DE102018205528A1 - Overtime assistance system for motor vehicles - Google Patents

Abstract

Overtime assistance system of a motor vehicle with a speed measuring device, a detection device comprising at least one sensor for detecting vehicles ahead, their type, their speed and distance, a comparison and decision unit for comparing the own speed and those of the preceding vehicle and deciding whether to overtake the vehicle in front, wherein the distance, the speeds and the vehicle type are incorporated, wherein the preceding vehicle detection device is adapted to perform an object detection based on the sensor data of the at least one sensor, wherein the object recognition a comparison with data from agricultural machinery and Performs special vehicles, which are included in a corresponding database, and is arranged to use the data of the detected object to determine how the loading z and / or the weight distribution and / or the movements of the agricultural machine or of the special vehicle, and a road condition prediction unit that is set up to create a road condition prediction based on weather data, and that the comparison and decision unit is set up to perform the object recognition to take into account the loading condition and / or the weight distribution and / or the movements of the agricultural machine or the special vehicle as well as the road condition forecast.

Description

The invention relates to an overtaking assistance system of a motor vehicle, in particular a car or minivan, with a speed measuring device for determining one's own speed, a detection device for vehicles in front comprising at least one sensor for detecting preceding vehicles, their type, their speed and distance, a comparison and decision unit for comparing the own speed and that of the preceding vehicle as well as for deciding whether overtaking of the preceding vehicle is safely possible, wherein the distance, the speeds and the vehicle type are included.

It is known in modern motor vehicles, especially in cars and minivans to use assistance systems for driver assistance. In addition to a variety of assistance systems, such as lane assistants, trailer assistants, etc., overtaking assistants are also known which support and guide driving during the overtaking process.

For example, the US 2016/272204 A1 a driving control device that performs an overhauling. It includes a preceding vehicle information acquiring unit configured to obtain information about a preceding vehicle with respect to a preceding vehicle speed; a determining unit configured to determine an accuracy of the passing control based on a driving environment; an overtaking vehicle speed calculating unit configured to calculate an overtaking vehicle speed of an own vehicle based on the information about a preceding vehicle in response to a determination by the determining unit that the overtaking control is possible; and a driving control unit configured to execute the passing control using the overtaking vehicle speed, wherein the overtaking vehicle speed calculating unit is configured to calculate a passing vehicle speed faster than a preceding vehicle speed and in the one speed difference with respect to the preceding vehicle speed a predetermined speed difference is going to charge.

US 9,682,712 B2 A1 discloses a car overtaking assistance system for notifying a driver of whether his host vehicle is allowed to overtake a first vehicle traveling in a slow lane in front of the host vehicle when the host vehicle is also traveling in the slow lane. The overtaking assistance system includes a speed detector configured to detect a speed of the host vehicle, a preceding vehicle detector configured to detect relative distances and relative speeds of the first vehicle and a second vehicle, the second vehicle in a fast lane and in front of the host vehicle, a speed comparison unit configured to compare the speeds of the first and second vehicles, and an overtake decision unit configured to determine whether the host vehicle is the first vehicle may overtake when the speed of the host vehicle is higher than the speed of the first vehicle and the speed of the second vehicle is higher than the speed of the first vehicle, and a notification unit configured to respond to the driving Of the carrier vehicle notifies that the host vehicle may overtake the first vehicle when the overtaking decision unit determines that the host vehicle may overtake the first vehicle. The assistance system uses a forward camera to detect preceding vehicles and their type from the recorded image data.

Sometimes, however, it is very difficult for a driver to estimate the distance to be maintained and the distance traveled to overtake an agricultural machine such as tractors, tedders, cultivators, plows, harrows, slurry tank trailers, etc., and also e.g. due to the multi-dimensional design of the machines, increased non-linear size and width, and in part "snake-line" handling due to high unsprung masses and associated negative resonance effects on the vehicle body. In addition, there is often not good visibility on the routes of agricultural machinery and a narrowed lane through overhangs.

For example, agricultural machinery may vary in size as an obstacle and may extend beyond the normal gauge when loaded. So it may be necessary to dodge the edge of the road to overtake, but could be unpaved, formed with a trough, etc.

In addition, unfavorable weather conditions or darkness may occur, with agricultural vehicles often not well lit.

There is therefore still the need for an improved overtake assistance system, which takes particular account of agricultural machinery or special vehicles.

This object is achieved by the overtaking assistance system specified in claim 1. Advantageous embodiments will become apparent from the dependent claims and the description.

According to the invention, it has been recognized that when the preceding vehicle recognition device is arranged to perform object recognition based on the sensor data of the at least one sensor, the object recognition compares with data of agricultural machines and special vehicles included in a corresponding database, and arranged to determine, by means of the data of the recognized object or agricultural machine or special vehicle, how the loading state and / or the weight distribution and / or the movements of the agricultural machine or the special vehicle are, and a road condition prediction unit which is set up, in order to compile a road condition prediction based on weather data, and in that the comparison and decision unit is set up to perform the object recognition, the load state and / or the weight distribution and / or the movements of the vehicle agricultural machinery or the special vehicle, as well as the road condition prediction, it is possible to allow drivers or drivers a safe overtaking of agricultural machinery or special vehicles, even if the environmental conditions are unfavorable. In addition, inexperienced or insecure drivers can be guided and assisted in overtaking, which increases traffic safety.

In other words, by means of database-supported object recognition, a preceding agricultural machine or special vehicle is recognized and its loading state (loaded, unloaded, overloaded, etc.) as well as the weight distribution of the load (central, lateral, overhanging, etc.) determined, in order then to use this information and the vehicle speeds of the own vehicle and the agricultural machine or the special vehicle and the weather data-based road condition prediction (wet slippery road, muddy road, etc.) the driver specified whether an overtaking operation is possible or not. Should this be possible, the driver is instructed via displays, steering wheel feedback, etc., what an optimized vehicle path for overtaking the agricultural machine or the special vehicle looks like.

As special vehicles, e.g. Military vehicles, tree rails, cranes, etc. understood. These may e.g. Also identified by the appropriate license plate (green license plate) or speed limits, as well of course, on the object recognition (concise shaping).

Therefore, the overtaking assistance system according to the invention is preferably set up in order to display or predetermine an optimal driving path for the driver and / or to intervene in the steering process in a corrective or predetermining manner. This can be z. B. by means of existing in the vehicle displays, lights, steering wheel shake, etc. are performed. It can also be provided that the overtaking process is carried out automatically.

Sensor data and / or data stored in a navigation system can also be used in the release and determination of the overtaking process in order to determine whether the passing lane is free. This can be done card-based. Real-time data from the sensors can also be used. It is also possible to integrate data from connected systems.

Thus, the overtaking assistance system can use data from multiple sensor sources by means of data fusion to create the most complete situation image, the sensor sources include one or more sources selected from the group consisting of front camera, front radar sensor, ultrasonic sensors, Lidarsensor, mobile devices (such as own mobile phones or tablets etc .), Dashcam, Car2Car sensors of other vehicles in front. In principle, any device which can generate suitable data is suitable as a data source, e.g. Both sensors on or in your own vehicle as well as third-party sensors. Infrastructure sensors, stationary or mobile or temporary sensors can also be used.

• - durch parkende Fahrzeuge eingeschränkt ist, und/oder
• - durch eine Baustelle eingeschränkt ist, und/oder
• - durch Lieferfahrzeuge, Müllfahrzeuge, Straßenreinigungsfahrzeuge eingeschränkt ist, und/oder
• - durch Gegenverkehr eingeschränkt ist, und/oder
• - durch außermittig fahrende Fahrzeuge eingeschränkt ist, und/oder
• - durch ungewöhnliche Kreuzungsausgestaltungen eingeschränkt ist und/oder
• - wie die Seitenstreifenbeschaffenheit (Oberfläche, befahrbar, Mulde, Winkel etc.) ist, und/oder
• - wie die Randsteinbeschaffenheit (vorhanden, Höhe, Winkel etc.) ist.

Furthermore, the overtake assistance system can be set up to determine from the sensor data and / or from data provided by a data system (eg from the Internet, online traffic data, or from other vehicles by means of Car2Car communication etc.) whether the passing lane is passable for overtaking or whether evasion on the side strip is necessary and safe, using data from multiple sensor sources by means of data fusion to create the most complete situation image, the data being used to determine whether the passing lane or the own lane

• - is restricted by parked vehicles, and / or
• - is restricted by a construction site, and / or
• - is restricted by delivery vehicles, refuse collection vehicles, road cleaning vehicles, and / or
• - is restricted by oncoming traffic, and / or
• - is restricted by vehicles driving off-center, and / or
• - is limited by unusual crossing configurations and / or
• - how the side stripe nature (surface, passable, trough, angle, etc.) is, and / or
• - like the curb texture (available, height, angle etc.).

Also, the road condition prediction unit may be configured to determine from the sensor data and / or from data provided by a data system (eg, from the Internet, online traffic data, or from other vehicles by Car2Car communication, etc.) the road condition into the possibilities of considering the overtaking process. Thus, e.g. in rainy weather a longer acceleration phase can be taken into account.

It is also possible that the system is set up to determine, from the sensor data and / or from data provided by a data system, whether the agricultural machine or the special vehicle can detect specific tires and their condition, e.g. whether balloon tires of the recognized agricultural machine or the special vehicle could have a negative impact on the overtaking process, as these are dirty and so the roadway could also be muddy.

It is preferred if this is set up with an artificial intelligence and / or machine learning module in order to process the sensor data and / or the data provided by a data system. Preferably, an AI based on artificial neural networks is used. The machine learning module can learn both unsupervised or supervised, whereby the module can learn from successful overtaking processes automatically or by input of the driver can learn whether an overtaking process was good or bad.

The overtaking assistance system according to the invention thus combines real-time data processing with object and pattern recognition and artificial intelligence for decision-making in order to determine from the sensor data and / or from data provided by a data system whether overtaking of the vehicle in front is possible without danger and then with the driver To guide an optimized route or even automatically take over the entire overtaking process.

In a first step, the system thus checks the current route and calculates the route for overtaking and takes into account detected or possible obstacles (known from historical data, current database, via C2C communication or C2I communication) or lane disturbances using all available ( Data fusion) sensor data together with dynamic models of the agricultural machine and own vehicle.

An essential difference to known solutions is that the invention uses a real shape model of the agricultural machine and no lane markings are used as a reference for the roadway prediction. Instead, real-time data, e.g. used by the camera and supported cards as reference orientation signals and additional data to support the determination.

It uses real-time data processing, some pattern-matching technologies (comparing unknown objects with farm machinery databases), and decision algorithm AI. This information is fed back to the driver at a man-machine interface (HMI), indicating to the driver the most adapted fast lane. It is thus indicated to the driver how he has to control on the lane when overtaking.

If e.g. If an obstacle is detected, the device guides the driver (visual assistance, steering assistance) to an optimized (safety, maximum distance, etc.) precalculated path to avoid any danger situation due to own vehicle speed, oncoming vehicle speed or static obstacle such as vehicle speed. Parking or service vehicle to avoid.

The system could also advise the driver to drive slower, steer right or left, including speed changes, stop, brake, manually or automatically retract the exterior mirrors, give adequate signaling (horn / beam) towards traffic or the curb to use.

In all of these operations, the driver could be instructed to take corrective action by a power steering device or this could take corrective action to move the vehicle to the calculated optimal path to avoid hazards or similar situations and reduce speed when needed by the system ,

In summary, the invention aims to avoid possible damage to the own vehicle and also to avoid a risk situation for other road users in overtaking maneuvers of agricultural machinery. Also in the near future, the invention could be used to support daily driving with autonomous vehicles.

• 1 ein schematisches Blockschaltbild eines Überholassistenzsystems und
• 2 eine schematische Draufsicht auf eine beispielhafte Überholsituation.

Further details of the invention will become apparent from the following description of an embodiment with reference to the drawing, in which

• 1 a schematic block diagram of a passing-through assistance system and
• 2 a schematic plan view of an exemplary Überholsituation.

In 1 is a block diagram of a designated as a whole by 1 overtake assistance system a car shown.

The overtaking assistance system 1 includes a speed measuring device 2 for determining the own speed, a recognition device 3 for vehicles in front comprising a front camera 4 and a front radar sensor 5 for detecting vehicles in front.

The recognition device 3 also has an object recognition 6 based on the image data of the front camera 4 on, with the object recognition 6 performs a comparison with data from agricultural machinery, which is in a corresponding database 7 are included, so their type, their speed and distance, and the loading state, the weight distribution and the movements of the agricultural machine in a determination unit 8th to be determined by AI application and data fusion.

The overtaking assistance system 1 also includes a comparison and decision unit 10 for comparing the own speed and that of the preceding vehicle as well as for deciding whether overtaking of the preceding vehicle is safely possible, wherein the distance, the speeds and the vehicle type are included.

The overtaking assistance system 1 also includes a road condition prediction unit 9 , which is set up to generate a road condition forecast based on weather data.

The comparison and decision unit 10 is set up to the results of the determination unit 8th and the road condition forecast 9 to take into account.

The result will be on a display to the driver 11 displayed at the same time the system suggests the driver an optimal track.

In addition, flow from a navigation system 12 Data in the comparison and decision unit 10 to determine if the passing lane is clear.

In the determination unit 8th is taken from the sensor data of the front camera 4 and the radar 5 as well as from the navigation data determines whether an evasion of the shoulder is necessary and safe, whereby the data are processed by means of data fusion to create the most complete situation image.

This takes into account whether from the camera or radar data 4 . 5 It is recognized that the passing lane or own lane is limited by parked vehicles or by a construction site or by delivery vehicles, refuse collection vehicles, road cleaning vehicles, etc. By means of the sensor data is of course also checked whether oncoming traffic meets on the passing lane or whether the passing lane is limited by off-center vehicles. Also considered are unusual intersection designs as they result from the map data of the navigation system 12 and if it is a curb or if so, how is this and whether it can be run over.

The system 1 then performs in the determination unit 8th and comparison and decision unit 10 the results together and ultimately determined under real-time data processing with artificial intelligence whether overhauling the vehicle ahead is safely possible and which path is possibly optimal. The result will then be on the screen for the driver 11 displayed.

Based on 2 the decision process should be visualized.

On a country road L with one lane each F1 , and an oncoming lane F2 , each with a fortified side strip S1 respectively. S2 have, drive in succession, a first leading car 300 , a hay bale transporter 200 and behind it a car that wants to overtake 100 ,

With its camera and radar data is a detection of hay bales 200 carried out and recognized that this is slow driving, heavily loaded, with the charge in the direction of travel overhangs to the left, so that a greater distance would be to keep in overtaking. Of course, your own speed and the one will of hay bales transporter 200 determined and compared.

From a Car2Car communication over the internet I with the car in front 300 , knows the overtaking assistance system of the car 100 that a preceding car 300 in front of the hay bale transporter 200 drives and that in front of this a bigger pothole H in the road surface of the carriageway F1 lies. Also, the Car2Car communication and the navigation data reveal that the roadway F1 go straight without curves for a long time and that no vehicles will meet.

The own camera and radar data also state that the oncoming lane F2 to overtake would be free.

The AI-supported decision unit of the overtake assistance system can thus decide on a passing process. In the present case, this seems possible, taking on the sidelines S2 the oncoming lane F2 would partially evade to the overhang of hay bales 200 compensate or maintain a sufficient distance.

The decision unit draws weather data from the Internet I approach, after which the road is dry and the shoulder S2 thus should also be passable.

Due to the knowledge of the preceding car 300 and the pothole H Therefore, the AI-assisted decision unit suggests driving to overtake, which is partly on the shoulder S2 and past the hay bale transporter 200 as well as passing the car in front 300 and only a pruning behind the pothole H provides. It is also proposed a slightly higher speed or acceleration, since the overtaking is long.

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

• US 2016272204 A1 [0003]
• US 9682712 B2 [0004]

Claims (9)

Overtime assistance system of a motor vehicle, in particular car or minivan, with a speed measuring device for determining the own speed, a detection device for preceding vehicles comprising at least one sensor for detecting preceding vehicles, their type, their speed and distance, a comparison and decision unit for comparing their own Speed and that of the preceding vehicle and for deciding whether overtaking of the preceding vehicle is safely possible, wherein the distance, the speeds and the vehicle type are incorporated, characterized in that the detection device is arranged for preceding vehicles to an object detection based on the sensor data the at least one sensor, wherein the object recognition performs a comparison with data from agricultural machinery and special vehicles, which corresponds in one DB = EPODOC & ... PN = EP0354351 and the data base are arranged to determine, using the data of the detected object or agricultural machine, what the loading state and / or the weight distribution and / or the movements of the agricultural machine or the special vehicle are, and a road condition prediction unit that comprises is arranged to generate a road condition prediction based on weather data, and that the comparison and decision unit is arranged to take into account the object recognition, the load state and / or the weight distribution and / or the movements of the agricultural machine or the special vehicle and the road condition prediction. Overtime assistance system after Claim 1 , characterized in that the system is set up in order to display or predetermine an optimum driving path for the driver and / or to intervene in the steering process in a corrective or predetermining manner. Overtime assistance system after Claim 1 or 2 , characterized in that the system is adapted to determine from the sensor data and / or data stored in a navigation system, whether the passing lane is free. Overtaking assistance system according to one of the preceding claims, characterized in that the system uses data from multiple sensor sources by means of data fusion to create a complete situation image, wherein the sensor sources comprise one or more sources selected from the group comprising the front camera, front radar sensor, ultrasonic sensors, Lidarsensor , Mobile device, dashcam, Car2Car sensors of other vehicles in front and other sensors on or in their own vehicle as well as third-party sensors or infrastructure sensors that are stationary or mobile or temporary sensors. Overtaking assistance system according to one of the preceding claims, characterized in that the system is set up to determine from the sensor data and / or data provided by a data system, whether the passing lane is passable to overtake or if avoiding the side stripes necessary and safe using data from a plurality of sensor sources by means of data fusion in order to create as complete a situation image as possible, from which data it is determined whether the passing lane or own lane is restricted by parked vehicles and / or is restricted by a construction site, and / or - is restricted by delivery vehicles, refuse vehicles, street cleaning vehicles, and / or - restricted by oncoming traffic, and / or - is restricted by off-board vehicles, and / or - is limited by unusual intersection designs and / or - like the Seitenstreifenbe Creativity is, and / or - as is the curb texture. Overtaking assistance system according to one of the preceding claims, characterized in that the road condition prediction unit is adapted to determine from the sensor data and / or data provided by a data system, which is the road condition Overtaking assistance system according to one of the preceding claims, characterized in that the system is set up to determine from the sensor data and / or provided by a data system data, whether the agricultural machine or the special vehicle has a special tires and to detect their condition. Overtaking assistance system according to one of the preceding claims, characterized in that the system is set up with an artificial intelligence and / or machine learning module to process the sensor data and / or provided by a data system data, in particular based on artificial neural networks. Overtaking assistance system according to one of the preceding claims, characterized in that the system real-time data processing with Object and pattern recognition and combined with artificial intelligence for decision making to determine based on the sensor data and / or from data provided by a data system, whether overhauling the preceding vehicle is safely possible.

Images