Method and system for driving decision-making based on a real-time map of road traffic conditions

Abstract

The present invention relates to a method for making driving decisions based on a real-time map of road traffic conditions, in which a plurality of quantum sensors are arranged in each of a plurality of vehicles, in which measurements of driving parameters are carried out simultaneously across all vehicles by the quantum sensors in a continued embodiment, in which a road environment surrounding the driving route is formed for a driving route of an ego vehicle (11), in which a volatile group (12) is formed by all vehicles of the plurality of vehicles that travel in the road environment, in which measurement data (13) of the driving parameters are received by a computing unit from all vehicles of the volatile group according to a quantum internet protocol, in which the real-time map (14) of road traffic conditions is provided for the ego vehicle on the basis of these measurement data and taking into account their mutual dependencies,in which the driving decision-making (15) is carried out by an autonomous driving system based on the real-time map, and driving operation of the ego vehicle controlled by the autonomous driving system is continued based on this driving decision-making. Furthermore, a system is presented with which the method can be carried out.

Description

[0001] The present invention relates to a method for making driving decisions based on a real-time map of road traffic conditions. Furthermore, a system is presented with which the method can be implemented.

[0002] Decision-making in autonomous driving processes can have fatal consequences even due to minor misjudgments of the vehicle's surroundings. To avoid such catastrophic situations, an autonomous decision-making system requires continuous input of real-time data from sensors monitoring the vehicle's surroundings. A real-time map of road conditions is particularly important here. Road conditions depend on many parameters, such as vehicle vibrations, weather conditions (including outside temperature), wear, and tire rotation speed. In particular, simultaneously measuring such parameters and addressing their interdependencies poses a major challenge in order to ultimately achieve correct decision-making.

[0003] The publication DE 10 2022 112 269 A1 describes a vehicle equipped with a deployable quantum computer. This quantum computer is part of the vehicle's navigation system and works with various sensors, including a GPS sensor and a quantum sensor. The quantum computer captures and classifies environmental data provided by the sensors and identifies objects in the vehicle's surroundings.

[0004] A vehicle navigation system based on quantum sensors is known from US 2016 / 0018525 A1. The system uses gravimeters and gravimetric maps to determine the vehicle's current position or to serve as a real-time terrain estimation tool. A photonic sensor module can be configured as an entanglement-based quantum sensor, providing information about the presence, range, and geometry of potential obstacles not included in the most up-to-date gravimetric and navigation maps. This data can be used to correct the current estimated navigation position or to plan safe movement.

[0005] Publication WO 2021 / 016095 A1 discusses a system in which a vehicle equipped with various sensors such as a gyroscope, an accelerometer, an orientation sensor, a proximity sensor, and a geolocation sensor requests more secure communication with another vehicle. This is done via a quantum network manager, which acts as a network function in a 5G network or as a service in vehicular networks. The requesting vehicle or a quantum network center connected to it sends a request to the quantum communication manager to establish a quantum connection between the two vehicles.

[0006] Against this background, it is an object of the present invention to present a method for providing real-time information on traffic conditions for a road map, whereby decisions regarding further travel or the route can be made based on this road map. This real-time road map should be available to both a vehicle driver and an autonomous driving system. Furthermore, a system with which the method can be implemented should be presented.

[0007] To solve the aforementioned problem, a method for driving decision-making based on a real-time map of road traffic conditions is proposed, in which a plurality of quantum sensors are arranged in each of a plurality of vehicles. The quantum sensors continuously perform measurements of driving parameters across all vehicles simultaneously. For a driving route of an ego vehicle, a road environment surrounding the route is formed. A volatile group is formed by all vehicles of the plurality of vehicles traveling in the road environment. A computing unit receives measurement data of the driving parameters from all vehicles of the volatile group according to a quantum internet protocol. Based on this measurement data and taking into account their mutual dependencies, the real-time map of road traffic conditions is provided for the ego vehicle.An autonomous driving system performs driving decisions based on the real-time map. The ego vehicle controlled by the autonomous driving system continues driving based on this driving decision.

[0008] By driving through the road environment with vehicles of the volatile group and transmitting the measurement data from their quantum sensors according to the Quantum Internet Protocol, the ego vehicle can advantageously access spatially distributed information sources on the road conditions prevailing at the same time. To this end, the computing unit generates the real-time map using a highly precise multi-parameter optimization. At the same time, the use of quantum sensors implicitly ensures the simultaneity of the measurement processes, so that the measurement data from the vehicles of the volatile group located at different locations can be compared with each other. Measurement data from a given vehicle can also be related to each other, advantageously enabling the treatment of their mutual dependencies, e.g., tire rotation speed in relation to ice or wet road conditions.Due to the quantized time signal, additional measurements whose measurement data have not been used so far can also be easily integrated into an analysis process for creating the real-time map.

[0009] Since the road environment of the ego vehicle can change depending on the driving decision, and furthermore the composition of the vehicles in the road environment at a given time can also change due to the ego vehicle's own driving activity, a dynamically changing, i.e. volatile, group membership takes place among the majority of vehicles.

[0010] It is conceivable that variables already calculated in the respective vehicles from the measurement data of the quantum sensors, such as parameter values of fit functions, could be exchanged using the Quantum Internet Protocol. It is also conceivable that the driving decision made for the ego vehicle based on the transmitted data could be sent back to the other vehicles in the volatile group, which could then, in turn, use this as a basis for their decision to adjust their own route if necessary. Thus, the real-time map of road traffic conditions is provided by the computing unit, but each driving decision is made by a respective autonomous driving system in the ego vehicle or the respective vehicles in the volatile group.

[0011] Real time is to be understood as at least a period of time in which a measurement in a quantum sensor in one of the vehicles of the group, a transmission of the measurement data to the ego vehicle and a conversion of the measurement data to the inventive provision of the real-time map of road traffic conditions are in a temporal relationship describing a current traffic situation, so that a driving decision can be made for an autonomous driving system or a vehicle driver based on this.

[0012] Accordingly, the real-time map can be displayed continuously on a driver display together with the current route, thus enabling the driver to monitor the respective driving decision of the autonomous driving system or, if necessary, to overrule it.

[0013] In one embodiment of the method according to the invention, the driving decision making for a driving behavior is selected from the following list: change of route, driving speed, headlight activity, fog light activity.

[0014] In a further embodiment of the method according to the invention, the driving parameters are selected from the following list: outside temperature, surrounding road users, driving speed, vehicle vibrations, weather conditions, outside temperature, air humidity, wetness, fog, snow, ice, wear condition and rotational speed of vehicle tires.

[0015] In a further embodiment of the method according to the invention, a traffic jam forecast along the route and for alternative routes in the surrounding road environment is calculated based on the real-time map and the measurement data on surrounding road users transmitted to the ego vehicle. The route is adjusted according to the shortest expected travel time. Alternatively or additionally, the route is adjusted with regard to safe road conditions based on the real-time map and the measurement data on the weather conditions, including in particular wetness, fog, snow, and ice.

[0016] In a further embodiment of the method according to the invention, the computing unit is formed by a central server in an information center. The central server continuously receives the measured data of the driving parameters from all vehicles in the volatile group according to the Quantum Internet Protocol, calculates the real-time map for the ego vehicle, and transmits the calculated real-time map to the ego vehicle.

[0017] Furthermore, a system for making driving decisions based on a real-time map of road traffic conditions is claimed, which system comprises a computing unit, a plurality of vehicles, each of which contains a plurality of quantum sensors, and an ego vehicle with an autonomous driving system. The quantum sensors are designed to simultaneously measure driving parameters across the plurality of vehicles. The computing unit is configured to form a volatile group with all vehicles from the plurality of vehicles that travel in a road environment of the ego vehicle, to receive measurement data of the driving parameters from all vehicles in the volatile group according to a quantum internet protocol, and to provide the real-time map of road traffic conditions for the ego vehicle based on this measurement data and taking into account their mutual dependencies.The autonomous driving system is configured to form a road environment surrounding a driving route of the ego vehicle and to transmit this to the computing unit, to execute the driving decision-making based on the real-time map, and to continue driving operation of the ego vehicle based on this driving decision-making.

[0018] In one embodiment of the system according to the invention, the driving decision-making process for a driving behavior is selected from the following list: change of route, driving speed, headlight activity, fog light activity.

[0019] In a further embodiment of the system according to the invention, the driving parameters are selected from the following list: outside temperature, surrounding road users, driving speed, vehicle vibrations, weather conditions, outside temperature, humidity, wetness, fog, snow, ice, wear condition and rotational speed of vehicle tires.

[0020] In a further embodiment of the system according to the invention, the autonomous driving system is configured to calculate a traffic jam forecast along the route and for alternative routes in the road environment on the basis of the real-time map in relation to measurement data on surrounding road users transmitted to the ego vehicle and to adapt the route according to a shortest expected travel time and / or to adapt the route with regard to safe road conditions in the case of measurement data on the weather conditions, including in particular wetness, fog, snow, ice.

[0021] In a further refinement of the system according to the invention, the computer unit is a central server in an information center. The central server is configured to continuously receive the measured data of the driving parameters from all vehicles in the volatile group according to the Quantum Internet Protocol, calculate the real-time map for the ego vehicle, and transmit the calculated real-time map to the ego vehicle.

[0022] Further advantages and embodiments of the invention will become apparent from the description and the accompanying drawings.

[0023] It is understood that the features mentioned above and those to be explained below can be used not only in the combination specified in each case, but also in other combinations or on their own, without departing from the scope of the present invention. Fig. 1 shows schematically an embodiment of the method according to the invention.

[0024] In the Fig. 1 schematically shows an embodiment 10 of the method according to the invention. A dynamically changing, i.e., volatile group of vehicles 12 comprising a plurality of vehicles equipped with quantum sensors continuously performs measurements of driving parameters, such as outside temperature, speed, wetness, etc., and is in mutual contact via a quantum internet protocol. For an ego vehicle 11 as part of the volatile group, a real-time map 14 of road traffic conditions is calculated from these measurement data 13. This map serves as the basis for an autonomous driving system controlling the ego vehicle 11 to make a driving decision 15 to control the driving operation. List of reference symbols 10 Scheme with real-time map of road traffic conditions 11 Ego vehicle 12 vehicles of the volatile group equipped with quantum sensors 13 Measurement data of the quantum sensors 14 Real-time map of road traffic conditions 15 Driving decision making QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2022 112 269 A1

[0003] US 2016 / 0018525 A1

[0004] WO 2021 / 016095 A1

[0005]

Claims

[1] A method for making driving decisions based on a real-time map of road traffic conditions, in which a plurality of quantum sensors are arranged in each of a plurality of vehicles, in which measurements of driving parameters are carried out simultaneously across all vehicles by the quantum sensors in a continued execution, in which a road environment surrounding the driving route is formed for a driving route of an ego vehicle (11), in which a volatile group (12) is formed by all vehicles of the plurality of vehicles that travel in the road environment, in which measurement data (13) of the driving parameters are received by a computing unit from all vehicles of the volatile group (12) according to a quantum internet protocol, in which the real-time map (14) of road traffic conditions is provided for the ego vehicle (11) on the basis of this measurement data (13) and taking into account their mutual dependencies,in which the driving decision-making (15) is carried out by an autonomous driving system on the basis of the real-time map (14), and driving operation of the ego vehicle (11) controlled by the autonomous driving system is continued on the basis of this driving decision-making (15). [2] Method according to claim 1, wherein the driving decision making (15) for a driving behavior is selected from the following list: change of route, driving speed, headlight activity, fog light activity. [3] Method according to one of the preceding claims, in which the driving parameters are selected from the following list: outside temperature, surrounding road users, driving speed, vehicle vibrations, weather conditions, outside temperature, air humidity, wetness, fog, snow, ice, state of wear and speed of vehicle tires. [4] Method according to claim 3, in which, on the basis of the real-time map (14) in relation to measurement data (13) transmitted to the ego vehicle (11) on surrounding road users, a traffic jam forecast is calculated along the route and for alternative routes in the road environment, and the route is adapted according to a shortest expected travel time and / or in the case of measurement data (13) on the weather conditions, including in particular wetness, fog, snow, ice, the route is adapted with regard to safe road conditions. [5] Method according to one of the preceding claims, in which the computing unit is formed by a central server in an information center, in which in continuous execution • the measurement data (13) of the driving parameters are received from the information center from all vehicles of the volatile group (12) according to the quantum internet protocol, • the real-time map (14) is calculated by the central server for the ego vehicle (11), • and the calculated real-time map (14) is transmitted to the ego vehicle (11). [6] A system comprising a computing unit, a plurality of vehicles, each of which has a plurality of quantum sensors arranged therein, and an ego-vehicle (11) with an autonomous driving system, wherein the quantum sensors are configured to carry out measurements of driving parameters simultaneously across the plurality of vehicles in a continued embodiment, wherein the computing unit is configured to form a volatile group (12) with all those vehicles from the plurality of vehicles that travel in a road environment of the ego-vehicle (11), to receive measurement data (13) of the driving parameters from all vehicles of the volatile group (12) according to a quantum internet protocol, to provide a real-time map (14) of road traffic conditions for the ego-vehicle (11) on the basis of this measurement data (13) and taking into account their mutual dependencies, and wherein the autonomous driving system is configured toto form a road environment surrounding the driving route of the ego vehicle (11) and to transmit it to the computing unit, to carry out a driving decision (15) on the basis of the provided real-time map (14) and to continue driving the ego vehicle (11) on the basis of this driving decision (15). [7] System according to claim 6, wherein the driving decision making (15) for a driving behavior is selected from the following list: driving route change, driving speed, headlight activity, fog light activity. [8] System according to one of claims 6 or 7, wherein the driving parameters are selected from the following list: outside temperature, surrounding road users, driving speed, vehicle vibrations, weather conditions, outside temperature, humidity, wetness, fog, snow, ice, wear condition and rotational speed of vehicle tires. [9] System according to claim 8, wherein the autonomous driving system is configured to calculate a traffic jam forecast along the route and for alternative routes in the road environment on the basis of the real-time map (14) with respect to measurement data (13) transmitted to the ego vehicle (11) on surrounding road users and to adapt the route according to a shortest expected travel time and / or to adapt the route with regard to safe road conditions in the case of measurement data (13) on the weather conditions, including in particular wetness, fog, snow, ice. [10] System according to one of claims 6 to 9, wherein the computing unit is a central server in an information center, wherein the central server is configured to continuously execute • to receive the measurement data (13) of the driving parameters from all vehicles of the volatile group (12) according to the Quantum Internet Protocol, • to calculate the real-time map (14) for the ego vehicle (11), and • to transmit the calculated real-time map (14) to the ego vehicle (11).

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