WO2018085107A1 - Mesure d'écart pour déplacement de véhicules en convoi - Google Patents

Mesure d'écart pour déplacement de véhicules en convoi Download PDF

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Publication number
WO2018085107A1
WO2018085107A1 PCT/US2017/058477 US2017058477W WO2018085107A1 WO 2018085107 A1 WO2018085107 A1 WO 2018085107A1 US 2017058477 W US2017058477 W US 2017058477W WO 2018085107 A1 WO2018085107 A1 WO 2018085107A1
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WO
WIPO (PCT)
Prior art keywords
vehicle
recited
radar
lead
state
Prior art date
Application number
PCT/US2017/058477
Other languages
English (en)
Inventor
Austin B. Schuh
Stephen M. Erlien
Stephan Pleines
John L. Jacobs
Joshua P. Switkes
Original Assignee
Peloton Technology, Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Priority claimed from PCT/US2016/060167 external-priority patent/WO2017070714A1/fr
Priority claimed from US15/590,715 external-priority patent/US20170242443A1/en
Priority claimed from US15/590,803 external-priority patent/US10520581B2/en
Application filed by Peloton Technology, Inc. filed Critical Peloton Technology, Inc.
Priority to JP2019523642A priority Critical patent/JP7152395B2/ja
Priority to CN202211662662.6A priority patent/CN116203551A/zh
Priority to CN201780081508.0A priority patent/CN110418745B/zh
Priority to CA3042647A priority patent/CA3042647C/fr
Priority to EP17867739.9A priority patent/EP3535171A4/fr
Publication of WO2018085107A1 publication Critical patent/WO2018085107A1/fr
Priority to JP2022155699A priority patent/JP7461431B2/ja

Links

Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/66—Radar-tracking systems; Analogous systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/66—Sonar tracking systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S15/00—Systems using the reflection or reradiation of acoustic waves, e.g. sonar systems
    • G01S15/86—Combinations of sonar systems with lidar systems; Combinations of sonar systems with systems not using wave reflection
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/66—Tracking systems using electromagnetic waves other than radio waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S17/00—Systems using the reflection or reradiation of electromagnetic waves other than radio waves, e.g. lidar systems
    • G01S17/87—Combinations of systems using electromagnetic waves other than radio waves
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G01S13/865—Combination of radar systems with lidar systems
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/86—Combinations of radar systems with non-radar systems, e.g. sonar, direction finder
    • G01S13/867—Combination of radar systems with cameras
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9316—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles combined with communication equipment with other vehicles or with base stations
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9318—Controlling the steering
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/93185—Controlling the brakes
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9319—Controlling the accelerator
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/932—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles using own vehicle data, e.g. ground speed, steering wheel direction
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
    • G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
    • G01S13/88—Radar or analogous systems specially adapted for specific applications
    • G01S13/93—Radar or analogous systems specially adapted for specific applications for anti-collision purposes
    • G01S13/931—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles
    • G01S2013/9325—Radar or analogous systems specially adapted for specific applications for anti-collision purposes of land vehicles for inter-vehicle distance regulation, e.g. navigating in platoons
    • G—PHYSICS
    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/22—Platooning, i.e. convoy of communicating vehicles

Definitions

  • the present invention relates generally to systems and methods for enabling vehicles to closely follow one another safely using automatic or partially automatic control.
  • vehicle automation relates to vehicular convoying systems that enable vehicles to follow closely together in a safe, efficient and convenient manner. Following closely behind another vehicle has significant fuel savings benefits, but is generally unsafe when done manually by the driver.
  • vehicle convoying system is sometimes referred to as vehicle platooning systems in which a second, and potentially additional, vehicle(s) is/are autonomously or semi-autonomously controlled to closely follow a lead vehicle in a safe manner.
  • a variety of methods, controllers and algorithms are described for identifying the back of a particular vehicle (e.g., a platoon partner) in a set of distance measurement scenes and/or for tracking the back of such a vehicle.
  • the described techniques can be used in conjunction with a variety of different distance measuring technologies including radar, LIDAR, sonar units or any other time-of-flight distance measuring sensors, camera based distance measuring units, and others.
  • a radar (or other distance measurement) scene is received and first vehicle point candidates are identified at least in part by comparing the relative position of the respective detected objects that they represent, and in some circumstances the relative velocity of such detected objects, to an estimated position (and relative velocity) for the first vehicle.
  • the first vehicle point candidates are categorized based on their respective distances of the detected objects that they represent from the estimated position of the first vehicle.
  • the categorization is repeated for a multiplicity of samples so that the categorized first vehicle point candidates include candidates from multiple sequential samples.
  • the back of the first vehicle is then identified based at least in part of the categorization of the first vehicle point candidates.
  • the identified back of the first vehicle or an effective vehicle length that is determined based at least in part on the identified back of the first vehicle may then be used in the control of the second vehicle.
  • the relative velocity of the vehicles is estimated together with an associated speed uncertainty.
  • object points within the set of detected object points that are moving at a relative speed that is not within the speed uncertainty of the estimated speed are not considered first vehicle point candidates.
  • a current radar (or other distance measurement) sample is obtained from a radar (or other distance measurement) unit.
  • the current distance measurement sample includes a set of zero or more object points.
  • a current estimate of a state of the lead vehicle corresponding to the current sample is obtained.
  • the current state estimate includes one or more state parameters which may include (but is not limited to), a position parameter (such as the current relative position of the lead vehicle), a speed parameter (such as a current relative velocity of the lead vehicle) and/or other position and/or orientation related parameters.
  • the current estimate of the state of the lead vehicle has an associated state uncertainty and does not take into account any information from the current distance measurement sample.
  • a determination is made regarding whether any of the object points match the estimated state of the lead vehicle within the state uncertainty. If so, the matching object point that best matches the estimated state of the lead vehicle is selected as a measured state of the lead vehicle. That measured state of the lead vehicle is then used in the determination of a sequentially next estimate of the state of the lead vehicle corresponding to a sequentially next sample. The foregoing steps are repeated a multiplicities of times to thereby track the lead vehicle.
  • the measured states of the lead vehicle may be used in the control of one or both of the vehicles - as for example in the context of vehicle platooning or convoying systems, in the at least partially automatic control of the trailing vehicle to maintain a desired gap between the lead vehicle and the trailing vehicle.
  • each sample indicates, for each of the object points, a position of a detected object corresponding to such object point (relative to the distance measuring unit).
  • Each current estimate of the state of the lead vehicle includes a current estimate of the (relative) position of the lead vehicle and has an associated position uncertainty. To be considered a valid measurement, the selected matching object point must match the estimated position of the lead vehicle within the position uncertainty.
  • the current estimate of the position of the lead vehicle estimates the current position of a back of the lead vehicle.
  • each sample indicates, for each of the object points, a relative velocity of a detected object corresponding to such object point (relative to the distance measuring unit).
  • Each current estimate of the state of the lead vehicle includes a current estimate of the relative velocity of the lead vehicle and has an associated velocity uncertainty. To be considered a valid measurement, the selected matching object point must match the estimated relative velocity of the lead vehicle within the velocity uncertainty.
  • the state uncertainty is increased for the sequentially next estimate of the state of the lead vehicle.
  • GNSS position updates are periodically received based at least in part on detected GNSS positions of the lead and trailing vehicles. Each time a vehicle GNSS position update is received, the estimated state of the lead vehicle and the state uncertainty are updated based on such position update.
  • vehicle speed updates are periodically received based at least in part on detected wheel speeds of the lead and trailing vehicles. Each time a vehicle speed update is received, the estimated state of the lead vehicle and the state uncertainty are updated based on such lead vehicle speed update.
  • a variety of methods, controllers and algorithms are described for fusing sensor data obtained from different vehicles for use in the at least partial automatic control of a particular vehicle. The described techniques are well suited for use in conjunction with a variety of different vehicle control applications including platooning, convoying and other connected driving applications.
  • information about a second vehicle is sensed at a first vehicle using a first sensor on the first vehicle while the first and second vehicles are driving.
  • Information about the second vehicle is also received by the first vehicle from the second vehicle.
  • the received second vehicle information is utilized to help determine whether the sensed information about the second vehicle is a valid measurement of the second vehicle.
  • the first vehicle is then at least partially automatically controlled based at least in part on an aspect of the sensed information about the second vehicle.
  • the first sensor measures a distance to the second vehicle. In some implementations, the first sensor also detects a velocity of the second vehicle relative to the first vehicle. In different embodiments, the first sensor may be any of a radar unit, a LIDAR unit, a sonar unit, a time-of-flight distance sensor, a sensor configured to receive a signal transmitted from a beacon on the second vehicle, a camera, and a stereo camera unit.
  • the received second vehicle information includes one or more of: a global navigation satellite systems (GNSS) position measurement of a current position of the second vehicle; speed information indicative of a speed or relative speed of the second vehicle (as for example wheel speed); and an indication of at least one of an acceleration, an orientation, a steering angle, a yaw rate, a tilt, an incline or a lateral motion of the second vehicle.
  • GNSS global navigation satellite systems
  • the received second vehicle information includes a predicted state of the second vehicle.
  • the predicted state may optionally include one or more of a predicted position, a predicted speed, a predicted acceleration, a predicted orientation, a predicted yaw rate, a predicted tilt, a predicted incline and a predicted lateral motion of the second vehicle.
  • the described approaches are well suited for use in vehicle platooning and/or vehicle convoying systems including tractor-trailer truck platooning applications.
  • FIG. 1 is a block diagram of a representative platooning control architecture.
  • FIG. 2 is a flow chart illustrating a method of determining the effective length of a platoon partner based on outputs of a radar unit.
  • FIG. 4A is a diagrammatic illustration showing exemplary radar object points that might be identified by a radar unit associated with a trailing truck that is following directly behind a lead truck.
  • FIG. 4B is a diagrammatic illustration showing a circumstance where the entire lead truck of FIG 4A is not within the radar unit' s field of view.
  • FIG. 4C is a diagrammatic illustration showing a circumstance where the bounding box associated with the lead truck of FIG 4A is not entirely within the radar unit' s field of view.
  • FIG. 4D is a diagrammatic illustration showing a circumstance where the lead truck is in a different lane than the trailing truck, but its entire bounding box is within the radar unit's field of view.
  • FIG. 5A is a graph that illustrates the relative location (longitudinally and laterally) of a first representative set of partner vehicle radar point candidates that might be detected when following a tractor-trailer rig.
  • FIG. 5B is a histogram representing the longitudinal distances of the detected partner vehicle radar point candidates illustrated in Fig. 5A.
  • FIG. 5C is a plot showing the mean shift centers of the histogram points represented in Fig. 5B.
  • FIG. 5D is a graph that illustrates the relative location (longitudinally and laterally) of a second (enlarged) set of partner vehicle radar point candidates that might be detected when following a tractor-trailer rig.
  • FIG. 5E is a histogram representing the longitudinal distances of the detected partner vehicle radar point candidates illustrated in Fig. 5D.
  • FIG. 5F is a plot showing the mean shift centers of the histogram points represented in Fig. 5E.
  • FIG. 6 is a diagrammatic block diagram of a radar scene processor suitable for use by a vehicle controller to interpret received radar scenes.
  • FIG. 7 is a flow chart illustrating a method of determining whether any particular radar scene reports the position of the back of a partner vehicle and updating the estimator of Fig. 6.
  • FIG. 8 is a representation of a Kalman filter state array and covariance matrix suitable for use in some embodiments.
  • the Applicant has proposed various vehicle platooning systems in which a second, and potentially additional, vehicle(s) is/are autonomously or semi- autonomously controlled to closely follow a lead vehicle in a safe manner.
  • a second, and potentially additional, vehicle(s) is/are autonomously or semi- autonomously controlled to closely follow a lead vehicle in a safe manner.
  • One of the goals of platooning is typically to maintain a desired longitudinal distance between the platooning vehicles, which is frequently referred to herein as the "desired gap". That is, it is desirable for the trailing vehicle (e.g., a trailing truck) to maintain a designated gap relative to a specific vehicle (e.g., a lead truck).
  • the vehicles involved in a platoon will typically have sophisticated control systems suitable for initiating a platoon, maintaining the gap under a wide variety of different driving conditions, and gracefully dissolving the platoon as appropriate.
  • FIG. 1 diagrammatically illustrates a vehicle control architecture that is suitable for use with platooning tractor- trailer trucks.
  • a platoon controller 110 receives inputs from a number of sensors 130 on the tractor and/or one or more trailers or other connected units, and a number of actuators and actuator controllers 150 arranged to control operation of the tractor's powertrain and other vehicle systems.
  • An actuator interface (not shown) may be provided to facilitate communications between the platoon controller 110 and the actuator controllers 150.
  • the platoon controller 110 also interacts with an inter-vehicle communications controller 170 which orchestrates communications with the platoon partner and a NOC communications controller 180 that orchestrates communications with a network operations center (NOC).
  • the vehicle also preferably has selected configuration files that include known information about the vehicle.
  • platoon controller 110 Some of the functional components of the platoon controller 110 include gap regulator 112, mass estimator 114, radar tracker 116 and brake health monitor 118. In many applications, the platoon controller 110 will include a variety of other components as well.
  • Some of the sensors utilized by the platoon controller 110 may include GNSS (GPS) unit 131, wheel speed sensors 132, inertial measurement devices 134, radar unit 137, LIDAR unit 138, cameras 139, accelerator pedal position sensor 141, steering wheel position sensor 142, brake pedal position sensor 143, and various accelerometers.
  • GPS global navigation satellite systems
  • Some of the vehicle actuators controllers 150 that the platoon controller directs at least in part include torque request controller 152 (which may be integrated in an ECU or power train controller); transmission controller 154, brake controller 156 and clutch controller 158.
  • the communications between vehicles may be directed over any suitable channel and may be coordinated by inter-vehicle communications controller 170.
  • DSRC Dedicated Short Range Communications
  • the DSRC protocol e.g. the IEEE 802.1 lp protocol
  • other communications protocols and channels may be used in addition to or in place of a DSRC link.
  • the inter vehicle communications may additionally or alternatively be transmitted over a Citizen's Band (CB) Radio channel, one or more General Mobile Radio Service (GMRS) bands, and one or more Family Radio Service (FRS) bands or any other now existing or later developed communications channels using any suitable communication protocol.
  • CB Citizen's Band
  • GMRS General Mobile Radio Service
  • FSS Family Radio Service
  • the transmitted information may include the current commands generated by the platoon controller such as requested/commanded engine torque, requested/commanded braking deceleration. They may also include steering commands, gear commands, etc. when those aspects are controlled by platoon controller.
  • Corresponding information is received from the partner vehicle, regardless of whether those commands are generated by a platoon controller or other autonomous or semi-autonomous controller on the partner vehicle (e.g., an adaptive cruise control system (ACC) or a collision mitigation system (CMS)), or through other or more traditional mechanisms - as for example, in response to driver inputs (e.g., accelerator pedal position, brake position, steering wheel position, etc.).
  • a platoon controller e.g., an adaptive cruise control system (ACC) or a collision mitigation system (CMS)
  • ACC adaptive cruise control system
  • CMS collision mitigation system
  • the information transmitted between vehicles may also include information about intended future actions. For example, if the lead vehicle knows it approaching a hill, it may expect to increase its torque request (or decrease its torque request in the context of a downhill) in the near future and that information can be conveyed to a trailing vehicle for use as appropriate by the platoon controller.
  • the nature of the expected events themselves can be indicated (e.g., a hill, or curve or exit is approaching) together with the expected timing of such events.
  • the intended future actions can be reported in the context of expected control commands such as the expected torques and/or other control parameters and the timing at which such changes are expected.
  • expected control commands such as the expected torques and/or other control parameters and the timing at which such changes are expected.
  • expected events there are a wide variety of different types of expected events that may be relevant to the platoon control.
  • the communications between the vehicles and the NOC may be transmitted over a variety of different networks, such as the cellular network, various Wi-Fi networks, satellite communications networks and/or any of a variety of other networks as appropriate.
  • the communications with the NOC may be coordinated by NOC communications controller 180.
  • the information transmitted to and/or received from the NOC may vary widely based on the overall system design.
  • the NOC may provide specific control parameters such as a target gap tolerance. These control parameters or constraints may be based on factors known at the NOC such as speed limits, the nature of the road/terrain (e.g., hilly vs. flat, winding vs. straight, etc.) weather conditions, traffic or road conditions, etc.
  • the NOC may provide information such information to the platoon controller.
  • the NOC may also provide information about the partner vehicle including its configuration information and any known relevant information about its current operational state such as weight, trailer length, etc.
  • the vehicles involved in a platoon will typically have one or more radar systems that are used to detect nearby objects. Since radar systems tend to be quite good at determining distances between objects, separation distances reported by the radar unit(s) are quite useful in controlling the gap between vehicles. Therefore, once a platooning partner is identified, it is important to locate that specific partner vehicle in the context of the radar system output. That is, to determine which (if any) of a variety of different objects that might be identified by the radar unit correspond to the targeted partner.
  • the platoon partner will not always correlate to the closest vehicle detected by the radar unit or to the vehicle that is directly in front of the trailing truck.
  • the partner may be out of sight of a host vehicle's radar unit because it is too far away.
  • the partner comes into sight of the radar unit, it becomes important to identify and distinguish that partner from other objects in the radar unit's field of view.
  • a lead truck may change lanes at which point it may not be directly in front of the trailing vehicle, so again, it is important for that the distance between the platoon partners reported by the radar unit be associated with the platoon partner rather than merely the closest vehicle or a vehicle that happens to be directly in front of the trailing truck. There may also be times when the radar unit may not be able to "see" the platooning partner. This could be because an interloper has gotten between the platoon partners or the lead vehicle has maneuvered out of view of the trailing vehicle's radar unit, interference with the radar signals, etc.
  • the position of the partner vehicle is generally known from the GPS based location information that is transmitted to the host vehicle.
  • the GPS system typically reports a location on the tractor, which could for example, be the position of the antenna(s) that receive the GPS signals.
  • the detected GPS position may then be translated to the position of a reference location on the vehicle that is a known distance from the GPS antenna, with the position of that reference location serving as the vehicle's reported GPS position.
  • the specific reference location chosen may vary based on control system preferences.
  • the reference location may be the center of the rear axles of the tractor.
  • the difference between the reported GPS position and the physical back of the vehicle can be significant to the platoon control. Therefore, it is often important to know the distance between the reported vehicle position and the actual back of the vehicle. This is sometimes referred to herein as the "effective vehicle length.”
  • the effective vehicle length is particularly important in the context of a tractor trailer truck where the reported GPS position is typically located somewhere on the cab (tractor) and the distance from the reported GPS position to the back of the trailer may be quite long.
  • trailer lengths on the order of 12-18 meters are common in the U.S. although they can be shorter or longer (indeed much longer in the context of double or triple trailers).
  • the distance from the reported GPS position to the back of the vehicle must also account for the longitudinal distance from the reported GPS position to the front of the trailer and/or any extensions associate with the load. It should be appreciated that in the trucking industry, the effective vehicle length often will not be known since any particular tractor may pull a variety of different trailers and the attachment point between the tractor and trailer is adjustable on the tractor.
  • the logic interpreting the output of the radar unit to have and maintain a good understanding of exactly where the partner vehicle is expected to be relative to the radar unit's field of view regardless of whether the partner vehicle is even in that field of view. This is possible even when no explicit mechanism is provided for identifying the partner because the platooning system preferably has multiple independent mechanisms that can be used to help determine a vehicle's position.
  • a communications link is preferably established between the platooning vehicles.
  • the communications may be established over one or more wireless links such as a Dedicated Short Range Communications (DSRC) link, a cellular link, etc.
  • DSRC Dedicated Short Range Communications
  • the processes used to identify potential platoon partners and to establish the platoon and appropriate communication links may vary widely. By way of example, a few representative techniques are described in U.S. Patent Application Nos. 13/542,622 and 13/542,627 as well as PCT Patent Application Nos. PCT/US2014/030770, PCT/US2016/049143 and PCT/US2016/060167 previously filed by Applicant, each of which is incorporated herein by reference.
  • the platoon controller 110 requests the radar system control logic attempt to find the partner vehicle. More specifically, the trailing vehicle's radar tracker 116 needs to find and thereafter track the back of the lead vehicle in the context of the radar unit's outputs so that its data can be used in gap control.
  • a method particularly well suited for establishing a radar fix on a platoon partner will be described.
  • One aspect of establishing a radar fix is to determine the length of the partner so the GPS position information can be correlated to radar system outputs.
  • radar tracker control logic determines, receives or requests an estimate of the current relative position of the partner vehicle and subscribes to or regularly receives updates regarding the partner vehicle's relative position as they become available as represented by step 203 of Fig. 2.
  • the estimated information may optionally include various additional position related information such as relative velocity of the vehicles, the relative heading of the vehicles, etc.
  • the radar tracker control logic is configured to estimate the current relative position, velocity and orientation (heading) of the partner vehicle based on a variety of sensor inputs from both the host vehicle and the partner vehicle.
  • the platoon partners are in communication with one another and during platooning, they send extensive information back and forth about themselves, including continually updated information about their current location and operating states.
  • some of the location related information that can be helpful to interpreting radar unit data may include information such as the partner vehicle's GPS position, wheel speed, orientation/heading (direction that the vehicle is heading), yaw rate (which indicates the vehicle's rate of turn), pitch, roll and acceleration/deceleration (longitudinal and angular in any of the forgoing directions).
  • Operational related information may also include a variety of other information of interest such the current torque requests, brake inputs, gear, etc.
  • Information about the vehicles may include information such as the make and model of the vehicle, its length (if known), its equipment, estimated weight, etc. Any of these and/or other available information can be used in the position related estimates.
  • one particular position estimator is described below with respect to Figs. 6 and 7.
  • the estimated partner vehicle position related information can come from any appropriate source and the estimation does not need to be made by the radar tracker control logic itself. Additionally, although it is preferred that position and operational information be transmitted in both directions between vehicles, that is not necessary as long as the host vehicle is able to obtain the required information about the partner vehicle(s).
  • the current location related information is updated very frequently. Although the actual frequency of the updates can vary widely based on the nature of the information being updated and the nature of the communication link or vehicle system that provides the information, update frequencies for items such as GPS position and wheel speed received over a DSRC link at frequencies on the order of 10 to 500 Hz, as for example 50 Hz work well although slower and much faster update frequencies may be used as appropriate in other embodiments. Furthermore, although regular updates of the location related information are desirable, there is no need that they be received synchronously or at consistent intervals. [0067] It should be appreciated that when the radar system begins trying to locate the partner vehicle, the partner vehicles may or may not be within the radar unit's field of view.
  • both the host vehicle's position and the partner vehicle's position are generally known based at least on the received GPS data so it is easy to estimate their separation with reasonable certainty.
  • GPS location signals tend to be pretty good, the reported locations may be off by some amount and thus it is better to treat any reported GPS position as an estimate with some appropriate amount of uncertainty rather than treating the reported position as infallible information. More details regarding some specific algorithms that are suitable for estimating the partner vehicle position will be described in more detail below.
  • GPS position readings from commercially available GPS sensors used in vehicle automation applications tend to be accurate within about 2-3 meters in practical road conditions when there is a direct line of sight to at least 4 GPS satellites.
  • some GPS sensors are regularly more precise and no GPS sensors are guaranteed to always be that accurate due to variables such as interference, operations is regions where there is not line of sight visibility to the required number of operational GPS satellites, etc.
  • a bounding box is applied around the estimated relative position of the partner (step 206 of Fig. 2).
  • the purpose of the bounding box is to define a region that the partner vehicle is "expected" to be found in.
  • the logic will thereafter look for radar detected objects located within that bounding box in an effort to identify objects that may correlate to the partner vehicle.
  • the concept of a bounding box is helpful for several reasons. Initially it should be appreciated that the GPS unit will typically report the location of its antenna, which in the context of a tractor-trailer truck is usually on the cab. This detected position is then typically translated to a predefined reference location on the tractor and that translated position is used as the reported GPS position.
  • the reported GPS position for a tractor-trailer will be well in front of the back of the trailer which is (a) the point that is of primary interest to the gap control purposes, and (b) is typically the most prominent feature identified by the radar unit from a trailing platoon partner.
  • the distance between the reported GPS position and the back of the trailer will not be known in many circumstances.
  • One reason for the uncertainty is that a particular tractor (cab) may be used to pull a variety of different trailers (or other loads) which potentially have different lengths. Therefore the effective length of the tractor-trailer combination may vary from trip to trip and from a control standpoint it is generally undesirable to count on the driver to manually input the effective length of the tractor-trailer combination each trip.
  • the reported GPS positions of both platoon partners are subject to a degree of uncertainty.
  • the actual size and geometry of the bounding box used may vary but it is desirable that the region be large enough to encompass the entire range of vehicle lengths and widths that are possible plus a buffer to account of uncertainty in the estimated GPS position.
  • the longitudinal length of the bounding box be longer than any tractor-trailer combination that might be expected to be encountered.
  • U.S. commercial trucking applications involving normal tractor trailer combinations typically don't significantly exceed a combined length of 23 meters.
  • bounding boxes on the order of 32 meters long and 3-4.5 meters, as for example 3.8 meters wide have been found to work well.
  • the tractor-trailer combinations may be longer and therefore longer bounding boxes may be appropriate.
  • the size of the bounding box can be adjusted accordingly to more accurately reflect the expected offset between the GPS position and the back of the trailer - which correlates to the effective vehicle length.
  • the effective length and width of the platoon partner is "known,” it is still desirable to utilize a bounding box greater in size than the reported length and width to accommodate uncertainty in the GPS estimates and the possibility that the load may include a feature that extends beyond the vehicle's reported length.
  • FIG. 3 A representative bounding box 255 applied around a lead truck 251 in a platoon of two trucks is diagrammatically illustrated in Fig. 3.
  • each truck has a GPS unit 258 located on its tractor (cab) and a radar unit 260 located at the front of the cab. It can be seen that the bounding box exceeds the length and width of the lead truck 251.
  • the bounding box may be defined more complexly.
  • the scaled squares of the lateral offset (Y 0ff ) and the relative velocity (V) of the vehicles may be compared to a threshold (Th).
  • Th a threshold
  • a radar point would then be rejected if the sum of these squares exceeds the designated threshold (Th), even if the radar point is within the longitudinal range of the bounding box.
  • the bounding box has the effective appearance of a tube with in a state space map with velocity being the third axis.
  • the logic of such an approach is that if both the measured lateral offset and the measured velocity of a detected object are relatively lower probability matches, then the detected point is less likely to be a match (and therefore more appropriate to disregard for the purposes of identifying the back of a partner vehicle) than if one of those parameters is off but the other very nearly matches the expected value.
  • the bounding box definition may be arranged to change over time. For example, one or more selected dimensions of the bounding box may be reduced as the algorithm begins to develop a better understanding of what radar object sample points are more likely to correspond to the partner vehicle or the back of the partner vehicle.
  • the logic determines whether the entire bounding box is within the other vehicle's radar unit's field of view 263 (step 209). If not, the logic waits for the entire bounding box to come within the radar unit's field of view thereby effectively ignoring the radar system outputs for the purpose of identifying the partner vehicle (although of course the radar system outputs can be used for other purposes such as collision avoidance if desired). There are a variety of reasons why the partner vehicle may not be within or fully within the radar units field of view at any particular time. Initially, it should be appreciated that although the radar unit(s) used to support platooning may be placed at a variety of different locations on the vehicles, they often have a relatively narrow field of view.
  • a forward facing radar unit having a relatively narrow fixed beam in the vicinity of the middle of the front bumper to detect objects in front of the vehicle.
  • Fig. 3 the field of view 263 of radar unit 260 located on the trailing truck 252 is also shown.
  • a forward facing radar unit When a forward facing radar unit is used, it will be unable to see any vehicle behind or to the side of its host vehicle. Even when the partner vehicle is ahead of the radar unit host, it may be out of the field of view if it is too far ahead of the host or is around a corner - as may be the case when a platoon partner is first identified. In some cases a platoon partner can be partially in the radar unit's field of view. A common example of this is when the partner vehicle in an adjacent lane and not far enough ahead for the back of its trailer to be seen by a narrow beamed forward facing radar unit.
  • Figures 4A-4D illustrate a few (of the many) potential relative positioning of two trucks that are in the process of establishing a platoon.
  • the lead truck 251 is directly ahead of the trailing truck 252 and its bounding box 255 is fully within the field of view 263 of trailing truck radar unit 260.
  • the lead truck 251 is in a lane adjacent the trailing truck 252 and some, but not all of the lead truck 251 itself (and thus not all of bounding box 255) is within the field of view 263 of trailing truck radar unit 260.
  • Fig. 4A the lead truck 251 is directly ahead of the trailing truck 252 and its bounding box 255 is fully within the field of view 263 of trailing truck radar unit 260.
  • the lead truck 251 is in a lane adjacent the trailing truck 252 and some, but not all of the lead truck 251 itself (and thus not all of bounding box 255) is within the field of view 263 of trailing truck radar unit 260.
  • the lead truck 251 is in a lane adjacent to the trailing truck 252 and all of the lead truck 251 itself, but not the entire bounding box 255, is within the field of view 263 of trailing truck radar unit 260.
  • the lead truck 251 is again in a lane adjacent the trailing truck 252 but differs from FIGS 4B and 4C in that the entire bounding box 255 associated with lead truck 251 is within the field of view 263 of trailing truck radar unit 260.
  • the partner vehicle identification logic waits at step 209 for the entire bounding box to come within the radar unit's field.
  • the radar system controller logic obtains a next radar sample (step 212) and a current estimate of the partner vehicle's position and velocity relative to itself (step 215).
  • a next radar sample step 212
  • a current estimate of the partner vehicle's position and velocity relative to itself step 215.
  • Commercially available short range radar units utilized in road vehicle applications are typically configured to output their sensed scene at a relatively rapid sample rate. Each scene typically identifies a set of zero or more objects that have been detected as well as the velocity of such objects relative to the radar unit itself.
  • the nature of radar systems is that the transmitted radio waves can be reflected by most anything in their path including both any intended target(s) and potentially a wide variety of different items. Therefore, when trying to establish a platoon, it is important to identify the reflected signal(s) that represent the desired partner and to be able to distinguish that partner from the noise reflected from other objects.
  • the radar unit may receive reflections from multiple different vehicles including any vehicle that is immediately ahead, passing vehicles going in the same or opposite direction objects to the side of the road such as highway or street signs, trees or other objects along the side of the road, etc..
  • the radar system control logic determines whether any of the identified objects are partner vehicle radar point candidates as represented by step 218.
  • Representative objects that might be detected by the radar unit 260 are marked with X's in Figs. 4A-4D.
  • an object detected in the scene must be located within the bounding box in terms of both position and speed. Radar objects located outside of the bounding box are preferably rejected because there is a relatively higher probability that they do not correspond to the partner vehicle. For example, they could correspond to vehicles in adjacent lanes 272, 273, an interloper located between the platoon partners (not shown), objects on the side of the road 274, etc.
  • Objects that do not closely match the expected relative speed of the partner vehicle are also preferably rejected even if they match the expected position aspects of the bounding box longitudinally and laterally because again, it is less likely that they correspond to the platoon partner.
  • a stationary object such as a feature to the side of the road (e.g. a road sign, tree or stationary vehicle), debris in the road, or a detected feature in the road itself (e.g. a pothole, etc.), will appear to be approaching the radar unit at the speed that the host vehicle is traveling at. It is noted that many commercially available radar units will automatically filter out, and therefore don't report, stationary objects. When such a radar unit is used, the stationary objects would not even be identified as part of the radar scene.
  • Some of the reported radar objects may be traveling in the same direction as the host vehicle but are moving at a relative velocity that is different than the expected partner velocity. There is a relatively high probability that such radar objects do not correspond to the partner vehicle and therefore these types of radar points are also preferably discarded.
  • any detected radar objects that appear to match the expected location and speed of the partner within the context of the defined bounding box are considered partner vehicle radar point candidates and are categorized with respect to how far they are longitudinally (along the longitudinal axis of the partner) from the estimated location of the partner (e.g., the partner's GPS position).
  • a histogram is utilized for to this categorization. The number of bins in the histogram may vary. For computational ease, 512 bins divided evenly over the length of the bounding box has been found to work well, although more or less bins can be used as appropriate for any particular application. In implementations that use a bounding box of approximately 32 meters, with 512 bins, each bin corresponds to approximately 6 cm (2-3 inches). If greater resolution is desired, then more bins can be used.
  • the radar when the radar is mounted relatively low on the host vehicle it may detect reflections from the transmission or other items along the truck's undercarriage or other features of the tractor-trailer such as the trailer's landing gear or the back of the tractor and identify those items as separate detected "objects.” Therefore, it is possible (indeed it is relatively common) that any particular sample may identify more than one object that meets the criteria of a partner vehicle radar point candidates. In such circumstances multiple candidates associated with a particular radar sample will be added to the histogram.
  • step 224 a determination is made regarding whether sufficient samples have been obtained to analyze the radar data to identify the partner vehicle in step 224. If not, the logic returns to step 212 where the next sample is obtained and the process repeats until sufficient samples have been obtained to facilitate analysis. If the bounding box moves partially out of the field of view of the radar unit at any point (as represented by the "no" branch from decision block 225), then the logic returns to step 209 where it waits for the bounding box to come back into full view before taking additional samples.
  • the large cluster 290 located furthest back in the histogram typically corresponds to the back of the vehicle and is often (although not always) the largest cluster.
  • Cluster 292 located further forward typically correspond to other features of the partner truck.
  • radar reflections from the forward features tend to be weaker and more sporadically identified as a discrete object by the radar unit, which translates to a smaller cluster in the histogram.
  • the logic follows the yes branch from decision block 224 and flows to step 227 where a clustering algorithm is applied to the histogram data.
  • the trigger point for when processing may start can vary widely based on the needs of any particular system. In general, it is desirable for the histogram to contain enough data points so that the partner vehicle can be accurately identified. In some specific implementations, the histogram must include data from a first threshold worth of samples (e.g., samples corresponding to at least 3 seconds worth of data or 60 samples) and include at least a second threshold worth of partner vehicle radar point candidates (e.g., at least 60 partner vehicle radar points). The thresholds used may vary based on the needs of a particular implementation.
  • the mean shift data is then analyzed to determine whether one of the clusters meets predefined back of partner vehicle criteria in step 230. If so, that cluster is identified as corresponding to the back of the vehicle. (Step 233). Since each cluster corresponds to a designated distance between the partner's reported GPS position and the back of the vehicle, the effective length of the vehicle is defined by the cluster. As noted above, the phrase "effective vehicle length" as used herein corresponds to the distance between the reported GPS position and the back of the vehicle - which is an important distance to know for control purposes. It should be appreciated that this is typically different than the actual length of the vehicle because the reported reference position may not be located at the front of the vehicle.
  • the cluster located closest to the back of bounding box that has over a threshold percentage of the total number of radar points in the histogram is identified as back of the platoon partner vehicle.
  • a further constraint is used that requires that the cluster location not move by more than a certain threshold on the last sample.
  • maximum movement thresholds on the order of 1 mm have been found to work well in some applications. This approach has been found to very reliably identify the radar point that corresponds to the back of a truck even when the radar unit controller has no predetermined knowledge of the length of the vehicle and regardless of the presence of other traffic.
  • the threshold percentage or other characteristics of the histogram used to identify the back of the vehicle may vary based on application.
  • cluster 290 is designated as the back of the lead truck.
  • the back of vehicle criteria used on the clustered histogram data effectively filters any other vehicles traveling within the footprint of the bounding box at very near the same speed as the platoon partner because the bins are small enough that it is highly unlikely that such an interloper can maintain a constant enough gap to fool the algorithm into thinking that the interloper is part of the target (e.g., even if the interloper is traveling at nearly the same speed as the partner vehicle, if it is located within the bounding box, it's position relative to the partner vehicle's position is likely to vary enough to cause the back of partner vehicle test to fail.
  • the back of vehicle criteria also filters out more random objects reported by the radar unit.
  • the back of the partner identification process continues to run or is periodically rerun even after the vehicle length has been determined.
  • the initial length determination is made while the platoon partners are relatively far apart (e.g., over 100 feet).
  • the gap controller may tighten the gap thereby drawing the vehicles closer together.
  • the radar reading are often more precise than they are when the vehicles are 100+ feet apart.
  • more measurement give a better statistical indication of the relative position of the vehicle.
  • Fig. 5D is a plot showing a set of 1700 detected partner vehicle radar point candidates on the same graph as shown in Fig. 5A.
  • the 1700 sample points include the 98 points illustrated in Figs. 5A-5C and were obtained by continuing to run the same radar point classification algorithm.
  • Figs. 5E and 5F show the histogram and mean shift centers respectively for the larger data set.
  • Figs. 5E corresponds to Fig. 5B
  • Fig. 5F corresponds to Fig. 5C. It can be seen that the larger dataset appears to have identified a small cluster 293 located near the front of the lead vehicle and has effectively filtered out some smaller clusters identified in the smaller data set.
  • the histogram and/or mean shift clusters also provide a very good indication of the radar signature of the partner vehicle.
  • This known signature of the partner vehicle can be used in a number of different ways as an independent mechanism for verifying that the proper vehicle is being tracked. For example, in scenarios where GPS data becomes unavailable or communications between the vehicles are disrupted for a period of time, the histogram can be used as a check to verify that the correct vehicle is being tracked by the radar unit.
  • the portion of the truck that can be seen can be compared to the histogram signature to determine the relative positioning of the trucks, which can be used as a measurement for gap control or as part of autonomous or semi-autonomous control of the trailing vehicle.
  • a new histogram in circumstances when radar contact is lost, can be started at an appropriate time and a new histogram can be compared to a stored histogram indicative of the platoon partner. When there is a match, that match can be good independent evidence that radar contact with the platoon partner has been reestablished.
  • newly created histograms can be compared to stored histograms representing the platoon partner at various times during platooning as a way of independently verifying that the platoon partner is still being tracked. This can be a good safety check to verify that the radar unit has not inadvertently switched and locked onto a vehicle that is traveling in parallel next to the platoon partner.
  • the histograms can also be saved as a radar signature of the partner vehicle and shared with other trucks that may later seek to platoon with that vehicle - which can be useful in the initial identification process.
  • the gap between vehicles can be determined using a number of different techniques.
  • One general approach is to use the distance to the platoon partner detected by the radar system. Although radar tends to very accurately measure the distance between vehicles, it is important to ensure that the distance being reported is actually the distance to the platoon partner rather than some other vehicle or feature. There are also times when the partner vehicle is not within the radar' s field of view or the radar or the radar unit is not operating as desired for a brief period.
  • An independent way of determining the distance between the platoon partners is to utilize their respective GPS data. Specifically, the distance between the vehicles should be the difference between the vehicle's respective GPS positions, minus the effective length of the lead vehicle and the offset distance between the front of the trailing vehicle and its GPS receiver.
  • GPS data Limitations of using the GPS data include the fact that the GPS data will not always be available due to factors such as the GPS receivers not having a clear view of sufficient GPS satellites to be able to determine a location or the communication link between vehicles being down for a period of time.
  • the GPS data is also fundamentally limited by the fact that the accuracy of the GPS data, which while good, is often less precise than desired for gap control.
  • Other systems for measuring distances between the platoon partners have their own advantages and limitations.
  • the gap expected at a time in the immediate future can be estimated based on factors such as the current positions, the relative velocities and yaw rates of the vehicles.
  • the respective velocities of the vehicles may also be measured, determined, estimated and/or predicted in a variety of different manners.
  • wheel speed sensors can be used to relatively accurately indicate the current speeds of the respective vehicles.
  • Knowledge of the vehicle's orientation can be used in conjunction with the knowledge of the vehicle's speed to determine its velocity.
  • the radar unit can be used to measure the relative speeds of the platoon partners. Knowledge of other factors such as torque request, vehicle weight, engine characteristics and road grade can be used to predict vehicle speeds in the future.
  • the radar system controller (or another controller whose determinations can be utilized by the radar system controller) includes a position estimator that maintains an estimate of the current position, orientation and relative speed of the partner vehicle relative to the radar unit.
  • a position estimator that maintains an estimate of the current position, orientation and relative speed of the partner vehicle relative to the radar unit.
  • One suitable radar scene processor 600 that includes a position/state estimator 612 is illustrated in Fig. 6.
  • radar scene processor 600 includes gap monitor 610 and a partner identifier 620.
  • the gap monitor 610 is configured to track the position of the back of the partner vehicle based on radar measurements (after the back of the partner vehicle has been identified) and to report radar position and speed measurements corresponding to the back of the partner vehicle to the gap controller and/or any other component interested in such measurements made by the radar unit.
  • One particular implementation of the gap monitoring algorithm will be described below with reference to the flow chart of Fig. 7.
  • the gap monitor 610 includes a position/state estimator 612 having a Kalman filter 615 that is used to determine both the most recent estimate of the position of the partner vehicle relative to the host vehicle and to predict the expected position of the partner vehicle at the time the next radar sample will be taken.
  • the position/state estimator 612 utilizes both the detected radar scenes and other available vehicle state information such as the respective GPS positions, wheel speeds, and inertial measurements of the host and partner vehicles in the estimate of the expected state (e.g. position, velocity etc.) of the leading vehicle. These state estimates can then be used to help interpret the received radar scene.
  • the gap monitor 600 properly identify the radar return object that corresponds to the back of the partner vehicle out of a radar scene that may include a set of detected objects. This helps ensure that the proper detected point is used in the gap control. It is also helpful in identifying situations in which the tracker does not have good confidence regarding which (if any) of the objects detected by the radar in a particular scene sample accurately represent the position of the back of the partner vehicle so that such a sample can be discounted, ignored or otherwise properly handled in the context of the gap control algorithm.
  • One particular Kalman filter design that is well suited for use in the position/state estimator 612 is described below with respect to Fig. 8.
  • the partner identifier 620 includes its own position/state estimator 622, a histogram 624, a clustering algorithm 625 which produces mean shift clusters 626 and partner length estimator 627.
  • the partner identifier 620 executes an algorithm such as the algorithm discussed above with respect to Fig. 2 to identify the back of the partner vehicle.
  • histogram 624 is populated.
  • the histogram is diagrammatically shown as being part of the partner identifier 620, but it should be appreciated that the histogram is merely a data structure that can be physically located at any appropriate location and may be made available to a variety of other processes and controllers within, or external to, the radar tracker 620.
  • the partner length estimator 624 is configured to determine the length of the partner vehicle (including its front and back relative to its GPS reference position) based on the histogram and other available information.
  • the position state estimation, partner detection, partner length estimating and gap monitoring algorithms may be executed on a radar tracking processor dedicated to radar tracking alone, or they may be implemented on a processor that performs other gap or platoon management tasks as well.
  • the respective algorithms may be implemented as distinct computing processes or they may be integrated in various manners with each other and/or other functionality in various computing processes. In other embodiments, discrete or programmable logic may be used to implement the described functionality. It should be apparent that a wide variety of different models can be used to track the position of the back of the partner vehicle relative to the radar unit and to estimate future positions. Two particular position state estimators are diagrammatically illustrated as part of Fig.
  • a method of tracking a partner vehicle and estimating its future position based in part on information received from the radar unit is illustrated in the flow chart of Fig. 7.
  • the trailing vehicle is tracking the position of the back of a lead vehicle, although an analogous process can be used by the lead vehicle to track a following vehicle or for parallel vehicles to track one another.
  • the described method presupposes that we have a reasonable estimate of the location of the back of the partner vehicle - which can initially be determined using the method described above with respect to Fig. 2 or in any other suitable manner. For example, when the effective length of the front vehicle is known, the initial estimate for the relative position of the back of the lead vehicle can be estimated based on GPS position data.
  • One way to determine whether a matching target is to quantify an uncertainty factor in association with the estimated position. If a radar target point is within the range of the uncertainty factor of the expected position, then it can be considered a match.
  • Kalman filtering is used to estimate the position of the back of the partner vehicle and to quantify the uncertainty. Kalman filtering is particularly appropriate because it inherently adjusts the uncertainty level based on the perceived accuracy of the measurements.
  • the closest radar object point identified in the radar scene is treated as the "matching" target.
  • the "closest” match may be selected based on a combination of metrics including longitudinal position, lateral position, relative speeds, etc.
  • the radar tracker transmits the distance to the matched object and relative speed of the matched object to the gap controller 112 as the current gap to and relative speed of, the back of partner vehicle (step 506).
  • the only information transmitted is the longitudinal distance to the back of the trailer and its relative speed. This is because while currently available radar units are generally quite good at measuring distance and relative speed, they are not as good at precisely measuring lateral velocities or providing precise lateral position information regarding identified objects. However, if the radar unit used can accurately measure other useful attributes of the target such as lateral velocities, acceleration, etc., - that information may optionally be transmitted as well.
  • the best matched target is used to update the radar tracking position and speed estimate for the back of the truck as well (step 508).
  • the position and speed estimate is then propagated in time to the position expected for the next radar sample in step 510. That is, the logic estimates the expected position of the back of the truck at the time the next radar sample is expected. This is a relatively simple matter since the radar samples are provided at regular intervals so the timing of the next expected sample is easy to determine. For example, if the radar sample rate is 20 Hz, the next sample can be expected to occur 0.05 seconds after the last sample.
  • the front and rear vehicles are traveling at exactly the same velocity and both vehicles are traveling in the same direction, than the "expected" position of the back of the front vehicle would be exactly the same as the last detected position of the back of the front vehicle.
  • vehicles will be traveling at slightly different speeds and possibly in slightly different directions if one of the vehicles is turned or turning slightly relative to the other. For example, using a simple example, if the trailing vehicle is moving in exactly the same direction as the lead vehicle at a constant velocity of 1.00 meters per second faster than the lead vehicle, then the back of the lead vehicle would be expected to be 5 cm closer to the lead vehicle at the time the next radar sample is taken (0.05 seconds after the last sample was taken).
  • Simple trigonometry may be used to determine the expected position if the vehicles are turned or turning slightly with respect to one another.
  • any number of other relevant variables that are known to or obtainable by the radar system controller can be considered in the calculation of the expected position and speed to further improve the estimates. These might include the respective accelerations (measured or estimated) of the vehicles, the respective directions of travel and/or rates of turn of the two vehicles, etc. Factors that may influence the velocity, acceleration or rate of turn of the vehicles such as the respective vehicles torque requests, the current grade, the vehicle weights, etc. may also be used to further refine the estimate.
  • the uncertainty estimate is updated as represented by block 512 as described in more detail below.
  • step 504 which utilizes the then current estimate of the position of the back of the lead vehicle to determine whether a match occurs.
  • the current estimate of the position of the lead vehicle can be expected to (indeed likely will) change over time.
  • the then current best estimate of the position of the back of front vehicle may be used which helps ensure that the partner vehicle is accurately tracked.
  • the platoon system preferably utilizes multiple independent or partially-independent mechanisms for tracking the position and speed, of the respective vehicles.
  • the platoon controller may have access to GPS position data which provides an independent mechanism for determining the relative positions of the platooning vehicles.
  • the platoon controller may also have access to wheel speed data which provides an alternative mechanism for determining the respective speeds, and thus the relative speed of the platoon partners.
  • Such data for the host vehicle is available from the host vehicle sensors.
  • Data for the partner vehicles is available over the communications link (e.g. the DSRC link, a cellular link or any other available communication method).
  • each time that a new GPS position estimates are received (as represented by box 520 in Fig. 7), the radar tracking position and speed estimate is updated using the current GPS position estimate (step 523), and that updated position and speed estimate is propagated in time to the expected receipt of the next radar sample as represented by step 510.
  • the radar tracking position and speed estimate is updated using the current wheel speed estimates (step 533), and that updated position and speed estimate is propagated in time to the expected receipt of the next radar sample as represented by step 510.
  • each time new inertial measurements such as yaw rates, vehicle orientation (heading), vehicle pitch and/or vehicle roll are received (as represented by box 540), the radar tracking position and speed estimate s updated using the current inertial measurements (step 542).
  • the GPS position, wheel speed and inertial measurements are preferably updated on a relatively rapid basis - which is often (although not necessarily) more frequent than the radar samples.
  • GPS update frequencies in the range of 25 to 500 Hz, as for example 50 Hz have been found to work well for open road platoon control applications.
  • Similar wheel speed and inertial measurement update frequencies have also been found to work well - although there is no need to update the GPS positions, wheel speed and/or inertial measurements at the same sample rate as each other, or at the same sample rate as the radar unit.
  • the updates from the radar unit, the GPS sensors, the wheel speed sensor and inertial measurements are handled asynchronously as they are received. Although not required, this is useful to help ensure that the latest sensor inputs are utilized in estimating the expected relative positions and speeds of the platooning vehicles at the time the next radar unit scene sample is received. This is contrasted with a system in which the wheel speed sensor and GPS sensor information is updated once each sample of the radar unit. Although synchronous updates can also work well, the use of asynchronous updates tends to improve the accuracy of the estimates because various sensor inputs can be updated more frequently than the radar unit sampling rate.
  • the same types of measurements on the different trucks are preferably synchronized in time. That is, GPS position measurements on the front truck are preferably synchronized in time with GPS position measurements on the back truck so that the relative positions of the trucks can be determined at a particular instant in time.
  • the wheel speed measurements on the front truck are preferably synchronized in time with wheel speed measurements on the back truck so that the relative speeds of the trucks can be determined at a particular instant in time.
  • the various inertial measurements are also preferably synchronized with each other as well.
  • the GPS system provides very accurate global timing signals.
  • the clocks used for the platoon partners can be synchronized with the GPS signals and the various measurements (e.g. GPS position measurements, wheel speed measurements, inertial measurements, etc.) can therefore be instructed to occur at specific synchronized times on the respective trucks.
  • Each measurement may also be accompanied by a timestamp that indicates when the measurement was taken so that the synchronization of the measurements can be verified (or accounted for if similar sensor measurements are not synchronized between vehicles).
  • step 504 utilizes the then current estimate of the position of the back of the lead vehicle to determine whether any of the received radar sample object points (targets) match the expected position of the back of the partner vehicle. It should be appreciated that there may be times when no radar sample targets match the expected position of the back of the partner vehicle as represented by the "no" branch from decision 504. In such cases the radar system controller still propagates the position estimate in time (step 510) so that the position estimate is updated for the next radar sample based on the other information the controller has. Such other information includes the then current estimates and may be further updated based on inputs from other systems (e.g., the GPS or wheel speed sensor) as previously discussed.
  • other systems e.g., the GPS or wheel speed sensor
  • the controller detects, or is informed, that an event is occurring that makes the measurements of any particular sensor suspect, the measurements from such sensor(s) can safely be ignored in the context of the position estimate.
  • inputs from other sensors deemed more reliable (if any) may continue to be used to update the position model and the position estimate may continue to be propagated in time for each subsequent sample.
  • the uncertainty associated with position estimate can be expected to increase slightly with each ignored sample, which has the effect of increasing the variation from the estimated position of the back of the partner vehicle that would be tolerated when determining whether there is a target that matches the expected position of the back of the partner vehicle.
  • the roll can be useful because on trucks the GPS antennas tend to be located on top of the cabs at locations over 4 meters above the ground (e.g. 14-15 feet). At such heights, even relatively small tilting in the roll direction can cause the reported position of the respective vehicles to vary significantly.
  • the pitch can be useful for similar reasons. For example, with a platooning gap of 15 meters, a difference in pitch of just ⁇ 2 degrees can result in a difference of a meter in the apparent or detected height of an object. At further distances and/or larger pitch variations, those differences are amplified. Since many radar units used in platooning systems have relatively narrow views this can lead to expected objects not being detected, or detected objects being discarded, because they are further from the estimated position than expected when pitch is not considered. Similarly, if longitudinal and/or angular accelerations are available, the position model can incorporate the acceleration measurements into the position estimates.
  • the relative positioning and/or speed and/or orientation of the vehicles can relatively accurately be measured using other systems such as LIDAR, sonar, other time of flight distance sensors, sensors configured to receive a signal transmitted from another vehicle, cameras, stereo cameras or other appropriate technologies, those measurements can be incorporated into the position model in addition to, or in place of, the GPS, wheel speed and inertial measurements.
  • the position model can be considerably more sophisticated using inputs such a torque requests, braking signals and/or other operational information about the respective platoon partners to further refine the predicted position at the time of the next radar sample.
  • the radar sample object points are compared to the estimated (expected) position and relative speed of the back of the partner vehicle.
  • more or fewer parameters can be compared to identify a match.
  • matches may be based on matching the expected position of the partner vehicle rather than position and speed/velocity. If the radar unit is capable of reliably reporting other information such as acceleration, rates of lateral movement, etc., then such information can also be compared to corresponding estimates as part of the match identification 504.
  • a significant advantage of the described approach is that the relative position and velocity estimates can reliably continue even when the back of the platoon partner is outside the view of the radar unit - as may sometimes be the case when the lead vehicle changes to a different lane, an interloper cuts in between the platooning vehicles, or a transitory fault occurs with the radar unit. With such tracking, radar identification of the platoon partner can more easily be reestablished when the back of the platoon partner comes back into the radar unit' s view. As will be appreciated by those familiar with the art, this is very different than adaptive cruise control systems that utilize radar only to track the distance to the vehicle directly in front of the host vehicle - regardless of who that leading vehicle may be.
  • histogram and/or mean shift clusters described above with respect to Fig. 5 can be used as another check to verify that the correct vehicle is being tracked by the radar unit or to provide a reference point when some, but not all of the truck is within the radar unit' s field of view.
  • Kalman filtering is intended to encompass linear quadratic estimation (LQE) as well as extensions and generalizations of LQE such as the extended Kalman filter and the unscented Kalman filter which are designed to work with nonlinear systems.
  • LQE linear quadratic estimation
  • extensions and generalizations of LQE such as the extended Kalman filter and the unscented Kalman filter which are designed to work with nonlinear systems.
  • Kalman filtering uses a series of measurements observed over time containing noise and other inaccuracies and produces estimates of unknown variables that tend to be more precise than those based on a single measurement alone.
  • the Kalman filter keeps track of the estimated state of the system and the variance or uncertainty of the estimate.
  • the state variables used in the Kalman filter may vary widely with the nature of the model used.
  • One particular state array (X) suitable for use in some of the described embodiments that involve a pair of platooning tractor-trailer trucks includes:
  • One particular control input array (U) includes:
  • Kalman filtering is particularly well adapted to making the types of position and velocity estimations useful in the techniques described herein. Although Kalman filtering works particularly well, it should be appreciated that other state/space estimation algorithms, such as Particle Filtering, etc. can be used in alternative embodiments.
  • information about the state of the partner vehicle that is received from the partner vehicle is used by the host to help verify or confirm that data from a sensor on the host vehicle that is believed to measure a characteristic of the partner vehicle is actually representative of the partner vehicle.
  • information from a lead vehicle about its position, speed, orientation etc. is used by a radar scene processor on the trailing vehicle to predict an expected position and speed of the lead vehicle. Those predictions are then used to help determine which (if any) of the detected radar objects correspond to the lead vehicle.
  • the state information received from the lead vehicle may be a measured value (such as a measure wheel speed) or a predicted value (such as a predicted speed) which may be even more reliable in circumstances in which the parameter (e.g., speed) is changing.
  • additional information about the partner vehicle can also be obtained from a third vehicle, a larger mesh of vehicles or from another external source.
  • a third vehicle travelling in parallel with the platoon partners may have measured the position, velocity and/or other characteristics of the partner vehicle and that information can be used as another independent check.
  • NOC network operations center
  • a network operations center (NOC) in communication with both platoon partners may know the intended route and communicate that route, or more short term directions to the host vehicle as appropriate.
  • information from the partner vehicle may be transmitted via an intermediary such as a third vehicle, a NOC, etc. Any of this type of data can be useful - and some of the information may be particularly helpful in circumstance in which communications between the vehicles is temporarily lost.
  • the described radar based vehicle identification and tracking can be used in any type of connected vehicle application in which independent information about the position and/or velocity of one or more other vehicles is known or available to the unit interpreting the radar data.
  • the described techniques are particularly well suited for use in convoying systems involving more than two vehicles.
  • the described techniques are very well adapted for use in autonomous vehicle traffic flow applications where knowledge about the intentions of other specific vehicles is deemed important. Indeed, this is expected to be an important application of the inventions with the growth of the autonomous and connected vehicle markets.
  • the platooning vehicles may have mechanisms such as transponders suitable for identifying themselves to the radar unit. When available, information from such devices can be used to further assist with the identification and tracking of the platoon partner.

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  • Engineering & Computer Science (AREA)
  • Radar, Positioning & Navigation (AREA)
  • Remote Sensing (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Computer Networks & Wireless Communication (AREA)
  • Electromagnetism (AREA)
  • Traffic Control Systems (AREA)
  • Control Of Driving Devices And Active Controlling Of Vehicle (AREA)
  • Radar Systems Or Details Thereof (AREA)
  • Optical Radar Systems And Details Thereof (AREA)

Abstract

L'invention concerne divers procédés, contrôleurs et algorithmes pour identifier l'arrière d'un véhicule particulier (par exemple un partenaire de convoi automatisé) dans un ensemble de scènes de mesure de distance et/ou pour suivre l'arrière d'un tel véhicule. Les techniques décrites peuvent être utilisées en association avec diverses technologies de mesure de distance différentes, dont des unités de mesure de distance par radar, LIDAR, caméra et autres. Les approches décrites sont bien adaptées à une utilisation dans des systèmes de convoi automatisé de véhicules et/ou de convoi de véhicules, y compris les applications de convoi automatisé de camions à tracteur semi-remorque. Dans un autre aspect, l'invention concerne une technique de fusion de données de capteur obtenues auprès de différents véhicules pour les utiliser dans la commande automatique au moins partielle d'un véhicule particulier. Les techniques décrites sont bien adaptées à une utilisation en association avec diverses applications de commande de véhicule différentes, dont le convoi automatisé, le déplacement en convoi et d'autres applications de conduite connectée, y compris les applications de convoi automatisé de camions à tracteur semi-remorque.
PCT/US2017/058477 2016-11-02 2017-10-26 Mesure d'écart pour déplacement de véhicules en convoi WO2018085107A1 (fr)

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JP2019523642A JP7152395B2 (ja) 2016-11-02 2017-10-26 車両隊列のためのギャップ測定
CN202211662662.6A CN116203551A (zh) 2016-11-02 2017-10-26 用于车辆护航的间隙测量
CN201780081508.0A CN110418745B (zh) 2016-11-02 2017-10-26 用于车辆护航的间隙测量
CA3042647A CA3042647C (fr) 2016-11-02 2017-10-26 Mesure d'ecart pour deplacement de vehicules en convoi
EP17867739.9A EP3535171A4 (fr) 2016-11-02 2017-10-26 Mesure d'écart pour déplacement de véhicules en convoi
JP2022155699A JP7461431B2 (ja) 2016-11-02 2022-09-29 車両隊列のためのギャップ測定

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PCT/US2016/060167 WO2017070714A1 (fr) 2015-09-15 2016-11-02 Identification et localisation de véhicules par fusion de capteurs et communication entre véhicules
US15/590,715 US20170242443A1 (en) 2015-11-02 2017-05-09 Gap measurement for vehicle convoying
US15/590,715 2017-05-09
US15/590,803 US10520581B2 (en) 2011-07-06 2017-05-09 Sensor fusion for autonomous or partially autonomous vehicle control
US15/590,803 2017-05-09

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