DE102016224290B4 - Process for computer-aided traffic monitoring of route sections of a road network - Google Patents

Abstract

Process for computer-aided traffic monitoring of route sections (FS) of a road network, in which
based on the provided traffic data (VD), which characterize the current and / or past traffic volume of vehicles (5) on several route sections (FS), priority measures (PM) are determined for the respective route sections (FS), a respective priority measure (PM) characterizes the amount of current and / or future traffic volume on the respective route section (FS);
A plurality of drones (1), each comprising an image capturing device (4), are controlled as a function of the priority measures (PM) in such a way that at least some of the drones (1) automatically fly to one or more such route sections (FS) whose priority measures ( PM) characterize higher current and / or future traffic volume compared to all other of the multiple route sections (FS);
the respective drones (1) use their image capture device (4) to capture image data (BD) from the route sections (FS) flown to;
the image data (BD) of a respective route section (FS) flown to and / or information derived therefrom about the traffic volume on the respective route section flown (FS) transmitted to a number of road users (6) and via at least one output unit (7, 9), which is assigned to a respective road user (6) of the number of road users (6), are output for perception by the respective road user (6).

Description

It is known from the prior art to use drones (i.e. unnamed flying objects) in combination with vehicles. For example, drones that include image capturing devices can accompany an assigned vehicle or support the parking of a vehicle. It is also known to use drones for traffic monitoring.

In the document DE 10 2012 019 064 B3 describes a traffic monitoring system in which a drone transmits data received from a stationary monitoring unit.

Out W02015 / 134453 A1 a method for estimating a volume of travelers is known, in which an aerial photograph is recorded. An image evaluation should recognize and count travelers in the recorded aerial photograph and estimate the volume of travelers from the number of travelers and the size of an evaluated area in the aerial photograph.

WO2016 / 155844 A1 describes a method for observing a control area, in which sensor nodes of a networked sensor platform collect measurement data for several sub-areas of the control area. A predictability of the measurement data is analyzed using a prediction model. Future measurement data are forecast and the reliability of the measurement data forecast is assessed using the prediction model. Drones, mobile robots or personal mobile devices are being considered as the sensor nodes of the networked sensor platform.

The object of the invention is to provide a method for computer-aided traffic monitoring of route sections of a road network, with which road users are reliably informed of route sections with increased traffic.

This object is achieved by the method according to claim 1 or the system according to claim 12. Further developments of the invention are defined in the dependent claims.

The method according to the invention is used for computer-aided traffic monitoring of route sections of a road network. In other words, the steps of the method explained below are carried out with the aid of a computer without manual intervention by a user. For this purpose, a computer means is used, which can possibly be distributed over several separate computer units.

In the method according to the invention, priority measures for the respective route sections are first determined on the basis of provided traffic data, which characterize the current and / or past traffic volume of vehicles (ie motor vehicles), a respective priority measure determining the level of the current and / or future traffic volume characterized a respective route section. Here and in the following, the term traffic volume is to be understood in such a way that the greater the traffic density (i.e. the number of vehicles per unit area), the greater the size. If necessary, the traffic volume can also depend on the traffic flow, a low traffic flow preferably corresponding to a higher traffic volume, since low traffic flow indicates a risk of congestion. In a simple variant of the invention, the priority measure corresponds to the current traffic volume, which results from the traffic data provided. Nevertheless, the priority measure can also be calculated with the aid of the current or past traffic volume for a future point in time. In particular, machine learning processes, such as Regression methods. The above term of the traffic data provided is to be understood as data which are input variables of the method according to the invention. Their determination is therefore not part of the method according to the invention. In particular, the traffic data provided comes from one or more external information sources.

In the method according to the invention, several drones, each comprising an image capturing device, are controlled as a function of the priority measures in such a way that at least some of the drones automatically fly to one or more sections of the route whose priority measures have higher current and / or future traffic volumes than all other traffic characterize several route sections. In other words, drones prefer to fly to sections of the route with high or increased traffic. To achieve this, the drones can e.g. Approach the individual route sections in chronological order in descending order of priority dimensions. Likewise, a threshold value can also be set, where appropriate, whereby drones only fly to those sections of the route whose priority measure is above the threshold value. If necessary, there is also the possibility that drones fly to other sections of the route in addition to the route sections defined above, e.g. those sections of the route for which it follows from the traffic data that an accident has occurred there.

After the drones have flown to the relevant route sections, record They use their image capturing device to image data from these route sections to which they are approached. The image data of a respective route section and / or information derived therefrom about the volume of traffic on the respective route section flown to is finally transmitted to a number of road users (i.e. people taking part in road traffic) and via at least one output unit (e.g. display unit) which a respective road user receives Number of road users assigned is issued for perception by this road user. The information about the traffic volume derived from the image data can be obtained by known image analysis methods.

The method according to the invention has the advantage that road users are informed very precisely and reliably by means of drones about route sections with increased traffic. This is achieved by activating the drones in such a way that information is recorded by the drones and transmitted to road users in any case for route sections with increased traffic.

In a variant of the method according to the invention, the drones are controlled by a central processing unit, which transmits corresponding commands for the flight of the drones to them. Alternatively or additionally, however, decentralized control of the drones can also be carried out via corresponding control devices in the drones, the control devices communicating with one another.

Depending on the design of the method according to the invention, different image capturing devices can be used in the drones. The image capture devices preferably each comprise one or more cameras and / or one or more radar sensors and / or one or more lidar sensors.

In a further variant of the method according to the invention, the image data of a respective route section flown to and / or the information derived therefrom about the traffic volume on the respective route section flown to is displayed on a display of a mobile terminal and / or on a display of a vehicle navigation system. In other words, the at least one output unit comprises a display of a vehicle navigation system or a mobile terminal, such as of a cell phone.

In a further embodiment of the method according to the invention, the image data of a respective route section flown to and / or the information derived therefrom about the volume of traffic on the respective route section flown to are transmitted at least temporarily by the respective drones by means of broadcast (i.e. without explicit recipient addressing). The image data or the derived information are preferably stored in a server after they have been sent out and then called up by the server by means of reception which are assigned to the respective road users.

In a further embodiment of the invention, the image data of a respective route section flown to and / or the information derived therefrom about the volume of traffic on the respective route section flown to are addressed at least temporarily to the number of road users, i.e. to corresponding receiving addresses of receiving means of the road users. It is thus determined before the image data or the information derived therefrom is sent, to which road users they should arrive.

In a further variant of the method according to the invention, the image data of a respective route section flown to and / or the information derived therefrom about the volume of traffic on the respective route section flown to are transmitted to those road users who are on the respective route section flown to or at a distance below a threshold value the respective route section flown to. This ensures that the image data or the derived information reaches those road users who are affected by it.

In a further embodiment of the method according to the invention, it is determined for at least one road user from the image data transmitted to him and / or information derived therefrom whether there is an increased traffic volume (i.e. a traffic volume above a predetermined threshold) at the location of the road user. If this is the case, a delay message, such as e.g. generates an SMS message, which is addressed to one or more contacts, which are stored in a digital memory, e.g. a digital address book. The digital memory is provided, for example, in a mobile terminal of the road user. With this variant according to the invention, contacts of a road user can be informed in good time about the delay.

Depending on the embodiment of the above embodiment, the generated delay message can be output to the respective road user via an output means and / or can be automatically sent to the contact or contacts via a transmission means. When the delay message is output via an output means, such as, for example, when it is shown on a display, there may be the possibility that the road user is still processing the message or that the decision is made that the message should not be sent.

In a further variant, the respective road user for whom the above delay message is generated is assigned a navigation destination in a vehicle navigation system and the generated delay message is addressed to contacts whose geographic addresses (e.g. place of residence or company location) contained in the digital memory Correspond to the navigation target or are in the vicinity of the navigation target (ie at a distance below a predetermined threshold from this target).

In a further embodiment, the generated delay message is addressed to those contacts which are stored in an appointment calendar in the digital memory as participants in an appointment within a predetermined period of time in the future (in particular the next future appointment). With the two variants of the invention just described, it is achieved that contacts affected by a delay of the road user are appropriately informed.

In addition to the method described above, the invention relates to a system for computer-aided traffic monitoring of route sections of a road network. This system is set up to carry out the method according to the invention or one or more preferred variants of the method according to the invention. In other words, the system comprises one or more suitable computer units for the computer-aided implementation of the corresponding method steps. The drones described above are also part of the system.

An embodiment of the invention is described below with reference to the accompanying 1 described in detail. This figure shows a schematic representation which illustrates the implementation of a variant of the method according to the invention.

That based on 1 explained embodiment uses a variety of drones 1 , what a 1 are shown schematically. The drones are operated using a central control or processing unit 2 appropriately controlled. This control unit issues appropriate commands to the individual drones 1 in order to control their flight to corresponding sections of the route and also to transmit image data recorded by the drones to certain road users. Instead of a central processing unit 2 the flight of the drones can also be controlled decentrally by control devices in the respective drones. In this case, the control devices of the individual drones communicate with each other wirelessly.

The central processing unit 2 accesses traffic data VD an external source of information 3 to as by the arrow P1 is indicated. The traffic data VD characterize the current and / or past and / or future traffic density (ie number of vehicles per unit area) on different route sections in a road network. If necessary, the traffic data can also contain the current and / or past and / or future traffic flow (ie the number of vehicles per unit of time) as information. The traffic data VD thus characterize the current or past and / or future traffic volume on different route sections. The traffic data represent input variables of the method described below and their determination is not part of the invention. The traffic data can, for example, come from road building authorities or common providers such as Google or Inrix.

The traffic data VD are in the processing unit 2 evaluated to measure priority from this data PM for the individual route sections specified in the traffic data. In the embodiment described here, a higher priority measure describes PM a higher current traffic volume. If necessary, the priority measure can also reflect a future traffic volume. In this case, the traffic data VD with machine learning methods known per se, such as, for example, regression methods, in order to predict future traffic volumes from current and past traffic data.

The determination of the priority measure PM can be done in different ways. For example, the priority measure may be the sum of two sizes, one size being proportional to traffic density and the other size being indirectly proportional to traffic flow. These sizes can be weighted differently if necessary. Other ways of calculating the priority measure are within the scope of professional action.

Based on the priority measures PM the individual sections of the route become the drones 1 appropriately controlled. The control takes place in such a way that sections of the route with a high volume of traffic are preferably approached by the drones in accordance with the priority measures. In other words, the priority measures are in descending order PM the individual sections of the route flown to by the respective drones. Alternatively, it is also possible for the drones to fly to all those route sections whose priority measure exceeds a predetermined threshold value.

Each of the drones 1 comprises an image capturing device in the form of a camera 4 , this camera only for the bottom of the in 1 shown drone is indicated. With the help of this drone, the further process steps are also explained, each of the drones shown 1 carries out these process steps analogously. The drone flies by means of control through the processing unit 2 a route section that in 1 With FS is designated and is shown in plan view. A large number of vehicles are located on this route section 5 , which are only indicated schematically. The route section has a higher traffic volume than the norm. The drone is controlled by the processing unit 2 over this route section FS positioned and takes with the camera 4 Images of this route section. The image data captured by the drone BD z. B. via a broadcast to the central processing unit 2 transmitted as through the arrow P2 is indicated.

The image data is obtained from the central processing unit BD z. B. then provided to other road users via a broadcast. Alternatively, the image data BD also directly from the drones 1 be provided as by the arrow P4 is indicated. In the embodiment described, corresponding receiving devices call the image data from interested or affected road users BD from. For example, such a picture data can be called up by a road user which relates to a route section on which the road user is currently himself. Likewise, the image data BD be provided as part of a push service. The image data are then automatically transmitted to receiving devices (in particular mobile end devices) by certain road users, such as subscribers to the push service. For this purpose, an app can be provided in the respective end devices. The image data can also be transmitted to a vehicle infotainment system of the vehicle belonging to the corresponding road user.

An example is in 1 the transmission of the image data BD towards the driver 6 of a vehicle 5 ' shown. The image data BD relate to a route section on which the vehicle is located 5 ' is currently located. The image data is in the vehicle 5 ' on the display of a vehicle infotainment system and a driver's device 6 brought to the display. This is in the detail view THERE in 1 shown. This detailed view DA shows the top view of the vehicle cockpit of the vehicle 5 ' , You can see the steering wheel 8th as well as the display 7 of the vehicle infotainment system. Furthermore, one from the driver 6 carried mobile phone 9 seen. The image data BD are both on the display of the mobile phone 9 as well as on the display 7 of the vehicle infotainment system.

In a preferred variant of the method described above is in the mobile phone 9 or possibly also in the vehicle infotainment system, a delay message is automatically generated and displayed on the display of the mobile phone or the vehicle infotainment system. The delay message contains a standard text that informs the recipient that the driver is late due to increased traffic. The recipients of the messages are from those in the cell phone 9 digitally saved contacts selected. This is done in a variant using the navigation target stored in the vehicle navigation system. The vehicle navigation system is part of the vehicle infotainment system. In this case, the message is sent to those contacts in the cell phone 9 sent whose place of residence or work is at the location of the navigation destination. In another form, the digital diary is in the mobile phone 9 analyzed. In this case, the message is sent to those contacts in the cell phone 9 sent, which are stored as participants for the next upcoming appointment in the appointment calendar.

The generated or displayed delay message can be sent by the driver 6 can be sent manually after the check, whereby it can be edited beforehand or the recipient group can be changed. Nevertheless, there is also the possibility that the corresponding message is automatically sent to the appropriate group of recipients immediately after being displayed or even without being displayed. The message is preferably only sent when an estimated delay exceeds a predetermined threshold or the delay is so great that the time of a corresponding appointment in the appointment calendar of the mobile telephone can no longer be kept.

The embodiments of the method according to the invention described above have a number of advantages. In particular, road users are informed quickly, reliably and precisely about the current traffic situation using drone image data. If necessary, the image data can also be used to more precisely predict the arrival time at a destination, which is calculated in a vehicle navigation system. The generated image data can also be used not only by road users, but also by other bodies, such as the police and authorities (e.g. road construction authorities). In particular, there is also the possibility that the drones fly off sections of the route at times when they are not fully utilized in order to capture image material purely for the purpose of data acquisition for authorities.

LIST OF REFERENCE NUMBERS

1

drones

2

central processing unit

3

external source of information

4

Image capture device

5, 5 '

vehicles

6

driver

7

Display of a vehicle infotainment system

8th

steering wheel

9

mobile phone

BD

image data

FS

Route section

PM

priority level

VD

traffic data

P1, P2, P3, P4

arrows

Claims (13)

Process for computer-aided traffic monitoring of route sections (FS) of a road network, in which based on the provided traffic data (VD), which characterize the current and / or past traffic volume of vehicles (5) on several route sections (FS), priority measures (PM) are determined for the respective route sections (FS), a respective priority measure (PM) characterizes the amount of current and / or future traffic volume on the respective route section (FS); A plurality of drones (1), each comprising an image capturing device (4), are controlled as a function of the priority measures (PM) in such a way that at least some of the drones (1) automatically fly to one or more such route sections (FS) whose priority measures ( PM) characterize higher current and / or future traffic volume compared to all other of the multiple route sections (FS); the respective drones (1) use their image capture device (4) to capture image data (BD) from the route sections (FS) flown to; the image data (BD) of a respective route section (FS) flown to and / or information derived therefrom about the traffic volume on the respective route section flown (FS) transmitted to a number of road users (6) and via at least one output unit (7, 9), which is assigned to a respective road user (6) of the number of road users (6), are output for perception by the respective road user (6). Procedure according to Claim 1 , characterized in that the drones (1) are controlled via a central processing unit (2) and / or decentrally via control devices in the individual drones (1) which communicate with one another. Procedure according to Claim 1 or 2 , characterized in that the image capture devices (4) in the drones (1) each comprise one or more cameras and / or one or more radar sensors and / or one or more lidar sensors. Method according to one of the preceding claims, characterized in that the image data (BD) of a respective route section (FS) flown to and / or the information derived therefrom about the traffic volume on the respective route section flown (FS) on a display of a mobile terminal (9) and / or are shown on a display (7) of a vehicle navigation system. Method according to one of the preceding claims, characterized in that the image data (BD) of a respective route section (FS) flown to and / or from it derived information about the volume of traffic on the respective route section (FS) flown to and preferably stored in a server (2) and then retrieved by the server (2) by receiving means which are assigned to the respective road users (6). Method according to one of the preceding claims, characterized in that the image data (BD) of a respective route section (FS) flown to and / or the information derived therefrom about the traffic volume on the respective route section flown (FS) addressed at least temporarily to the number of road users (6) are transmitted. Method according to one of the preceding claims, characterized in that the image data (BD) of a respective route section (FS) flown to and / or the information derived therefrom about the traffic volume on the respective route section flown (FS) are transmitted to such road users (6) , which are located on the respective route section flown to (FS) or at a distance below a threshold value to the respective route section flown to (FS). Method according to one of the preceding claims, characterized in that for at least one road user (6) it is determined from the image data (BD) transmitted to it and / or information derived therefrom whether there is an increased traffic volume at the location of the respective road user (6), in the event of increased traffic volume, a delay message is generated with a computer unit assigned to the respective road user (6) and is addressed to one or more contacts which are read from a digital memory. Procedure according to Claim 8 , characterized in that the generated delay message is output to the respective road user (6) via an output means and / or is automatically sent to the contact or contacts via a transmission means. Procedure according to Claim 8 or 9 , characterized in that the respective road user (6) is assigned a navigation destination in a vehicle navigation system and the generated delay message is addressed to contacts whose geographic addresses contained in the digital memory correspond to the navigation destination or are in the vicinity of this navigation destination. Procedure according to one of the Claims 8 to 10 , characterized in that the generated delay message is addressed to those contacts which are stored in a diary in the digital memory as participants in an appointment within a predetermined period of time in the future. System for computer-aided traffic monitoring of route sections (FS) of a road network, the system being set up to carry out a method in which Based on the provided traffic data (VD), which characterize the current and / or past traffic volume of vehicles (5) on several route sections (FS), priority measures (PM) are determined for the respective route sections (FS), a respective priority measure (PM) characterizes the amount of current and / or future traffic volume on the respective route section (FS); A plurality of drones (1), each comprising an image capturing device (4), are controlled as a function of the priority measures (PM) in such a way that at least some of the drones (1) automatically fly to one or more such route sections (FS) whose priority measures ( PM) characterize higher current and / or future traffic volume compared to all other of the multiple route sections (FS); the respective drones (1) use their image capture device (4) to capture image data (BD) from the route sections (FS) flown to; the image data (BD) of a respective route section (FS) flown to and / or information derived therefrom about the traffic volume on the respective route section flown (FS) transmitted to a number of road users (6) and via at least one output unit (7, 9), which is assigned to a respective road user (6) of the number of road users (6), are output for perception by the respective road user (6). System according to Claim 12 , characterized in that the system for performing a method according to one of the Claims 2 to 11 is set up.

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