DE102012220146A1 - Method for characterizing driving behavior of driver of e.g. motor car, involves obtaining accumulation information of trends over deviation time and providing accumulation information for characterizing driving behavior - Google Patents

Abstract

The method involves determining the current reference driving parameter of driver corresponding to the target parameter with respect to the driving behavior of vehicle. The current reference driving parameter is compared with the target parameter to obtain the deviation over preset period between current reference driving parameter and target parameter to obtain the accumulation information of trends over the deviation time. The accumulation information about trends is provided through an interface (114) for characterizing the driving behavior. Independent claims are included for the following: (1) device for characterizing driving behavior of driver of vehicle; and (2) computer program product for characterizing driving behavior of driver of vehicle.

Description

State of the art

The present invention relates to a method for characterizing a driving behavior of a driver of a vehicle, to a corresponding device and to a corresponding computer program product.

Road traffic is increasing worldwide. It can be observed that many road users partially not compliant with the rules on the road. Likewise, many road users, especially novice drivers are overwhelmed by the complexity of the traffic. Furthermore, many road users are less willing to consider unnecessary or inconvenient road traffic behavior rules in their eyes.

The DE 43 38 073 A1 describes a method for evaluating the driving style with a motor vehicle.

Disclosure of the invention

Against this background, the present invention provides a method for characterizing a driving behavior of a driver of a vehicle, furthermore a device which uses this method and finally a corresponding computer program product according to the main claims. Advantageous embodiments emerge from the respective subclaims and the following description.

With the approach presented here, a behavior of a single traffic participant in traffic can be evaluated on the basis of a desired-actual comparison of at least one characteristic criterion. Both the desired criterion and the actual criterion are obtained based on a current traffic situation. Here, the desired criterion represents a theoretically possible, optimal behavior in the traffic situation and the actual criterion represents an actual behavior of the road user in the traffic situation. The result of the target-actual comparison represents a difference between the optimal behavior and the actual behavior in a processable manner. A plurality of results that are acquired over a period of time can reveal a tendency of the behavior of the road user. This tendency can be passed on to the road user as feedback, so that the road user can approach his behavior in the future to the optimal behavior. This allows road users to learn correct behaviors and eliminate wrong behaviors.

A method is presented for characterizing a driving behavior of a driver of a vehicle, the method having the following steps:
Determining at least one parameter, wherein the parameter represents the determined instantaneous driving behavior of the driver with respect to a vehicle movement of the vehicle with respect to at least one environmental parameter and / or with respect to a lateral dynamics of the vehicle;
Determining one each, to the at least one parameter corresponding, desired parameters, wherein the desired parameter represents a current reference driving;
Comparing the at least one parameter with the corresponding desired parameter to obtain a deviation between the at least one parameter and the corresponding desired parameter;
Cumulating the deviation over a period of time to obtain a trend; and
Providing information about the trend via an interface, the trend characterizing the driving behavior of the driver.

Driving behavior may be understood to mean a type or quality of a driving task performed by a driver of a vehicle. Such a driving task can solve different drivers in different ways and thus drive in different ways on a road. Likewise, a driver may act differently on different trips across the same road. The driving behavior can be characterized by several different criteria. A parameter can represent a criterion. At least one parameter can be determined using environment sensors, inertial sensors and / or sensors for monitoring a relative movement between the vehicle and a road, for example the vehicle or a mobile device, such as a smartphone. For example, the parameter can be determined by evaluating one or a plurality of images of an environment of the vehicle. One or more further parameters may also be determined using the or another environmental sensor system or determined using another vehicle sensor system. A parameter can also be determined by evaluating a signal transmitted via a line of the vehicle or by evaluating information stored in a memory. If the parameter is based on a sensor signal, the sensor signal can be used directly, preprocessed or evaluated to determine the parameter. For example, an angular velocity value determined by a yaw rate sensor may be integrated to determine an angle change of the vehicle, which in turn may be included in the parameter. An environment parameter can For example, a roadway boundary, a lane marking, in front in the direction of travel, next to or behind the vehicle object, such as a foreign vehicle or an obstacle. By inputting the environment of the vehicle defined via the environmental parameter into the determination of the driving behavior of the driver, it is possible, for example, to evaluate the vehicle movement in relation to the roadway or in relation to one or more other road users. This may, for example, be understood as driving too close to a vehicle ahead. In this case, a longitudinal dynamics of the vehicle can be taken into account. The lateral dynamics of the vehicle may allow an assessment of the driving stability or driving physics of the vehicle. For example, an understeer or oversteer (skidding) or drifting out of a curve of the vehicle can be detected via lateral dynamics measured variables such as the lateral acceleration or the yaw rate. In the step of determining, a single parameter can be determined. Likewise, a plurality of parameters can be determined. For each parameter corresponds a setpoint parameter. A reference driving style can represent an ideal solution of the driving task. For example, the reference driving mode may represent an optimal speed movement, optionally at an optimum distance from a preceding vehicle, along an ideal line. The reference driving style may include all necessary actions of the driver while driving. A deviation can have a negative or positive value. The further the driver deviates from the reference driving method, the greater the value of the deviation can be. The deviation may also have the value zero when the vehicle is driven by the driver with optimum driving style. The deviation may be a result of a target-actual comparison. The deviation may be zero within a tolerance range around the target parameter. The deviation can also be understood as the distance from the limits of a driving range. Then the distance can have a maximum value with optimal driving. In order to cumulate the deviation and obtain a trend of the deviation, an average of the deviations can be formed. The mean value can be determined by sliding. Longer deviations can be weighted less than shorter deviations. Likewise, a fluctuation range of the deviation can be detected. A frequency of deviation values can be recorded. The deviation can be cumulated over different periods of time. For example, a long-term trend may be slow to react to momentary variations in the deviation. A medium-term trend, for example, an improvement in driving or a driving style in, for example, a period of a few weeks capture. A short-term trend can capture a current driving style, for example, within a few days. In the step of cumulating, the deviations can be statistically evaluated. For example, a trend line may represent a plurality of deviations in a polynomial. Information about the trend may be, for example, an instantaneous value of the trend and / or an instantaneous spread of the deviations. An interface can be, for example, an interface for wireless data transmission to a central database. The interface can also be a display in the vehicle, via which the driver can be informed graphically about the trend. If there is only one value, then cumulation can be understood as the cumulation of only one value, that is, the instantaneous situation.

According to one embodiment, the parameter may represent the driver's instantaneous driving behavior determined using environment sensors, vehicle sensors, motion sensors, and / or inertial sensors. The inertial sensor system may be, for example, an acceleration sensor or angular velocity sensor. Furthermore, a sensor for monitoring a steering of the vehicle can be used. In the case of the sensor system mentioned, it can generally be a vehicle sensor system. With such a sensor is z. B. too fast cornering on the basis of the lateral acceleration recognizable without an environment sensor is used. Movement information about the vehicle can also be determined with magnetic field sensors by z. B. the change in the angle between the vehicle and geomagnetic field is measured in a turn. In a broader sense, one can count magnetic field sensors to environment sensors, since the Earth's magnetic field is considered "in the environment" of the vehicle.

The desired parameter may be determined using information about a road segment and / or information about at least one other road user in the road segment. The road section may represent a road section currently being traveled by the vehicle. Information about a road section may be, for example, a speed limit in the road section, a lane width in the road section, a lane inclination in the road section, and / or a turning radius in the road section. Likewise, the information about the road section may be weather information, traffic information, obstacle information and / or road condition information. Another road user may be, for example, a preceding, following or oncoming vehicle. The other road user may also be a cyclist or pedestrian. An information about another road user may be, for example, a distance to the other road user, a lateral offset to the other road user and / or a speed difference to the other road user. The information can influence the reference driving style. For example, the ideal line may provide for avoidance of the other road user. Likewise, a speed reduction can be provided before a curve.

The parameter and / or the desired parameter can be determined using video information about an area in front of the vehicle and / or a movement information of the vehicle and / or an activity information of at least one subsystem of the vehicle. Video information may be provided by a camera facing the area in front of the vehicle. From the video information, various other information can be extracted. For example, a width of the road, a position of the vehicle on the road, a curvature of the road, a nature of the road, information about a speed limit, a distance to a preceding vehicle, and / or a position of other road users may be extracted from the video information. A movement information may be a speed of the vehicle, a direction information of the movement of the vehicle and / or an acceleration of the vehicle relative to one or more axes. For example, an activity information may be a signal of a security system such as ABS and / or ESP. Likewise, the activity information may be a signal that an input means such as a pedal, a lever, a switch and / or the steering wheel of the vehicle is operated or used. Thus, for example, in the activity information, a use of headlamps, lamps, a turn signal operation, brakes and / or an engagement of a gear stage of the vehicle can be stored.

The deviation may be cumulated over a plurality of trips of the vehicle. By accumulating over several trips, a current condition of the driver can be compensated. As a result, the trend has a greater significance. Furthermore, the deviation can be cumulated over a predetermined period of time. Such a period may for example comprise at least several minutes, at least one hour or a journey, for example from boarding to disembarking the driver.

In the step of providing, a trend of at least one other road user can also be provided. The trend of at least one other road user can be received from a database, for example via a wireless connection. It may be provided to the driver as a reference and / or to classify the cumulative trend. This allows the driver to classify what his driving style is compared to at least one other driver.

The method may include a step of forming a comparison result between the deviation and at least one other deviation. The other deviation characterizes a driving behavior of at least one other road user. The comparison result can be provided at a driver interface. The other deviation can serve as a reference value for the deviation. The other deviation may represent an average of several other road users, for example from a reference group of road users.

At least one additional parameter can be determined. A corresponding additional setpoint parameter can be determined. The further parameter can be compared with the further setpoint parameter in order to obtain a further deviation. Either the further deviation may be cumulated to obtain another trend that may be provided, or the trend may be further cumulated using the at least one further deviation and a processing rule. The driving behavior can be detected by means of a plurality of parameters. With increasing number, a higher accuracy can be achieved in the mapping of the driving behavior. In particular, one of the available sensors in the vehicle and / or in a mobile device on which the method is executed can be used for the further parameter.

The at least one parameter may represent a lateral position of the vehicle in a lane of the vehicle and the desired parameter may represent a desired position within the lane. The at least one parameter may represent a distance of the vehicle to a preceding vehicle and the desired parameter may represent a desired distance to the preceding vehicle. The at least one parameter may represent a speed of the vehicle and the desired parameter may represent a desired speed. The at least one parameter may represent an event sequence of a driving maneuver of the vehicle and the desired parameter may represent a desired event sequence. The at least one parameter may represent an acceleration on the vehicle at least in a vehicle axle, and the desired parameter may represent a desired acceleration. The at least one parameter may represent an intervention of at least one safety system of the vehicle and the Target parameter may represent a desired state of the safety system. For example, a desired position within the lane may be a center of the lane. The desired position may be determined depending on various factors such as a lane width, a turning radius and / or an obstacle. A desired distance to a vehicle ahead, for example, be a safe distance. The desired distance may be determined, for example, using a speed of the vehicle. A target speed may be, for example, a maximum speed. Likewise, the desired speed may be a consumption-optimized speed. The desired speed may be determined, for example, using a speed limit, the turning radius, a road condition, and / or a distance to a preceding vehicle. A desired event sequence may be a sequence of a driving maneuver, as defined by regulations and / or laws, for example. For example, the desired event sequence may include setting the turn signal before a lane change. Likewise, the desired event sequence may include a stop at a stop sign. A desired acceleration, for example, represent a desired ride comfort. Abrupt delays and accelerations can reduce ride comfort and driving safety, for example due to a risk of collision in the event of sudden heavy braking. Likewise, large acceleration values can characterize a non-ecological driving style. A target state of a security system may be an inactive state. An intervention of the safety system, such as ABS / ESP or traction control can characterize an unsafe driving style.

The present invention further provides an apparatus for characterizing a driving behavior of a driver of a vehicle, which is designed to implement the steps of the method according to the invention in corresponding devices. Also by this embodiment of the invention in the form of a device, the object underlying the invention can be solved quickly and efficiently.

In the present case, a device can be understood as meaning an electrical device which processes sensor signals and outputs control and / or data signals in dependence thereon. The device may have an interface, which may be formed in hardware and / or software. In the case of a hardware-based embodiment, the interfaces can be part of a so-called system ASIC, for example, which contains a wide variety of functions of the device. However, it is also possible that the interfaces are their own integrated circuits or at least partially consist of discrete components. In a software training, the interfaces may be software modules that are present, for example, on a microcontroller in addition to other software modules.

A computer program product with program code which can be stored on a machine-readable carrier such as a semiconductor memory, a hard disk memory or an optical memory and is used to carry out the method according to one of the embodiments described above if the program product is installed on a computer or a device is also of advantage especially on a smartphone.

The invention will now be described by way of example with reference to the accompanying drawings. Show it:

1 a representation of a vehicle with a device for characterizing a driving behavior of a driver of the vehicle according to an embodiment of the present invention;

2 a flowchart of a method for characterizing a driving behavior of a driver of a vehicle according to an embodiment of the present invention;

3 a schematic representation of a method for characterizing a driving behavior of a driver of a vehicle according to an embodiment of the present invention;

4 an illustration of a mobile device on which a method for characterizing a driving behavior of a driver of a vehicle according to an embodiment of the present invention is executable;

5 a representation of a visualization of a trend according to an embodiment of the present invention; and

6 an illustration of providing multiple trends according to an embodiment of the present invention.

In the following description of preferred embodiments of the present invention, the same or similar reference numerals are used for the elements shown in the various figures and similarly acting, wherein a repeated description of these elements is omitted.

1 shows a representation of a vehicle 100 with a device 102 to characterize a driving behavior of a driver of the vehicle 100 according to an embodiment of the present invention. The device 102 has a facility 104 for determining a facility 106 for determining a device 108 for comparison, a facility 110 to cumulate and a facility 112 to deploy. The device 104 for determining is designed to determine at least one parameter representing the current driving behavior of the driver. The device 106 for determining is designed in each case to determine a nominal parameter corresponding to the parameter, which represents a current reference driving method. The device 108 for comparison is designed to compare the parameter with the desired parameter to obtain a deviation. The device 110 for cumulating is designed to cumulate the deviation over a predetermined period of time to obtain a trend. The device 112 for providing is designed to provide information about the trend via an interface 114 The trend characterizes the driving behavior. The device 104 for determining and furnishing 106 for determining are with at least one sensor 116 connected. The sensor 116 may comprise a plurality of individual sensors. For example, the sensor 116 a camera, acceleration sensors and / or a microphone. About the sensor 116 get the decor 104 for determining and furnishing 106 for determining information about an environment or a vehicle movement of the vehicle. 100 , In the information is at least one lane 118 in front of the vehicle 100 represents. The information may represent other road users, such as other vehicles, pedestrians and / or cyclists. The facility determines from the information 104 for determining at least the one parameter and the device 106 for determining determines at least the one desired parameter. Furthermore, the device 104 be configured to evaluate signals that are transmitted for example via a data bus of the vehicle. For example, the device 104 be configured to evaluate a turn signal representing an actuation of a direction indicator of the vehicle.

In other words, shows 1 a vehicle 100 with a device 102 for in-vehicle social edutainment. Driver assistance systems such as Lane Departure Warning, Lane Keeping Assist, Lane Change Assist or Adaptive Cruise Control, for example, data from the sensor 116 can help the driver in his driving task by monitoring the driving and warning the driver or actively intervene in the vehicle guidance in deviation from an optimal driving style either. The device 102 can be used for example in connection with a navigation system.

According to one embodiment, a navigation system of the vehicle comprises 100 Functions designed to playfully improve the driver's driving style by awarding points for a particularly exemplary driving style. In this case, for example, driving safety aspects or the compliance with the traffic rules can be targeted. It can also be based on data from the vehicle 100 be accessed to determine the parameters to be monitored. Such a system can also use a community, similar to a social network, in which the own results can be published and compared with other participants (partially anonymized). This competition with other participants provides an additional incentive to improve your own driving style. The driver can also be rewarded with points for the reporting of traffic, map updates, or even for the sole use of the system.

The driver can also be motivated in a playful way to improve his driving behavior. The driver can be rewarded in the approach presented here in particular for a particularly safe, prudent or considerate driving style. An environmentally friendly driving style can also be considered. The device 102 uses this already in the vehicle 100 (or in a smartphone) existing environment sensor and / or motion sensors 116 in order to determine an ideal driving behavior and to evaluate the driver behavior compared to the ideal behavior. In addition to the direct positive feedback in the form of a score or targeted praise for particularly good behavior, the driver can be motivated in particular by the competition with other drivers to improve his own driving behavior.

The system presented here enables the driver to improve his driving style informally and in a playful way by comparing his current driving style with his personal best performance or by trying to become the "best" driver in competition with other drivers positive feedback can alert the driver to very good handling, which he may not have realized without the system, and motivate him to repeat it in the future.

In addition, the system increases the experience of the already installed environment sensors and driver assistance systems, by continuously giving feedback on the driving behavior, and not only in exceptional cases such as gross misconduct of Warn drivers or intervene. For example, while a good motorist driving right in the middle of his lane would, ideally, never experience a lane departure warning, the lane departure warning information provided in the system presented here can be used to continuously tell the driver how closely he is following the center of his lane ,

If sufficient protection against manipulation of the determined "ride quality" is achieved, the underlying method can not only lead to an improvement in the driving behavior of broad masses through "best driving competitions", but also affect insurance premiums. This means that drivers who drive more efficiently and safely can be rewarded by their insurers with cheaper premiums, which is another incentive for safe and compliant driving.

In addition, winning the prize among the best drivers in the web community can provide additional incentives to buy and use the system.

Based on the in the vehicle 100 installed sensors 116 different criteria can be calculated to evaluate the driving behavior. Depending on the sensor equipment, the following criteria can be determined, for example.

For example, the device 104 trained to a position of the vehicle 100 relative to the street 118 to determine while the establishment 106 is formed to a target position for the vehicle relative to the road 118 to determine. In the embodiment shown here is the vehicle 100 closer to a right lane boundary of the road 118 , as at a left lane boundary of the road 118 , In general, it would be better if the vehicle 100 would drive in the middle of his lane. That's why the device determines 106 the desired position in the middle of the lane. A tolerance range can be indicated around the desired position, within which the vehicle 100 can drive as well. The position and the target position are in the device 108 compared for comparison and determines a position deviation. The position deviation is in the device 110 cumulated to accumulate to obtain a positional trend. From the device 112 to provide information about the position trend is provided. For example, it can be statistically evaluated where the driver is the vehicle 100 Most often or most of the time on the road 118 has positioned. Likewise, a frequency distribution of the position can be provided. With the information, the driving style of the driver can be characterized. For example, it can be shown whether the driver shuttles back and forth uncertainly between the lane boundary lines or whether he has a comfortable and stable position on the road 118 has found. It can also be shown if the driver is holding too far to the left or to the right, for example, because he keeps too much distance from parked cars and injures another lane, for example.

For evaluating track-accurate driving, the deviation of the vehicle position from the lane center can be determined via a typically video-based, lane recognition. For example, the percentage of driving time in the middle of the lane (taking into account a certain tolerance and the deviations that inevitably result from real lane changes) can be used as a criterion for "punctually correct driving".

If the sensor 116 Provides information about other road users, in particular about, the vehicle 100 vehicle in front, may be in the facility 104 for determining a distance to the preceding vehicle can be determined. In the facility 106 for determining, a target distance to the preceding vehicle is then determined. For example, using a speed of the vehicle 100 a safety distance can be determined as the desired distance to the vehicle in front. The speed can be obtained, for example, from the information of the sensor and / or from a control unit (not shown) of the vehicle 100 for example via a data bus of the vehicle 100 be received. The distance and the target distance are in the device 108 compared for comparison and determines a distance deviation. The distance deviation is in the device 110 cumulated to accumulate to obtain a distance trend. From the device 112 For providing, information about the distance trend is provided. For example, it can be statistically evaluated which distance the driver most often or most of the time adheres to the preceding vehicle. Likewise, a frequency distribution of the distance may be provided. With the information, the driving style of the driver can be characterized. For example, it can be shown if the rider promotes a "concertina effect" in convoy traffic by returning too close and then holding too much distance or keeping a correct safety distance. It can also be shown if the driver is driving too close or too far away from the vehicle in front.

For an assessment of compliance with the prescribed safety distances can with a distance sensor 116 z. As radar or lidar and the vehicle speed compliance with prescribed safety distance. As a criterion z. B. the percentage of travel time with a sufficient safety distance over the entire journey time can be determined.

If the sensor 116 Information about an operation of a turn signal of the vehicle 100 provides or the operation of the turn signal is detected by evaluating the operation of the turn signal indicating and provided via a data signal flasher signal, the device 104 for determining a sequence of, for example, a lane change, an exit from a roundabout and / or a turning off the road 118 determine. In this case, the sensor can 116 For example, include a camera for detecting the lane position. Alternatively, the presence of a turn on the basis of a highly integrated angular velocity about the vertical axis can be detected. The device 106 can then provide a target sequence that represents a rule compliant use of the turn signal. In the facility 108 For comparison, a process deviation can be determined. For example, it can be detected whether the driver has set the turn signal before he changes lane, leaves the roundabout and / or the road 118 leaves. It can also be determined whether the driver sets the turn signal too late and / or too short and / or wrong, for example. In the facility 110 For cumulation, the correct processes and / or the less good processes and / or the wrong processes can be cumulated via the process deviation in order to obtain a process trend. In the facility 112 for example, it can be provided as information what percentage of the lane changes, roundabouts and / or turns have been executed correctly, carelessly and / or incorrectly.

To evaluate correct lane change, a turn signal can be used. As a criterion z. B. the percentage of lane changes are determined with correct turn signal operation on all lane changes.

If the sensor 116 Information about a maximum speed limit in a straight line of the vehicle 100 traveled section of the road 118 The institution can provide 106 determine a desired speed for determining. The device 104 to determine a currently driven speed of the vehicle 100 determine. The device 106 for determining, other factors for determining the target speed may also be used. For example, a curve radius of the road 118 require a reduced speed. Likewise, a condition of the road 118 require a reduced speed. An approach to a lower permissible maximum speed range can slow the vehicle 100 in front of the area. The device 108 For comparison, a speed deviation can be determined from the speed and the setpoint speed. In the facility 110 For cumulation, speed deviations can be cumulated to a speed trend. The device 112 for providing, for example, can provide as information whether the driver tends to drive too fast or too slow. For example, it can be provided if the driver heaps speed limits in certain sections of the road 118 or generally ignored.

To assess compliance with the maximum permissible speed information about the maximum speed limit can be determined for example by means of video-based traffic sign recognition or speed limits recorded in the navigation chart. Compliance with the maximum speed limit can be determined.

If the sensor 116 Acceleration information can be provided by the facility 104 to provide an actual acceleration for determining. The device 106 for determining, based on ecological specifications, comfort specifications, road conditions and / or weather conditions, a target acceleration can be determined. For example, the target acceleration may be an acceleration limit. The device 108 For comparison, an acceleration deviation can be determined from the acceleration and the target acceleration. The device 110 For cumulation, acceleration deviations can cumulate to an acceleration trend. The device 112 providing may provide information about the acceleration trend. For example, it may be provided if the driver is the vehicle 100 too much accelerates and / or slows down. Likewise, it can be provided whether the driver drives too fast in curves, that is to say excessive lateral accelerations act. It can also be provided whether the driver is driving on bad roads at too high a speed because accelerations in the vertical axis of the vehicle 100 are too big. The information from the acceleration trend may also represent whether the driver is driving with high or low continuity.

For the evaluation of braking and acceleration processes a continuity can be considered. Driving behavior which is favorable for traffic flow and fuel consumption is characterized by "continuity", ie a few strong braking and acceleration processes, a criterion for which can be defined by means of longitudinal acceleration be, by z. B. the integral of the amount of longitudinal acceleration is related to the covered during a trip path. In continuous driving, such a criterion has small values.

If the device 104 for determining information about safety systems of the vehicle 100 receives, such as ABS / ESP and / or traction control, the device can 104 provide intervention information when the security systems intervene. The information can be received over the data bus, for example. A target state may be an inactivity of the security systems. The device 108 For comparison, an intervention deviation may be determined. The device 110 Cumulating can cumulate an intervention trend. The device 112 providing may provide information about the intervention trend. For example, a frequency of interventions can be provided.

In favor of an increase in traffic safety, the vehicle stability with known methods, such as. B. are used in stability control systems such as ESP, be converted into a criterion.

2 shows a flowchart of a method 200 for characterizing a driving behavior of a driver of a vehicle according to an embodiment of the present invention. The procedure 200 can on a device like in 1 be executed. The procedure 200 has a step 202 determining, a step 204 determining, a step 206 of comparing, one step 208 of accumulating and one step 210 of providing. In step 202 When determining, at least one parameter is determined, wherein the parameter represents the instantaneous driving behavior. In step 204 the determination is determined in each case one, to the parameter corresponding, desired parameters, wherein the desired parameter represents a current reference driving manner. In step 206 comparing, the parameter is compared with the desired parameter to obtain a deviation. In step 208 of cumulating, the deviation is cumulated over a predetermined period of time to obtain a trend. In step 210 the provision of information about the trend is provided via an interface, wherein the trend characterizes the driving behavior.

3 shows a schematic diagram 300 a method for characterizing a driving behavior of a driver of a vehicle according to an embodiment of the present invention. Shown are an environment sensor 302 , a vehicle sensor 304 , a calculation 306 , a visualization 308 , a storage 310 and a transmission 312 , The environment sensor 302 and the vehicle sensors 304 are with the calculation 306 connected. The calculation 306 is with the visualization 308 and storage 310 connected. The storage 310 is with the transfer 312 connected. In the environment sensor 302 Information about an environment of the vehicle is recorded. In vehicle sensors 304 Information about the vehicle is recorded. In the calculation 306 are calculated from the information about an environment and the information about the vehicle criteria. In the visualization 308 For example, the criteria are visualized in an instrument cluster of the vehicle. In storage 310 the criteria are stored. In the transmission 312 For example, the criteria are transferred to www (world wide web).

The criteria determined during the journey can be provided to the driver via a suitable visualization 308 are displayed. It would be conceivable z. B. a computer games based on a system for point collecting, z. B. in the form of coins that fall into a basket. Various criteria 306 could also be summarized to reduce the amount of information to be presented. So could in the simplest case, a single driving quality measure z. B. can be displayed as% bars. Alternatively or additionally, the system can also inform the driver about the current status via a voice output. So the driver z. B. be pointed to a lane change without blinker actuation.

The determined criteria can be stored while driving. The data can after the end of the driver z. B. on a storage medium (USB stick) are taken to view them later with a PC software. This software also allows you to compare with an Internet community, so competitions for the best driving can be created. Data synchronization can also be done directly via a data connection built into the vehicle 312 (eg WLAN or mobile network).

In other words shows 3 a schematic diagram of the process. Based on the information provided by environment and vehicle sensors, the above criteria are calculated. These are displayed, for example, in the instrument cluster and optionally additionally stored in order to be transmitted to the web community either via a wireless data connection or a data carrier (such as, for example, USB memory stick).

4 shows a representation of a mobile device 400 on the steps of a method for characterizing a driving behavior of a driver of a vehicle according to an exemplary embodiment of the present invention is executable. The mobile device 400 is networked, for example, with a device of the vehicle and / or an off-board device. In this embodiment, the mobile device is 400 a smartphone. The mobile device 400 has sensors. The mobile device 400 has at least one video camera, a microphone, motion sensors and / or a position determination. The one or more sensors of the mobile device 400 may alternatively or in addition to the or the sensors of the vehicle, such as based on 1 used to implement the method. The mobile device 400 has an interface 402 , here for the realization of one or more radio connection. In this embodiment, the mobile device is 400 with a combination instrument 404 of the vehicle via a radio link 406 connected to receive information about the vehicle. The mobile device 400 can also be connected via a cable connection to the vehicle, which is offered for example during a charging process in the vehicle. About the interface 402 and the radio connection 406 can the mobile device 400 also with the internet 408 be connected. On the Internet 408 can the mobile device 400 for example, access social networks. Using the camera, according to the approach presented here, a lane detection and an object recognition are performed. Based on this, a criteria calculation and a storage of the criteria are carried out. A display of the mobile device 400 is used to display the criteria. The criteria can be over the radio connection 406 be transferred to the internet. For example, the criteria can be found on the Internet 406 used to conduct a contest with other participants of the social networks.

The whole process can be done on a smartphone 400 will be realized. This is, as for already known applications such as Lane Departure Warning, mounted with front-facing camera to the windshield. Using the video images, GPS data and smartphone 400 built-in inertial sensors, a majority of in 1 mentioned criteria directly on the smartphone 400 be determined. The smartphone 400 can via suitable interfaces 402 also access vehicle data, so then the entire range of criteria on a smartphone 400 can be calculated (for example, so turn signal information on the data connection from the car to the smartphone 400 be transmitted). The smartphone 400 allows via a data connection 406 the upload to the social network.

In other words illustrated 4 the realization of the approach presented here as a smartphone app. In this case, the environment sensor can be the one in the smartphone 400 serve built-in video camera. With suitable algorithms can be selected from the video images z. B. the lane information but also the distance to the vehicle in front can be determined. In a preferred embodiment, the vehicle (eg integrated into the instrument cluster) has a (eg wireless WLAN) connection 406 to the smartphone 400 , on the status information such. B. blinker operation are transmitted. In the case of availability of such information may be the number of, on the smartphone 400 calculable criteria and their quality. The smartphone 400 is also via a wireless data connection 406 with the Internet 408 Connected so that the information obtained during the journey can be uploaded directly to the community portal.

5 shows a representation of a visualization of a trend according to an embodiment of the present invention. The visualization takes place on a display 500 in a field of vision of the driver. The ad 500 is an instrument cluster in this embodiment. On the display 500 is a speedometer in the middle 502 integrated. The speedometer 502 has the shape of a pointer instrument. Such a configuration is merely exemplary. Instead of the shown ad 500 a common vehicle display can be used. Laterally next to the speedometer 502 is a graphical representation 504 a trend according to an embodiment of the present invention. The graphic representation 504 shows a "Driving Quality" display. The graphic representation 504 shows a transparent container 506 in which a filling level of a virtual liquid represents the trend. The container 506 is shown here as glass. A maximum filling level of the container 506 represents a reference mode or 100%. Next to the container 506 is a numerical display of the level arranged. In this embodiment, the container 506 48% full. Above the container is a representation of a drop of water 508 arranged. The water drop 508 represents a source of the virtual liquid in the container 506 , In the embodiment, a size of the water droplet represents 508 one to the container 506 number of points to add due to a maneuver well executed by the driver.

Next to the water drop 508 is a text 510 arranged, which represents information about the driving maneuver. In the embodiment, the text refers 510 on a well-executed lane change. In the container 506 Points of different criteria can be cumulated into an overall trend.

In other words shows 5 an exemplary presentation of the "driving quality information" in the instrument cluster 500 , While driving fills up in compliance with the traffic rules the glass 506 It is also conceivable to reduce the score for violations of the traffic rules again, so that an immediate feedback of the score can be achieved.

6 shows a representation of providing several trends 600 . 602 . 604 . 606 according to an embodiment of the present invention. In this embodiment, a first trend 600 "Fuel saving", a second trend 602 "Safety margin", a third trend 604 "Follow regulations" and a fourth trend 606 "Lane keeping" of a driver shown. The trends 600 . 602 . 604 . 606 are ever by a rhombus 608 characterized. The trends 600 . 602 . 604 . 606 are shown next to each other in a bar chart with a maximum attainable value of 100%. To the trends 600 . 602 . 604 . 606 Being able to compare with other drivers is the first trend 600 a first average 610 the second trend 602 a second average 612 the third trend 604 a third average 614 and the fourth trend 606 a fourth average 616 assigned. The means 610 . 612 . 614 . 616 can also represent a maximum score of a reference group from other drivers. The first average 610 has 98% "fuel economy", the second average 612 has 60% "safety distance", the third average 614 has 70% "Follow Instructions" and the fourth average 616 has 98% "tracking". The means 610 . 612 . 614 . 616 are pillars in the background of trends 600 . 602 . 604 . 606 shown. In this embodiment, the trends 600 . 602 . 604 . 606 and averages 610 . 612 . 614 . 616 presented on an internet platform "best driver". The trends 600 . 602 . 604 . 606 represent trends deposited by the driver in the Internet platform, which, according to the approach presented here, during driver's driving with a vehicle such as in 1 have been recorded. The driver is registered on the internet platform. His username 618 and a user picture are displayed with an indication of a login to the Internet platform. The means 610 . 612 . 614 . 616 represent trends of other users of the internet platform. The means 610 . 612 . 614 . 616 can also represent selected users. The third trend 604 "Follow instructions" is better than the third average 614 , Therefore, a congratulation 620 with the text "Congratulations! They are the best in following regulations "about the trends 600 . 602 . 604 . 606 appears. For the design of a corresponding portal, there are as many as desired, deviating from the described embodiment solutions.

The community network allows for various competitions ("challenges"), with each participant competing for the best seats in the ranking of the entire community, and it is also possible to define personalized challenges, making it possible, for example, among friends Finding the best rider The search for the best seats (which may be coupled with previously mentioned incentives such as discounted insurance premiums or prize draws) will improve the driving habits of all involved and thus increase overall road safety because not all participants have the same criteria (depending on the equipment of the vehicle / smartphone, available criteria are also possible on the basis of the individual criteria.) Examples: "Who is the lurking driver?", "Who can best keep the safety distances?"

In other words outlined 6 the community portal, where participants can register and compare their performance with the community and individual friends. The example shows the classification of the own driving quality criteria 600 . 602 . 604 . 606 regarding the community best.

The approach presented here is suitable, for example, for drivers who are already active in social networks. This may particularly apply to young drivers who can be trained early on a safe and prudent driving style with such a system. As a built-in solution, the system may require suitable sensors, such as environment sensors, such as those found in mid-range to high-end vehicles; In the alternative version as a smartphone application, the system can be used in all vehicles, from the bicycle to the truck.

The embodiments described and shown in the figures are chosen only by way of example. Different embodiments may be combined together or in relation to individual features. Also, an embodiment can be supplemented by features of another embodiment. Furthermore, method steps according to the invention can be repeated as well as carried out in a sequence other than that described. If an exemplary embodiment comprises a "and / or" link between a first feature and a second feature, then this is to be read so that the embodiment according to one embodiment, both the first feature and the second feature and according to another embodiment either only first feature or only the second feature.

QUOTES INCLUDE IN THE DESCRIPTION

This list of the documents listed by the applicant has been generated automatically and is included solely for the better information of the reader. The 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

• DE 4338073 A1 [0003]

Claims (11)

Procedure ( 200 ) for characterizing a driving behavior of a driver of a vehicle ( 100 ), the process ( 200 ) comprises the following steps: 202 ) at least one parameter, said parameter representing the determined instantaneous driving behavior of the driver with respect to a vehicle movement of the vehicle with respect to at least one environmental parameter and / or with respect to a lateral dynamics of the vehicle; Determine ( 204 ) each one of the at least one parameter corresponding desired parameter, wherein the desired parameter represents a current reference mode of operation; To compare ( 206 ) of the at least one parameter with the corresponding desired parameter to obtain a deviation between the at least one parameter and the corresponding desired parameter; Cumulate ( 208 ) the deviation over a period of time to a trend ( 600 . 602 . 604 . 606 ) to obtain; and deploy ( 210 ) information about the trend ( 600 . 602 . 604 . 606 ) via an interface ( 114 ), whereby the trend ( 600 . 602 . 604 . 606 ) characterizes the driving behavior of the driver. Procedure ( 200 ) according to claim 1, wherein the parameter represents the current driving behavior of the driver determined using an environment sensor system and / or an inertial sensor system. Procedure ( 200 ) according to one of the preceding claims, wherein in step ( 204 ) determining the target parameters using information about a road segment and / or information about at least one other road user in the road segment, the road segment identifying one of the vehicle ( 100 ) currently represented road section represents. Procedure ( 200 ) according to one of the preceding claims, wherein in the step of determining ( 202 ) the parameter and / or in step ( 204 ) of determining the target parameters using video information about an area in front of the vehicle ( 100 ) and / or movement information of the vehicle ( 100 ) and / or activity information of at least one subsystem of the vehicle ( 100 ) is determined. Procedure ( 200 ) according to one of the preceding claims, wherein in step ( 208 ) of accumulating the deviation over a plurality of journeys of the vehicle ( 100 ) or accumulated over a period of at least several minutes. Procedure ( 200 ) according to one of the preceding claims, wherein in step ( 210 ) of providing a trend ( 610 . 612 . 614 . 616 ) is provided to at least one other road user. Procedure ( 200 ) according to one of the preceding claims, comprising a step of forming a comparison result between the deviation and at least one other deviation which characterizes a driving behavior of at least one other road user. 210 ) of providing the comparison result to a driver interface. Procedure ( 200 ) according to one of the preceding claims, wherein in step ( 202 ) of determining at least one further parameter is determined and in step ( 204 ) of determining a corresponding further desired parameter is determined, wherein in step ( 206 ) of comparing the further parameters with the further desired parameter in order to obtain a further deviation, wherein in step ( 208 ) of cumulating either the further deviation is cumulative to another trend ( 600 . 602 . 604 . 606 ) obtained in step ( 210 ) or the trend ( 600 . 602 . 604 . 606 ) is accumulated using the further deviation and a processing instruction. method ( 200 ) according to one of the preceding claims, wherein the at least one parameter is a lateral position of the vehicle ( 100 ) in a lane of the vehicle ( 100 ) and the target parameter represents a desired position within the lane and / or the at least one parameter represents a distance of the vehicle ( 100 ) to a preceding vehicle and the target parameter represents a desired distance to the preceding vehicle and / or the at least one parameter is a speed of the vehicle ( 100 ) and the target parameter represents a target speed and / or the at least one parameter represents an event sequence of a driving maneuver of the vehicle ( 100 ) and the target parameter represents a desired event sequence and / or the at least one parameter represents an acceleration on the vehicle ( 100 ) represents at least in a vehicle axle and the desired parameter represents a target acceleration and / or the at least one parameter is an intervention of at least one safety system of the vehicle ( 100 ) and the desired parameter represents a desired state of the safety system. Contraption ( 102 ) for characterizing a driving behavior of a driver of a vehicle ( 100 ), which is adapted to the steps of a method ( 200 ) according to any one of claims 1 to 9 in corresponding facilities. Computer program product with program code for carrying out the method ( 200 ) according to one of claims 1 to 9, when the program product is stored on a device ( 102 ), especially on a smartphone ( 400 ) is performed.

Images