Continental Teves, Ag and Company Ohg

Conti Temic Microelectronic Gmbh

Continental Autonomous Mobility Germany Gmbh

Bernd Hartmann

Ulrich Stählin

Stefan Fritz

Joachim Denzler

Alfred Eckert

Manuel Amthor

Thomas Raste

Peter Lauer

Peter E Rieth

Georg Roll

Dieter Kroekel

Ulrich Staehlin

Kai Bretzigheimer

Andreas Hartmann

Thorsten Staab

Daniel Förster

Daniel Foerster

Stefan Schubert

Eric Bach

Michael Kemmler

Bjoern Froehlich

A method for classifying a roadway condition on the basis of image data from a camera system includes providing image data which is configured to image at least one portion of the surroundings of the vehicle, at least part of the portion containing the roadway on which the vehicle is driving. The method includes distinguishing diffuse reflection and specular reflection of the roadway by evaluating differences in the appearances of at least one point of the roadway in at least two images. The method also includes determining whether, in at least one image, there are disturbances that have been caused by at least one wheel of a vehicle whirling up a substance covering a roadway as said wheel travels thereover. The method further includes classifying the roadway condition into one of several roadway condition classes, taking account of the results with regard to the reflection type and the disturbance intensity.

Method and device for recognizing and evaluating roadway conditions and weather-related environmental influences

A method for determining road surface conditions in a system with at least one vehicle and a data processing device. The vehicle exchanges data with the data processing device wirelessly. The vehicle has at least one sensor for determining measured values describing a road surface friction coefficient, and a computing unit. The data processing device includes a database, containing a road map having a plurality of route sections. The method includes determining measured values for a route section by the sensor, determining a first friction coefficient for the route section by the vehicle's computing unit, sending a data record, containing measured values and/or the first determined friction coefficient and a piece of information identifying the route section, to the data processing device, determining an average friction coefficient for the route section, sending the average friction coefficient determined for the route section to the vehicle, and determining the road surface condition.

Method for determining road surface conditions

A road condition is classified based on spray water occurring at a wheel of the vehicle. To this end, the space around a wheel of the vehicle is imaged by a camera and the image captured by the camera is analyzed to detect spray water therein. A distinction can be made between a dry road, a wet road or a road having a risk of aquaplaning on the basis of the detected spray water, e.g. based on the angle, direction or projection range of the spray water.

Method and apparatus for determining a road condition

In a method for detecting and assessing reflections on a road (), a camera () produces at least two digital images of at least one point () of the road, respectively from different recording perspectives (A, B) of the camera (). Diffuse reflection and specular reflection of the road () are then detected by assessing differences in the appearances of the point () of the road in the at least two digital images using digital image processing algorithms. Road reflections are preferably assessed using an approximative approach. An item of road condition information is determined based on the detected reflection, preferably an item of road condition information which states whether the road is dry, wet, snow-covered or icy. Also provided are an apparatus () for carrying out the above-mentioned method, and a vehicle having such an apparatus.

Method and apparatus for detecting and assessing road reflections

A method and a device are for determining the presence and type of a roadway coating by a vehicle camera system. The vehicle camera system records at least one image of the surroundings of the subject vehicle. The at least one image is evaluated to detect indications of the presence of a roadway coating including a characteristic feature of the roadway coating that results as the roadway is traveled over by the subject vehicle or by another vehicle. The detected indications and characteristic feature are taken into consideration in the determination of the presence and type of a roadway coating. The result of the determination of the roadway coating, or a friction coefficient estimation derived therefrom, is output to a driver assistance function, a vehicle control function or as information to the driver.

Method and device for determining a roadway state by means of a vehicle camera system

A method and an apparatus determine a road condition using a vehicle camera. At least one image is acquired using the camera. A first image area that includes an image of the road surface is determined in the at least one image. A classifier assigns the first image area to at least one class (among pre-established classes) that represents a specific road condition of the road surface. Information regarding this specific road condition is output.

For determining a state of a pavement from surroundings sensor data, local data received from at least one device that measures a local pavement state or coefficient of friction is merged with camera image data received from a camera for imaging a pavement extending in front of the vehicle. When analyzing the camera image data, the local data representing the measured pavement state or coefficient of friction is assigned to individual image sectors of a camera image while taking odometric and time information into account to achieve proper correspondence, and the local data is taken into account for supporting and/or plausibility-checking of an anticipatory estimation of the local coefficient of friction or pavement state based on the camera image data.

Method for determining a state of a pavement from surroundings sensor data

In a device and a method for increasing the safety of a motor vehicle, a first sensor unit () detects the environment, in particular free spaces and objects () and the position and motion thereof, a second sensor unit () detects the environment state, a third sensor unit () detects the vehicle state, and a fourth sensor unit () detects the driver inputs. The respective data from the several sensor units are combined. In consideration of the data, a driving safety coordinator () calculates the risk of collision on the basis of a risk evaluation, and determines pre-collision phases (P, P, P, P, P) of the motor vehicle () with regard to the object ().

Safety device for a motor vehicle and method for operating a motor vehicle

The invention relates to a method and a device for performing open-loop or closed-loop control of the driving stability of a vehicle and for avoiding collisions with an object located in the traffic lane. The invention also relates to a closed-loop driving stability controller. The method according to aspects of the invention comprises: determining based on environmental signals whether a critical situation in terms of driving dynamics, in particular an imminent collision, exists, calculating an avoidance path if a critical situation in terms of driving dynamics exists, determining based on a plurality of input variables pressures for individual brakes of the vehicle, and activating preparatory measures of the driving dynamics regulator, in particular dynamic switching over of closed-loop control parameters if the critical situation in terms of driving dynamics exists. The device and the closed-loop driving stability controller are suitable for carrying out the method.

Method and device for performing closed-loop or open-loop control of the driving stability of a vehicle

A method and a device are for prediction and adaptation of movement trajectories of a vehicle for assisting the driver and/or for preventing or reducing the severity of a collision. Situatively required movement trajectories for assisting the driver or collision avoidance are determined using an environment sensor system. Physically possible movement trajectories are determined from characteristic properties of the driving dynamics of the vehicle and from the coefficient of friction between the tires and the road up to a maximum coefficient of friction. An intersection between the above two sets of trajectories is determined, and only trajectories that are included in this intersection are taken into account for the prediction and adaptation of movement trajectories for the driving assistance or collision avoidance function.

Method and device for the prediction and adaptation of movement trajectories of motor vehicles

The application relates to a device and a method for increasing the safety of a motor vehicle. A first sensor unit () senses the surroundings, in particular in order to detect free spaces and objects (), and the position and movement thereof. A second sensor unit () senses the state of the surroundings, a third sensor unit () senses the state of the vehicle, and a fourth sensor unit () senses the driver's commands. The data are merged and a driving safety coordinator () determines at least one reliable driving corridor (K, K, K, Kto Kn) predictively and situationally in order to determine the operational safety. The driver's command can be limited to the driving corridor (K, K, K, Kto Kn) by means of components () which can be actuated actively and/or the motor vehicle () can be kept in the driving corridor (K, K, K, Kto Kn) by means of the components () which can be actuated actively.

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Bad Homburg, Germany

Bernd Hartmann