• 专利附录
  • 专利说明
  • 权利要求
  • 类似技术
  • 同族专利
  • 引用文献
  • 法律状态
  • 优先权
    • 专利摘要:
    The invention relates to a device for regulating an autonomous vehicle in connection with the risk of a breakdown. The device comprises a processor unit which is adapted to receive one or more sensor signals SS which indicate the state of at least one system or a component in the vehicle. The processor unit is adapted to: analyze the condition based on a first set of rules, and generate an error signal depending on the result of the analysis, the error signal indicating a fault in the system or a component, deciding at least one action for the vehicle at least according to a second set of rules for said inaccuracy and a third set of rules for the traffic system in which the vehicle operates; generate one or more control signal (s) that realize the action or actions; send Still at least one control system in the vehicle, the vehicle being regulated accordingly. The invention also relates to a method for regulating an autonomous vehicle (Figure 3).
    公开号:SE1350334A1
    申请号:SE1350334
    申请日:2013-03-19
    公开日:2014-09-20
    发明作者:Jon Andersson；Joseph Ah-King；Tom Nyström
    申请人:Scania Cv Ab；
    IPC主号:
    专利说明:

    2 carry out their task as quickly as possible without making mistakes. Autonomous vehicles have, among other things, been developed for use 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 approach the work area of the autonomous vehicles, they normally cause a break in work due to safety reasons. When the work area eats is free, the autonomous vehicles can be ordered to resume work.
    The autonomous vehicle uses information regarding the road, the surroundings and other aspects that affect the travel to automatically regulate the throttle, braking and steering. A careful assessment and identification of the planned progress is necessary to assess whether a road is passable and is necessary to be able to successfully replace a person's assessment 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 find, for example, a passable road past objects that may be on the road. In order to be able to replace the human perception ability with an autonomous system, this means, among other things, being able to perceive objects in an accurate way in order to be able to effectively regulate the vehicle so that you steer past these objects.
    The technical methods used to identify an object adjacent to 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 distances. These are often referred to as LIDAR (Light Detection and Flanging) 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 with GPS (Global Positioning System) 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. 3 Autonomous vehicles are used today as load carriers in, for example, the mining industry - both in opencast mines and underground mines. An accident in a bottleneck such as a transport link or in a mining town in many cases immediately stops the entire production chain with significant loss of income as a result. In primitive, driver-controlled vehicles, the driver is usually responsible for listening for noise and "recognizing" the condition of the vehicle and, in the event of an imminent accident, immediately moving the vehicle to a safe place where the risk of disruption to the production system is minimized. JP-O3201111-A describes that a production line can be prevented from being stopped by examining the accumulated distance traveled when an autonomous vehicle reaches a station, and deciding whether or not the vehicle should continue to travel based on the distance traveled. -2011 / 0241862-A1 describes a method and a system for ensuring continued operation of a partially autonomous vehicle. Several conditions are monitored that are necessary for a preferred and reliable use of the partially autonomous vehicle. An error handling and degradation strategy can be initiated which is configured to operate the vehicle to a preferred condition in case the driver is unable to control a vehicle manually. The driver is warned first, and then the vehicle can, for example, be maneuvered to the side of the road and stopped there.
    In a traffic system comprising a number of autonomous vehicles, an improved system is needed than those described above in order to be able to adapt the regulation of the autonomous vehicles with a greater variation so that faults detected in the vehicles do not affect the overall efficiency of the traffic system.
    The object of the invention is thus to provide an improved system for regulating an autonomous vehicle in a traffic system in the event of a suspected fault in the vehicle, taking into account the overall efficiency of the traffic system.
    Summary of the invention 4 According to a first aspect, the object is achieved with a device for regulating an autonomous vehicle in connection with the risk of a breakdown according to the preamble of the first independent claim. The device comprises a processor unit which is adapted to receive one or more sensor signals S1-Sk which indicate the state of at least one system or a component in the vehicle. The processor unit is adapted to analyze the state based on a first set of rules, and generate an error signal depending on the result of the analysis, the error signal indicating an error in at least the system or component.
    The processor unit is further adapted to decide on at least one measure for the vehicle at least according to a second set of rules for said fault and a third set of rules for the traffic system in which the vehicle operates, and to generate one or more control signal (s) SCONTR which realizes the measure or measures and send SCONTR to a control system in the vehicle. The vehicle is then regulated accordingly.
    By adding this functionality to the vehicle, with the aim of automatically regulating the vehicle in the event of a risk of production disruption or loss, an increased total productivity can be achieved. The vehicle can, for example, be driven to a safe place or directly to a service point.
    According to a second aspect, the object of the invention is achieved with a method for controlling an autonomous vehicle according to the second independent claim.
    Preferred embodiments are defined by the dependent claims, which will be described with reference to the accompanying figures.
    Brief description of the figures Figure 1 schematically shows a part of a traffic system with three autonomous vehicles shown here.
    Figure 2 shows an autonomous vehicle comprising a device according to an embodiment of the invention.
    Figure 3 shows a device according to an embodiment of the invention. Figure 4 shows a flow chart of the method according to an embodiment of the invention.
    Detailed Description of Preferred Embodiments of the Invention Figure 1 schematically shows a traffic system comprising three autonomous vehicles 2 traveling along a road. The arrows in the autonomous vehicles 2 show their respective direction of travel. The autonomous vehicles 2 can communicate with a line center 1 via eg V2 | communication (Vehicle-to-Infrastructure) 3 and / or with each other via eg V2V communication (Vehicle-to-Vehicle) 4. This communication is wireless and can e.g. take place via a WLAN protocol (Wireless Local Area Network) IEEE 802.11, for example IEEE 802.1 1 p. However, other wireless communication methods are also conceivable. The control center 1 organizes the autonomous vehicles 2 and gives them assignments to perform. When an autonomous vehicle has been given an assignment, the vehicle can independently ensure that the assignment is performed. An assignment can, for example, consist of an instruction to pick up goods at a goods collection point A. The vehicle 2 then has the capacity to determine its current position, determine a road from the current position to the goods collection point A, and get there. Along the way, the vehicle must also have the capacity to give way to obstacles and handle other autonomous vehicles 2 that may have a more important task and must be given priority. Figure 2 shows an autonomous vehicle 2 with a device 5 which will be described next. The device 5 can for instance be a computer in the vehicle 2, or a control unit (ECU - Electronic Control Unit). The device 5 is adapted to communicate with different units and components in the vehicle via one or more different networks in the vehicle 2, such as a wireless network, via CAN (Controller Area Network), LNN (Local Interconnect Network) or Flexray etc.
    Figure 3 shows a device 5 for regulating an autonomous vehicle 2 in connection with the risk of a breakdown. The device 5 comprises a processor unit 6 which is adapted to receive one or more sensor signals S1-Sk which indicate the state of at least one system or a component in the vehicle 2. Sensor signals Si-Sk may 6 come from sensors which monitor systems and / or components in vehicle, and transmitted over any of the networks described above. A system can be, for example, a cooling system, engine system, gearbox, exhaust system or pneumatic system. A component can be, for example, a wheel bearing, a drive joint, a brake pad, etc. The one or more sensor signals Sj-Sk can, for example, indicate acceleration, temperature, vibrations, frequency, pressure and / or exhaust gases.
    The processor unit 6 is further adapted to analyze the state based on a first set of rules, and generate an error signal depending on the result of the analysis. The error signal indicates a fault in the system or component. The first set of rules may, for example, include threshold values for the one or more different sensor signals Sl-Sk depending on which system or component they come from. A sensor signal S1 can, for example, indicate the engine temperature of the vehicle 2. This engine temperature can then be compared with a threshold value for the engine temperature that should not be exceeded without there being a risk of the engine failing. If the temperature exceeds the threshold value, it is indicated in the error signal. The sensor signals Sj-Sk can also include information about which system or component they are monitoring. In this way, the processor unit 6 can know which analysis is to be performed for each sensor signal Sj-Sk. Other examples of faults that can be determined are leaking brake fluid from pneumatic systems, hot wheel bearings, leaking coolant, faults in the exhaust gas purification, vibrations, noise, etc. Faults in the exhaust gas purification can be determined by sensing and analyzing the exhaust gases coming out of the exhaust system. Vibrations and noises can be detected using frame-mounted accelerators.
    The processor unit 6 can also be adapted to make a more complex analysis.
    For example, a number of sensed parameters can be used to make a safer analysis, and can also be combined with other vehicle-specific parameters such as which gear is engaged, the number of teeth each gear has, the vehicle's speed, etc. When, for example, problems occur in the gearbox, this can first enter the processor unit 6 as a sensed temperature and a sensed frequency on the gearbox. The temperature can be sensed with a temperature sensor, 7 and the frequency through, for example, an accelerator. Because the processor unit 6 knows which gear is engaged, and how many teeth each gear has, the processor unit 6 can determine what frequency the gearbox should have. If the sensed frequency has exceeded the frequency that the gearbox should have at the same time as the sensed temperature has exceeded a threshold value for the gearbox temperature, the elevated temperature and the elevated frequency can be traced to something being wrong with the gearbox. The error signal can then indicate that there is a fault in the gearbox, and that the gearbox has an elevated frequency and an elevated temperature. Appropriate action can then be taken based on where the fault is located. The first set of rules may, for example, include prediction methods and / or probability methods to assess whether the system or component will soon become broken or broken, respectively.
    The device 5 may also comprise a computer memory 7 for storing sensor signals S1-Sk during time to analyze trends etc. The computer memory 7 may also comprise instructions for the processor unit 6 to be able to perform the steps described herein. Alternatively or as a complement, the processor unit 6 may comprise memory capacity for storing instructions, etc. The processor unit 6 may, for example, comprise a CPU (Computer Programmable Unit). The processor unit 6 and the computer memory 7 are preferably adapted to communicate with each other.
    Based on the error signal, the processor unit 6 is then adapted to decide at least one action for the vehicle 2 at least according to a second set of rules for the error and a third set of rules for the traffic system in which the vehicle 2 operates. The second set of rules for error in the system or component includes rules for what consequences the error has for the vehicle 2 depending on which error has occurred. If the fault is, for example, leaking brake fluid, there is a high risk that the vehicle, for example, will stop and block the way for other vehicles. Leaking coolant is also an example of a fault that requires quick action. The measure is therefore also decided according to a third set of rules for the traffic system in which the vehicle 2 operates. The third set of rules for the traffic system preferably includes rules for the efficiency of the traffic system, ie how the vehicle 2 should act based on how it is affected by the error. the entire traffic system. If the vehicle 2 drives along a stretch with a lot of traffic, and faults in the vehicle 2 are detected which puts the vehicle 2 at risk of an emergency breakdown and stop the traffic, the vehicle 2 should, according to one embodiment, drive to a safe place as soon as possible. If the vehicle 2 drives along a section with little traffic when a risk of accident is detected, and is judged to need to drive along a section with a lot of traffic to get to a place where the vehicle 2 can be repaired, it may be more advantageous from the traffic system's efficiency to let the vehicle 2 crashes where it is, than to take the risk that the vehicle 2 starts the journey towards the repair site, crashes and stops traffic along the route with a lot of traffic. If the vehicle 2 is in a one-way tunnel when a fault in the vehicle 2 is detected, and the vehicle 2 is at risk of crashing, the vehicle 2 should drive out of the tunnel as soon as possible to ensure that it does not risk stopping traffic. These rules for the traffic system can be predetermined rules that describe which roads are usually busier, where tunnels are located, where important transport lines are located, etc. The rules can also include obtaining information about the traffic system, about the traffic in the traffic system, etc., and use this information to determine an appropriate action. This can be done via V2V or V2 | information, or through an ambient signal SENV which will be described in more detail below.
    The processor unit 6 is further adapted to generate one or more control signal (s) SCONTR which realize the one or more measures, and to send the control signals SCONTR to at least one control system 8 in the vehicle 2, the vehicle 2 being regulated accordingly. In this way, in the event of a fault in the vehicle 2, vehicle 2 can act in the best interests of the entire traffic system.
    An action may include, for example, finding the shortest route to a safe place.
    The control signal SCONTR then indicates a path for the autonomous vehicle 2 to reach a safe place. To find a shortest path to a safe location, the processor unit 6 is adapted to receive a position signal Spos indicating the position of the vehicle, for example from a GNSS unit (Global Navigation Satellite 20 9 System) in the vehicle 2. One or more safe locations may be predetermined, and the processor unit 6 can then be adapted to find the nearest safe place based on the position of the vehicle 2. Through, for example, a map for the traffic system, a road can be determined, and control signals are generated so that the vehicle 2 can be regulated to get there. The birds for the traffic system may, for example, include that the vehicle 2 may not travel on certain roads when a fault is discovered. According to another embodiment, the measure comprises finding the best way to a safe place from a production perspective. The control signals SCONTR then indicate a path for the autonomous vehicle 2 to get to this place. For example, the best route from a production perspective may be to take a route around an entire transport route so as not to risk interrupting the transports.
    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 measurement for a receiver. The American GPS system is the most famous GNSS system, but in addition there are the Russian GLONASS and the future European Galileo. The position of the vehicle 2 can also be determined by monitoring the signal strength from several nearby wireless network access points (WiFi). Another way of determining the position is to measure the number of wheel revolutions and, with the aid of the circumference of the wheels, determine how far the vehicle 2 has traveled. The position of the vehicle 2 in relation to a map can be determined, and in this way you can always know where the vehicle is.
    A safe place can for example be a predetermined place in the traffic system where the vehicle 2 can be placed without disturbing the other vehicles in the traffic system. It can also be a place where the vehicle 2 can be repaired or visually inspected, automatically or manually. The site can be a building where the entire vehicle 2 is automatically scanned for leakage of various fluids and photographed with thermal imaging cameras to find areas (wheel bearings, brakes, driveline components) with elevated temperature levels. Data from the scan can then be communicated to the vehicle 2 or the control center 1, which then, in combination with already saved vehicle internal data, decides whether further work is appropriate. The processor unit 6 can thus be adapted to receive this data, as well as analyze and make decisions also based on this data. Alternatively, the control center 1 can make a decision based on data from the scan and possibly also on sensor signals S1-Sk or analysis already made in the processor unit 6 and which is communicated via V21 to the control center 1. For this purpose, the device may be provided with a unit 9 for wireless communication adapted to receive data from the processor unit 6 and generate wireless signals 3 which the control center 1 can receive. The unit for wireless communication can also be adapted to receive wireless signals 3 with data and to transmit this data to the processor unit 6. This decision can then be communicated back to the vehicle 2. Scanning can also or instead take place at scheduled times. The measure may also comprise determining an advantageous speed for the autonomous vehicle 2. If the fault has been found to be for hot wheel bearings, as described above, then it is for the vehicle 2 in which the fault has been detected slower to drive slowly to reach the final destination. However, a higher speed may be better in terms of the efficiency of the entire traffic system. If the fault has been found to be leaking coolant or leaking brake fluid, the speed of the vehicle 2 according to one embodiment shall be as high as the vehicle 2 and the traffic system allow. If the vehicle 2 has to travel along a road with other vehicles, the vehicle 2 can adapt its speed to the speed of the other vehicles so as not to stop the traffic.
    The processor unit 6 may also be adapted to take into account the distance to the safe location when determining an advantageous speed for the autonomous vehicle 2. The processor unit 6 may then be adapted to determine the distance to the safe location based on the determined road there. The determined route is determined by information about the vehicle's position, information about where the safe place is, map information and the third set of rules for the traffic system in which the vehicle 2 operates. In case an excessive engine temperature has been determined and it is a short way to the safe place, thus a length of the road below a predetermined ll limit value, the vehicle 2 can have a relatively higher speed than if the road had been longer to the safe place.
    According to one embodiment, the processor unit 6 is also adapted to receive an ambient signal SENV which indicates at least one ambient parameter, the decision of at least one measure also being based on this at least one ambient parameter. The environmental parameter can, for example, include information about the number of vehicles along a certain road, road conditions, temperature, traffic accidents, etc. This information can then be included in the decision on action. The ambient signal SENV can be, for example, a wireless signal from another vehicle, from the control center 1 or from a roadside unit adapted for wireless communication. The ambient signal SENV can then be received in the unit 9 for wireless communication. The ambient signal SENV can instead come from a sensing unit in the vehicle 2 such as a camera unit, a laser unit, a radar unit or a temperature unit etc. The information obtained by these units can be analyzed, for example in each unit, in a separate analysis unit and / or in the processor unit 6 to obtain one or more ambient parameters.
    The ambient signal SENV can also be an interleaved signal that includes information from a plurality of the above units.
    According to an example, the processor unit 6 receives a sensor signal S1 which indicates a temperature of a wheel bearing. This temperature is analyzed according to a first set of rules which in this case means comparing the temperature of the wheel bearing with a predetermined threshold value for the temperature of the wheel bearing. If the temperature of the wheel bearing is greater than the threshold value, an error signal is generated which indicates the error that the wheel bearing has too high a temperature. The processor unit 6 is then adapted to decide on a measure for the vehicle based on how the high temperature of the wheel bearing will affect the vehicle 2, according to the second set of rules for the fault, and the third set of rules for the traffic system in which the vehicle 2 operates. for example, state that the too high temperature in the wheel bearing does not give any risk of an immediate stop of the vehicle 2, but there is a risk that the vehicle 2 will crash further ahead 12 and the wheel bearing should be replaced. The 2 speed of the vehicle should also be kept low. If the vehicle 2 is, for example, on a road where it does not interfere with another vehicle, then the third set of rules may state that the speed of the vehicle 2 must be adapted to a low speed, and that a fastest road to a safe place must be determined. The measures to regulate the vehicle's 2 speed to a low speed and find the fastest route to a safe place can then be determined. If the vehicle 2 is instead in the middle of an important production line with a lot of traffic, the third set of rules may state that the speed of the vehicle 2 must be adapted to the speed of the other vehicles in order not to disturb the production. The measures to regulate the speed of the vehicle 2 to an adapted speed after the other vehicles and to find a way to a safe place that does not disturb the production line can then be determined. According to the third set of rules for the traffic system, the processor unit can be adapted to match the vehicle 2's position with information about where production lines, tunnels, a lot of traffic, etc. are located and thus find out if the vehicle 2 risks interfering with the traffic system's efficiency.
    The invention also relates to a method for controlling an autonomous vehicle 2 which will now be illustrated with reference to the flow chart in Figure 4. The method comprises a first step A1) which comprises receiving one or more sensor signals Sj-Sk indicating the state of at least one system or component in the vehicle 2. Sensor signals Sj-Sk can, for example, indicate acceleration, temperature, vibrations, frequency, pressure and / or exhaust gases, etc.
    In a second step A2), the state is analyzed based on a first set of rules, and an error signal is generated depending on the result of the analysis, the error signal indicating an error in the at least one system or component. In a third step A3), at least one action for the vehicle 2 is decided at least according to a second set of rules for the fault and a third set of rules for the traffic system in which the vehicle 2 operates. According to one embodiment, the set of rules for the traffic system comprises rules for the efficiency of the traffic system.
    The decision can also be based on an ambient parameter from an ambient signal SENV. The method can then in step A1) also comprise receiving this ambient signal SENV which indicates an ambient parameter. In a fourth step A4), the vehicle 2 is regulated in accordance with the measure or measures.
    According to one embodiment, the measure comprises finding a shortest path to a safe place. According to another embodiment, the measure comprises finding the best way to a safe place from a production perspective. Action may also include determining an advantageous speed for the autonomous vehicle. The distance to the safe location can be taken into account to determine an advantageous speed for the autonomous vehicle. Examples and advantages of these embodiments have been explained in connection with the device.
    The invention also relates to a computer program P in an autonomous vehicle 2, wherein the computer program P comprises program code for causing the device 5 to perform the steps according to the method. Figure 3 shows the computer program P as part of the computer memory 7. The computer program P is thus stored on the computer memory 7. The computer memory 7 is connected to the processor unit 6, and when the computer program P is executed by the processor unit 6, at least parts of the methods described herein are performed. The invention further comprises a computer program product comprising program code stored on a computer readable medium for performing the method steps described herein, when the program code is run on the device 5.
    The present invention is not limited to the preferred embodiments described above. Various alternatives, modifications and equivalents can be used.
    The above embodiments are therefore not to be construed as limiting the scope of the invention as defined by the appended claims.
    权利要求:
    Claims (18)
    [1]
    Device (5) for regulating an autonomous vehicle (2) in connection with the risk of a breakdown, the device (5) comprising a processor unit (6) which is adapted to receive one or more sensor signals S1-Sk which indicate the state of at least one system or component of the vehicle (2); characterized in that the processor unit (6) is adapted to: - analyze said state based on a first set of rules, and generate an error signal depending on the result of the analysis, the error signal indicating an error in said at least one system or component; - decide on at least one measure for the vehicle at least according to a second set of rules for said defect and a third set of rules for the traffic system in which the vehicle (2) operates; - generating one or more control signal (s) SCONTR which realizes said action (s); sending said control signal (s) SCONTR to at least one control system (8) in the vehicle (2), the vehicle (2) being regulated accordingly.
    [2]
    The device according to claim 1, wherein the processor unit (6) is also adapted to receive an ambient signal SENV indicating at least one ambient parameter, said decision of at least one measure also being based on said at least one ambient parameter.
    [3]
    Device according to claim 1 or 2, wherein said third set of rules for the traffic system comprises rules for the efficiency of the traffic system.
    [4]
    Device according to any one of the preceding claims, wherein said measure comprises finding a shortest path to a safe place, said control signals SCONTR indicating a path for the autonomous vehicle (2) to reach a safe place.
    [5]
    Device according to any one of claims 1 to 3, wherein said measure comprises finding the best way from a production perspective to a safe place, said control signals SCONTR indicating a path for the autonomous vehicle (2) to reach a safe place .
    [6]
    Device according to any one of claims 4 or 5, wherein said measure also comprises determining an advantageous speed for the autonomous vehicle (2) -
    [7]
    Device according to claim 6, wherein said processor unit (6) is adapted to also take into account the distance to the safe place when determining an advantageous speed for the autonomous vehicle (2).
    [8]
    Device according to any one of the preceding claims, wherein said one or more sensor signals S1-Sk indicate acceleration, temperature, vibrations, frequency, pressure and / or exhaust gases.
    [9]
    A method of controlling an autonomous vehicle (2), comprising the steps of receiving one or more sensor signals S1-Sk indicating the state of at least one system or component of the vehicle (2); analyzing said state based on a first set of rules, and generating an error signal depending on the result of the analysis, the error signal indicating an error in said at least one system or component; - decide at least one measure for the vehicle (2) at least according to a second set of rules for said fault and a third set of rules for the traffic system in which the vehicle (2) operates; - control the vehicle (2) in accordance with the measure or measures.
    [10]
    The method of claim 1, comprising the step of receiving an ambient signal SENV indicating an ambient parameter, said decision of at least one action also being based on said ambient parameter. 16
    [11]
    A method according to claim 9 or 10, wherein said set of rules for the traffic system comprises rules for the efficiency of the traffic system.
    [12]
    A method according to any one of claims 9 to 11, wherein said step comprises finding a shortest path to a safe location.
    [13]
    A method according to any one of claims 9 to 12, wherein said eating measure comprises finding the best way from a production perspective to a safe place.
    [14]
    A method according to any one of claims 9 to 13, wherein said act of eating also comprises determining an advantageous speed for the autonomous vehicle.
    [15]
    The method of claim 14, further comprising taking into account the distance to the safe location when determining an advantageous speed for the autonomous vehicle.
    [16]
    A method according to any one of claims 9 to 15, wherein said one or more sensor signals S1-Sk indicate acceleration, temperature, vibrations, frequency, pressure and / or exhaust gases.
    [17]
    Computer program (P) in an autonomous vehicle, said computer program (P) comprising program code for causing a device (5) to perform the steps according to any one of claims 9-16.
    [18]
    A computer program product comprising a program code stored on a computer readable medium for performing the method steps according to any one of claims 9-16, when said program code is executed in a device (5).
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    同族专利:
    公开号 | 公开日
    SE540269C2|2018-05-22|
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    引用文献:
    公开号 | 申请日 | 公开日 | 申请人 | 专利标题
    CN110147101A|2019-05-13|2019-08-20|中山大学|A kind of end-to-end distributed robots formation air navigation aid based on deeply study|JPH03201111A|1989-12-28|1991-09-03|Omron Corp|Unmanned vehicle controller|
    US7979174B2|2007-09-28|2011-07-12|Honeywell International Inc.|Automatic planning and regulation of the speed of autonomous vehicles|
    EP2317412A1|2009-10-23|2011-05-04|BAE SYSTEMS plc|Safety management system|
    US8618922B2|2010-03-30|2013-12-31|GM Global Technology Operations LLC|Method and system for ensuring operation of limited-ability autonomous driving vehicles|
    US8509982B2|2010-10-05|2013-08-13|Google Inc.|Zone driving|US10373259B1|2014-05-20|2019-08-06|State Farm Mutual Automobile Insurance Company|Fully autonomous vehicle insurance pricing|
    US9972054B1|2014-05-20|2018-05-15|State Farm Mutual Automobile Insurance Company|Accident fault determination for autonomous vehicles|
    US10599155B1|2014-05-20|2020-03-24|State Farm Mutual Automobile Insurance Company|Autonomous vehicle operation feature monitoring and evaluation of effectiveness|
    US10026130B1|2014-05-20|2018-07-17|State Farm Mutual Automobile Insurance Company|Autonomous vehicle collision risk assessment|
    DE102014212384A1|2014-06-27|2015-12-31|Robert Bosch Gmbh|Device and method for operating a vehicle|
    US10832327B1|2014-07-21|2020-11-10|State Farm Mutual Automobile Insurance Company|Methods of providing insurance savings based upon telematics and driving behavior identification|
    US20200219197A1|2014-11-13|2020-07-09|State Farm Mutual Automobile Insurance Company|Personal insurance policies|
    DE102015002913B4|2015-03-06|2019-10-24|Audi Ag|Method for the driverless operation of a motor vehicle and motor vehicle|
    US9869560B2|2015-07-31|2018-01-16|International Business Machines Corporation|Self-driving vehicle's response to a proximate emergency vehicle|
    US9483948B1|2015-08-07|2016-11-01|International Business Machines Corporation|Automated control of interactions between self-driving vehicles and pedestrians|
    US9785145B2|2015-08-07|2017-10-10|International Business Machines Corporation|Controlling driving modes of self-driving vehicles|
    US9721397B2|2015-08-11|2017-08-01|International Business Machines Corporation|Automatic toll booth interaction with self-driving vehicles|
    US9718471B2|2015-08-18|2017-08-01|International Business Machines Corporation|Automated spatial separation of self-driving vehicles from manually operated vehicles|
    US9481366B1|2015-08-19|2016-11-01|International Business Machines Corporation|Automated control of interactions between self-driving vehicles and animals|
    US9896100B2|2015-08-24|2018-02-20|International Business Machines Corporation|Automated spatial separation of self-driving vehicles from other vehicles based on occupant preferences|
    US9870649B1|2015-08-28|2018-01-16|State Farm Mutual Automobile Insurance Company|Shared vehicle usage, monitoring and feedback|
    US9731726B2|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|
    US9513632B1|2015-09-16|2016-12-06|International Business Machines Corporation|Driving mode alerts from self-driving vehicles|
    US9566986B1|2015-09-25|2017-02-14|International Business Machines Corporation|Controlling driving modes of self-driving vehicles|
    US9481367B1|2015-10-14|2016-11-01|International Business Machines Corporation|Automated control of interactions between self-driving vehicles and animals|
    US9834224B2|2015-10-15|2017-12-05|International Business Machines Corporation|Controlling driving modes of self-driving vehicles|
    US9751532B2|2015-10-27|2017-09-05|International Business Machines Corporation|Controlling spacing of self-driving vehicles based on social network relationships|
    US9944291B2|2015-10-27|2018-04-17|International Business Machines Corporation|Controlling driving modes of self-driving vehicles|
    US10607293B2|2015-10-30|2020-03-31|International Business Machines Corporation|Automated insurance toggling for self-driving vehicles|
    US10176525B2|2015-11-09|2019-01-08|International Business Machines Corporation|Dynamically adjusting insurance policy parameters for a self-driving vehicle|
    US9791861B2|2015-11-12|2017-10-17|International Business Machines Corporation|Autonomously servicing self-driving vehicles|
    US10061326B2|2015-12-09|2018-08-28|International Business Machines Corporation|Mishap amelioration based on second-order sensing by a self-driving vehicle|
    US10249109B1|2016-01-22|2019-04-02|State Farm Mutual Automobile Insurance Company|Autonomous vehicle sensor malfunction detection|
    US9940834B1|2016-01-22|2018-04-10|State Farm Mutual Automobile Insurance Company|Autonomous vehicle application|
    US11242051B1|2016-01-22|2022-02-08|State Farm Mutual Automobile Insurance Company|Autonomous vehicle action communications|
    US10395332B1|2016-01-22|2019-08-27|State Farm Mutual Automobile Insurance Company|Coordinated autonomous vehicle automatic area scanning|
    US10324463B1|2016-01-22|2019-06-18|State Farm Mutual Automobile Insurance Company|Autonomous vehicle operation adjustment based upon route|
    US10134278B1|2016-01-22|2018-11-20|State Farm Mutual Automobile Insurance Company|Autonomous vehicle application|
    US9836973B2|2016-01-27|2017-12-05|International Business Machines Corporation|Selectively controlling a self-driving vehicle's access to a roadway|
    US10685391B2|2016-05-24|2020-06-16|International Business Machines Corporation|Directing movement of a self-driving vehicle based on sales activity|
    US10571908B2|2016-08-15|2020-02-25|Ford Global Technologies, Llc|Autonomous vehicle failure mode management|
    US10054947B2|2016-08-17|2018-08-21|Omnitracs, Llc|Emergency stopping for autonomous commercial vehicles|
    US10093322B2|2016-09-15|2018-10-09|International Business Machines Corporation|Automatically providing explanations for actions taken by a self-driving vehicle|
    US10643256B2|2016-09-16|2020-05-05|International Business Machines Corporation|Configuring a self-driving vehicle for charitable donations pickup and delivery|
    SG10201911758YA|2016-12-14|2020-01-30|Uber Technologies Inc|Vehicle management system|
    US9811086B1|2016-12-14|2017-11-07|Uber Technologies, Inc.|Vehicle management system|
    US10395441B2|2016-12-14|2019-08-27|Uber Technologies, Inc.|Vehicle management system|
    US10259452B2|2017-01-04|2019-04-16|International Business Machines Corporation|Self-driving vehicle collision management system|
    US10529147B2|2017-01-05|2020-01-07|International Business Machines Corporation|Self-driving vehicle road safety flare deploying system|
    US10363893B2|2017-01-05|2019-07-30|International Business Machines Corporation|Self-driving vehicle contextual lock control system|
    US10152060B2|2017-03-08|2018-12-11|International Business Machines Corporation|Protecting contents of a smart vault being transported by a self-driving vehicle|
    US10569784B2|2017-09-28|2020-02-25|Waymo Llc|Detecting and responding to propulsion and steering system errors for autonomous vehicles|
    US10611381B2|2017-10-24|2020-04-07|Ford Global Technologies, Llc|Decentralized minimum risk condition vehicle control|
    US10726645B2|2018-02-16|2020-07-28|Ford Global Technologies, Llc|Vehicle diagnostic operation|
    US10696307B2|2018-07-10|2020-06-30|Ford Global Technologies, Llc|Anomaly detector for vehicle control signals|
    DE102018212025A1|2018-07-19|2020-01-23|Robert Bosch Gmbh|Method for operating an autonomous vehicle and autonomous vehicle|
    DE102019205480A1|2019-04-16|2020-10-22|Robert Bosch Gmbh|Method for operating a team, team, convoy|
    US11242067B2|2019-05-14|2022-02-08|Liebherr Mining Equipment Newport News Co.|Interlock system for autonomous vehicle|
    CN111986478A|2020-08-20|2020-11-24|杭州海康威视系统技术有限公司|Vehicle analysis method, device, platform, system and computer storage medium|
    法律状态:
    优先权:
    申请号 | 申请日 | 专利标题
    SE1350334A|SE540269C2|2013-03-19|2013-03-19|Device and method for regulating an autonomous vehicle|SE1350334A| SE540269C2|2013-03-19|2013-03-19|Device and method for regulating an autonomous vehicle|
    DE112014001059.6T| DE112014001059T5|2013-03-19|2014-03-06|Apparatus and method for controlling an autonomous vehicle with a fault|
    BR112015019996A| BR112015019996A2|2013-03-19|2014-03-06|device and method for controlling an autonomous vehicle with a failure|
    PCT/SE2014/050280| WO2014148976A1|2013-03-19|2014-03-06|Device and method for controlling an autonomous vehicle with a fault|
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