider. Here, the user can pre-determine user preferences, i.e., which event categories should be preferentially suggested automatically, such as whale watching or aurora viewing. This ensures an improved user experience. Therefore, suggestions that the user would not accept can be disregarded. To input user preferences, the user can use any mature human-machine interface, such as a touch-sensitive display device.

[0065] A navigation system, comprising at least one navigation device, particularly an in-vehicle navigation device, is configured according to the invention to perform the methods described above. A computing unit may be integrated into the navigation device. Alternatively, the computing unit may be integrated into the corresponding vehicle. The computing unit may also be an external computing device, such as a cloud server. Therefore, in addition to the navigation device, the navigation system may also include a computing unit located external to the navigation device. The computing unit possesses a corresponding interface to obtain information about spatiotemporal change events. In particular, the corresponding information can be obtained via the Internet through an API.

[0066] The computing unit and the navigation device each include a computer-readable storage medium having a computer program product that, when implemented on a processor, enables the provision of method steps to be performed by the respective components according to the method of the invention. Attached Figure Description

[0067] Other advantageous technical solutions of the navigation method according to the present invention are also embodied in the embodiments described in detail below with reference to the accompanying drawings.

[0068] in:

[0069] Figure 1 The diagram shows two map segments that illustrate dynamic regions of interest derived from spatiotemporally changing events, as well as various observation points used to observe these events.

[0070] Figure 2 This diagram illustrates the discretization of a digital street map using a dynamic graph.

[0071] Figure 3 A schematic diagram showing the position of the dynamic region of interest in the dynamic graph at different points in time;

[0072] Figure 4 A schematic diagram of the node chain is shown; and

[0073] Figure 5A schematic diagram of the components involved in the navigation method according to the present invention is shown. Detailed Implementation

[0074] The navigation method according to the present invention enables for the first time the calculation of a navigation route 20 to a dynamic region of interest 2 or an observation point 3 (see...). Figure 5 This allows us to observe spatiotemporal change event 1 corresponding to dynamic region of interest 2. Spatiotemporal change event 1 is, for example, a periodic change event, such as sunrise or sunset, or an event with a specific occurrence time window, such as a march or demonstration.

[0075] exist Figure 1 In a), event 1, the spatiotemporal change, is a march, the route of which is highlighted in bold on digital street map 6. At different points in time, the marching contingent is located at different points along the march route. Figure 1 In a), the location of the parade at different times is highlighted as a separate dynamic area of ​​interest 2.

[0076] Moreover, in Figure 1 a) also includes an example drawing of observation point 3, where the parade is located exactly at... Figure 1 When the dynamic area of ​​interest 2 is outlined with a solid line in a), the parade can be observed "very well" from that observation point.

[0077] exist Figure 1 In (b), the spatiotemporal change event 1 is sunset, which can be advantageously observed from the exemplary observation point 3. Depending on the date, observation points 3 at different times or locations are suggested here, enabling users of navigation devices to reach the appropriate observation point 3 in a timely manner to observe the sunset when determining navigation route 20. Since sunsets are typically observable throughout the city, the dynamic area of ​​interest 2 here is very large.

[0078] To map the dynamic region of interest 2 onto digital street map 6, digital street map 6 is discretized. This is done in... Figure 2 This is explained in the diagram. For clarity, only certain elements of the same type are labeled with reference numerals. Thus, the digital street map 6 is divided into multiple polygons 7, from which a dynamic diagram 8 is derived. The dynamic diagram 8 includes multiple nodes 9, with each polygon 7 assigned one node 9. The polygons 7 are adjacent to each other via edges 13. Edges 13 are represented in the dynamic diagram 8 by connecting lines 14 between nodes 9.

[0079] Moreover, in Figure 2 The image also highlights dynamic region of interest 2 and one of its adjacent nodes 11. The following text is based on... Figure 4 Explanation: How can we determine the free line of sight to the dynamic region of interest 2 through node chain 12 using dynamic graph 8?

[0080] Figure 3 To reiterate, the dynamic region of interest 2 or spatiotemporal change event 1 is represented in the digital street map 6 and the dynamic graph 8 at different time points t1, t2, t3, and t4. n The direction.

[0081] The navigation device can calculate the navigation route to either the dynamic region of interest 2 or the observation point 3. Here, a free line of sight must exist from the observation point 3 to the dynamic region of interest 2 or to the spatiotemporal change event 1. The operation for this is performed via… Figure 4 This will be explained. Starting from the dynamic region of interest 2, a node chain 12 is generated radially outward in the dynamic graph 8, wherein... Figure 2 and Figure 4 A representative node chain 12 is drawn. Each node 9 is assigned a height information 10, which describes the topographical height of the terrain or the geodesic height of an object located within polygon 7. Figure 4 In this diagram, the shape of height information 10 is represented by the degree of its vertical extension. Here, one of the nodes 9 highlighted with shade can be chosen as observation point 3 because the height continuously decreases in the direction towards the dynamic region of interest 2. All other nodes 9 in the node chain 12 cannot be observation points 3 because the free / unobstructed line of sight is blocked by node 9.1. The orientation of node chain 12 in the dynamic diagram 8 is... Figure 2 and Figure 4 Each element is indicated by an arrow.

[0082] Figure 5 The components participating in the navigation method according to the invention are illustrated in schematic form. An event database 4 is provided, which stores at least the following information: whether it is possible to travel to and / or observe event 1, and when and where event 1 occurs. The corresponding information is forwarded to the computational model 16 via data stream 15. Connected to data stream 15 is a memory 17 for storing metadata about the dynamic region of interest 2. This metadata may specifically include: event category, method for identifying the event in data stream 15, location of the spatiotemporally changing event 1, method for calculating the time variation of event 1, method for calculating observation point 3 or observation surface (depending on time), method for mapping the dynamic region of interest 2 on a map or digital street map 6, and other information. Other information includes, for example, what items the user should preferably carry to participate in the spatiotemporally changing event 1. If event 1 is, for example, bioluminescent plankton, the user should bring a swimsuit to allow themselves to be surrounded by plankton in the sea.

[0083] Information about the spatiotemporal change event 1 is obtained from external sources 5. For example, source 5.1 is the vehicles in the convoy, source 5.2 is a satellite providing aerial photographs of the dynamic region of interest 2, source 5.3 is a social network, and source 5.4 is a service provider. Information can be obtained via mature interfaces, such as through the internet using known APIs.

[0084] Information is provided to computational model 16, which determines the dynamic region of interest 2 and observation point 3. Different mathematical models are prepared for this purpose, depending on the type of information provided. The spatiotemporal trajectory of periodic events (such as sunsets) can be calculated using known equations. AI models, among others, can be used to predict the location of elephant herds based on aerial photographs.

[0085] Operational model 18 has access to computational model 16. Matching module 19 of operational model 18 acts as an interface between computational model 16 and the navigation route 20 output on the navigation device. Therefore, computational model 16 calculates or estimates the time trajectory of the dynamic region of interest 2. Similarly, it determines the corresponding observation point 3. Both results are labeled and stored at the front end of dynamic graph 8. The navigation device can then read the corresponding time-dependent points, ultimately enabling the determination of navigation route 20. Components "event database 4" and "computational model 16" are part of a computational unit not shown in detail here. In this case, this is specifically a cloud server or the navigation device itself. The matching module 19 and the calculation of navigation route 20 are then performed within the navigation device itself. Therefore, operational model 18 is part of the navigation device.

Claims

1. A navigation method, wherein a navigation device calculates a navigation route (20) from a point of origin to a destination. in - The computing unit acquires information about at least one spatiotemporal change event (1); - The computing unit estimates the spatiotemporal trajectory of the event (1) within a future time range and stores it as a dynamic region of interest (2). - The navigation device receives the dynamic interest area (2), sets the departure point and departure time, and calculates the navigation route (20) from the departure point to the destination, wherein the destination is located within the dynamic interest area (2), or sets the observation point (3) that can observe the event (1) as the destination; - The computing unit divides the digital street map (6) into multiple polygons (7), each polygon (7) being assigned map information, so that the polygons (7) represent the digital street map (6) in the form of a dynamic graph (8), and the computing unit maps the dynamic region of interest (2) on the dynamic graph (8), wherein the dynamic graph (8) includes multiple nodes (9), each polygon (7) being assigned a node (9). Its features are, - Height information (10) is assigned as map information to each node (9) of the dynamic map (8), wherein the height information (10) describes the topographic height of the terrain and / or the geodesic height of objects located within the corresponding polygon (7), and the calculation unit calculates the height difference between each node (9) of the dynamic map (8) and its respective neighboring node (11), wherein there is a free line of sight to the neighboring node (11) when the height relative to a neighboring node (11) remains constant or decreases; and wherein - The computing unit determines a chain of nodes (12) that starts from the dynamic region of interest (2) and has a free line of sight to the dynamic region of interest (2), and sets one node (9) of the chain of nodes (12) as the observation point (3).

2. The navigation method according to claim 1, Its features are, The computing unit stores information about spatiotemporal change events (1) in an event database (4), wherein at least the following information is stored for each event (1): - Whether it is possible to travel to and / or observe the event (1); and - When and where the event (1) occurs.

3. The navigation method according to claim 1 or 2, Its features are, The computing unit obtains current information about the spatiotemporal change event (1) from at least one of the following sources (5): - Vehicles in a networked fleet (5.1). - Satellite (5.2), wherein the satellite provides aerial photographs that at least partially display the dynamic region of interest; - Social networks (5.3), wherein articles about the event are shared on the social network; and / or - Service Provider (5.4).

4. The navigation method according to any one of claims 1 to 3, Its features are, The computing unit determines multiple potential observation points (3), and the user manually selects or the computing unit automatically selects the observation point (3) determined as the destination, thereby minimizing the travel time and / or distance from the origin to the destination, especially by considering the observation point (3) as an intermediate target.

5. The navigation method according to any one of claims 1 to 4, Its features are, The navigation device recalculates the navigation route (20) on the way to the destination, in particular by taking into account the updated dynamic region of interest (2).

6. The navigation method according to any one of claims 1 to 5, Its features are, The navigation device proactively suggests to the user that they go to or observe spatiotemporal change events (1) represented by dynamic regions of interest (2), in particular by taking into account user preferences, wherein the user preferences describe the user’s preferred event categories.

7. A navigation system, comprising at least one navigation device, particularly an in-vehicle navigation device. Its features are, The navigation device is configured to perform the method of any one of claims 1 to 6.

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