SE537184C2 - Method and system for controlling autonomous vehicles - Google Patents
Method and system for controlling autonomous vehicles Download PDFInfo
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- SE537184C2 SE537184C2 SE1350329A SE1350329A SE537184C2 SE 537184 C2 SE537184 C2 SE 537184C2 SE 1350329 A SE1350329 A SE 1350329A SE 1350329 A SE1350329 A SE 1350329A SE 537184 C2 SE537184 C2 SE 537184C2
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- 238000004458 analytical method Methods 0.000 claims abstract description 113
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- 238000004590 computer program Methods 0.000 claims description 11
- 230000003993 interaction Effects 0.000 claims description 9
- 238000007726 management method Methods 0.000 claims description 8
- 230000001276 controlling effect Effects 0.000 abstract description 5
- 230000001105 regulatory effect Effects 0.000 abstract description 5
- 238000004891 communication Methods 0.000 description 8
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- 230000008859 change Effects 0.000 description 5
- 230000032258 transport Effects 0.000 description 4
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- 238000005516 engineering process Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 2
- 238000005065 mining Methods 0.000 description 2
- 238000012544 monitoring process Methods 0.000 description 2
- 230000008447 perception Effects 0.000 description 2
- 238000013439 planning Methods 0.000 description 2
- 230000007123 defense Effects 0.000 description 1
- 230000001419 dependent effect Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B62—LAND VEHICLES FOR TRAVELLING OTHERWISE THAN ON RAILS
- B62D—MOTOR VEHICLES; TRAILERS
- B62D1/00—Steering controls, i.e. means for initiating a change of direction of the vehicle
- B62D1/24—Steering controls, i.e. means for initiating a change of direction of the vehicle not vehicle-mounted
- B62D1/28—Steering controls, i.e. means for initiating a change of direction of the vehicle not vehicle-mounted non-mechanical, e.g. following a line or other known markers
- B62D1/283—Steering controls, i.e. means for initiating a change of direction of the vehicle not vehicle-mounted non-mechanical, e.g. following a line or other known markers for unmanned vehicles
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/02—Control of position or course in two dimensions
- G05D1/021—Control of position or course in two dimensions specially adapted to land vehicles
- G05D1/0287—Control of position or course in two dimensions specially adapted to land vehicles involving a plurality of land vehicles, e.g. fleet or convoy travelling
- G05D1/0291—Fleet control
- G05D1/0297—Fleet control by controlling means in a control room
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0011—Planning or execution of driving tasks involving control alternatives for a single driving scenario, e.g. planning several paths to avoid obstacles
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0015—Planning or execution of driving tasks specially adapted for safety
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- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W60/00—Drive control systems specially adapted for autonomous road vehicles
- B60W60/001—Planning or execution of driving tasks
- B60W60/0027—Planning or execution of driving tasks using trajectory prediction for other traffic participants
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/60—Intended control result
- G05D1/646—Following a predefined trajectory, e.g. a line marked on the floor or a flight path
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D1/00—Control of position, course, altitude or attitude of land, water, air or space vehicles, e.g. using automatic pilots
- G05D1/60—Intended control result
- G05D1/69—Coordinated control of the position or course of two or more vehicles
- G05D1/692—Coordinated control of the position or course of two or more vehicles involving a plurality of disparate vehicles
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B60—VEHICLES IN GENERAL
- B60W—CONJOINT CONTROL OF VEHICLE SUB-UNITS OF DIFFERENT TYPE OR DIFFERENT FUNCTION; CONTROL SYSTEMS SPECIALLY ADAPTED FOR HYBRID VEHICLES; ROAD VEHICLE DRIVE CONTROL SYSTEMS FOR PURPOSES NOT RELATED TO THE CONTROL OF A PARTICULAR SUB-UNIT
- B60W2555/00—Input parameters relating to exterior conditions, not covered by groups B60W2552/00, B60W2554/00
- B60W2555/60—Traffic rules, e.g. speed limits or right of way
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05D—SYSTEMS FOR CONTROLLING OR REGULATING NON-ELECTRIC VARIABLES
- G05D2101/00—Details of software or hardware architectures used for the control of position
- G05D2101/10—Details of software or hardware architectures used for the control of position using artificial intelligence [AI] techniques
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- Engineering & Computer Science (AREA)
- Automation & Control Theory (AREA)
- Mechanical Engineering (AREA)
- Transportation (AREA)
- Radar, Positioning & Navigation (AREA)
- Aviation & Aerospace Engineering (AREA)
- Human Computer Interaction (AREA)
- Remote Sensing (AREA)
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Abstract
537 184 Sammandrao Uppfinningen hanfor sig till ett system for att reglera ett autonomt fordon i ett trafiksystem innefattande ett flertal autonoma fordon. Systemet analyserar extern information enligt farutbestamda regler och genererar analyssignaler till fordonet som ges olika prioritet beroende pa vilken analys som utfOrts och resultatet av analysen. En sammanvagd analyssignal Sx bestams baserat pa analyssignalernas innehall samt deras prioritering. Fordonet kan sedan anpassa sin reglering efter den sammanvagda analyssignalen S. Uppfinningen hanfor sig aven till en metod for att reglera ett autonomt fordon i ett trafiksystem innefattande ett flertal autonoma fordon. The invention relates to a system for regulating an autonomous vehicle in a traffic system comprising a plurality of autonomous vehicles. The system analyzes external information according to pre-determined rules and generates analysis signals to the vehicle which are given different priority depending on which analysis has been performed and the result of the analysis. A weighted analysis signal Sx is determined based on the content of the analysis signals and their prioritization. The vehicle can then adapt its control to the interleaved analysis signal S. The invention also relates to a method for controlling an autonomous vehicle in a traffic system comprising a plurality of autonomous vehicles.
Description
537 184 Metod och system far styrning av autonoma fordon Uppfinningens omrade Foreliggande uppf inning avser teknik far att hantera olika situationer i trafiksystem som innefattar ett flertal autonoma fordon. 537 184 Method and system for controlling autonomous vehicles Field of the invention The present invention relates to technology for handling various situations in traffic systems which comprise a plurality of autonomous vehicles.
Bakgrund till uppfinningen Ett fordon som kan framfaras utan farare pa marken kallas ett fararlast markgaende fordon (Eng. Unmanned ground vehicle; UGV). Det finns tva. typer 10 av forarlosa markgdende fordon, de som fjarrstyrs och de som är autonoma. Background of the Invention A vehicle that can be driven without a driver on the ground is called an unmanned ground vehicle (UGV). There are two. types 10 of driverless ground-moving vehicles, those that are remotely controlled and those that are autonomous.
Ett fjarrstyrt UGV är ett fordon som regleras av en mansklig operator via en kommunikationslank. Alla atgdrder bestams av operataren baserat pa antingen direkt visuell observation eller med anvandning av sensorer sasom digitala videokameror. Ett enkelt exempel pa en fjarrstyrd UGV är en fjarrstyrd leksaksbil. A remote-controlled UGV is a vehicle that is regulated by a human operator via a communication link. All actions are determined by the operator based on either direct visual observation or with the use of sensors such as digital video cameras. A simple example of a remote-controlled UGV is a remote-controlled toy car.
Det finns en stor variation av fjarrstyrda fordon som anvands idag. Ofta anvands dessa fordon i farliga situationer och miljoer som är oldmpliga for manniskor att vistas i, till exempel for att desarmera bomber och vid farliga kemiska utsldpp. Fjarrstyrda forarlasa fordon anvands ocksâ i samband med overvakningsuppdrag och liknande. There is a wide variety of remote controlled vehicles in use today. These vehicles are often used in dangerous situations and environments that are unsuitable for people to live in, for example to disarm bombs and in the event of dangerous chemical spills. Remote-controlled driverless vehicles are also used in connection with monitoring assignments and the like.
Med ett autonomt fordon avses har ett fordon som ãr kapabelt att navigera och manavrera utan mansklig styrning. Fordonet anvander sensorer far att skaffa sig forstaelse for omgivningen. Sensordata anvands sedan av regleralgoritmer for att bestamma vad som är ndsta steg for fordonet att ta med hansyn till ett overordnat mai far fordonet, exempelvis att hamta och lamna gods vid olika positioner. Mera specifikt maste ett autonomt fordon kunna avlasa omgivningen tillrackligt bra far att kunna genomfora den uppgift som den blivit tilldelad, exempelvis "flytta stenblocken fran plats A till plats B via gruvgangen C". Det autonoma fordonet behover planera och folja en vag till den valda destinationen under det att den detekterar och undviker hinder pa vagen. Dessutom maste det autonoma fordonet genomfara sin uppgift sá fort som majligt utan att bega. misstag. Autonoma fordon 1 537 184 har bland annat utvecklats for att kunna anvdndas i farliga miljoer, exempelvis inom fOrsvars- och krigsindustrin och inom gruvindustrin, bade ovanjord och underjord. Om mdnniskor eller vanliga, manuellt styrda fordon ndrmar sig de autonoma fordonens arbetsomrade orsakar de normalt ett avbrott i arbete pa grund av sakerhetsskal. NI& arbetsomradet ater är fritt kan de autonoma fordonen beordras att ateruppta arbetet. By an autonomous vehicle is meant a vehicle that is capable of navigating and maneuvering without human control. The vehicle uses sensors to gain an understanding of the surroundings. Sensor data is then used by control algorithms to determine what is the next step for the vehicle to take into account a superior may the vehicle, for example to pick up and drop off goods at different positions. More specifically, an autonomous vehicle must be able to read the surroundings sufficiently well to be able to carry out the task assigned to it, for example "move the boulders from place A to place B via the mine passage C". The autonomous vehicle needs to plan and follow a road to the selected destination while detecting and avoiding obstacles on the road. In addition, the autonomous vehicle must carry out its task as quickly as possible without committing. mistake. Autonomous vehicles 1,537,184 have been developed to be used in dangerous environments, for example in the defense and war industry and in the mining industry, both above ground and underground. If people or ordinary, manually controlled vehicles change the working range of the autonomous vehicles, they normally cause a break in work due to safety concerns. NI & the work area is free again, the autonomous vehicles can be ordered to resume work.
Det autonoma fordonet anvander information avseende vdgen, omgivningen och andra aspekter som paverkar framfarten for att automatiskt reglera gaspadraget, bromsningen och styrningen. En noggrann bedOmning och identifiering av den planerade framfarten är nodvandig fOr att bedOma om en vag âr farbar och âr nOdvdndig for att pa ett framgangsrikt salt kunna ersalta en manniskas bedOmning när det gdller att framfora fordonet. VagfOrhallanden kan vara komplexa och vid kOrning av ett vanligt fOrarstyrt fordon gOr fOraren hundratals observationer per minut och justerar driften av fordonet baserat pa de uppfattade vagforhallandena fOr att exempelvis finna en framkomlig vag forbi objekt som kan finnas pa vdgen. For att kunna ersdtta den manskliga uppfattningsformagan med ett autonomt system innebdr det bland annat att pa ett exakt satt kunna uppfatta objekt for att effektivt kunna reglera fordonet sa att man styr forbi dessa objekt. The autonomous vehicle uses information regarding the road, the surroundings and other aspects that affect the progress to automatically regulate the throttle, braking and steering. An accurate assessment and identification of the planned progress is necessary to assess whether a road is passable and necessary in order to be able to salt a person's assessment on a successful salt when it comes to driving the vehicle. Road conditions can be complex and when driving a normal driver-controlled vehicle, the driver makes hundreds of observations per minute and adjusts the operation of the vehicle based on the perceived road conditions to, for example, find a passable road past objects that may be on the road. In order to be able to replace the human perception with an autonomous system, this means, among other things, being able to perceive objects in an exact way in order to be able to effectively regulate the vehicle so that one steers past these objects.
De tekniska metoder som anvands for att identifiera ett objekt i anslutning till fordonet innefattar bland annat att anvdnda en eller flera kameror och radar fOr att skapa bilder av omgivningen. Aven laserteknik anvands, bade avscannande lasrar och fasta lasrar, for att detektera objekt och mdta avstand. Dessa bendmns ofta LIDAR (Light Detection and Ranging) eller LADAR (Laser Detection and Ranging). Dessutom är fordonet forsett med olika sensorer bland annat for att avkanna hastighet och accelerationer i olika riktningar. Positioneringssystem och annan tradlos teknologi kan dessutom anvdndas fOr att bestamma om fordonet till exempel narmar sig en korsning, en avsmalning av vagen, och/eller andra fordon. The technical methods used to identify an object in connection with the vehicle include using one or more cameras and radar to create images of the surroundings. Laser technology is also used, both scanning lasers and fixed lasers, to detect objects and measure distance. These bends are often LIDAR (Light Detection and Ranging) or LADAR (Laser Detection and Ranging). In addition, the vehicle is equipped with various sensors, among other things to detect speed and accelerations in different directions. Positioning systems and other wireless technology can also be used to determine if the vehicle is approaching, for example, an intersection, a narrowing of the road, and / or other vehicles.
Vid anvdndande av autonoma fordon maste aven mdnniskans fOrmaga att folja bade trafikregler och trafikkultur emuleras av fordonens styrsystem. En f6rare av 2 537 184 ett vanligt fordon undviker exempelvis vanligtvis instinktivt en krock fOre det hailer hastighetsgranserna. Dagens autonoma fordons uppfattning om trafiken begransar sig normalt till "stanna om nagon kommer nara eller kommer in i mitt arbetsomrade". FOr att kunna ta hansyn till manga olika parametrar maste det autonoma fordonet veta vilka eller vilken parameter som är viktigast. When using autonomous vehicles, human ability to follow both traffic rules and traffic culture must be emulated by the vehicle's control system. A driver of a normal vehicle, for example, usually instinctively avoids a collision before it reaches the speed limits. Today's autonomous vehicle's perception of traffic is normally limited to "stop if someone comes near or enters my work area". In order to be able to take into account many different parameters, the autonomous vehicle must know which parameter or which parameter is most important.
I US-8103438-B2 beskrivs en metod och ett system fOr att automatiskt styra trafik pa ett arbetsomrade. Bemannande fordon tilldelas olika prioritet beroende till exempel pa vilken vag de Icor eller hur tunga de är. Vid konflikt sa jamfors fordonens prioriteter, och fordonet med lagre prioritet far ge vag at fordonet med hOgre prioritet. US-8103438-B2 describes a method and a system for automatically controlling traffic in a work area. Manning vehicles are assigned different priorities depending on, for example, how heavy they are or how heavy they are. In the event of a conflict, the vehicle's priorities will be compared, and the vehicle with lower priority will give way to the vehicle with higher priority.
I US-7979174-B2 visas automatisk planering och reglering av hastigheten hos autonoma fordon. Hastighetsplaneringen sker utifran ett antal begransningar med olika prioriteringar, t ex är det hogre prioriterat att undvika kollision an att fOlja hastighetsbegransningar. US-7979174-B2 discloses automatic speed planning and control of autonomous vehicles. Speed planning is based on a number of restrictions with different priorities, for example, it is a higher priority to avoid collisions than to follow speed restrictions.
For att ett helt transportsystem bestaende av manga autonoma fordon blandat med exempelvis manuellt styrda fordon och fotgangare ska kunna fungera langvarigt tillsammans, behovs fOrbattrade metoder for att ta hansyn till manga olika parametrar och uppdrag samtidigt som de autonoma fordonen pa effektivaste satt nar sina uppsatta mal. In order for a complete transport system consisting of many autonomous vehicles mixed with, for example, manually controlled vehicles and pedestrians to work together for a long time, improved methods are needed to take into account many different parameters and tasks while the autonomous vehicles more efficiently set their set goals.
Syftet med uppfinningen är sdledes att tillhandahalla en forbdttrad metod for att assistera ett autonomt fordon att fatta beslut da fordonet maste ta hansyn till ett flertal olika handelser. The object of the invention is thus to provide an improved method for assisting an autonomous vehicle in making decisions when the vehicle must take into account a number of different actions.
Sammanfattnino av uppfinningen Enligt en aspekt av uppfinningen uppnas syftet genom ett system for att reglera ett autonomt fordon i ett trafiksystem innefattande ett flertal autonoma fordon enligt det f6rsta oberoende kravet. Systemet analyserar extern information enligt fOrutbestamda regler och genererar analyssignaler till fordonet som ges olika 3 537 184 prioritet beroende pa vilken analys som utforts och resultatet av analysen. En sammanvagd analyssignal Sx bestams baserat pa analyssignalernas innehall samt deras prioritering. Fordonet kan anpassa sin reglering efter den sammanvagda analyssignalen S. SUMMARY OF THE INVENTION According to one aspect of the invention, the object is achieved by a system for regulating an autonomous vehicle in a traffic system comprising a plurality of autonomous vehicles according to the first independent claim. The system analyzes external information according to predetermined rules and generates analysis signals to the vehicle which are given different 3,537,184 priorities depending on the analysis performed and the result of the analysis. A weighted analysis signal Sx is determined based on the content of the analysis signals and their prioritization. The vehicle can adapt its regulation to the interleaved analysis signal S.
Genom systemet kan transporterna i systemet hela tiden utforas pa effektivaste sat inte bara genom att undvika kollisioner och fOlja trafikregler, utan genom att kontinuerligt se till att alla delar i transportsystemet samarbetar mot de mai som angivits. Det autonoma fordonet vet i varje situation hur den ska agera for att dess agerande ska vara sdkert och effektivt fOr hela trafiksystemet. Through the system, the transports in the system can always be carried out in the most efficient way, not only by avoiding collisions and following traffic rules, but by continuously ensuring that all parts of the transport system cooperate with those specified. The autonomous vehicle knows in each situation how to act in order for its action to be safe and effective for the entire traffic system.
Enligt en annan aspekt uppnds syftet genom en metod for att reglera ett autonomt fordon i ett trafiksystem innefattande ett flertal autonoma fordon. According to another aspect, the purpose is achieved by a method for regulating an autonomous vehicle in a traffic system comprising a plurality of autonomous vehicles.
Enligt en tredje aspekt uppnas syftet med en datorprogramprodukt som innefattar datorprograminstruktioner for att fOrmä ett datorsystem att utfora stegen enligt metoden. According to a third aspect, the object is achieved with a computer program product which includes computer program instructions for forming a computer system to perform the steps of the method.
Fordonen som beskrivs hdri är fOretradesvis autonoma, men kan enligt en utforingsform aven vara delvis manuellt styrbara. Varje fordon kanner till var de andra fordonen är och vad de gar genom kommunikation mellan fordon och mellan fordon och ledningscentral. Ett autonomt fordon kan enligt en utforingsform dven upptdcka andra, ej uppkopplade trafikanter som rOr sig i trafikomrddet och meddela detta till ledningscentralen och de andra fordonen. The vehicles described herein are preferably autonomous, but according to one embodiment may also be partially manually steerable. Each vehicle knows where the other vehicles are and what they are doing through communication between vehicles and between vehicles and control center. According to one embodiment, an autonomous vehicle can also detect other, unconnected road users moving in the traffic area and notify the control center and the other vehicles.
Foredragna utforingsformer definieras av de beroende patentkraven. Preferred embodiments are defined by the dependent claims.
Kort figurbeskrivning Figur 1 illustrerar ett trafiksystem med ett flertal autonoma fordon. Brief description of the figures Figure 1 illustrates a traffic system with a number of autonomous vehicles.
Figur 2 visar ett system fOr att reglera ett autonomt fordon i ett trafiksystem enligt en utfOringsform av uppfinningen. 4 537 184 Figur 3 visar ett flodesschema for en metod enligt en utforingsform av uppfinningen. Figure 2 shows a system for controlling an autonomous vehicle in a traffic system according to an embodiment of the invention. 4,537,184 Figure 3 shows a flow chart of a method according to an embodiment of the invention.
Detaljerad beskrivning av fOredragna utfOringsformer av uppfinningen Figur 1 visar schematiskt tre autonoma fordon 2, 3 och 4 som tar sig fram langs en vag. Pilarna i de autonoma fordonen 2, 3, 4 visar deras respektive kOrriktning. De autonoma fordonen 2, 3, 4 kan kommunicera med en ledningscentral 1 via exempelvis V21-kommunikation (Vehicle-to-Infrastructure) 5 och/eller med varandra via exempelvis V2V-kommunikation (Vehicle-to-Vehicle) 6. Denna kommunikation är tradlos och kan exempelvis ske via WLAN (Wireless Local Area Network) protokollet IEEE 802.11, exempelvis IEEE 802.11p. Aven andra tradlOsa kommunikationssatt är dock tankbara. Ledningscentralen 1 organiserar de autonoma fordonen 2, 3, 4 och ger dem uppdrag att utfora. Nar ett autonomt fordon fatt ett uppdrag, kan fordonet sjalvstandigt se till att uppdraget utfOrs. Ett uppdrag kan exempelvis besta av en instruktion att hamta gods vid en godsuthamtningsplats A. Fordonet har da kapacitet att bestamma sin nuvarande position, bestamma en vag fran den nuvarande positionen till godsuthamtningsplatsen A, samt ta sig dit. Under vagen maste fordonet aven ha kapacitet att vaja fOr hinder, hantera andra autonoma fordon som kanske har ett viktigare uppdrag och maste ges foretrade. Fordonet kan aven fã ett nytt uppdrag under pagaende uppdrag som ska prioriteras hOgre an det pagaende uppdraget. I ett bemannat fordon fattar f6raren dessa beslut kontinuerligt under fard. Ett autonomt fordon behOver ha ferutbestamda regler fOr hur det ska prioritera i olika uppkomna handelser for att kunna styra sig sjalv pa ett salt som är det mest effektiva for hela trafiksystemet. Detailed Description of Preferred Embodiments of the Invention Figure 1 schematically shows three autonomous vehicles 2, 3 and 4 traveling along a wagon. The arrows in the autonomous vehicles 2, 3, 4 show their respective direction of travel. The autonomous vehicles 2, 3, 4 can communicate with a control center 1 via eg V21 communication (Vehicle-to-Infrastructure) 5 and / or with each other via eg V2V communication (Vehicle-to-Vehicle) 6. This communication is wireless and can be done, for example, via WLAN (Wireless Local Area Network) protocol IEEE 802.11, for example IEEE 802.11p. However, other wireless communications are also conceivable. The command center 1 organizes the autonomous vehicles 2, 3, 4 and gives them assignments to perform. When an autonomous vehicle has been given an assignment, the vehicle can independently ensure that the assignment is carried out. An assignment can, for example, consist of an instruction to pick up goods at a goods collection point A. The vehicle then has the capacity to determine its current position, determine a vagueness from the current position to the goods collection point A, and get there. During the journey, the vehicle must also have the capacity to sway for obstacles, handle other autonomous vehicles that may have a more important task and must be presented. The vehicle can also be given a new assignment during the ongoing assignment, which must be given priority higher than the ongoing assignment. In a manned vehicle, the driver makes these decisions continuously while driving. An autonomous vehicle needs to have pre-determined rules for how it should prioritize in various transactions that have arisen in order to be able to control itself on a salt that is the most efficient for the entire traffic system.
I figur 2 illustreras ett system 16 enligt en utfOringsform av uppfinningen fOr att reglera ett autonomt fordon i ett trafiksystem innefattande ett flertal autonoma fordon. Det autonoma fordonet kan exempelvis vara ett av de autonoma fordonen som visas i figur 1 och refereras till som 2, 3 eller 4. Systemet 16 kan vara helt placerat antingen i det autonoma fordonet eller i ledningscentralen 1, eller delvis i fordonet och delvis i ledningscentralen 1. Systemet 16 kommer nu att fOrklaras 537 184 med hanvisning till figur 2. Systemet 16 innefattar en banenhet 7 som är anpassad att ta emot en uppdragssignal Su som indikerar ett uppdrag fOr det autonoma fordonet, varvid uppdraget innefattar destinationsinformation gallande dtminstone en destination kw fordonet. Uppdraget kommer foretrddesvis fran ledningscentralen 1. Uppdraget kan exempelvis innefatta destinationsinformation i form av en destination i GPS-koordinater. Banenheten 7 är vidare anpassad att bestamma dtminstone delvis en bana langs vilken fordonet ska kOra fOr att nâ namnda destination baserat pa dtminstone destinationsinformationen, och generera en bansignal SB som indikerar banan. Banenheten 7 kan exempelvis fã kartinformation fran en extern kartenhet 15 via en kartsignal Sm, och positionsinformation fran en positionsbestamningsenhet 18 via en positionssignal SG. Detta kan ske genom satellitpositionering (Global Navigation Satellite System, ofta fOrkortat till GNSS) fOr de fall systemet 16 anvands utomhus. GNSS är ett samlingsnamn fOr en grupp varldstackande navigeringssystem som utnyttjar signaler fran en konstellation av satelliter och pseudosatelliter fOr att mOjliggOra positionsinmatning for en mottagare. Det amerikanska GPS-systemet är det mest kanda GNSS-systemet, men ddrutover finns bland annat det ryska GLONASS och det framtida europeiska Galileo. Fordonets position kan ocksâ bestammas genom att Overvaka signalstyrkan fran flera accesspunkter for trddlosa natverk (WiFi) i narheten. Ett annat salt att bestamma positionen âr att mata antalet hjulvarv och med hjdlp av hjulens omkrets bestamma hur langt fordonet har fardats. Tillsammans med kunskap om fordonets riktning kan fordonets position i fOrhallande till en karta bestdmmas. Pa sâ salt kan man hela tiden veta var fordonet bef inner sig. Figure 2 illustrates a system 16 according to an embodiment of the invention for controlling an autonomous vehicle in a traffic system comprising a plurality of autonomous vehicles. The autonomous vehicle may, for example, be one of the autonomous vehicles shown in Figure 1 and referred to as 2, 3 or 4. The system 16 may be located entirely in either the autonomous vehicle or in the control center 1, or partly in the vehicle and partly in the control center. The system 16 will now be explained 537 184 with reference to Figure 2. The system 16 comprises a track unit 7 which is adapted to receive a mission signal Su indicating a mission for the autonomous vehicle, the mission comprising destination information validating at least one destination kw the vehicle. . The assignment preferably comes from the command center 1. The assignment may, for example, include destination information in the form of a destination in GPS coordinates. The path unit 7 is further adapted to determine at least in part a path along which the vehicle is to drive to reach said destination based on at least the destination information, and to generate a path signal SB indicating the path. The path unit 7 can, for example, receive map information from an external map unit 15 via a map signal Sm, and position information from a position determining unit 18 via a position signal SG. This can be done by satellite positioning (Global Navigation Satellite System, often abbreviated to GNSS) in cases where the system 16 is used outdoors. GNSS is a collective name for a group of worldwide navigation systems that use signals from a constellation of satellites and pseudo-satellites to enable position input for a receiver. The American GPS system is the most well-known GNSS system, but there are also the Russian GLONASS and the future European Galileo. The position of the vehicle can also be determined by monitoring the signal strength from several wireless network access points (WiFi) nearby. Another salt to determine the position is to feed the number of wheel revolutions and, using the circumference of the wheels, determine how far the vehicle has traveled. Together with knowledge of the direction of the vehicle, the position of the vehicle in relation to a map can be determined. On such salt you can always know where the vehicle is.
Systemet 16 innefattar vidare ett flertal analysenheter 8, 9, 10, 11 som är anpassade att ta emot extern information 13 langs banan. Denna externa information 13 visas schematiskt med en pil 13 till systemet 16, och kan exempelvis vara ytterligare uppdrag fran ledningsenheten 1, information fran sensorer i det autonoma fordonet, information via V2V frdn andra fordon, information via V2I fran exempelvis trafikljus, hastighetsskyltar, etc. Analysenheterna 8, 9, 10, 11 är anpassade att analysera den externa 6 537 184 informationen 13 atminstone enligt forutbestamda regler samt bestamma och generera analyssignaler S1, S2, S3, S4 for analysenheterna 8, 9, 10, 11 baserat pa resultatet av analyserna. The system 16 further comprises a plurality of analysis units 8, 9, 10, 11 which are adapted to receive external information 13 along the path. This external information 13 is shown schematically with an arrow 13 to the system 16, and can for example be additional assignments from the control unit 1, information from sensors in the autonomous vehicle, information via V2V from other vehicles, information via V2I from eg traffic lights, speed signs, etc. The analysis units 8, 9, 10, 11 are adapted to analyze the external 6 537 184 information 13 at least according to predetermined rules and to determine and generate analysis signals S1, S2, S3, S4 for the analysis units 8, 9, 10, 11 based on the results of the analyzes.
Enligt en utfOringsform innefattar analysenheterna 8, 9, 10, 11 en kollisionsenhet 8, en navigeringsenhet 9, en samverkansenhet 10 och/eller en uppdragsenhet 11. En analysenhet 8, 9, 10, 11 kan vara anpassad att ta emot extern information 13 i form av sensorsignaler fran olika sensorer i det autonoma fordonet, exempelvis kamera, laser (ex LIDAR eller LADAR), radar, hastighetssensorer, accelerationssensorer, samt information am andra fordon eller hinder via V2V- och/eller V21-kommunikation. Den externa informationen 13 kan aven innefatta ett nytt uppdrag for fordonet, eller annan information fran ledningscentralen 1. Denna externa information 13 kan sedan anvandas av de olika analysenheterna 8, 9, 10, 11 pa olika sail. Harnast kommer de olika analysenheterna 8, 9, 10, 11 att forklaras mer i detalj. According to one embodiment, the analysis units 8, 9, 10, 11 comprise a collision unit 8, a navigation unit 9, a collaboration unit 10 and / or a mission unit 11. An analysis unit 8, 9, 10, 11 may be adapted to receive external information 13 in the form of sensor signals from various sensors in the autonomous vehicle, for example camera, laser (eg LIDAR or LADAR), radar, speed sensors, acceleration sensors, and information on other vehicles or obstacles via V2V and / or V21 communication. The external information 13 may also include a new assignment for the vehicle, or other information from the command center 1. This external information 13 can then be used by the various analysis units 8, 9, 10, 11 on different sails. Most recently, the various analysis units 8, 9, 10, 11 will be explained in more detail.
Kollisionsenheten 8 är anpassad att anvanda den externa informationen 13 for att forutse en risk for kollision flied ett annat fordon eller objekt langs banan som indikeras av bansignalen SB. Enligt en utfOringsform ãr kollisionsenheten 8 anpassad att analysera den externa information 13 baserat pa regler for risk for kollision med det egna fordonet. Pa sâ salt kan risken for kollision kontinuerligt utvarderas. Den externa informationen 13 analyseras alltsa enligt forutbestamda regler och en analyssignal S1 bestams fOr kollisionsenheten 8 baserat pa resultatet av analysen. Analyssignal S1 indikerar exempelvis om det finns risk for kollision. Analyssignalen S1 kan enligt en utforingsform aven innefattar styrinstruktioner som indikerar hur fordonet ska styras for att undvika hindret, exempelvis en sankt hastighet, vajningsinstruktioner, stop, eller en ny bana fOr fordonet. Foreligger det ingen risk f6r kollision, indikerar analyssignalen S1 enligt en utfOringsform aven detta. The collision unit 8 is adapted to use the external information 13 to anticipate a risk of collision with another vehicle or object along the path indicated by the path signal SB. According to one embodiment, the collision unit 8 is adapted to analyze the external information 13 based on rules for risk of collision with one's own vehicle. On such salt, the risk of collision can be continuously assessed. The external information 13 is thus analyzed according to predetermined rules and an analysis signal S1 is determined for the collision unit 8 based on the result of the analysis. Analysis signal S1 indicates, for example, whether there is a risk of collision. According to one embodiment, the analysis signal S1 may also comprise steering instructions which indicate how the vehicle is to be steered in order to avoid the obstacle, for example a slow speed, turning instructions, stops, or a new lane for the vehicle. If there is no risk of collision, the analysis signal S1 according to an embodiment also indicates this.
Navigeringsenheten 9 kan anvanda den externa informationen 13 fOr att se till att fordonet inte bryter mot nagra trafikregler och/eller se till att fordonet hittar 7 537 184 narmsta vagen till sitt uppdrag under fordonets vag langs banan som indikeras av bansignalen SB. Trafikreglerna kan vara olika beroende pa vilken milja trafiksystemet är i. Exempelvis kan det vara olika trafikregler i en gruva och i vanlig, civil trafik. Enligt en utforingsform ãr navigeringsenheten 9 anpassad att analysera den externa informationen 13 baserat pa trafikregler och/eller far att finna narmsta vagen far att uppna uppdraget. Trafikregler kan exempelvis innebara ett max antal fordon pa en vagstracka, eller max- och minhastigheter far det autonoma fordonet. Navigeringsenheten 9 kan fâ kartinformation fran kartenheten 15 via en kartsignal Sm, och positionsinformation fran en positionsbestamningsenhet 18 via en positionssignal SG, vilket visas som streckade linjer i figur 2, far att kunna bestamma den narmsta vagen for att utfora uppdraget. Genom att kombinera krav pa att folja trafikregler samt att kora narmsta vagen, kan man uppna en effektiv 'corning i enlighet med trafikregler. Navigeringsenheten 9 är anpassad att bestamma och generera en analyssignal S2 far navigeringsenheten 9 baserat pa resultatet av analysen. Analyssignalen S2 kan exempelvis indikera att den forut bestamda banan som indikeras av bansignalen SB inte gar att falja pa grund av trafikreglerna, eller att den inte är den narmsta vagen. Enligt en utforingsform är navigeringsenheten 9 anpassad att bestamma en ny bana som foljer trafikreglerna och/eller ãr den narmsta vagen for att utfara uppdraget. Analyssignalen S2 kan dã indikera detta. Fareligger det ingen forandring av banans strackning baserat pa trafikregler och/eller fordonet redan ' Samverkansenheten 10 kan anvanda den externa informationen 13 for att se till att det autonoma fordonet samverkar med andra fordon i trafiksystemet pa ett satt som ãr effektivt far hela trafiksystemet. Enligt en utforingsform är samverkansenheten 10 anpassad att analysera den externa informationen 13 baserat pa samverkansregler med andra trafikanter. Bade de enskilda autonoma fordonen och ledningscentralen 1 tar vid samverkan hansyn till effektiviteten i hela trafiksystemet. Vad effektivitet innebar kan skilja sig at fran trafiksystem till trafiksystem och kan valjas av trafiksystemets manskliga Overvakare. Om tva olika tunga fordon mats vid en flaskhals, exempelvis en tunnel eller gruvgang med bara 8 537 184 en vagbana, och det tyngre är pa \fag uppfor kan det vara effektivare att det tyngre fordonet lamnas foretrade av det lattare fordonet som är pa \fag nedfor. Samverkansenheten 10 kan dã vara anpassad att jamfora parametrar fran de olika fordonen med varandra, exempelvis viktparametrar. Om ett ensamt autonomt fordon mOter ett fordonstag kan det vara effektivare att det ensamma autonoma fordonet stannar dven om det är tyngre, men inte om det leder till att det inte kommer att kunna komma igang igen efter stoppet. I samma situationer kan nagot av fordonen istallet sdnka hastigheten i god tid fOr att helt undvika konflikt. Samverkansenheten 10 är sedan anpassad att bestamma och generera en analyssignal S3 fOr samverkansenheten 10 baserat pa resultatet av analysen. The navigation unit 9 can use the external information 13 to ensure that the vehicle does not break any traffic rules and / or to ensure that the vehicle finds the nearest lane for its mission under the vehicle's lane along the lane indicated by the lane signal SB. The traffic rules may be different depending on the environment the traffic system is in. For example, there may be different traffic rules in a mine and in ordinary, civilian traffic. According to one embodiment, the navigation unit 9 is adapted to analyze the external information 13 based on traffic rules and / or to find the nearest route to achieve the task. Traffic rules can, for example, mean a maximum number of vehicles on a carriageway, or maximum and minimum speeds for the autonomous vehicle. The navigation unit 9 can receive map information from the map unit 15 via a map signal Sm, and position information from a position determining unit 18 via a position signal SG, which is shown as dashed lines in Figure 2, to be able to determine the nearest route to perform the task. By combining requirements to follow traffic rules and to drive the nearest road, one can achieve an effective 'corning in accordance with traffic rules. The navigation unit 9 is adapted to determine and generate an analysis signal S2 for the navigation unit 9 based on the result of the analysis. The analysis signal S2 may, for example, indicate that the predetermined path indicated by the path signal SB may not fall due to the traffic rules, or that it is not the nearest road. According to one embodiment, the navigation unit 9 is adapted to determine a new lane which follows the traffic rules and / or is the nearest road to carry out the mission. The analysis signal S2 can then indicate this. If there is no change in the route of the track based on traffic rules and / or the vehicle already, the interoperability unit 10 can use the external information 13 to ensure that the autonomous vehicle interacts with other vehicles in the traffic system in a way that effectively runs the entire traffic system. According to one embodiment, the interaction unit 10 is adapted to analyze the external information 13 based on interaction rules with other road users. In collaboration, both the individual autonomous vehicles and the control center 1 take into account the efficiency of the entire traffic system. What efficiency meant may differ from traffic system to traffic system and can be chosen by the traffic system's human Supervisor. If two different heavy vehicles are fed at a bottleneck, for example a tunnel or mining corridor with only one lane, and the heavier one is on the bay up, it may be more efficient for the heavier vehicle to be left lined by the lighter vehicle on the bay. down. The interaction unit 10 can then be adapted to compare parameters from the different vehicles with each other, for example weight parameters. If a lone autonomous vehicle meets a vehicle roof, it may be more efficient for the lone autonomous vehicle to stop even if it is heavier, but not if it means that it will not be able to start again after the stop. In the same situations, some of the vehicles may instead slow down in good time to completely avoid conflict. The interaction unit 10 is then adapted to determine and generate an analysis signal S3 for the interaction unit 10 based on the result of the analysis.
Analyssignalen S3 kan exempelvis indikera att samverkan behover ske och/eller vilken samverkan som behover ske. Foreligger det inget behov av samverkan, indikerar analyssignalen S3 enligt en utforingsform detta. The analysis signal S3 can, for example, indicate that collaboration needs to take place and / or which collaboration needs to take place. If there is no need for cooperation, the analysis signal S3 according to an embodiment indicates this.
Den externa informationen 13 kan enligt en utforingsform innefatta ett externt trafikledningsbeslut. Ett externt trafikledningsbeslut kan exempelvis vara ett beslut till ett autonomt fordon att ta sig ut ur en gruva efter avslutat uppdrag fOr att det skett en olycka. Trafikledningsbeslutet innebar dá aven ett nytt uppdrag — att ta sig ut ur gruvan till en forutbestamd plats. Enligt en utforingsform är uppdragsenheten 11 dâ anpassad att analysera den externa informationen 13 baserat pa regler fOr externa trafikledningsbeslut. Uppdragsenheten 11 är sedan anpassad att bestamma och generera en analyssignal S4 fOr uppdragsenheten 11 baserat pa resultatet av analysen. Analyssignalen 34 kan dâ innefatta informationen om att ett nytt uppdrag har inkommit och exempelvis destinationsinformation. According to one embodiment, the external information 13 may comprise an external traffic management decision. An external traffic management decision can, for example, be a decision for an autonomous vehicle to get out of a mine after completing an assignment because an accident has occurred. The traffic management decision then also meant a new assignment - to get out of the mine to a predetermined place. According to one embodiment, the assignment unit 11 is then adapted to analyze the external information 13 based on rules for external traffic management decisions. The assignment unit 11 is then adapted to determine and generate an analysis signal S4 for the assignment unit 11 based on the result of the analysis. The analysis signal 34 may then include the information that a new assignment has been received and, for example, destination information.
I svara specialfall dâ det saknas klara regler far hur fordonen ska agera i den uppkomna situationen, exempelvis hur tva fordon ska samverka, kan systemet 16 be en ledningscentral 1 eventuellt inkluderande en mansklig overvakare om rad fOr att komma till ett beslut. Enligt en utfOringsform är atminstone en av analysenheterna 8, 9, 10, 11 anpassad att sdnda en fOrfragansignal 131 som indikerar en fOrfragan till en ledningscentral 1 relaterat till den externa 9 537 184 informationen 13. Forfragan behandlas sedan i led ningscentralen 1 och ett beslut tas. Beslutet kan exempelvis tas av en mansklig overvakare eller operator. Analysenheten 8, 9, 10, 11 är sedan anpassad att mottaga en beslutsignal 132 som indikerar beslutet fran ledningscentralen 1, och att analysera den externa information 13 baserat pa beslutet fran ledningscentralen 1. pa sa salt kan aven svara eller komplexa situationer i systemet 16 hanteras. In special cases where there are no clear rules on how the vehicles should act in the situation that has arisen, for example how two vehicles should interact, the system 16 can ask a command center 1 possibly including a human supervisor in a row to come to a decision. According to one embodiment, at least one of the analysis units 8, 9, 10, 11 is adapted to send an inquiry signal 131 indicating an inquiry to a control center 1 related to the external 9 537 184 information 13. The inquiry is then processed in the control center 1 and a decision is made . The decision can, for example, be made by a human supervisor or operator. The analysis unit 8, 9, 10, 11 is then adapted to receive a decision signal 132 indicating the decision from the control center 1, and to analyze the external information 13 based on the decision from the control center 1. on such salt even responses or complex situations in the system 16 can be handled. .
Systemet 16 innefattar vidare en resultatenhet 12 som är anpassad att ta emot analyssignaler Si, S2, S3, S4. Resultatenheten 12 är anpassad att relatera en prioritering till atminstone en analyssignal Si, S2, S3, S4 baserat pa vilken analysenhet 8, 9, 10, 11 de kommer ifran samt deras innehâll. lfall analyssignalen Si inte indikerar nagon risk for kollision, far inte denna analyssignal nagon prioritet. Samma gdller fOr analyssignalen S2, och ifall denna analyssignal indikerar att ingen fOrandring behOver ske far inte analyssignalen S2 nagon prioritet. lfall analyssignalen S3 inte anger nagot behov av samverkan, far inte analyssignalen S3 nagon tilldelad prioritet. Ifall analyssignalen S4 inte anger nagot nytt uppdrag fdr inte denna nagon prioritet. lfall ingen av analyssignalerna indikerar nagot behov av fOrdndring fran nuvarande bana, foljer fordonet enligt en utforingsform en bestdmd bana, exempelvis SB. Enligt en utfOringsform ãr analyssignalen Si fran kollisionsenheten 8 hOgst rankad, foljt av analyssignalen S3 fran samverkansenheten 10 och sedan analyssignalen S2fran navigeringsenheten 9 och till sist analyssignalen S4 fran uppdragsenheten 11. Pa sa sdtt far alltid en kollisionsrisk den hOgsta prioriteten if all det fOreligger en risk for kollision. Den exemplifierade prioriteringen kan dock goras annorlunda. The system 16 further comprises a result unit 12 which is adapted to receive analysis signals S1, S2, S3, S4. The result unit 12 is adapted to relate a priority to at least one analysis signal S1, S2, S3, S4 based on which analysis unit 8, 9, 10, 11 they come from and their contents. If the analysis signal Si does not indicate any risk of collision, this analysis signal does not have any priority. The same applies to the analysis signal S2, and if this analysis signal indicates that no change needs to take place, the analysis signal S2 does not have any priority. If the analysis signal S3 does not indicate any need for cooperation, the analysis signal S3 does not receive any assigned priority. If the analysis signal S4 does not indicate a new assignment, this does not give any priority. If none of the analysis signals indicates any need for change from the current lane, the vehicle follows a specific lane according to one embodiment, for example SB. According to one embodiment, the analysis signal Si from the collision unit 8 is ranked highest, followed by the analysis signal S3 from the interaction unit 10 and then the analysis signal S2 from the navigation unit 9 and finally the analysis signal S4 from the mission unit 11. In this way a collision risk always has the highest priority for collision. However, the exemplified prioritization can be done differently.
Resultatenheten 12 är vidare anpassad att bestamma en sammanvagd analyssignal Sx baserat pa analyssignalernas innehall samt deras eventuella prioriteringar. For att bestdmma en sammanvagd analyssignal Sxär resultatenheten anpassad att ta hansyn till mojligheten for fordonet att exempelvis undvika att krocka genom att ' If all exempelvis tva fordon kOr mot var sin ande av en trang tunnel, och det fordon som har lagst prioritering ur transportsystemets synvinkel rdknar med att det ska hinna igenom tunneln innan det mOtande hOgre prioriterade fordonet kommer fram till tunneln, sá satsar det lagre prioriterade fordonet pa det och Icor pa. Detta kan exempelvis indikeras i analyssignalen S3 som att samverkan inte behover ske ifall fordonet med lagst prioritering hailer en viss hastighet eller nar tunneln inom en sdrskild tid etc. Precis innan tunneln sa upptdcker kollisionsenheten 8 dock ett hinder, vilket enligt regler for risk for kollision med det egna fordonet ger en analyssignal S1 som indikerar en risk fOr kollision. Att ta sig runt hindret ãr mOjligt, men den extratid det kommer att ta gOr att det mOtande fordonet under tiden kommer att hinna fram till tunneln. Resultatenheten 12 är cid anpassad att analysera ifall det ldgre prioriterade fordonet kan ta sig forbi hindret, men anda nâ tunneln inom den sdrskilda tiden, och att bestdmma en sammanvagd analyssignal S, som indikerar resultatet av analysen. I detta fall kan inte det lagre prioriterade fordonet ta sig runt hindret och anda nâ tunneln i tid, vilket resulterar i en sammanvagd analyssignal som innefattar instruktioner till fordonet att det maste stanna och invanta det motande fordonet innan det kan ta sig forbi hindret. The result unit 12 is further adapted to determine a weighted analysis signal Sx based on the content of the analysis signals and their possible priorities. In order to determine a weighted analysis signal, the result unit is adapted to take into account the possibility for the vehicle to avoid, for example, a collision by 'If all two vehicles, for example, run against each other in a narrow tunnel, and the vehicle that has the lowest priority from the transport system's point of view with it having to get through the tunnel before the oncoming higher priority vehicle arrives at the tunnel, the lower priority vehicle invests in it and Icor in it. This can be indicated, for example, in the analysis signal S3 that cooperation does not have to take place if the vehicle with the lowest priority reaches a certain speed or reaches the tunnel within a specific time, etc. Just before the tunnel, the collision unit 8 the own vehicle gives an analysis signal S1 which indicates a risk of collision. Getting around the obstacle is possible, but the extra time it will take means that the oncoming vehicle will meanwhile reach the tunnel. The result unit 12 is adapted to analyze whether the lower priority vehicle can get past the obstacle, but reach the tunnel within the specific time, and to determine a weighted analysis signal S, which indicates the result of the analysis. In this case, the lower priority vehicle cannot get around the obstacle and breathe the tunnel in time, resulting in a weighted analysis signal that includes instructions to the vehicle to stop and overtake the oncoming vehicle before it can pass the obstacle.
Resultatenheten 12 är sedan anpassad att sanda den sammanvagda analyssignalen S, till ett styrsystem 17 i det autonoma fordonet, varefter fordonet anpassar sin reglering i enlighet med den sammanvagda analyssignalen S. Pa sa salt kan det autonoma fordonet prioritera i olika situationer sa att hela trafiksystemet blir sâ effektivt som mOjligt. Analyssignalen S kan enligt en utforingsform aven innefatta styrparametrar som styrsystemet 17 kan styra efter. The result unit 12 is then adapted to send the interleaved analysis signal S, to a control system 17 in the autonomous vehicle, after which the vehicle adapts its control in accordance with the interleaved analysis signal S. as efficiently as possible. According to an embodiment, the analysis signal S may also comprise control parameters according to which the control system 17 can control.
De beskrivna enheterna kan vara inkorporerade i en processorenhet som innefattar en eller flera processorer samt tillhorande datorminne 19. I datorminnet 11 537 184 19 kan instruktioner lagras fOr att fâ processorn eller processorerna att utfora stegen som beskrivs had. The described units may be incorporated in a processor unit comprising one or more processors and associated computer memory 19. In the computer memory 11 537 184 19 instructions may be stored to cause the processor or processors to perform the steps described.
Uppfinningen hanfor sig aven till en metod for att reglera ett autonomt fordon i ett trafiksystem innefattande ett flertal autonoma fordon, metoden kommer harnast att fOrklaras med hanvisning till flOdesschemat i figur 3. Metoden innefattar ett fOrsta steg Al) att ta emot ett uppdrag fOr det autonoma fordonet, varvid uppdraget innefattar destinationsinformation gallande atminstone en destination for fordonet. Uppdraget kan exempelvis komma frail en ledningscentral 1. The invention also relates to a method for regulating an autonomous vehicle in a traffic system comprising a plurality of autonomous vehicles, the method will most likely be explained with reference to the flow chart in Figure 3. The method comprises a first step A1) to receive an assignment for the autonomous the vehicle, the assignment comprising destination information galling at least one destination of the vehicle. The assignment may, for example, come from a command center 1.
Metoden innefattar vidare ett andra steg A2) att bestamma atminstone delvis en bana langs vilken fordonet ska kOra for att na namnda destination. I samband med beskrivningen av systemet 16 har det forklarats hur en bana kan bestammas, vilket aven galler fOr metoden. I ett tredje steg A3) tas extern information 13 emot langs banan. Under tiden det autonoma fordonet framfOrs langs den bestamda banan sa tar fordonet hela tiden emot extern information 13, vilket kan innebara information via kamera, laser (t ex LIDAR eller LADAR), radar, hastighetssensorer, accelerationssensorer, samt information om andra fordon eller hinder via V2V- och/eller V21-kommunikation. Den externa informationen 13 kan aven innefatta ett nytt uppdrag for fordonet, eller annan information fran ledningscentralen 1. I ett fjarde steg A4) analyseras den externa informationen atminstone enligt fOrutbestamda regler. Beroende pa vad man vill undersoka, analyseras den externa informationen 13 enligt bestamda regler. Enligt en utfOringsform innefattar analyssteget A4) att analysera den externa informationen 13 baserat pa regler for risk for kollision med det egna fordonet. Pa sâ satt kan risken for att fordonet krockar med ett annat fordon eller objekt bestammas. Det autonoma fordonet kan i senare steg sedan regleras for att undvika kollisionen. Enligt en annan utfOringsform innefattar analyssteget A4) att analysera den externa informationen 13 baserat pa trafikregler och/eller fOr att finna narmsta vagen fOr att uppna. uppdraget. Olika trafiksystem kan ha olika trafikregler som de autonoma fordonen maste anpassa sig efter. Hur den narmsta vagen kan bestammas har beskrivits med hanvisning till systemet 16, vilket aven galler for metoden. Enligt en annan utfOringsform innefattar analyssteget A4) att analysera 12 537 184 den externa information 13 baserat pa samverkansregler med andra trafikanter. Pa sa salt kan en effektiv Miming uppnas som är effektiv for ett flertal fordon. Enligt en annan utforingsform innefattar analyssteget A4) att analysera den externa informationen 13 baserat pa regler fOr externa trafikledningsbeslut. Pa sa satt kan externa trafikledningsbeslut hanteras. De ovan angivna exemplen pa. steg A4) kan exempelvis gams parallellt. I ett femte steg A5) bestams analyssignaler Si, S2, S3, S4 som indikerar resultatet av analyserna. I ett sjatte steg A6) relateras en prioritering till atminstone en analyssignal Si, S2, S3, S4 baserat pa vilken analys som gjorts samt analyssignalernas innehâll. Enligt en utforingsform sd. far analyssignalen Si som indikerar risken for kollision hOgst proritet, foljt av analyssignalen S3 som indikerar behovet av samverkan, sedan analyssignalen S2 som indikerar huruvida den forut bestamda banan som indikeras av bansignalen SB inte gar att fOlja pa grund av trafikreglerna, eller att den inte är den narmsta vagen. Lagst prioritet har dâ analyssignalen fran analyssignalen S4 SOM exempelvis kan indikera ett nytt uppdrag. Detta baserat pa att en analyssignal som far en prioritet ocksä indikerar en forandring for fordonet. The method further comprises a second step A2) to determine at least in part a path along which the vehicle is to drive to reach said destination. In connection with the description of the system 16, it has been explained how a path can be determined, which also applies to the method. In a third step A3) external information 13 is received along the path. While the autonomous vehicle is being driven along the designated lane, the vehicle is constantly receiving external information 13, which may include information via camera, laser (eg LIDAR or LADAR), radar, speed sensors, acceleration sensors, and information about other vehicles or obstacles via V2V and / or V21 communication. The external information 13 may also include a new assignment for the vehicle, or other information from the control center 1. In a fourth step A4), the external information is analyzed at least according to predetermined rules. Depending on what you want to examine, the external information 13 is analyzed according to certain rules. According to one embodiment, the analysis step A4) comprises analyzing the external information 13 based on rules for risk of collision with one's own vehicle. In this way, the risk of the vehicle colliding with another vehicle or object can be determined. In later stages, the autonomous vehicle can then be adjusted to avoid the collision. According to another embodiment, the analysis step A4) comprises analyzing the external information 13 based on traffic rules and / or to find the nearest path to achieve. the mission. Different traffic systems may have different traffic rules that the autonomous vehicles must adapt to. How the nearest wagon can be determined has been described with reference to the system 16, which also applies to the method. According to another embodiment, the analysis step A4) comprises analyzing the external information 13 based on interaction rules with other road users. On such salt an efficient Miming can be achieved which is efficient for several vehicles. According to another embodiment, the analysis step A4) comprises analyzing the external information 13 based on rules for external traffic management decisions. In this way, external traffic management decisions can be handled. The above examples pa. step A4) can, for example, gams in parallel. In a fifth step A5) analysis signals Si, S2, S3, S4 are determined which indicate the result of the analyzes. In a sixth step A6), a prioritization is related to at least one analysis signal S1, S2, S3, S4 based on the analysis performed and the content of the analysis signals. According to an embodiment sd. the analysis signal Si indicating the risk of collision is given the highest priority, followed by the analysis signal S3 indicating the need for cooperation, then the analysis signal S2 indicating whether the predetermined path indicated by the path signal SB cannot be followed due to the traffic rules, or that it is not the nearest wagon. The lowest priority is given to the analysis signal from the analysis signal S4, which can, for example, indicate a new assignment. This is based on the fact that an analysis signal that is given a priority also indicates a change for the vehicle.
I ett sjatte steg A6) bestams en sammanvagd analyssignal S, baserat pa analyssignalernas innehall samt deras prioritering. I ett sjunde steg A7) sands den sammanvagda analyssignalen S, till ett styrsystem 17 i det autonoma fordonet, varefter fordonet anpassar sin reglering i enlighet med den sammanvagda analyssignalen S. In a sixth step A6) a weighted analysis signal S is determined, based on the content of the analysis signals and their prioritization. In a seventh step A7), the interleaved analysis signal S is sent to a control system 17 in the autonomous vehicle, after which the vehicle adjusts its control in accordance with the interleaved analysis signal S.
Enligt en utforingsform innefattar analyssteget A4) understegen A41) — A43) att A41) sanda en forfragan relaterat till den externa informationen 13 till en ledningscentral 1, A42) mottaga ett beslut fran ledningscentralen 1, samt A43) analysera den externa informationen 13 baserat pa beslutet. Pa sá satt kan man fã experthjalp dâ en komplicerad situation uppstar. According to one embodiment, the analysis step A4) comprises sub-steps A41) - A43) that A41) sends a request related to the external information 13 to a control center 1, A42) receives a decision from the control center 1, and A43) analyzes the external information 13 based on the decision . In this way, you can get expert help when a complicated situation arises.
Uppfinningen hanfOr sig aven till ett datorprogram P vid ett autonomt fordon 2, dar datorprogrammet P innefattar programkod for att fOrma systemet 16 att utfOra stegen enligt metoden. I Figur 2 visas datorprogrammet P som en del av 13 537 184 datorminnet 19. Datorprogrammet P är alltsa lagrat pa datorminnet 19. Datorminnet 19 är anslutet till enheterna 7, 8, 9, 10, 11, 12 i systemet 16, och nar hela eller delar av datorprogrammet P exekveras av flagon eller flera av enheterna 7, 8, 9, 10, 11, 12, sa utfors atminstone delar av metoderna som har beskrivits hari. Uppfinningen innefattar vidare en datorprogramprodukt innefattande en programkod lagrad pa ett av en dator lasbart medium f6r att utfOra metodstegen som beskrivits hari, nar programkoden kers pa systemet 16. The invention also relates to a computer program P in an autonomous vehicle 2, wherein the computer program P comprises program code for forming the system 16 to perform the steps according to the method. Figure 2 shows the computer program P as part of the computer memory 19. The computer program P is thus stored on the computer memory 19. The computer memory 19 is connected to the units 7, 8, 9, 10, 11, 12 in the system 16, and when the whole or parts of the computer program P are executed by the flag or more of the units 7, 8, 9, 10, 11, 12, then at least parts of the methods described herein are performed. The invention further comprises a computer program product comprising a program code stored on a computer readable medium for performing the method steps described herein when the program code is executed on the system 16.
Foreliggande uppf inning är inte begransad till ovan-beskrivna foredragna utforingsformer. Olika alternativ, modifieringar och ekvivalenter kan anvandas. The present invention is not limited to the preferred embodiments described above. Various alternatives, modifications and equivalents can be used.
Utferingsformerna ovan skall dal& inte betraktas som begransande uppfinningens skyddsomfang vilket definieras av de bifogade patentkraven. 14 The above embodiments are not to be construed as limiting the scope of the invention as defined by the appended claims. 14
Claims (12)
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DE112014001058.8T DE112014001058T5 (en) | 2013-03-19 | 2014-03-06 | Method and system for controlling autonomous vehicles |
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Families Citing this family (53)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US10096038B2 (en) | 2007-05-10 | 2018-10-09 | Allstate Insurance Company | Road segment safety rating system |
US9932033B2 (en) | 2007-05-10 | 2018-04-03 | Allstate Insurance Company | Route risk mitigation |
US8606512B1 (en) | 2007-05-10 | 2013-12-10 | Allstate Insurance Company | Route risk mitigation |
US10157422B2 (en) | 2007-05-10 | 2018-12-18 | Allstate Insurance Company | Road segment safety rating |
US10096067B1 (en) | 2014-01-24 | 2018-10-09 | Allstate Insurance Company | Reward system related to a vehicle-to-vehicle communication system |
US9390451B1 (en) | 2014-01-24 | 2016-07-12 | Allstate Insurance Company | Insurance system related to a vehicle-to-vehicle communication system |
US9355423B1 (en) | 2014-01-24 | 2016-05-31 | Allstate Insurance Company | Reward system related to a vehicle-to-vehicle communication system |
US9886036B2 (en) | 2014-02-10 | 2018-02-06 | John Bean Technologies Corporation | Routing of automated guided vehicles |
US9940676B1 (en) | 2014-02-19 | 2018-04-10 | Allstate Insurance Company | Insurance system for analysis of autonomous driving |
US10783586B1 (en) | 2014-02-19 | 2020-09-22 | Allstate Insurance Company | Determining a property of an insurance policy based on the density of vehicles |
US10796369B1 (en) | 2014-02-19 | 2020-10-06 | Allstate Insurance Company | Determining a property of an insurance policy based on the level of autonomy of a vehicle |
US10803525B1 (en) | 2014-02-19 | 2020-10-13 | Allstate Insurance Company | Determining a property of an insurance policy based on the autonomous features of a vehicle |
US10783587B1 (en) | 2014-02-19 | 2020-09-22 | Allstate Insurance Company | Determining a driver score based on the driver's response to autonomous features of a vehicle |
US9864371B2 (en) | 2015-03-10 | 2018-01-09 | John Bean Technologies Corporation | Automated guided vehicle system |
EP3303083B1 (en) * | 2015-06-08 | 2024-05-08 | Arity International Limited | Route risk mitigation |
US9869560B2 (en) | 2015-07-31 | 2018-01-16 | International Business Machines Corporation | Self-driving vehicle's response to a proximate emergency vehicle |
US9483948B1 (en) | 2015-08-07 | 2016-11-01 | International Business Machines Corporation | Automated control of interactions between self-driving vehicles and pedestrians |
US9785145B2 (en) | 2015-08-07 | 2017-10-10 | International Business Machines Corporation | Controlling driving modes of self-driving vehicles |
US9721397B2 (en) | 2015-08-11 | 2017-08-01 | International Business Machines Corporation | Automatic toll booth interaction with self-driving vehicles |
US9718471B2 (en) | 2015-08-18 | 2017-08-01 | International Business Machines Corporation | Automated spatial separation of self-driving vehicles from manually operated vehicles |
US9481366B1 (en) | 2015-08-19 | 2016-11-01 | International Business Machines Corporation | Automated control of interactions between self-driving vehicles and animals |
US9896100B2 (en) | 2015-08-24 | 2018-02-20 | International Business Machines Corporation | Automated spatial separation of self-driving vehicles from other vehicles based on occupant preferences |
US9731726B2 (en) | 2015-09-02 | 2017-08-15 | International Business Machines Corporation | Redirecting self-driving vehicles to a product provider based on physiological states of occupants of the self-driving vehicles |
US9587952B1 (en) | 2015-09-09 | 2017-03-07 | Allstate Insurance Company | Altering autonomous or semi-autonomous vehicle operation based on route traversal values |
US9513632B1 (en) | 2015-09-16 | 2016-12-06 | International Business Machines Corporation | Driving mode alerts from self-driving vehicles |
US9566986B1 (en) | 2015-09-25 | 2017-02-14 | International Business Machines Corporation | Controlling driving modes of self-driving vehicles |
US9481367B1 (en) | 2015-10-14 | 2016-11-01 | International Business Machines Corporation | Automated control of interactions between self-driving vehicles and animals |
US9834224B2 (en) | 2015-10-15 | 2017-12-05 | International Business Machines Corporation | Controlling driving modes of self-driving vehicles |
US9751532B2 (en) | 2015-10-27 | 2017-09-05 | International Business Machines Corporation | Controlling spacing of self-driving vehicles based on social network relationships |
US9944291B2 (en) | 2015-10-27 | 2018-04-17 | International Business Machines Corporation | Controlling driving modes of self-driving vehicles |
US10607293B2 (en) | 2015-10-30 | 2020-03-31 | International Business Machines Corporation | Automated insurance toggling for self-driving vehicles |
US10176525B2 (en) | 2015-11-09 | 2019-01-08 | International Business Machines Corporation | Dynamically adjusting insurance policy parameters for a self-driving vehicle |
US9791861B2 (en) | 2015-11-12 | 2017-10-17 | International Business Machines Corporation | Autonomously servicing self-driving vehicles |
US10061326B2 (en) | 2015-12-09 | 2018-08-28 | International Business Machines Corporation | Mishap amelioration based on second-order sensing by a self-driving vehicle |
US9836973B2 (en) | 2016-01-27 | 2017-12-05 | International Business Machines Corporation | Selectively controlling a self-driving vehicle's access to a roadway |
US10269075B2 (en) | 2016-02-02 | 2019-04-23 | Allstate Insurance Company | Subjective route risk mapping and mitigation |
US10685391B2 (en) | 2016-05-24 | 2020-06-16 | International Business Machines Corporation | Directing movement of a self-driving vehicle based on sales activity |
US10093322B2 (en) | 2016-09-15 | 2018-10-09 | International Business Machines Corporation | Automatically providing explanations for actions taken by a self-driving vehicle |
US10643256B2 (en) | 2016-09-16 | 2020-05-05 | International Business Machines Corporation | Configuring a self-driving vehicle for charitable donations pickup and delivery |
US10202118B2 (en) | 2016-10-14 | 2019-02-12 | Waymo Llc | Planning stopping locations for autonomous vehicles |
US10259452B2 (en) | 2017-01-04 | 2019-04-16 | International Business Machines Corporation | Self-driving vehicle collision management system |
US10529147B2 (en) | 2017-01-05 | 2020-01-07 | International Business Machines Corporation | Self-driving vehicle road safety flare deploying system |
US10363893B2 (en) | 2017-01-05 | 2019-07-30 | International Business Machines Corporation | Self-driving vehicle contextual lock control system |
US10152060B2 (en) | 2017-03-08 | 2018-12-11 | International Business Machines Corporation | Protecting contents of a smart vault being transported by a self-driving vehicle |
US10988143B2 (en) * | 2017-08-25 | 2021-04-27 | International Business Machines Corporation | Using cloud-based traffic policies to alleviate issues with cross geographic traffic in autonomous vehicles |
US10768637B2 (en) * | 2018-08-30 | 2020-09-08 | Pony Ai Inc. | Prioritizing vehicle navigation |
DE102018220835A1 (en) * | 2018-12-03 | 2020-06-04 | Zf Friedrichshafen Ag | Method and sensor system for autonomous operation of a group of vehicles |
US11860643B2 (en) | 2019-07-02 | 2024-01-02 | Liebherr Mining Equipment Newport News Co. | System for controlling a plurality of autonomous vehicles on a mine site |
DE102019214445A1 (en) | 2019-09-23 | 2021-03-25 | Robert Bosch Gmbh | Method for assisting a motor vehicle |
DE102019214448A1 (en) * | 2019-09-23 | 2021-03-25 | Robert Bosch Gmbh | Method for assisting a motor vehicle |
US11847919B2 (en) | 2020-05-19 | 2023-12-19 | Toyota Motor North America, Inc. | Control of transport en route |
CN111832965B (en) * | 2020-07-24 | 2024-04-12 | 上海海得控制系统股份有限公司 | Unmanned same-span multi-crown block cooperative scheduling method and system, medium and terminal |
CN113220476B (en) * | 2021-04-22 | 2024-02-23 | 行云新能科技(深圳)有限公司 | Driving teaching system compatible method, automobile practical training platform and readable storage medium |
Family Cites Families (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US5586030A (en) * | 1994-10-24 | 1996-12-17 | Caterpillar Inc. | System and method for managing access to a resource in an autonomous vehicle system |
IL117792A (en) * | 1995-05-08 | 2003-10-31 | Rafael Armament Dev Authority | Autonomous command and control unit for mobile platform |
EP0913751B1 (en) * | 1997-11-03 | 2003-09-03 | Volkswagen Aktiengesellschaft | Autonomous vehicle and guiding method for an autonomous vehicle |
US8577538B2 (en) * | 2006-07-14 | 2013-11-05 | Irobot Corporation | Method and system for controlling a remote vehicle |
US7734387B1 (en) * | 2006-03-31 | 2010-06-08 | Rockwell Collins, Inc. | Motion planner for unmanned ground vehicles traversing at high speeds in partially known environments |
US20070288132A1 (en) * | 2006-06-07 | 2007-12-13 | Raytheon Company | Cooperative swarm of unmanned vehicles |
US8255092B2 (en) * | 2007-05-14 | 2012-08-28 | Irobot Corporation | Autonomous behaviors for a remote vehicle |
US7979174B2 (en) * | 2007-09-28 | 2011-07-12 | Honeywell International Inc. | Automatic planning and regulation of the speed of autonomous vehicles |
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- 2013-03-19 SE SE1350329A patent/SE537184C2/en unknown
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