EP3069296A1 - Procédé et dispositif de détermination d'un état d'une voie de circulation au moyen d'un système de caméra de véhicule - Google Patents

Procédé et dispositif de détermination d'un état d'une voie de circulation au moyen d'un système de caméra de véhicule

Info

Publication number
EP3069296A1
EP3069296A1 EP14820736.8A EP14820736A EP3069296A1 EP 3069296 A1 EP3069296 A1 EP 3069296A1 EP 14820736 A EP14820736 A EP 14820736A EP 3069296 A1 EP3069296 A1 EP 3069296A1
Authority
EP
European Patent Office
Prior art keywords
vehicle
road
roadway
image
determined
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Withdrawn
Application number
EP14820736.8A
Other languages
German (de)
English (en)
Inventor
Bernd Hartmann
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Continental Teves AG and Co OHG
Original Assignee
Continental Teves AG and Co OHG
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Continental Teves AG and Co OHG filed Critical Continental Teves AG and Co OHG
Publication of EP3069296A1 publication Critical patent/EP3069296A1/fr
Withdrawn legal-status Critical Current

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle
    • G06V20/588—Recognition of the road, e.g. of lane markings; Recognition of the vehicle driving pattern in relation to the road
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B60—VEHICLES IN GENERAL
    • B60R—VEHICLES, VEHICLE FITTINGS, OR VEHICLE PARTS, NOT OTHERWISE PROVIDED FOR
    • B60R11/00—Arrangements for holding or mounting articles, not otherwise provided for
    • B60R11/04—Mounting of cameras operative during drive; Arrangement of controls thereof relative to the vehicle
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/50—Context or environment of the image
    • G06V20/56—Context or environment of the image exterior to a vehicle by using sensors mounted on the vehicle

Definitions

  • the invention relates to a method and a device for determining a roadway support by means of a vehicle camera system.
  • Camera-based driver assistance systems capture the surroundings of a vehicle.
  • Camera systems placed behind the windscreen capture the apron of the vehicle according to the visual perception of the driver.
  • the functional scope of such assistance systems extends from the high-beam automatic lighting via detection and display of speed limits to the warning of lane departure errors or imminent collision.
  • radar, lidar sensors or laser scanners allow the detection of other vehicles, unprotected road users such as road users. Pedestrians and cyclists and the infrastructure such as Crash barriers and traffic lights. Thus, the condition is created to describe the direct vehicle environment more accurate.
  • DE 10 2004 018 088 A1 shows a tramway recognition system with a temperature sensor, an ultrasound sensor and a camera.
  • the temperature, roughness and image data (lane data) obtained from the sensors are filtered and compared with reference data and a degree of security for the comparison is generated.
  • the condition of the road surface is determined.
  • the road surface eg concrete, asphalt, dirt, grass, sand or gravel
  • their condition eg dry, icy, snowy, wet
  • WO 2012/110030 A2 shows a method and a device for friction estimation by means of a 3D camera, for example a stereo camera.
  • the 3D camera captures at least one image of the surroundings of the vehicle. From the image data of the 3D camera, a height profile of the road surface is created in the entire vehicle apron.
  • the expected local coefficient of friction of the road surface ⁇ area is estimated in the vehicle ahead from the relief. May be made of special determined height profiles ⁇ in individual cases, a classification of the road surface, for example, be carried out as a snow cover or muddy road.
  • WO 2013/117186 A1 shows a method and a device for detecting the condition of a road surface by means of an SD camera.
  • the 3D camera captures at least one image of the environment ahead of the vehicle. From the image data of the SD camera, height profiles of the road surface transversely to the direction of travel of the vehicle are determined along a plurality of lines. From the determined height gradients, the condition of the road surface is detected.
  • Optional 2D image data will be evaluated at least a monocular camera, the 3D camera in addition to the determined height gradients, flow, for example by means of a texture or pattern analysis, and in recognition of the nature of the Fahrbahnoberflä ⁇ surface.
  • the object of the present invention is therefore to provide a road condition determination by means of a camera which, when using different vehicle camera system configurations, for example also only a monocamera system, enables an optimized road condition recognition or friction coefficient estimation derived therefrom.
  • a main idea of the invention is to determine by means of aletsys ⁇ tems and an image processing targeted evidence for the existence of a roadway support when traveling over the road by a vehicle.
  • a road surface is eg snow, rain water, ice, leaves, dust, so media / objects the surface (ceiling, carpet) on the road surface (asphalt, tar, concrete, ...) rest.
  • the sheet resting can be called a blanket or carpet of the medium or the items, but it does not have the entire Fahrbahnoberflä ⁇ che be covered.
  • Different roadway pads typically exhibit different behaviors when run over by a vehicle. Some of them can be observed or detected with a camera and recognized or identified in a subsequent image analysis, from which conclusions can be drawn on the presence and type of the road surface.
  • An inventive method for determining a road pad by means of an on-vehicle camera system comprising the steps of: by means of the vehicle camera system is at least capture an image of a traveling ⁇ imaging environment.
  • the at least one image is evaluated in order to determine indications of the presence of a road surface when driving over the road through the vehicle with the vehicle camera system or by another vehicle.
  • the determined indications are taken into account when determining a road surface.
  • the He ⁇ result of the determination of the roadway support can preferably with a direct road surface condition estimation by a classification or egg ne application of a neural network combined and output to a sesas ⁇ sistenzfunktion, a vehicle control function or as information to the driver.
  • Driver assistance functions may in particular include collision warnings, emergency braking or emergency steering
  • vehicle control functions may include occupant protection measures (airbag pre-control, brake pre-control, belt tensioner pre-control) and (partially) autonomous braking and / or steering interventions.
  • the determined indicia or the result of the determination of the road surface are taken into account in the design of driver assistance functions, vehicle control functions.
  • the result of the determination of the road surface can in particular be included in an estimate of the coefficient of friction for the road area, which is shown in the image, or an otherwise determined current or prospective determined coefficient of friction. Because the Fahrbahnauf ⁇ location has a significant impact on the actual coefficient of friction.
  • the coefficient of friction, also coefficient of friction, adhesion coefficient, (static) friction coefficient or coefficient of friction indicates which force relative to the wheel load between a road surface and a vehicle ⁇ tires (eg in the tangential direction) can be transmitted maximum and is thus an essential measure of driving safety , In addition to the driving ⁇ ground-state properties of the tire to a complete determination of the coefficient of friction are required.
  • the effects of precipitation for example rain, snow, hail or even fog
  • the effects of precipitation for example rain, snow, hail or even fog
  • the effects of precipitation are determined as indications.
  • Type and amount of precipitation can be in the image evaluation ⁇ true are.
  • the detection direction of the camera system can advantageously be linked to the current vehicle movement direction.
  • the effects of a roadway overlay when passing over at least one tire of a vehicle are determined as indicia in the image evaluation. Effects here are in particular changes in the road surface including the road surface when driving over a vehicle or more precisely when driving over at least one tire of the vehicle.
  • At least one area in the at least one image is advantageously determined, from which indications for the presence of a roadway pad can be taken.
  • the area in the at least one image becomes one
  • Classifier supplied, which maps the determined indicia to a set of classes, each associated with a roadway pad.
  • the vehicle camera system has a rearward and / or lateral detection area of the surroundings of the own vehicle.
  • the own vehicle here is what the vehicle camera system has.
  • the image analysis can be limited to a fixed image area in which the effects of an existing roadway pad typically show, for example, an area behind a tire or at the rear of one's own vehicle, which is reflected by a rear camera or an area next to a tire of one's own Vehicle a side camera images.
  • the advantage with this embodiment is that one is not dependent on the detection range of Vietnamesekame ⁇ rasystems other vehicles located for determining a road support.
  • the vehicle camera system has a detection area in front of the driver's own vehicle, then that indicia for the presence of a roadway surface when driving over the roadway by a preceding, crossing or oncoming vehicle in the image analysis are determined.
  • the image analysis can be limited to an image area in which the rear and / or the side of a vehicle in front or the front of the vehicle and / or the side of a ent ⁇ oncoming vehicle is displayed.
  • the relevant image area can be determined on the basis of the tire contact zones with the roadway in the image.
  • An advantage of this embodiment is the fact that a forward-looking determination of a road surface is possible.
  • the indications for the presence of a roadway surface when driving over the roadway comprise swirled components of the vehicle seat.
  • these include, in particular, the detection of spray water or spray slush, spray mist or spray,
  • the indications of the presence of a roadway covering include visual obstructions in the field of view of the vehicle camera system due to the driving over the roadway by a preceding, traversing or oncoming vehicle.
  • the evidence of the presence of a road surface when driving over the roadway by a vehicle include tire tracks in the road surface.
  • Tire lanes are formed at specific roadway pads directly behind the tires of a moving vehicle, partially, for example. In a snow pad even the imprint of the tire tread can be detected within a tire lane.
  • determining the presence of a road surface next to the evidence of the presence of a roadway surface when driving over the roadway by a vehicle additionally typical generic properties of different road surface conditions can be determined and taken into account.
  • This refers to characteristics which are characteristic of roadway pads and which A camera image can be detected even without a vehicle running over, for example, puddles and reflections in rainwater or the Topolo- gie the surface.
  • headlights oncoming vehicles are more reflected in rainy or icy road than in a dry road.
  • the classifier comprises a neural network which has been trained to be able to assign the determined indicia to a roadway pad.
  • the neural network can also continuously learn to associate indicia with a class of roadway pads.
  • the result of the determination of the roadway support is combined with the result of a roadway condition detection or classification, and a friction coefficient estimate is made therefrom.
  • the road condition detection or classification particularly determines the material and geometric road surface, e.g. rough or smooth tar, asphalt or concrete possibly with existing ruts and may in particular be based on image data of the same vehicle camera system.
  • the invention relates to a device for determining a road surface comprising a vehicle camera system , an evaluation ⁇ unit, a determination unit and an output unit.
  • the driving ⁇ imaging camera system is adapted to receive at least an image of a driving ⁇ imaging environment.
  • the evaluation unit is designed for the evaluation of the at least one image to determine indications of the EXISTING ⁇ densein a roadway support by precipitation and / or when traveling over the road by a vehicle (E, F).
  • the determination unit is designed to determine a roadway surface taking into account the determined indicia.
  • the output unit is set up to output the result determined by the determination unit. Evaluation, determination and output unit may in particular be part of the control unit of the vehicle camera system or other vehicle control units.
  • Fig. 1 shows schematically a binarized camera image of a vehicle tire when driving over a rainy roadway.
  • Fig. 2 shows different detection ranges of a complex Kame ⁇ rasystems a vehicle.
  • a black and white image of a camera image of a vehicle tire when driving over a rainy road surface is shown.
  • the vehicle tire is on a rim (white, circular) and the vehicle is moving to the right.
  • Wassertrop ⁇ fen and water yarns white dots and filaments which are displaced and when passing the water-covered road surface by the tire accelerated.
  • the tire When driving over wet roads, namely splashing water forms, starting from the vehicle tires. Due to the high surface pressure, the tire displaces the water on the road to all sides. Particularly pronounced is the appearance of trucks whose tires have correspondingly higher surface pressure to displace more water than cars.
  • the spray is mainly seen in the direction of travel behind and to the side of the vehicle tire. There it can be detected by a vehicle camera and recognized by an image processing as splashing, from which it can be concluded that a rainwater layer as a road surface.
  • Ka merasent in some roadway pads more evidence in Ka merasent be identified and identified, then form when driving over wet or snowy roads or even when driving from slush tire tracks behind a moving vehicle, in part, for example, from a thin layer of snow from the pressure of the tire profile are detected within a tire lane in addition, precipitates in the form of rain, snow or hail, and also the fog can be detected as evidence of the road condition in Ka ⁇ merasent.
  • the different classes can be roughly subdivided (no driving track / water / snow), but also finer subdivided (for example be snow: powder snow up to 5mm height, powder snow> 5mm height, hard snow, slush). This subdivision can be carried out in particular as a function of an assignment of the class to a mean coefficient of friction, or the change in the associated average friction coefficient during the transition from one subclass to another.
  • FIG. 2 shows the detection areas (la-lf, 2, 3) of a camera system arranged in or on a first vehicle (E).
  • a second vehicle (F) Comprising an all ⁇ vision system (1) six single camera sensors with wide angle detection areas (la-lf), which allow a 360 ° -Er charged of the vehicle: the camera system of the first vehicle (E) comprises three different camera subsystems (1, 2 and 3) , a front camera with a ge forwardly directed ⁇ detection region (2) and a rear camera with a rearward detection area (3).
  • a stereo camera can be used as the front camera ⁇ , whereby a spatial resolution of the captured image data is achieved.
  • Objects such as sprayed water drops can be analyzed in terms of its spatial form and extent, which improves the CLASSIFICA ⁇ tion of an existing road pad.
  • the image processing for determining a lane support can be advantageously in which a tire contact area of the roadway located on one or more regions of the camera image restric ⁇ ken.
  • an image area can be evaluated in which the rear of the vehicle in front is located.
  • indicia of the presence of a road surface when driving over the road through the tires of the own vehicle (E) can be determined.
  • the advantage here is that one does not depend on vehicles traveling ahead or on the wrong track (F), but on the basis of the detection and determination of the effects caused by the own vehicle (E) on the basis of a rear-facing and / or laterally oriented sensor system other vehicles (F) can determine a currently relevant road surface.
  • other vehicles (F) can determine a currently relevant road surface.
  • a 360 ° camera sensor that detects a surround view, which can be used by the driver e.g.
  • a "top view” can be displayed in a bird's eye view, so the reliable determination of a road surface is realistic.

Landscapes

  • Engineering & Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Multimedia (AREA)
  • Theoretical Computer Science (AREA)
  • Mechanical Engineering (AREA)
  • Traffic Control Systems (AREA)
  • Image Analysis (AREA)
  • Regulating Braking Force (AREA)
  • Image Processing (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)

Abstract

L'invention concerne un procédé ou encore un dispositif de détermination d'un revêtement d'une voie de circulation au moyen d'un système de caméra de véhicule. Ledit procédé comprend les étapes suivantes : au moyen d'un système de caméra d'un véhicule, l'enregistrement d'au moins une image d'un environnement du véhicule ; l'évaluation de l'image ou des images afin de définir des indices pour des précipitations et/ou la présence d'un revêtement de la voie de circulation lors du passage sur la voie de circulation par le véhicule (E) avec le système de caméra du véhicule ou par un autre véhicule (F) ; la prise en compte des indices définis lors de la détermination du revêtement de la voie de circulation. Le résultat de la détermination du revêtement de la voie de circulation ou une estimation de valeur de frottement en résultant peut être délivré(e) de préférence à une fonction d'assistance à la conduite, à une fonction de commande du véhicule ou également au conducteur sous forme d'une information.
EP14820736.8A 2013-11-15 2014-10-28 Procédé et dispositif de détermination d'un état d'une voie de circulation au moyen d'un système de caméra de véhicule Withdrawn EP3069296A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
DE102013223367.1A DE102013223367A1 (de) 2013-11-15 2013-11-15 Verfahren und Vorrichtung zur Bestimmung eines Fahrbahnzustands mittels eines Fahrzeugkamerasystems
PCT/DE2014/200601 WO2015070861A1 (fr) 2013-11-15 2014-10-28 Procédé et dispositif de détermination d'un état d'une voie de circulation au moyen d'un système de caméra de véhicule

Publications (1)

Publication Number Publication Date
EP3069296A1 true EP3069296A1 (fr) 2016-09-21

Family

ID=52231781

Family Applications (1)

Application Number Title Priority Date Filing Date
EP14820736.8A Withdrawn EP3069296A1 (fr) 2013-11-15 2014-10-28 Procédé et dispositif de détermination d'un état d'une voie de circulation au moyen d'un système de caméra de véhicule

Country Status (5)

Country Link
US (1) US10289920B2 (fr)
EP (1) EP3069296A1 (fr)
JP (1) JP2017503715A (fr)
DE (2) DE102013223367A1 (fr)
WO (1) WO2015070861A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102022211241A1 (de) 2022-10-24 2024-04-25 Continental Autonomous Mobility Germany GmbH Erkennen von Fahrbahnauflage auf einer Fahrbahn

Families Citing this family (37)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102012112724A1 (de) 2012-12-20 2014-06-26 Continental Teves Ag & Co. Ohg Verfahren zur Bestimmung eines Fahrbahnzustands aus Umfeldsensordaten
DE102012112725A1 (de) 2012-12-20 2014-06-26 Continental Teves Ag & Co. Ohg Reibwertschätzung aus Kamera- und Raddrehzahldaten
DE102013101639A1 (de) 2013-02-19 2014-09-04 Continental Teves Ag & Co. Ohg Verfahren und Vorrichtung zur Bestimmung eines Fahrbahnzustands
US9610893B2 (en) 2015-03-18 2017-04-04 Car1St Technologies, Llc Methods and systems for providing alerts to a driver of a vehicle via condition detection and wireless communications
US10328855B2 (en) 2015-03-18 2019-06-25 Uber Technologies, Inc. Methods and systems for providing alerts to a connected vehicle driver and/or a passenger via condition detection and wireless communications
US9972206B2 (en) * 2015-12-03 2018-05-15 GM Global Technology Operations LLC Wet road surface condition detection
US9836660B2 (en) * 2015-12-03 2017-12-05 GM Global Technology Operations LLC Vision-based wet road surface condition detection using tire tracks
US9971945B2 (en) * 2015-12-03 2018-05-15 GM Global Technology Operations LLC Vision-based wet road surface condition detection using tire side splash
US9928427B2 (en) * 2015-12-03 2018-03-27 GM Global Technology Operations LLC Vision-based wet road surface condition detection using tire rearward splash
DE102016223556B4 (de) 2015-12-09 2023-09-28 Ford Global Technologies, Llc Kraftfahrzeug mit Staubsensor und Verfahren zur Minderung von Staubaufwirbelung durch ein Kraftfahrzeug
DE102016205430A1 (de) 2016-04-01 2017-10-05 Robert Bosch Gmbh Verfahren und Vorrichtung zur Reibwertbestimmung eines befahrbaren Untergrunds mittels eines Ego-Fahrzeugs
FR3049524B1 (fr) * 2016-04-05 2020-06-19 Valeo Vision Procede de commande d'affichage automatique d'un pictogramme representatif d'une chaussee glissante
DE102016210632A1 (de) 2016-06-15 2017-12-21 Bayerische Motoren Werke Aktiengesellschaft Verfahren zum Überprüfen eines Medienverlustes eines Kraftfahrzeuges sowie Kraftfahrzeug und System zum Ausführen eines solchen Verfahrens
US10082795B2 (en) * 2016-08-24 2018-09-25 GM Global Technology Operations LLC Vision-based on-board real-time estimation of water film thickness
US10078892B1 (en) 2017-03-16 2018-09-18 GM Global Technology Operations LLC Methods and systems for vehicle tire analysis using vehicle mounted cameras
DE102017206244A1 (de) * 2017-04-11 2018-10-11 Continental Teves Ag & Co. Ohg Verfahren und vorrichtung zur ermittlung eines fahrbahnzustands
DE102017112073A1 (de) * 2017-06-01 2018-12-06 Man Truck & Bus Ag Verfahren und Vorrichtung zur vorausschauenden Beurteilung einer Fahrbahn
US20190057272A1 (en) * 2017-08-18 2019-02-21 GM Global Technology Operations LLC Method of detecting a snow covered road surface
JP6664360B2 (ja) * 2017-09-08 2020-03-13 本田技研工業株式会社 判定装置および車両
DE102017216195A1 (de) * 2017-09-13 2019-03-14 Bayerische Motoren Werke Aktiengesellschaft Verfahren zur Untersuchung von Reifen
JP6592051B2 (ja) * 2017-09-25 2019-10-16 本田技研工業株式会社 車両制御装置
US10589742B2 (en) * 2017-11-30 2020-03-17 Ford Global Technologies, Llc Vehicle snow level response
CN107977641A (zh) * 2017-12-14 2018-05-01 东软集团股份有限公司 一种智能识别地形的方法、装置、车载终端及车辆
US20210012119A1 (en) * 2018-03-01 2021-01-14 Jaguar Land Rover Limited Methods and apparatus for acquisition and tracking, object classification and terrain inference
DE102018203807A1 (de) 2018-03-13 2019-09-19 Continental Teves Ag & Co. Ohg Verfahren und Vorrichtung zur Erkennung und Bewertung von Fahrbahnzuständen und witterungsbedingten Umwelteinflüssen
US11206375B2 (en) 2018-03-28 2021-12-21 Gal Zuckerman Analyzing past events by utilizing imagery data captured by a plurality of on-road vehicles
JP2021524416A (ja) 2018-07-06 2021-09-13 イーグル エアロスペース, リミテッドEagle Aerospace, Ltd. 適応型制動および方向制御システム（ａｂａｄｃｓ）
US11138418B2 (en) 2018-08-06 2021-10-05 Gal Zuckerman Systems and methods for tracking persons by utilizing imagery data captured by on-road vehicles
DE102018127342B4 (de) 2018-11-01 2022-09-29 Mercedes-Benz Group AG Verfahren und Vorrichtung zum Betrieb eines Assistenzsystems eines Fahrzeuges
US11142209B2 (en) 2019-02-12 2021-10-12 Ford Global Technologies, Llc Vehicle road friction control
DE102019210935A1 (de) * 2019-07-24 2021-01-28 Zf Friedrichshafen Ag Erkennen und Bewerten einer Wasseransammlung auf einer Fahrbahn
US11124192B2 (en) 2019-08-13 2021-09-21 Ford Global Technologies, Llc Electrified vehicle configured to selectively increase energy recovery threshold based on friction prediction and corresponding method
DE102019130922A1 (de) * 2019-11-15 2021-05-20 Bayerische Motoren Werke Aktiengesellschaft System und Verfahren für ein Fahrzeug
EP3926523A1 (fr) * 2020-06-19 2021-12-22 Toyota Jidosha Kabushiki Kaisha Système de reconnaissance de surface
DE102020213428A1 (de) 2020-10-26 2022-04-28 Volkswagen Aktiengesellschaft Verfahren zum Betreiben eines Assistenzsystems eines Kraftfahrzeugs, sowie Assistenzsystem
CN112380930B (zh) * 2020-10-30 2022-04-29 浙江预策科技有限公司 一种雨天识别方法和系统
US20220366786A1 (en) * 2021-05-03 2022-11-17 Here Global B.V. Method and apparatus for estimating lane pavement conditions based on street parking information

Family Cites Families (98)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JPH072448B2 (ja) 1986-01-13 1995-01-18 アイシン・エィ・ダブリュ株式会社 ４輪駆動の制御装置
GB8918303D0 (en) 1989-08-10 1989-09-20 Lucas Ind Plc Monitoring and predicting road vehicle/road surface conditions
JP3393654B2 (ja) 1991-12-25 2003-04-07 マツダ株式会社 車両のスリップ制御装置
JPH0735522A (ja) 1993-07-23 1995-02-07 Nippon Doro Kodan レーザーを利用した舗装路面横断プロフィル測定方法
US5586028A (en) 1993-12-07 1996-12-17 Honda Giken Kogyo Kabushiki Kaisha Road surface condition-detecting system and anti-lock brake system employing same
US5774821A (en) 1994-11-25 1998-06-30 Itt Automotive Europe Gmbh System for driving stability control
JPH08263784A (ja) 1995-03-23 1996-10-11 Honda Motor Co Ltd 道路状況認識装置
JPH08258588A (ja) 1995-03-27 1996-10-08 Mazda Motor Corp 車両における路面状態検出装置
US7085637B2 (en) * 1997-10-22 2006-08-01 Intelligent Technologies International, Inc. Method and system for controlling a vehicle
EP1383100A3 (fr) 1996-08-28 2005-02-02 Matsushita Electric Industrial Co., Ltd. Appareil de positionement local et méthode associée
JPH11211659A (ja) * 1998-01-23 1999-08-06 Nagoya Denki Kogyo Kk 路面状態判別方法およびその装置
JP3620628B2 (ja) * 1998-02-05 2005-02-16 オムロン株式会社 路面状態検出装置
DE19856510C2 (de) 1998-02-20 2002-10-24 Cegelec Anlagen Und Automatisi Verfahren und System zur Ermittlung von Unebenheiten und Schadstellen in der Oberfläche einer Verkehrsfläche
DE19854964A1 (de) 1998-11-29 2000-06-08 Martin Spies Sensor zur Fahrbahnbeurteilung
JP2001334921A (ja) 2000-05-30 2001-12-04 Fuji Heavy Ind Ltd 車両の路面摩擦係数推定装置
JP3271963B1 (ja) 2000-10-26 2002-04-08 富士重工業株式会社 車両の路面摩擦係数推定装置
JP3539722B2 (ja) 2000-11-16 2004-07-07 富士重工業株式会社 車両の路面摩擦係数推定装置
DE10060333A1 (de) 2000-12-04 2002-06-13 Daimler Chrysler Ag Vorrichtung zur Erkennung einer während des Fahrbetriebes eines Fahrzeuges auftretenden Aquaplaninggefahr
JP2002310896A (ja) * 2001-04-19 2002-10-23 Mitsubishi Heavy Ind Ltd 路面状態判別装置及び路面状態判別方法
US20020176608A1 (en) 2001-05-23 2002-11-28 Rose David Walter Surface-profiling system and method therefor
DE10155488A1 (de) 2001-11-13 2003-05-28 Wilhelm Caspary Verfahren zur Erfassung der Oberfläche einer Fahrbahn
US6636258B2 (en) 2001-10-19 2003-10-21 Ford Global Technologies, Llc 360° vision system for a vehicle
US7203579B2 (en) 2001-12-21 2007-04-10 Kabushiki Kaisha Bridgestone Method and apparatus for estimating road surface state and tire running state, ABS and vehicle control using the same
ES2391556T3 (es) 2002-05-03 2012-11-27 Donnelly Corporation Sistema de detección de objetos para vehículo
AU2003263131A1 (en) 2002-08-09 2004-03-19 Automotive Distance Control Systems Gmbh Means of transport with a three-dimensional distance camera and method for the operation thereof
JP4046059B2 (ja) 2002-11-08 2008-02-13 株式会社豊田中央研究所 路面状態推定装置
DE10256726A1 (de) 2002-12-05 2004-06-24 Conti Temic Microelectronic Gmbh Verfahren zur fahrbahnabhängigen Signalgenerierung in einem Kraftfahrzeug
JP4165380B2 (ja) 2003-01-31 2008-10-15 株式会社豊田中央研究所 車両制御方法及び車両制御装置
US6807473B1 (en) * 2003-04-09 2004-10-19 Continental Teves, Inc. Road recognition system
JP2005028887A (ja) 2003-07-07 2005-02-03 Fuji Heavy Ind Ltd 路面摩擦係数推定装置および路面摩擦係数推定方法
JP4100336B2 (ja) * 2003-12-04 2008-06-11 日産自動車株式会社 画像処理装置
JP2005189983A (ja) * 2003-12-24 2005-07-14 Denso Corp 車両運転支援装置
US7417738B2 (en) 2004-01-27 2008-08-26 Tradewind Scientific Ltd. Determining surface properties of a roadway or runway from a moving vehicle
JP4453382B2 (ja) 2004-02-10 2010-04-21 トヨタ自動車株式会社 車両の走行制御装置
JP2007522981A (ja) * 2004-02-20 2007-08-16 シャープ株式会社 状況検出表示システム、状況検出表示方法、状況検出表示システム制御プログラム、および当該プログラムを記録した記録媒体
US8310545B2 (en) 2004-03-29 2012-11-13 Pioneer Corporation Apparatus and method for analyzing road view
DE102004016288B3 (de) 2004-04-02 2005-08-18 Daimlerchrysler Ag Verfahren zur Bestimmung eines Reibwerts
DE102004019337A1 (de) 2004-04-21 2005-11-17 Siemens Ag Assistenzsystem für Kraftfahrzeuge
JP4092308B2 (ja) 2004-06-02 2008-05-28 トヨタ自動車株式会社 境界線検出装置
DE102004055069B4 (de) 2004-07-15 2007-02-15 Daimlerchrysler Ag Mehrdimensionale Fahrbahnvermessung
DE102004047914A1 (de) 2004-09-29 2006-03-30 A.D.C. Automotive Distance Control Systems Gmbh Methode zur Einschätzung des Fahrbahnzustands
DE102004048637A1 (de) 2004-10-04 2006-04-06 Daimlerchrysler Ag 3D-Fahrbahnmessung mit redundanten Messdaten
JP4548196B2 (ja) 2005-04-21 2010-09-22 株式会社デンソー 車輪位置検出装置およびそれを備えたタイヤ空気圧検出装置
DE102005039167A1 (de) 2005-08-17 2007-02-22 Daimlerchrysler Ag Fahrerassistenzsystem zur Fahrerwarnung bei einem drohenden Verlassen der Fahrspur
DE102006012289A1 (de) 2006-03-17 2007-09-20 Man Nutzfahrzeuge Ag Verfahren zur vorausschauenden Erkennung der Reibwertänderung eines Straßenbelags
JP2007322231A (ja) 2006-05-31 2007-12-13 Fujifilm Corp 路面状況検出装置
US7693629B2 (en) * 2006-11-14 2010-04-06 Denso Corporation Onboard fog determining apparatus
US8306747B1 (en) 2007-01-19 2012-11-06 Starodub, Inc. Travel way measurement system
WO2008150153A1 (fr) 2007-06-08 2008-12-11 Tele Atlas B.V. Procédé et appareil permettant de produire un panorama à plusieurs points de vue
DE102008047750A1 (de) 2007-09-18 2009-05-07 Continental Teves Ag & Co. Ohg Bestimmung eines Kraftschlusses mit wenigen Sensoren
EP2048476B1 (fr) * 2007-10-08 2013-12-11 Delphi Technologies, Inc. Procédé d'assistance au conducteur
JP5011186B2 (ja) * 2008-03-27 2012-08-29 富士重工業株式会社 運転支援装置および運転支援システム
JP5089545B2 (ja) 2008-09-17 2012-12-05 日立オートモティブシステムズ株式会社 道路境界検出判断装置
FI124059B (fi) 2008-09-19 2014-02-28 Aalto Korkeakoulusaeaetioe Parannus ajoneuvojen ajonhallintajärjestelmiin
US8737628B2 (en) 2008-10-30 2014-05-27 Bridgestone Corporation Method for estimating road surface state
DE102009033219A1 (de) 2009-01-23 2010-07-29 Daimler Ag Verfahren zur Ermittlung eines Fahrzeug vorausliegenden Straßenprofils einer Fahrspur
JP5172764B2 (ja) 2009-03-30 2013-03-27 本田技研工業株式会社 路面摩擦係数推定装置
US8395529B2 (en) 2009-04-02 2013-03-12 GM Global Technology Operations LLC Traffic infrastructure indicator on head-up display
US8564657B2 (en) 2009-05-29 2013-10-22 Honda Research Institute Europe Gmbh Object motion detection system based on combining 3D warping techniques and a proper object motion detection
EP2454137B1 (fr) 2009-07-17 2015-09-09 Continental Teves AG & Co. oHG Procédé à laser permettant la classification de coefficients de frottement dans des véhicules automobiles
DE102009041566B4 (de) 2009-09-15 2022-01-20 Continental Teves Ag & Co. Ohg Verfahren zur Klassifizierung des Fahrbahnreibwerts
KR101089650B1 (ko) 2009-09-23 2011-12-06 삼성전기주식회사 차량 속도 제어 장치 및 방법
US8849474B2 (en) * 2009-12-25 2014-09-30 Yamaha Hatsudoki Kabushiki Kaisha Rider characteristic determining apparatus, and a saddle riding type vehicle having the same
JP5325765B2 (ja) 2009-12-28 2013-10-23 日立オートモティブシステムズ株式会社 路肩検出装置及び路肩検出装置を用いた車両
US9092981B2 (en) 2010-03-03 2015-07-28 Panasonic Intellectual Property Management Co., Ltd. Road condition management system and road condition management method
DE102010011093A1 (de) 2010-03-11 2011-09-15 Daimler Ag Verfahren zur Bestimmung einer Fahrzeugaufbaubewegung
DE102010013339A1 (de) 2010-03-30 2011-01-05 Daimler Ag Vorrichtung und Verfahren zur Steuerung eines Motorlagers für ein Fahrzeug
JP2011254590A (ja) * 2010-05-31 2011-12-15 Nobuyoshi Muto 電気自動車およびプログラム
DE102010020688A1 (de) 2010-05-15 2011-05-19 Daimler Ag Verfahren zur Bestimmung eines Fahrspurverlaufs für ein Fahrzeug
DE102010045162A1 (de) 2010-09-11 2012-03-15 Volkswagen Ag Schlaglochassistent mit Umfeldwahrnehmung
JP2012066785A (ja) 2010-09-27 2012-04-05 Fuji Heavy Ind Ltd 車両の統合制御装置
DE102010063017A1 (de) * 2010-12-14 2012-06-14 Robert Bosch Gmbh Verfahren in einem Fahrerassistenzsystem zur Erkennung von Nässe auf einer Fahrbahn
US8957949B2 (en) 2011-02-14 2015-02-17 Conti Temic Microelectronic Gmbh Estimation of coefficients of friction using a 3-D camera
DE102011011755A1 (de) 2011-02-18 2012-08-23 Conti Temic Microelectronic Gmbh Halbleiterschaltkreis und Verfahren in einem Sicherheitskonzept zum Einsatz in einem Kraftfahrzeug
WO2012117044A2 (fr) 2011-03-01 2012-09-07 Continental Teves Ag & Co. Ohg Procédé et dispositif de prédiction et d'adaptation de trajectoires de déplacement de véhicules automobiles
WO2012117057A1 (fr) 2011-03-01 2012-09-07 Continental Teves Ag & Co. Ohg Dispositif de sécurité pour véhicule automobile et procédé permettant de faire fonctionner un véhicule automobile
DE102012203673A1 (de) 2011-03-09 2012-10-04 Continental Teves Ag & Co. Ohg Sicherheitsvorrichtung für ein Kraftfahrzeug und Verfahren zum Betrieb eines Kraftfahrzeugs
DE102011100907A1 (de) 2011-05-09 2012-01-12 Daimler Ag Vorrichtung und Verfahren zur Ermittlung eines Fahrbahnzustands
KR20130005107A (ko) 2011-07-05 2013-01-15 현대자동차주식회사 차간거리 자동 가변 시스템 및 그 방법
US10081308B2 (en) 2011-07-08 2018-09-25 Bendix Commercial Vehicle Systems Llc Image-based vehicle detection and distance measuring method and apparatus
GB2492953A (en) * 2011-07-13 2013-01-23 Land Rover Uk Ltd Vehicle control system and method employing output from an imaging device
DE102011081362A1 (de) * 2011-08-23 2013-02-28 Robert Bosch Gmbh Verfahren und Vorrichtung zur Ermittlung eines Oberflächenzustands einer von einem Fahrzeug befahrenen oder zu befahrenden Fahrbahn
DE102011056671A1 (de) 2011-12-20 2013-06-20 Conti Temic Microelectronic Gmbh Bestimmung eines Höhenprofils einer Fahrzeugumgebung mittels einer 3D-Kamera
DE102012201896A1 (de) * 2012-02-09 2013-08-14 Robert Bosch Gmbh Fahrerassistenzverfahren und Fahrerassistenzsystem für verschneite Straßen
DE102012101085A1 (de) 2012-02-10 2013-08-14 Conti Temic Microelectronic Gmbh Bestimmung einer Beschaffenheit einer Fahrbahnoberfläche mittels einer 3D-Kamera
JP2013213793A (ja) * 2012-04-04 2013-10-17 Toyota Motor Corp 路面状態推定装置およびその推定結果を利用する車両制御装置
EP2852831A4 (fr) 2012-05-23 2016-04-20 Raqib Omer Procédé et système de classification de conditions de surface de roulement
DE102012221518A1 (de) 2012-11-26 2014-05-28 Robert Bosch Gmbh Verfahren zur Ermittlung der Straßenglätte in einem Fahrzeug
DE102012024874B4 (de) 2012-12-19 2014-07-10 Audi Ag Verfahren und Vorrichtung zum prädikativen Ermitteln eines Parameterwertes einer von einem Fahrzeug befahrbaren Oberfläche
DE102012112724A1 (de) 2012-12-20 2014-06-26 Continental Teves Ag & Co. Ohg Verfahren zur Bestimmung eines Fahrbahnzustands aus Umfeldsensordaten
DE102012112725A1 (de) 2012-12-20 2014-06-26 Continental Teves Ag & Co. Ohg Reibwertschätzung aus Kamera- und Raddrehzahldaten
US8788146B1 (en) 2013-01-08 2014-07-22 Ford Global Technologies, Llc Adaptive active suspension system with road preview
DE102013002333A1 (de) 2013-02-12 2014-08-14 Continental Teves Ag & Co. Ohg Verfahren und Strahlensensormodul zur vorausschauenden Straßenzustandsbestimmung in einem Fahrzeug
DE102013101639A1 (de) 2013-02-19 2014-09-04 Continental Teves Ag & Co. Ohg Verfahren und Vorrichtung zur Bestimmung eines Fahrbahnzustands
US9187099B2 (en) 2013-10-17 2015-11-17 Richard M. Powers Systems and methods for predicting weather performance for a vehicle
DE102013113431A1 (de) 2013-12-04 2015-06-11 Dr. Ing. H.C. F. Porsche Aktiengesellschaft Bestimmen einer Aquaplaning-Gefahr
US9434388B2 (en) 2014-10-31 2016-09-06 GM Global Technology Operations LLC Surface estimation for vehicles
DE102016009928A1 (de) 2016-08-16 2017-02-02 Daimler Ag Verfahren zum Erfassen von Nässe auf einer Fahrbahn

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
None *
See also references of WO2015070861A1 *

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
DE102022211241A1 (de) 2022-10-24 2024-04-25 Continental Autonomous Mobility Germany GmbH Erkennen von Fahrbahnauflage auf einer Fahrbahn
WO2024088484A1 (fr) 2022-10-24 2024-05-02 Continental Autonomous Mobility Germany GmbH Reconnaissance d'un revêtement de chaussée sur une chaussée

Also Published As

Publication number Publication date
WO2015070861A1 (fr) 2015-05-21
US10289920B2 (en) 2019-05-14
DE112014002376A5 (de) 2016-03-31
JP2017503715A (ja) 2017-02-02
US20160379065A1 (en) 2016-12-29
DE102013223367A1 (de) 2015-05-21

Similar Documents

Publication Publication Date Title
EP3069296A1 (fr) Procédé et dispositif de détermination d'un état d'une voie de circulation au moyen d'un système de caméra de véhicule
EP2675685B1 (fr) Estimation de valeur de frottement au moyen d'une caméra 3d
DE102005044486B4 (de) Verfahren zur Detektion des Oberflächenzustands einer Fahrbahn, sowie Detektionssystem und Fahrerassistenzsystem zur Umsetzung des Verfahrens
WO2019174682A1 (fr) Procédé et dispositif de détection et d'évaluation des états de voie de circulation et des influences environnementales météorologiques
DE102012101085A1 (de) Bestimmung einer Beschaffenheit einer Fahrbahnoberfläche mittels einer 3D-Kamera
DE102009041566B4 (de) Verfahren zur Klassifizierung des Fahrbahnreibwerts
DE102013112459B4 (de) Vorrichtung und Verfahren zum Beurteilen einer Wahrscheinlichkeit einer Kollision zwischen einem Fahrzeug und einem Ziel, Fahrzeugkollisionsvermeidungssystem, und Verfahren zum Vermeiden einer Kollision zwischen einem Fahrzeug und einem Ziel
WO2014094767A1 (fr) Estimation d'un coefficient de frottement sur la base de données de caméra et de données de nombre de tours d'une roue
DE102014201159A1 (de) Verfahren und Vorrichtung zum Klassifizieren eines Verhaltens eines Fußgängers beim Überqueren einer Fahrbahn eines Fahrzeugs sowie Personenschutzsystem eines Fahrzeugs
WO2014094766A1 (fr) Procédé pour déterminer un état de la chaussée à partir de données de capteurs de l'environnement
DE102011056671A1 (de) Bestimmung eines Höhenprofils einer Fahrzeugumgebung mittels einer 3D-Kamera
DE102012201896A1 (de) Fahrerassistenzverfahren und Fahrerassistenzsystem für verschneite Straßen
WO2013083313A1 (fr) Procédé et dispositif permettant d'identifier une situation de freinage
DE102008020007A1 (de) Verfahren zum Unterstützen eines Fahrers beim Fahren mit einem Fahrzeug mit einer Fahrspurerkennung
DE102013013243A1 (de) Fahrerassistenzsystem und Betriebsverfahren für ein Fahrerassistenzsystem zur Fahrzeug-Längsregelung
DE102013013232A1 (de) Fahrerassistenzsystem und Betriebsverfahren für ein Fahrerassistenzsystem zur Fahrzeug-Längslenkung
DE102013013242A1 (de) Fahrerassistenzsystem und Betriebsverfahren für ein Fahrerassistenzsystem zur Fahrzeug-Längsregelung
DE102017223439A1 (de) Warnvorrichtung vor Gefahrensituationen für ein Kraftfahrzeug
WO2014090247A1 (fr) Détection basée sur la vidéo d'obstacles sur une voie de roulement
DE102013013233A1 (de) Fahrerassistenzsystem und Betriebsverfahren für ein Fahrerassistenzsystem zur Fahrzeug-Längsregelung
DE102016221591A1 (de) Verfahren und Vorrichtung zur Bewertung eines Fahrbahnzustands und Fahrerassistenzsystem
WO2013026599A1 (fr) Procédé et dispositif de détection d'objets perturbateurs dans l'environnement d'un véhicule
DE102020005754B3 (de) Verfahren zum Betrieb eines automatisiert fahrenden Fahrzeugs
DE102019000434A1 (de) Hinderniserfassungsvorrichtung für ein Fahrzeug sowie Verfahren zum Ausweichen eines Hindernisses für ein Fahrzeug
DE102020131127A1 (de) Verfahren zum betreiben eines fahrzeugs, computerprogrammprodukt, steuervorrichtung und fahrzeug

Legal Events

Date Code Title Description
PUAI Public reference made under article 153(3) epc to a published international application that has entered the european phase

Free format text: ORIGINAL CODE: 0009012

17P Request for examination filed

Effective date: 20160615

AK Designated contracting states

Kind code of ref document: A1

Designated state(s): AL AT BE BG CH CY CZ DE DK EE ES FI FR GB GR HR HU IE IS IT LI LT LU LV MC MK MT NL NO PL PT RO RS SE SI SK SM TR

AX Request for extension of the european patent

Extension state: BA ME

DAX Request for extension of the european patent (deleted)
RAP1 Party data changed (applicant data changed or rights of an application transferred)

Owner name: CONTINENTAL TEVES AG & CO. OHG

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: EXAMINATION IS IN PROGRESS

17Q First examination report despatched

Effective date: 20200420

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: EXAMINATION IS IN PROGRESS

STAA Information on the status of an ep patent application or granted ep patent

Free format text: STATUS: THE APPLICATION HAS BEEN WITHDRAWN

18W Application withdrawn

Effective date: 20220411