DE102020114253A1 - System and method for automated vehicles - Google Patents

Abstract

The present disclosure relates to a system for automatically driving vehicles, comprising: a receiving module which is set up to receive a remote driving order from an automatically driving vehicle, the remote driving order including at least one order parameter; a detection module that is configured to detect at least one current state parameter of a potential remote driver; and a processor module that is set up to determine, based on the at least one order parameter, a driver profile of the potential remote driver and the at least one current status parameter of the potential remote driver, whether the remote driving order should be assigned to the potential remote driver .

Description

The present disclosure relates to a system for automatically driving vehicles, a method for automatically driving vehicles and a storage medium for carrying out the method. The present disclosure relates in particular to an assignment of orders to remote drivers based on emotion recognition, in particular for remote-controlled vehicles.

State of the art

Driver assistance systems for automated driving are becoming increasingly important. Automated driving can be done with different degrees of automation. Exemplary degrees of automation are assisted, partially automated, highly automated or fully automated driving. These degrees of automation were defined by the Federal Highway Research Institute (BASt) (see BASt publication “Research compact”, edition 11/2012). For example, the vehicles with level 4 are fully autonomous in city operation.

Fully autonomous driving varies in complexity depending on the environment (e.g. driving on a motorway or in inner-city traffic) and traffic situation. It can therefore happen that a situation cannot or can no longer be controlled by the vehicle itself.

Disclosure of the invention

It is an object of the present disclosure to specify a system for automatically driving vehicles, a method for automatically driving vehicles and a storage medium for executing the method, which enable a reliable assignment of a remote driver to a corresponding automatically driving vehicle. In particular, it is an object of the present disclosure to improve traffic safety during automated driving.

This problem is solved by the subject matter of the independent claims. Advantageous refinements are given in the subclaims.

According to an independent aspect of the present disclosure, a system for automatically driving vehicles, and in particular for remote control of the vehicle by a remote driver, is specified. The system comprises a receiving module which is set up to receive a remote driving order from an automated driving vehicle, wherein the remote driving order comprises at least one order parameter; a detection module that is configured to detect at least one current state parameter of a potential remote driver; and a processor module that is configured to determine, based on the at least one order parameter, a driver profile of the potential remote driver and the at least one current status parameter of the potential remote driver, whether the remote driving order should be assigned to the potential remote driver .

The term “remote”, as it is used in the context of the present disclosure, relates to remote control of the automatically driving vehicle by the (human) driver. In other words, while the vehicle is being controlled, the driver is not in the vehicle, but rather outside the vehicle, e.g. in a center for controlling a fleet of vehicles. This means, for example, that automated trucks can be controlled centrally without a human driver having to be in the vehicle.

According to the invention, a remote driver is assigned to a driving order individually based on the circumstances, that is to say the order parameters, the driver profile and the status parameters. This means that the assignment and processing of remote jobs can be carried out efficiently. In addition, the risk of accidents during journeys made using remote control can be reduced. Furthermore, a remote driver's performance and / or job satisfaction can be improved.

For example, the at least one order parameter can define a night trip to transport sensitive freight. On the basis of this, a remote driver can now be determined whose driving profile indicates an experience when driving at night and / or a gentle driving style. If the current status parameter also indicates that the potential remote driver has slept well, the remote drive task can be assigned to this remote driver.

The processor module is preferably set up to compare driver profiles and current status parameters of a large number of potential remote drivers with the at least one order parameter in order to select a potential remote driver from the large number of potential remote drivers to whom the remote driving order is to be assigned. This enables a comparison to take place so that the remote driver who is best suited for the remote driving order can be selected from a pool of remote drivers.

• historischen Daten in Bezug auf den potenziellen Remote-Fahrer; und/oder
• Daten betreffend Fahrten, die durch den potenziellen Remote-Fahrer durchgeführt wurden; und/oder
• Daten betreffend ein Fahrverhalten des potenziellen Remote-Fahrers; und/oder
• einem aktuellen Emotionszustand des potenziellen Remote-Fahrers.

The driver profile preferably includes historical data relating to the potential remote driver and / or data relating to trips that were carried out by the potential remote driver, and / or data relating to a driving behavior of the potential remote driver. In particular, the processor module can be further set up to create the driver profile of the potential remote driver based on at least one of the following aspects:

• historical data related to the potential remote driver; and or
• Data relating to trips made by the potential remote driver; and or
• Data relating to driving behavior of the potential remote driver; and or
• a current emotional state of the potential remote driver.

In some embodiments, the driving profile may include an emotion profile of the potential remote driver. In some embodiments, the emotion profile can be a profile generated from historical data or an emotion profile determined in real time. In particular, emotion recognition can take place at the time the order is placed (or around the time the order is placed).

In preferred embodiments, the emotion recognition takes place at the moment or (time) frame of the job distribution. In other words, the emotion profile cannot be a profile generated from historical data, but rather it can indicate a current emotional state of the remote driver. For example, negative emotions can be taken into account when assigning orders. If, for example, the emotions "disgust" and / or "contempt" are generated by a camera that records the remote driver, the order can be assigned to another driver.

If the remote driving order includes the transport of sensitive or fragile goods, for example, a remote driver can be selected who shows gentle or calm driving behavior, no tendency to aggression, etc. In a further example, if the remote driving order requires a punctual arrival at a destination, for example, a remote driver can be selected who has excellent punctuality statistics, few breaks, quick driving behavior, etc.

In addition, when assigning orders to the driver, a current emotional state can be recorded by the sensors of the remote control unit and taken into account when assigning orders. If a previous event, such as a completed remote drive order, placed a heavy or less strain on the remote driver, this can be taken into account when assigning the next order.

The processor module is preferably set up to update the driver profile of the potential remote driver based on the at least one current status parameter. This can ensure that the driver profile is up-to-date at all times, even if, for example, the driving behavior of the potential remote driver changes over time.

The acquisition module is preferably set up to acquire the at least one current state parameter of the potential remote driver based on bio-data of the potential remote driver.

The potential remote driver's bio-data may, in some embodiments, include biometric data and / or biochemical data. The biometric data can include a heart rate, for example. The biochemical data can include, for example, an adrenaline level. Additional data from the context of the vehicle, the context of the driver (each situation-related data) and other profiles from other areas of the driver's life (potentially situation-influencing data) can optionally be included in order to sharpen the driver's profile.

Preferably, at least one sensor can be used to record the bio-data of the potential remote driver. The at least one sensor can be present, for example, at a workstation of the remote driver that is located outside the vehicle.

In some embodiments, the at least one sensor is selected from the group consisting of at least one camera, at least one acoustic sensor, at least one driving maneuver sensor (e.g. for steering movements, operating an accelerator pedal, etc.), and at least one biometric sensor (e.g. a heartbeat sensor ) includes, or consists of it. The bio-data can be measured directly or derived from measurement data.

The driver profile of the potential remote driver is preferably stored in the form of a blockchain. This means that the driver profile can be platform-independent, so that it can still be used by the remote driver and the new employer if the remote driver changes employer, for example.

The at least one order parameter is preferably selected from the group that includes a start location, a destination, a planned start time, includes or consists of a planned arrival time, a route characteristic and a traffic situation. However, the present disclosure is not limited, and the at least one job parameter can be any parameter suitable for describing and / or classifying the remote drive job.

According to a further independent aspect of the present disclosure, a method for automatically driving vehicles is specified. The method comprises receiving a remote driving order from an automated driving vehicle, the remote driving order including at least one order parameter; detecting at least one current state parameter of a potential remote driver; and determining, based on the at least one order parameter, a driver profile of the potential remote driver and the at least one current status parameter of the potential remote driver, whether the remote driving order should be assigned to the potential remote driver.

The method can implement the aspects of the system described in this document for automated vehicles.

According to a further independent aspect of the present disclosure, a software (SW) program is specified. The software program can be set up to be executed on one or more processors and thereby to execute the method described in this document for automated vehicles.

According to a further independent aspect of the present disclosure, a storage medium is specified. The storage medium can comprise a SW program which is set up to be executed on one or more processors and thereby to execute the method described in this document for automated vehicles.

The term vehicle includes cars, trucks, buses, mobile homes, motorcycles, etc. that are used to transport people, goods, etc. In particular, the term includes trucks for the transport of people and / or goods.

The vehicle includes a driver assistance system for automated driving. In the context of the document, the term “automated driving” can be understood to mean driving with automated longitudinal or lateral guidance or autonomous driving with automated longitudinal and lateral guidance. The automated driving can be, for example, driving on the motorway for a longer period of time or driving for a limited time as part of parking or maneuvering. The term “automated driving” includes automated driving with any degree of automation. Exemplary degrees of automation are assisted, partially automated, highly automated or fully automated driving. These degrees of automation were defined by the Federal Highway Research Institute (BASt) (see BASt publication “Research compact”, edition 11/2012).

With assisted driving, the driver continuously performs the longitudinal or lateral guidance, while the system takes on the other function within certain limits. With partially automated driving (TAF), the system takes over the longitudinal and lateral guidance for a certain period of time and / or in specific situations, whereby the driver has to constantly monitor the system as with assisted driving. In the case of highly automated driving (HAF), the system takes over the longitudinal and lateral guidance for a certain period of time without the driver having to permanently monitor the system; however, the driver must be able to take control of the vehicle within a certain period of time. With fully automated driving (VAF), the system can automatically manage driving in all situations for a specific application; a driver is no longer required for this application.

The four degrees of automation mentioned above correspond to SAE levels 1 to 4 of the SAE J3016 standard (SAE - Society of Automotive Engineering). For example, highly automated driving (HAF) Level 3 corresponds to the SAE J3016 standard. SAE J3016 also provides SAE level 5 as the highest degree of automation, which is not included in the definition of BASt. SAE level 5 corresponds to driverless driving, in which the system can automatically cope with all situations like a human driver during the entire journey; a driver is generally no longer required.

Figure list

• 1 schematisch ein System zum automatisierten Fahren eines Fahrzeugs gemäß Ausführungsformen der vorliegenden Offenbarung,
• 2 schematisch eine Auswahl eines Remote-Fahrers für ein Fahrzeug gemäß Ausführungsformen der vorliegenden Offenbarung,
• 3 schematisch ein Fahrzeug mit einem Fahrassistenzsystem zum automatisierten Fahren gemäß Ausführungsformen der vorliegenden Offenbarung, und
• 4 ein Flussdiagram eines zum automatisierten Fahren eines Fahrzeugs gemäß Ausführungsformen der vorliegenden Offenbarung.

Exemplary embodiments of the disclosure are shown in the figures and are described in more detail below. Show it:

• 1 schematically a system for automated driving of a vehicle according to embodiments of the present disclosure,
• 2 schematically a selection of a remote driver for a vehicle according to embodiments of the present disclosure,
• 3 schematically a vehicle with a driver assistance system for automated Driving in accordance with embodiments of the present disclosure, and
• 4th a flowchart for automated driving of a vehicle in accordance with embodiments of the present disclosure.

Embodiments of the disclosure

Unless otherwise noted, the same reference symbols are used below for elements that are the same and have the same effect.

1 shows schematically a system 100 for the automated driving of a vehicle, and in particular for the remote control of the vehicle by a remote driver, according to embodiments of the present disclosure.

The system 100 includes a receiving module 110 which is set up to receive a remote driving order of an automated driving vehicle, wherein the remote driving order comprises at least one order parameter; an acquisition module 120 which is configured to acquire at least one current state parameter of a potential remote driver; and a processor module 120 which is set up to determine, based on the at least one order parameter, a driver profile of the potential remote driver and the at least one current status parameter of the potential remote driver, whether the remote driving order should be assigned to the potential remote driver.

The receiving module 110 and / or the acquisition module 120 and / or the processor module 130 can be implemented in a common software and / or hardware module. Alternatively, you can use the receiving module 110 and / or the acquisition module 120 and / or the processor module 130 be implemented in separate software and / or hardware modules.

The system 100 can receive the remote drive order from a client, for example. The client can be an external client, or it can be an (internal) system for processing / handling / creating remote driving orders.

In preferred embodiments, emotions are recognized as part of the order distribution in order to record a current emotional state of the remote driver. For example, negative emotions can be taken into account when assigning orders. If, for example, the emotions "disgust" and / or "contempt" are generated by a camera that records the remote driver, the order can be assigned to another driver.

2 shows schematically a selection of a remote driver F for a vehicle 10 , and especially for remote control of the vehicle 10 , according to embodiments of the present disclosure,

The processor module of the system according to the invention can be set up to compare driver profiles and current status parameters of a large number of potential remote drivers (group or pool G) with the at least one order parameter in order to identify a potential remote driver F from the large number of potential remote drivers G. to which the remote drive task is to be assigned. A comparison can thus take place so that from the pool G of remote drivers that remote driver F can be selected who is best suited for the remote driving order.

For example, a partially autonomous vehicle can be driven remotely on certain route sections by a connected remote driver. At the workstation of the remote driver there can be a suitable sensor system for recording the emotional and / or physical condition of the remote driver in order to determine an individual and efficient selection of a remote driver for a specific remote driving order.

Typically, at least one sensor can be present at the workstation of the remote driver, which sensor is set up to record various biometric and / or biochemical data of the remote driver. The system according to the invention evaluates the measurement data and uses them to determine the physical and / or emotional state of the remote driver.

In some embodiments, the recorded data can be collected and aggregated into a driver profile that depicts historical information about the driver, including, for example, an emotion profile. Data of completed journeys (e.g. start / finish, route, time, weather conditions, etc.) can also be saved in the driver profile. If necessary, additional driving data (e.g. braking and acceleration behavior, distance maintenance) can be included in the driver profile.

If a remote control is requested from a semi-autonomous vehicle, order parameters (e.g. approximate and specific location, time, route characteristics, traffic situation, etc.) are assigned to this travel order. A comparison of the parameters with the driver profiles and the current physical and / or emotional state of the available remote drivers provides information about which driver is best suited for the job.

A remote driver's particular suitability can result, for example, from local knowledge, particularly careful behavior in difficult traffic situations, the remote driver's current ability to concentrate, etc. In addition, using emotion recognition, the remote drivers can be assigned breaks as required, or they can switch between monotonous and varied driving tasks.

3 shows schematically a vehicle 10 with a driver assistance system 300 for automated driving in accordance with embodiments of the present disclosure.

The term vehicle includes cars, trucks, buses, mobile homes, motorcycles, etc. that are used to transport people, goods, etc. In particular, the term includes trucks for the transport of people and / or goods.

The vehicle 10 includes the driver assistance system 300 to automated driving. In the case of automated driving, the vehicle is guided longitudinally and / or transversely 10 automatically. The driver assistance system 300 So takes over the vehicle guidance. The driver assistance system controls this 300 the drive 20th , The gear 22nd , the (e.g. hydraulic) service brake 24 and the steering 26th via intermediate units, not shown.

To plan and carry out automated driving, information about the surroundings is provided by an environmental sensor system that monitors the surroundings of the vehicle from the driver assistance system 300 accepted. In particular, the vehicle 10 at least one environmental sensor 12th which is set up to record environmental data indicating the vehicle surroundings. The at least one environmental sensor 12th can for example comprise a LiDAR system, one or more radar systems and / or one or more cameras.

The vehicle 10 , and in particular the driver assistance system for automated driving, can be connected to an external control unit via a communication link. The communication link between the vehicle and the external control unit can be established using a mobile network, for example. The mobile network can be, for example, an LTE network or 5G network.

The remote driver can operate the external control unit in order to control the vehicle completely manually or with the assistance of the driver assistance system. In other words, the remote driver is not in the vehicle while the vehicle is being controlled, but outside the vehicle, e.g. in a center for controlling a fleet of vehicles. This means, for example, that automated trucks can be controlled centrally without a human driver having to be in the vehicle.

4th schematically shows a flow diagram of a method 400 for the automated driving of a vehicle, and in particular a method for the remote control of the vehicle by a remote driver, according to embodiments of the present disclosure. The procedure 400 can be implemented by appropriate software that can be executed by one or more processors (e.g. a CPU).

The procedure 400 includes in the block 410 receiving a remote driving order from an automated driving vehicle, wherein the remote driving order comprises at least one order parameter; in the block 420 detecting at least one current state parameter of a potential remote driver; and in the block 430 determining, based on the at least one order parameter, a driver profile of the potential remote driver and the at least one current status parameter of the potential remote driver, whether the remote driving order should be assigned to the potential remote driver.

According to the invention, a remote driver is assigned to a driving order individually based on the circumstances, that is to say the order parameters, the driver profile and the status parameters. This means that the assignment and processing of remote jobs can be carried out efficiently. In addition, the risk of accidents during journeys made using remote control can be reduced. Furthermore, a remote driver's performance and / or job satisfaction can be improved.

Although the invention has been illustrated and explained in more detail by preferred exemplary embodiments, the invention is not restricted by the disclosed examples and other variations can be derived therefrom by the person skilled in the art without departing from the scope of protection of the invention. It is therefore clear that there is a multitude of possible variations. It is also clear that the embodiments mentioned by way of example really only represent examples that are not to be interpreted in any way as a limitation, for example, of the scope of protection, the possible applications or the configuration of the invention. Rather, the preceding description and the description of the figures enable the person skilled in the art to specifically implement the exemplary embodiments, whereby the person skilled in the art, with knowledge of the disclosed inventive concept, can make various changes, for example with regard to the function or the arrangement of individual elements mentioned in an exemplary embodiment, without the To leave the scope of protection, which is defined by the claims and their legal equivalents, such as further explanations in the description.

Claims (10)

System (100) for automated vehicles (10), comprising: a receiving module (110) which is set up to receive a remote driving order for an automated driving vehicle (10), wherein the remote driving order comprises at least one order parameter; a detection module (120) which is set up to detect at least one current state parameter of a potential remote driver (F); and a processor module (130), which is set up to determine, based on the at least one order parameter, a driver profile of the potential remote driver (F) and the at least one current status parameter of the potential remote driver (F), whether the remote drive order should be assigned to the potential remote driver (F). The system (100) according to Claim 1 , wherein the processor module (130) is set up to compare driver profiles and current status parameters of a large number of potential remote drivers (G) with the at least one order parameter in order to identify a potential remote driver (F) from the large number of potential remote drivers ( G) to which the remote motion task is to be assigned. The system (100) according to Claim 1 or 2 , wherein the processor module (130) is set up to create and / or update the driver profile of the potential remote driver (F) based on the at least one current state parameter. The system (100) according to Claim 3 wherein the processor module (130) is further configured to create the driver profile of the potential remote driver (F) based on at least one of the following aspects: historical data relating to the potential remote driver (F); and / or data relating to trips made by the potential remote driver (F); and / or data relating to a driving behavior of the potential remote driver (F); and / or a current emotional state of the potential remote driver (F). The system (100) according to one of the Claims 1 until 4th wherein the acquisition module (120) is set up to acquire the at least one current state parameter of the potential remote driver (F) based on bio-data of the potential remote driver. The system (100) according to Claim 5 , wherein the bio-data of the potential remote driver (F) comprises biometric data and / or biochemical data. The system (100) according to one of the Claims 1 until 6th , whereby the driver profile of the potential remote driver (F) is stored in the form of a blockchain. The system (100) according to one of the Claims 1 until 7th wherein the at least one order parameter is selected from the group consisting of a start location, a destination, a planned start time, a planned arrival time, a route characteristic and a traffic situation. Method (400) for automated vehicles, comprising: Receiving (410) a remote driving order for an automated driving vehicle, wherein the remote driving order comprises at least one order parameter; Acquiring (420) at least one current status parameter of a potential remote driver; and Determining (430), based on the at least one order parameter, a driver profile of the potential remote driver and the at least one current status parameter of the potential remote driver, whether the remote driving order should be assigned to the potential remote driver. A storage medium, comprising a software program which is set up to be executed on one or more processors, and in order to thereby carry out the method (400) according to Claim 9 to execute.

Images