Methods for increasing the driving safety of a vehicle

Abstract

Method for increasing the driving safety of a vehicle, in particular a two-wheeler, in which sensor data classifies the driver of the vehicle into a type category and a safety signal is generated in the vehicle from the type category and from data of other road users who have already completed a section of the route ahead of the vehicle, wherein the data of other road users are only transmitted if the route is curved.

Description

[0001] The invention relates to a method for increasing the driving safety of a vehicle, for example a two-wheeler. State of the art

[0002] Motorcyclists face an increased safety risk due to their unstable balance, the lack of a crumple zone, and heightened physical and mental demands. In particular, cornering inherently carries a higher risk of accidents, especially for inexperienced riders. Overconfidence and unfamiliarity with the road layout and conditions are further risk factors. Disclosure of the invention

[0003] The method according to the invention serves to increase the driving safety of a vehicle, in particular a motorized two-wheeler such as a motorcycle or a scooter, whereby other vehicle types such as motor vehicles may also be considered. In the method, driver-specific information is linked with route-specific information and, if necessary, a safety signal, for example a target speed signal, is generated, which can be further processed in the vehicle in various ways, for example, displayed to the driver or processed further in a driver assistance system.

[0004] The rider-specific data relates to the rider type category, for example, an experienced or sporty rider, an average rider, and a cautious or inexperienced rider. Sensor data is used to classify the current rider of the two-wheeler into a type category that reflects the rider's behavior. This sensor data includes, for example, acceleration values ​​in the vehicle in the longitudinal and / or lateral direction, which are then analyzed.

[0005] The route-specific information relates to the section of road ahead of the driver. This information is derived from data of other road users who have already traveled the same route. It is based on the experience of other road users regarding their speeds. From this data, a speed value is generated, which is stored in the vehicle and, together with the driver's vehicle category, processed into a safety signal, such as a target speed signal. The data from these other road users is used to determine, for example, an average speed or a median speed, which forms the basis for the safety signal in the vehicle.

[0006] Based on the speed of other road users, the vehicle adjusts its speed according to the driver's vehicle category, for example, by displaying a higher or lower target speed signal, or, if necessary, a constant target speed signal. For instance, the speed of other road users might be increased for a sporty driver, kept unchanged for an average driver, and decreased for a cautious or inexperienced driver. The corresponding speed signal is displayed to the driver, so that even before reaching the relevant section of road, the driver receives information about the speed at which this section can be traversed with acceptable risk.

[0007] The speed signal may be displayed as a warning to encourage the rider to reduce their speed. Additionally or alternatively, the speed signal can be processed by a driver assistance system, for example, to reduce engine power in order to lower the current speed of the two-wheeler.

[0008] As an alternative to speed information from other road users, it is also possible for these other road users to provide other information, which can then be used as the basis for generating the target speed signal. For example, acceleration signals from other road users can be evaluated. However, according to a preferred embodiment, the speed information from other road users is taken into account, optionally supplemented by further data such as additional state variables, for example, accelerations, in particular longitudinal and / or lateral dynamic parameters. Furthermore, the speed information can optionally be supplemented or replaced by environmental information and / or road surface information about the distance already traveled.For example, it is possible to detect weather conditions affecting the road surface, such as wet or icy surfaces, and make this information available to the two-wheeler. It is also possible to detect unexpected obstacles on the road, such as those caused by accidents, and make this information available to the vehicle.

[0009] According to yet another advantageous embodiment, driving condition variables of other road users, in particular speed information, are categorized according to driver type. Accordingly, the driving condition information is weighted by driver type, so that, for example, average or median speeds for different driver types are generated from the data of other road users available in the vehicle. The categorization of other road users and the driver categorization expediently coincide, so that the data of other road users can be directly assigned to a specific driver type. In this way, the accuracy of the target speed signal is improved.

[0010] According to yet another practical implementation, the driver of the vehicle receives the data from a central database containing information about the routes already traveled by other road users. In this implementation, the central database is located outside the vehicle, and the driver can access data from it online.

[0011] The information on other road users stored in the central database originates from a narrowly defined time period, such as the past one or two hours. This has the advantage of ensuring that the information is up-to-date, particularly regarding the surrounding environment and road conditions. The data on these other road users is primarily entered into the central database online.

[0012] However, it is also possible to additionally or alternatively consider a further back period, possibly without a time limit, so that while current information can be entered into the database, older information is also taken into account. This approach has the advantage that the database continuously grows and, consequently, a larger data basis is available for determining the target speed signal.

[0013] In another, alternative configuration, the database is available in the vehicle. The information stored in the database either pertains to a closed data record that is not continuously updated, or, in another variant, a data record that is continuously updated online by data from other road users.

[0014] According to yet another practical implementation, only vehicles of the same type are considered as other road users; for example, in the case of a two-wheeler, the data of other two-wheelers are taken into account. This has the advantage that the data comes from comparable road users and, accordingly, the target speed signals are better adapted to the current vehicle.

[0015] In an alternative version, there is no restriction to the vehicle type, but other road users, preferably passenger cars, are also taken into account in addition to vehicles of the same type, which has the advantage that a larger database is available.

[0016] The various process steps take place in a control unit within the vehicle. If the database is centralized and located outside the vehicle, a transmitter and receiver unit is required inside the vehicle to request and receive data from the database. The vehicle also contains a positioning system to determine its current position and to query the database for the upcoming route, starting from that position. This positioning system could be, for example, a Global Positioning System (GPS) or a positioning system integrated into a smartphone, with the smartphone connected to the control unit in the vehicle.

[0017] According to another practical implementation, rider type recognition is achieved via sensor data supplied by sensors integrated into the vehicle, particularly via driving condition parameters relating to longitudinal and lateral dynamics, for example, via acceleration sensors. For instance, a sufficient data basis for rider type categorization can be obtained from the sensors of an anti-lock braking system (ABS) installed in the motorcycle. In addition to or as an alternative to sensors installed in the motorcycle, sensors from a smartphone carried by the rider and connected to the vehicle can also be used, especially motion sensors with acceleration sensors.

[0018] Further advantages and practical designs can be found in the additional requirements, the figure description, and the drawings. These show:

[0019] Fig. 1. A block diagram showing the process steps for driver type recognition in a two-wheeler and for determining and displaying a safety signal.

[0020] Fig. 2 another block diagram in which driver type recognition is carried out via the sensors of a connected smartphone.

[0021] In the figures, identical components are labelled with the same reference symbols.

[0022] The in Fig. The block diagram shown in Figure 1 refers to a method for driver type recognition of a motorized two-wheeler, for example a motorcycle, using sensors integrated into the two-wheeler, and to the data exchange with a central database for receiving driving condition variables and other information from other road users about an upcoming section of road.

[0023] The procedure consists of an input block 1 , a block 2for identifying the driver type and classifying it into a specific type category, a block 3 to generate a safety signal and an output block 4 together. The input block 1 includes engine management 1a , an anti-lock braking system 1b , a block MSC (Motorcycle Stability Control) 1c and a database 1d including communication with a control unit in the vehicle, in which the various steps according to the blocks 2 and 3 as well as the control of the output units in the output block 4 is carried out.

[0024] About the blocks or functions 1a , 1b and 1c Information about the current rider of the two-wheeler is collected and used as the basis for classification into a specific type category. For example, the ABS block contains this information. 1b and the MSC block 1cSensor data from sensors in the vehicle are used to determine driving parameters of the longitudinal and lateral dynamics of the two-wheeler, in particular the vehicle speed, longitudinal and lateral acceleration, as well as the lean and pitch angles and other parameters. This is combined with information from the engine management system. 1a From the information on the driver's engine operation, the current driving style can be determined, allowing for driver type categorization. For example, it is possible to distinguish between driver types with a sporty, average, and cautious driving style. The corresponding information is stored in the block. 2 The data is used to identify the driver type and generate a corresponding type category.

[0025] In the block 3First, the current position of the two-wheeler is determined using a positioning system, for example, a Global Positioning System (GPS) integrated into a navigation system. Communication also takes place with a central database, preferably located outside the two-wheeler, with which the two-wheeler communicates via a transceiver unit. This central database contains data from other road users who have already traveled the route ahead of the two-wheeler, which the rider will be using as the basis for their immediate travel. The information from these other road users pertains to driving parameters such as vehicle speed, but advantageously also includes data on the type of driver and, if applicable, information on the surrounding environment and road conditions, such as obstacles on the road or wet or icy surfaces.The two-wheeler can access this information stored in the database, with the block . 3 from this information and taking into account the information in the block 2 A safety signal is generated based on the identified driver type category.

[0026] This safety signal is primarily a target speed signal displayed to the driver, serving as a recommendation for the speed at which the driver can travel the upcoming section of road. The safety signal can also, or alternatively, include other information, such as a warning if there is an obstacle on the road. By taking into account the driver type category of both other road users and the motorcyclist, a high degree of precision in the safety signal, particularly with regard to the target speed signal, can be achieved.

[0027] It can be advantageous to receive and evaluate only information from other motorcyclists from the database. Furthermore, it may be useful to generate a safety signal only for a specific type of road ahead, for example, only for a curve or series of curves with a minimum curvature.

[0028] The security signal is stored in one or more units of the output block. 4 processed. For example, a display appears in an instrument cluster. 4a of the two-wheeler. In addition, or alternatively, it is possible to display information on a smartphone. 4b to represent what is connected to the two-wheeler, or an acoustic indication via a helmet radio. 4c to be stated explicitly. Finally, it can also be useful to include information about one's own route traveled, including driver type identification, in the subblock. 4dto transfer to the central database in order to make this information available to other road users.

[0029] The block diagram according to Fig. 2 also applies as Fig. 1. Rider type recognition in a two-wheeler and the generation of a safety signal. The procedure is essentially the same as in Fig. 1, however, with the difference that the input block 1 is implemented in different ways. The sensor data used for driver type recognition in the block 2 The data used is based on a smartphone carried by the user. 1e , which is equipped with motion sensors and communicates with a control unit in the bicycle. The sensor data from the smartphone 1e These data can be used in addition to the sensor data from the bicycle's own sensors, if necessary. Regarding the smartphone... 1e Is this the same smartphone as in the output block? 4b, which can also be used to display the safety signal.

Claims

[1] Method for increasing the driving safety of a vehicle, in particular a two-wheeler, in which sensor data classifies the driver of the vehicle into a type category and a safety signal is generated in the vehicle from the type category and from data of other road users who have already completed a section of road ahead of the vehicle. [2] Method according to claim 1, characterized by that the safety signal is a target speed signal. [3] Method according to claim 1 or 2, characterized by that the safety signal is displayed to the driver and / or processed further in a driver assistance system. [4] Method according to any one of claims 1 to 3, characterized by that the data of other road users includes driving condition information, in particular speed information, with which the other road users have already completed the route in front of the vehicle. [5] Method according to any one of claims 1 to 4, characterized by that the driving condition information of other road users is categorized according to driver type. [6] Method according to any one of claims 1 to 5, characterized by that the data of other road users includes environmental and / or roadway information about the route already traveled. [7] Method according to any one of claims 1 to 6, characterized by that the data of other road users is recorded in a central database and the driver of the vehicle receives data online from the central database. [8] Method according to claim 7, characterized by that the data of the other road users will be entered online into the central database. [9] Method according to any one of claims 1 to 8, characterized by that only vehicles of the same type, in particular two-wheelers, are considered as other road users. [10] Method according to any one of claims 1 to 9, characterized by that the data of other road users will only be transmitted if the route is winding. [11] Method according to any one of claims 1 to 10, characterized by that the sensor data for categorizing the driver type comes from sensors integrated into the vehicle. [12] Method according to any one of claims 1 to 11, characterized by that the sensor data for categorizing the driver type comes from sensors in a smartphone carried with the vehicle and communicating with the vehicle. [13] Method according to any one of claims 1 to 12, characterized by that a position determination signal is generated in the vehicle from a position determination system to determine the route ahead of the vehicle. [14] Control device for carrying out the method according to any one of claims 1 to 13. [15] Vehicle, in particular two-wheeler with a control unit according to claim 14.

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