Method for operating a host vehicle

Abstract

Method (100) for operating a host vehicle (10 HV ) having a vehicle body (12) and a forward-facing first sensor and a forward-facing second sensor mounted at first and second locations of the vehicle body (12), respectively, the method (100) comprising: Receiving gradient data via a vehicle control of the host vehicle (10 HV ), indicating that the host vehicle (10 HV ) travels a route with mixed gradients; Detecting a target vehicle (10 TV ) in front of the host vehicle (10 HV ) on the mixed gradient path via the first sensor and the second sensor after receiving the gradient data; Determine the vehicle control after detecting the target vehicle (10 TV ), whether both the first sensor and the second sensor detect the target vehicle (10 TV ) have lost; Determining, via the vehicle control in response to determining that the target vehicle (10 TV ) was lost, whether the target vehicle (10 TV ) is re-detected by the first sensor and not by the second sensor, and Transmitting a command signal to a resident subsystem of the host vehicle (10 HV ) via the vehicle control in response to determining that the target vehicle (10 TV ) is detected again by the first sensor and not by the second sensor in order to enable automated driving of the host vehicle (10 HV ) to suppress.

Description

[0001] This description generally relates to intelligent control systems for motor vehicles. More specifically, aspects of this description relate to advanced driver assistance systems with adaptive driving capabilities using sensor-based targeting of objects.

[0002] Current production vehicles, such as modern automobiles, can be equipped with a network of on-board electronic devices that enable automated driving to minimize driver effort. In automotive vehicles, one of the most well-known types of automated driving is cruise control, which allows the driver to set a desired speed, which is then maintained by the on-board computer system without the driver having to use the accelerator or brake pedal. Next-generation adaptive cruise control (ACC) not only controls the vehicle speed but also manages the distance between the host vehicle and a leading "target vehicle." Another type of automated driving is the Collision Avoidance System (CAS), which detects impending collisions and warns the driver while independently taking preventative measures, such as steering or braking, without driver input.Intelligent parking assistance systems (IPAS), lane keeping and automatic steering systems, electronic stability control (ESC) and other advanced driver assistance systems (ADAS) are also present in many modern vehicles.

[0003] Automated and autonomous vehicle (AV) systems can employ a range of on-board sensor components to enable the detection, tracking, and ranging of target objects. For example, radar systems detect the presence, distance, and / or speed of a target object by emitting pulses of high-frequency electromagnetic waves that are reflected back from the object to a suitable radio receiver. As a further option, a vehicle can employ a LIDAR (Light Detection and Ranging) system, which emits and detects pulsed laser beams to determine distances to stationary or moving targets using various forms of light energy, including invisible, infrared, and near-infrared light spectra. A vehicle-mounted sensor array, including various digital cameras, ultrasonic sensors, and so on, also provides real-time target data.In the past, these object detection and distance measurement systems have been limited in their accuracy and application due to varying gradients in the roadway topography and system-inherent limitations caused by restrictions on available installation sites and the total number of sensors.

[0004] DE 195 43 402 A1 describes a device for determining the distance of vehicles, in which two beam fans, consisting of several laser beams running in one plane, are emitted from one vehicle with different elevation angles in the direction of another vehicle and the reflected laser beams are received, wherein the beam fan directed at the desired distance is activated and considered dominantly for determining the distance by means of an evaluation circuit assigned to the receivers, while the other beam fan is not considered or is considered with significantly less weight.

[0005] German Patent Application No. 10 2011 083 610 A1 describes a method for controlling the speed of a motor vehicle, comprising the steps of scanning an area in front of the motor vehicle using a distance sensor to detect a vehicle traveling ahead, detecting the vehicle traveling ahead, and controlling the speed of the motor vehicle such that a predetermined distance from the vehicle traveling ahead is maintained. Furthermore, it is detected that the vehicle traveling ahead leaves the detection range of the distance sensor while the motor vehicle is traveling uphill or downhill on off-road terrain, thereby limiting the acceleration of the motor vehicle to a predetermined value.

[0006] US 7 650 217 B2 describes a cruise control device of a controlled vehicle, comprising a terrain detector, a vehicle speed controller, first cruise control execution means, second cruise control execution means, a preceding vehicle loss determiner, a target speed setter and a cruise control switch.

[0007] US 2016 / 0 070 000 A1 describes an in-vehicle device comprising a first distance sensor, a pitch angle sensor, a radio communicator, an angle difference calculator and a processor.

[0008] It can be considered a task to provide an improved method for detecting objects and measuring a distance.

[0009] This object is achieved by a method according to the invention as claimed in claim 1. Furthermore, vehicle systems and vehicles equipped with such systems are described. The systems and vehicles operated with the method according to the invention.

[0010] The following presents intelligent vehicle systems with control logic that provide AV / ADAS driving characteristics with enhanced in-vehicle sensor operation for roads with varying gradients, as well as methods for manufacturing and operating such systems and motor vehicles equipped with such systems. By way of illustration and without limitation, a closed-loop vehicle control algorithm helps mitigate sensor limitations on hilly roads by detecting large variations in road gradient (e.g., ≥10 degrees of gradient) and, when detected, compensating for delays between the camera detection of a nearby vehicle (CIPV) and the subsequent detection of the CIPV target by a forward long-range radar (LRR). For example, monocular camera systems used for AV / ADAS functions often assume a level road surface throughout their field of view.Consequently, the vehicle's AV / ADAS control system may need to actively adjust all associated driving functions when the host vehicle (ego vehicle) travels through a mixed-grade road (e.g., a hilly road, a winding mountain pass, a downhill road, etc.). For example, the AV / ADAS control system collects sensor data output by an onboard inertial measurement unit (IMU) to detect when the host vehicle is climbing a hilly roadway. When the vehicle climbs a grade, the roof-mounted front-facing camera module (FCM) reacquires a previously lost CIPV target before the front-facing LRR package acquires the CIPV target. Upon detecting this deceleration, the AV / ADAS control system dampens the system response to the detected, lost, and then reacquired CIPV target (e.g., suppressing ACC / CAS braking) to prevent a false-positive system response (e.g.,to prevent braking that could cause a collision.

[0011] Parts of this description relate to intelligent vehicle control systems, stored control protocols, and system control logic as an application of the inventive method for providing AV / ADAS driving functions with improved on-board sensor operation for mixed-grade paths. The inventive method is presented for operating a host vehicle equipped with a first forward-facing, on-board sensor and a second forward-facing, on-board sensor, each mounted at a specific location on the vehicle body. The inventive method comprises: receiving, e.g.via a built-in or remote microcontroller, control module, integrated circuit (IC), or network of controllers / modules / devices (collectively, "controller") of the host vehicle, gradient data indicating that the host vehicle is traveling along a mixed-grade path; detecting, e.g., via both forward-facing sensors of the host vehicle after receiving the gradient data, a target vehicle in front of the host vehicle on the mixed-grade path; determining, e.g., via the vehicle controller after initially detecting the target vehicle, whether both forward-facing sensors have subsequently lost the target vehicle (e.g., new sensor data indicates that the target is no longer detected); determining, e.g.via the vehicle controller, in response to confirmation that the target vehicle has been lost from both sensors when the target vehicle is initially re-acquired only by the first sensor and not by the second sensor; and transmitting, e.g., via the vehicle controller, in response to confirmation that the target vehicle was initially re-acquired only by the first sensor, one or more command signals to one or more resident subsystems of the host vehicle to suppress automatic driving operation of the host vehicle (e.g., restrict CAS-activated CIB and autosteer).

[0012] Portions of this description refer to computer-readable media (CRM) containing instructions to be executed by a controller to mitigate the limitations of vehicle sensors on hilly roads, as an application of the inventive method. In one example, a non-transitory CRM stores instructions that can be executed by one or more processors of a vehicle controller of a host vehicle. The host vehicle is equipped with a first forward-facing sensor and a second forward-facing sensor mounted at first and second locations on the vehicle body, respectively. The CRM-stored instructions, when executed by the processor(s), cause the vehicle controller to perform operations including: receiving grade data indicating that the host vehicle is traversing a mixed-grade path;Determining, in response to receiving the grade data, that both the first and second sensors detect a target vehicle ahead of the host vehicle on the mixed-grade path; determining, after detection of the target vehicle by the first and second sensors, whether both the first and second sensors have dropped the target vehicle; determining, in response to the target vehicle being dropped by the first and second sensors, whether the target vehicle is re-detected by the first sensor and not by the second sensor; and transmitting, in response to determining that the target vehicle has been re-detected by the first sensor and not by the second sensor, a command signal to a resident subsystem of the host vehicle to suppress automatic driving operation of the host vehicle.

[0013] Parts of this description refer to motor vehicles equipped with intelligent control systems that provide AV / ADAS driving functions with enhanced in-vehicle sensor operation for mixed-grade roads as an application of the inventive method. As used herein, the terms "vehicle" and "motor vehicle" may be used interchangeably and synonymously to include any relevant vehicle platform, such as passenger cars (ICE, HEY, FEV, fuel cell, fully and semi-autonomous vehicles, etc.), commercial vehicles, industrial vehicles, tracked vehicles, off-road and all-terrain vehicles (ATVs), motorcycles, agricultural equipment, etc. In one example, a motor vehicle includes a vehicle body with a passenger compartment, a plurality of wheels attached to the vehicle body (e.g., via corner modules coupled to a unibody or body-on-frame chassis), and other standard original equipment.A prime mover, such as an electric traction motor and / or an internal combustion engine, drives one or more of the wheels, thus providing propulsion for the vehicle. A network of sensors is also mounted on the vehicle body, including a series of cameras, radar scanners, lidar packages, near-infrared sensors, ultrasonic proximity sensors, etc., mounted at individual locations on the vehicle body.

[0014] Continuing the discussion of the above example, the motor vehicle also includes a vehicle controller programmed to receive grade data, e.g., from an onboard multi-axis IMU (inertial measurement unit) or GPS transceiver, indicating that the motor vehicle is traveling through a mixed-grade path, and, in response to receiving the grade data, confirms that two of the forward-facing vehicle-mounted sensors simultaneously detect a target vehicle ahead of the motor vehicle on the mixed-grade path. Following sensor-linked acquisition of the target vehicle, the vehicle controller determines whether both sensors have subsequently lost the target vehicle (e.g., lost over the crest of a hill); if so, the vehicle controller determines whether the target vehicle is initially reacquired only by the first sensor and not by the second sensor.If the vehicle controller confirms that the target vehicle was initially only re-detected by the first sensor, it commands at least one resident subsystem to suppress at least one automated driving operation of the motor vehicle. The resident subsystem may, for example, include the braking system and / or the steering system of the host vehicle, and the automated driving operation may include an AV / ADAS automated braking operation and / or steering operation.

[0015] For each of the described vehicles, methods, and CRMs, the vehicle controller may respond to determining that the target vehicle has been lost by determining a lost position at which the target vehicle was lost from the first sensor and the second sensor. In this case, the vehicle controller may also determine an estimated travel time for the host vehicle to reach this lost position, e.g., at the host vehicle's ACC set speed. In addition, the vehicle controller may command the host vehicle's powertrain control module (PCM) to maintain, or slowly ramp up or down to, the current (e.g., the ACC set) vehicle speed for at least the estimated time. Normal control of the powertrain may resume when the vehicle has reached the lost position of the target vehicle.As a further option, determining that the target vehicle has been re-detected by the single first sensor may include the vehicle controller confirming, based on the sensor data output by the sensor(s), that the host vehicle is concurrently traversing the mixed-grade path when the target vehicle is re-detected.

[0016] For all described vehicles, methods, and CRM, the vehicle controller can respond to confirmation that the target vehicle is initially only detected by the first sensor by determining whether the target vehicle is at least a predefined minimum distance ahead of the host vehicle upon re-detection. In this case, the vehicle controller transmits the command signal to the resident subsystem to further suppress automated driving if it is determined that the target vehicle is at least the predefined minimum distance ahead of the host vehicle. Furthermore, the vehicle controller can respond to the determination that the target vehicle is not at least the predefined minimum distance ahead of the host vehicle by commanding the host vehicle's braking system to immediately perform a braking action (e.g., immediately activate CIB).

[0017] For all described vehicles, methods, and CRM, the vehicle controller may be programmed not to command the resident subsystem to suppress automated driving operation if it determines that the target vehicle was reacquired by the first sensor and the second sensor at substantially the same time. If both forward-facing sensors reacquire the lost target vehicle at substantially the same time, the AV / ADAS system is not expected to erroneously activate CIB or another false-positive system response. In at least some applications, determining that the target vehicle was lost by both forward-facing sensors may involve the vehicle controller confirming that neither the host vehicle nor the target vehicle changed lanes at substantially the same time as the sensors discarded the target vehicle.Confirmation that the target vehicle has been lost may also include the vehicle controller confirming that there has been no significant change in the dynamic characteristics of the host vehicle within a vehicle-calibrated range.

[0018] For each of the described vehicles, methods, and CRMs, the command signal may cause the resident subsystem to suppress automated driving operation: (1) for at least one vehicle-calibrated suppression timeframe; (2) until the second sensor re-detects the target vehicle after the first sensor initially re-detects the target vehicle; and / or (3) until the vehicle controller determines that the target vehicle is not at least a predefined minimum distance ahead of the host vehicle (e.g., at least about 50 meters (m)). As a further option, detecting the target vehicle ahead of the host vehicle may include the vehicle controller confirming that the target vehicle is a close-following vehicle and is in the same lane as the host vehicle.As a further option, the gradient data may be in the form of real-time sensor data generated by a multi-axis IMU mounted on the vehicle body and including one or more gyroscopes and one or more accelerometers. In at least some desired implementations, the first sensor may be a digital video camera mounted at a first height on the vehicle body (e.g., on the roof structure of the passenger compartment), and the second sensor may be a long-range radar mounted at a second height lower than the first height on the vehicle body (e.g., behind the front grille). As mentioned above, the mixed-grade route may be a hilly road or other steeply inclined route (e.g.,with a gradient of at least 10-25°), and the gradient data may indicate that the host vehicle is approaching and / or will reach the apex of the hilly road. Fig. 1 is a partially schematic side view of a representative motor vehicle having a network of in-vehicle control units, sensor devices, and communication devices providing advanced driving functions with enhanced sensor operation for mixed-grade paths. Fig. 2 is a flowchart illustrating a representative vehicle control protocol for providing advanced driving functions with enhanced sensor operation for mixed-grade paths, which, in accordance with aspects of the described concepts, may correspond to memory-stored instructions executable by a fixed or remote microcontroller, control logic circuit, system control module, or other integrated circuit (IC) or network of circuits / modules / microcontrollers / IC devices (collectively, "Control Unit"). The Fig. 3A and Fig. 3B are partially schematic side views of a representative host vehicle acquiring (t1), then losing (t2), then reacquiring (t3) with camera only, and then reacquiring with a fused camera and radar (t4) to mitigate sensor limitations and thereby improve AV / ADAS driving.

[0019] With reference to the drawings, in which like reference numerals refer to like features in the several views, Fig. 1 illustrates a representative motor vehicle, generally designated 10, which is depicted here for discussion as an electric sedan. The depicted motor vehicle 10—also referred to herein as a “motor vehicle” or “vehicle” for short—is merely an exemplary application with which aspects of the present description may be practiced. Likewise, the execution of the present concepts by the depicted network of vehicle hardware devices should be understood as a non-limiting implementation of the described features. It is to be understood that the aspects and features of this description may also be implemented by other vehicle device architectures and may be incorporated into any logically relevant vehicle type. Furthermore, only selected components of the motor vehicle and the intelligent vehicle system are shown and described in detail herein.Nevertheless, the vehicles and systems described below may include numerous additional and alternative features and other available peripheral hardware to perform the various methods and functions of this description.

[0020] The representative vehicle 10 of Fig. 1 is originally equipped with a vehicle telecommunications and information unit (“telematics”) 14 that communicates wirelessly, e.g., via cell towers, base stations, mobile switching centers, satellite services, etc., with a remote or “off-board” cloud computing host service 24 (e.g., OnStar®). Some of the other vehicle hardware components 16 that are included in Fig. 1 include, by way of non-limiting examples, an electronic video display device 18, a microphone 28, audio speakers 30, and various user input controls 32 (e.g., knobs, buttons, pedals, switches, touchpads, joysticks, touchscreens, etc.). These hardware components 16 function, in part, as a human-machine interface (HMI) that allows the user to communicate with the telematics unit 14 and other components located within and remote from the vehicle 10. For example, the microphone 28 provides occupants with the ability to input verbal or other audible commands; the vehicle 10 may be equipped with an embedded speech processing unit that utilizes audio filtering, processing, and analysis modules.Conversely, the speaker(s) 30 provide an audible output to a vehicle occupant and may either be a standalone speaker dedicated for use with the telematics unit 14 or may be part of an audio system 22. The audio system 22 is operatively connected to a network connection interface 34 and an audio bus 20 to receive analog information and reproduce it as sound through one or more speaker components.

[0021] Communicatively coupled to the telematics unit 14 is a network connection interface 34, suitable examples of which include twisted pair / fiber optic Ethernet switches, parallel / serial communication buses, local area network (LAN) interfaces, controller area network (CAN) interfaces, and the like. The network connection interface 34 enables the vehicle hardware 16 to send and receive signals with each other and with various systems both onboard and external to the vehicle body 12. This enables the vehicle 10 to perform various vehicle functions, such as modulating driveline power, activating friction and regenerative braking systems, controlling the vehicle's steering, regulating the charging and discharging of a vehicle's battery, and other automatic functions.For example, the telematics unit 14 may exchange signals with a powertrain control module (PCM) 52, an advanced driver assistance system (ADAS) module 54, an electronic battery control module (EBCM) 56, a steering control module (SCM) 58, a braking system control module (BSCM) 60, and various other vehicle ECUs, such as a transmission control module (TCM), an engine control module (ECM), a sensor system interface module (SSIM), etc.

[0022] With further reference to Fig. 1, the telematics unit 14 is an in-vehicle computing device that provides a mix of services both individually and through its communication with other networked devices. This telematics unit 14 may generally consist of one or more processors 40, each of which may be embodied as a discrete microprocessor, an application-specific integrated circuit (ASIC), or a dedicated control module. The vehicle 10 may provide centralized vehicle control via a central processing unit (CPU) 36 operatively coupled to a real-time clock (RTC) 42 and one or more electronic storage devices 38, each of which may take the form of a CD-ROM, a magnetic disk, an integrated circuit (IC), solid-state drive (SSD), hard disk drive (HDD), flash memory, semiconductor memory (e.g., various types of RAM or ROM), etc.

[0023] Long-range communication (LRC) with remote devices outside the vehicle may be provided via one or more or all of the cellular chipsets / components, navigation and positioning chipsets / components (e.g., GPS transceiver), or a wireless modem, all shown collectively at 44. Short-range wireless connection may be established via a short-range communication device (SRC device) 46 (e.g., a Bluetooth® unit or an NFC transceiver), a DSRC component 48, and / or a dual antenna 50. The communication devices described above may enable data exchange as part of a periodic broadcast in a vehicle-to-vehicle (V2V) communication system or a vehicle-to-general (V2X) communication system, e.g., vehicle-to-infrastructure (V2I), vehicle-to-pedestrian (V2P), vehicle-to-device (V2D), etc.

[0024] The CPU 36 receives sensor data from one or more sensing devices using, for example, photodetection, radar, laser, ultrasound, optics, infrared, or other suitable technologies, including short-range communication technologies (e.g., DSRC) or ultra-wide-band (UWB) radio technologies, to perform an automated driving (AV / ADAS) operation or a vehicle navigation service. According to the example shown, the vehicle 10 may be equipped with one or more digital cameras 62, one or more range sensors 64, one or more vehicle speed sensors 66, one or more vehicle dynamics sensors 68, and the necessary filtering, classification, fusion, and analysis hardware and software to process the raw sensor data.The type, placement, number and interoperability of the distributed array of vehicle sensors can be individually or collectively adapted to a specific vehicle platform to achieve a desired level of automated vehicle operation.

[0025] The digital camera(s) 62 may use a CMOS (Complementary Metal Oxide Semiconductor) sensor or other suitable optical sensing device to generate images indicative of a field of view of the vehicle 10 and may be configured for continuous image generation, e.g., at least about 50+ frames per second. For comparison, a range sensor(s) 64 may transmit and detect reflected radio, infrared, light, or other electromagnetic signals (e.g., short-range radar, long-range radar, inductive EM sensing, Light Detection and Ranging (LIDAR), etc.) to detect, for example, the presence, speed, proximity, etc. of a target object. The vehicle speed sensor(s) 66 may take various forms, including wheel speed sensors that measure wheel speeds, which are then used to determine real-time host speed (ego speed).In addition, the vehicle dynamics sensor(s) 68 may be a single- or three-axis accelerometer, a yaw rate sensor, a pitch sensor, etc., for measuring longitudinal and lateral acceleration, yaw, roll, and / or pitch rates, or other dynamics-related parameters. Using data from these on-board sensors, the CPU 36 can determine the surrounding driving conditions, roadway characteristics, and surface conditions, identify target objects within a vehicle detection zone, determine target object attributes such as size, relative position, orientation, distance, approach angle, relative speed, etc., and execute automatic control maneuvers based on these operations.

[0026] These vehicle-mounted sensors may be distributed throughout the motor vehicle 10 in functional, unobstructed positions relative to the forward, rearward, port, and / or starboard views of the vehicle body 12. Each sensor generates electrical signals indicative of a feature or condition of the host vehicle or one or more target objects, generally as an estimate with a corresponding standard deviation. The operating characteristics of these sensors are generally complementary, but some are more reliable at estimating certain parameters than others. Most sensors have different ranges and sensing areas and are capable of sensing various parameters within their operating range.For example, a radar-based sensor can estimate an object's distance, ranging rate, and azimuth position, but is not necessarily reliable at estimating a target's shape / extent. Cameras using optical processing, on the other hand, can better estimate an object's shape / size and azimuth position, but are less efficient at estimating a target's distance and ranging rate. A scanning LIDAR sensor can be efficient and accurate at estimating distance and azimuth position, but may not be able to accurately estimate the ranging rate and therefore may not be accurate at detecting / detecting new objects. Ultrasonic sensors, on the other hand, can estimate distance but are generally unable to accurately determine the ranging rate and azimuth position.Furthermore, the performance of many sensor technologies can be affected by varying environmental conditions. Consequently, sensors generally exhibit parametric variations, the operational overlap of which provides opportunities for active and continuous sensor fusion.

[0027] To propel the motor vehicle 10, an electrified drive train is operable to generate and transmit traction torque to one or more of the drive wheels 26 of the vehicle. The drive train is Fig. 1 is generally represented by a rechargeable energy storage system (RESS), which may be in the form of a chassis-mounted traction battery pack 70 connected to an electric traction motor (M) 78. The traction battery pack 70 generally includes one or more battery modules 72, each containing a bundle of battery cells 74, such as lithium, zinc, nickel, or organosilicon class cells of the pouch, can, or cylindrical type. One or more electric machines, such as traction motor / generator (M) units 78, draw electrical energy from, and optionally supply electrical energy to, the traction battery pack 70. A power inverter module (PIM) 80 electrically connects the traction battery pack 70 to the motor(s) 78 and modulates the transfer of electrical power between them. The presented concepts are similarly applicable to HEV- and ICE-based powertrains.

[0028] The traction battery pack 70 may be designed so that the functions for module management, cell sensing, module-to-module, and / or module-to-host communication are integrated directly into each battery module 72 and performed by an integrated electronics package, such as a wireless cell monitoring unit (CMU) 76. The CMU 76 may be a microcontroller-based, printed circuit board (PCB)-mounted sensor array. Each CMU 76 may include a GPS transceiver and RF capabilities and may be housed on or within a battery module enclosure. The battery module cells 74, the CMU 76, the enclosure, the coolant lines, the bus bars, etc., may together form a cell module assembly.

[0029] During normal operation of the motor vehicle 10 Fig. 1, which may also be referred to herein as a "host" or "ego" vehicle, the vehicle 10 may traverse a mixed-gradient path (e.g., a hilly road, a winding mountain pass, a steeply banked road, etc.). Before, simultaneously, or after entering an incline of the path, the host vehicle 10 may encounter one or more leading vehicles; the closest of these leading vehicles may be identified and referred to as the CIPV (Closest-In-Path Vehicle) target vehicle. While tracking the CIPV target vehicle across the mixed-gradient path, a forward-facing front camera module (FCM) (e.g., the digital camera 62 of Fig. 1 or the waterproof 1.2 megapixel CMOS HD camera module 62' from Fig. 3A and Fig. 3B) and a forward-looking long-range radar (LRR) package (e.g., the range sensor 64 of Fig. 1 or the fixed-mounted pulsed X- and K-band radar array 64' of the Fig. 3A and Fig. 3B) lose the target vehicle (e.g., when new data from both sensors indicate that the target is no longer detected). When exiting the grade (e.g., when climbing a hill), the host vehicle's FCM may report erroneous position and speed measurements if the target vehicle appears above the local horizon and is reacquired by the FCM before being reacquired by the LRR. In particular, the particular topology of the road and the varying locations of the host vehicle's sensors may result in a delay in the LRR detecting the target vehicle. Without mitigation, the vehicle's ACC and / or CAS control module may generate a false-positive urgent driving scenario requiring immediate braking (e.g., collision imminent braking (CIB)).

[0030] This paper presents intelligent vehicle systems with control logic that mitigates sensor limitations on mixed-grade (hilly) roads by using GPS and / or IMU sensor data to determine when such edge cases occur and reactively dampening inaccurate camera sensor data to prevent false braking. During host vehicle operation, the AV / ADAS control module actively monitors and identifies when the host vehicle is traveling in a hilly environment. Once this occurs, the host vehicle monitors and locates the presence of a CIPV target vehicle. If this CIPV target vehicle is lost without changing direction, lane, etc., the host vehicle's ego speed can be held essentially constant or controlled to a preset ACC speed for a calculated period of time.Upon reaching the position where the CIPV target was lost, the host vehicle can resume speed on the clear roadway. If a CIPV target vehicle detected only by the camera reappears, the AV / ADAS module can observe the IMU gradient signal to determine characteristics of the road conditions. If the gradient is positive and approaching zero, the control module can set a flag indicating that the host vehicle is climbing a hill. The calculated distance of the host vehicle to the CIPV target vehicle and the gradient signal characteristics that triggered the flag can establish calibratable limits for the duration and extent of automated driving for the host vehicle. Calibratable exit criteria can include the distance of the camera target, the stability of the target, and the condition of the road gradient.If the above conditions are met, a target suppression flag can be set to prevent false-positive activation of automatic braking / steering.

[0031] Among the advantages offered by at least some of the presented concepts is the ability to compensate for limitations in the sensor field of view (FoV) caused by discrete sensor positions and mixed-grade (hilly) road scenarios. The features described here can also help compensate for inaccurate target speed and position data generated by the host vehicle's camera sensors. By implementing the advanced driving features described here with improved in-vehicle sensing for mixed-grade roads, the host vehicle is able to prevent erratic vehicle behavior while simultaneously improving passenger driving experience.In addition to predicting relevant hilly road scenarios to suppress erroneous vehicle responses, the host vehicle is also capable of improving target tracking performance and ensuring appropriate vehicle response to detected, dropped, and recovered CIPV target vehicles.

[0032] Next, referring to the flowchart in Fig. 2, at 100, an improved method or control strategy for providing advanced control automated driving functions through improved sensor operation for a host vehicle traveling over a mixed grade route, such as the vehicle 10 in Fig. 1 or the host vehicle 10 HV in the Fig. 3A and Fig. 3B, which travels up a hilly road 11, in accordance with aspects of the present description. Some or all of the Fig. 2 and described in more detail below may represent an algorithm corresponding to non-transitory, processor-executable instructions located, for example, in main or auxiliary memory or remote storage (e.g., in the resident storage device 38 and / or in the database of the remote cloud computing service 24 of Fig. 1) are stored and are executed, for example, by an electronic controller, a processing unit, a dedicated control module, a logic circuit or another module or device or a network of controllers / modules / devices (e.g. CPU 36 and / or processor 40 of Fig. 1) to perform any or all of the functions described above and below associated with the concepts described. It should be recognized that the order of execution of the illustrated operation blocks may be changed, that additional operation blocks may be added, and that some of the operations described herein may be modified, combined, or eliminated.

[0033] The procedure 100 begins at starting block 101 of Fig. 2 with processor-executable instructions stored in memory for initializing a mixed-grade driving scenario procedure for a particular host vehicle. This routine may be executed in real time, near real time, continuously, systematically, and / or at predefined time intervals, e.g., every 10 or 100 milliseconds during normal operation of the motor vehicle 10. As a further option, the process block 101 may be initialized in response to a user command prompt (e.g., via telematics input controls 32), a request from a resident vehicle controller (e.g., from the CPU 36), or a broadcast request signal received from a centralized back-office (BO) vehicle service system (e.g., from the cloud host service 24).As a non-limiting example, the method 100 may be automatically initiated during a power-on process in which a driver, owner, passenger, or other authorized operator of the vehicle 10 (collectively, "user") engages the vehicle's powertrain and places the vehicle in drive mode. Upon completion of some or all of the steps described in . Fig. 2, the method 100 may proceed to the final method block 123 and temporarily terminate, or optionally return to the method block 101 and run in a continuous loop. Method block 123 may be automatically triggered when the driver switches to park mode or when a user turns off the host vehicle 10.

[0034] The method 100 proceeds from the start block 101 to the HILLY ROAD decision block 103 to determine whether or not the host vehicle is traveling through a mixed-grade road. For example, the host vehicle's AV / ADAS control module may aggregate sensor-based grade data output by an onboard inertial measurement unit (IMU) to detect when the host vehicle is traveling up a hilly road (e.g., with a grade of ≥10 degrees). The IMU may take various forms, such as a 3-axis, 6-axis, or 9-axis design rigidly mounted within the host vehicle body and including three gyroscopes, three accelerometers, and, if desired, three magnetometers. During vehicle operation, the IMU may track the host vehicle's (ego vehicle's) longitudinal pitch angle and its changes.If an absolute value of a change in the host vehicle's gradient angle is greater than a predefined threshold (e.g., 10 degrees), the AV / ADAS system concludes that the host vehicle is currently on a mixed-grade road. Fig. 3A shows an example in which a host vehicle 10 HV approaching a hilly road 11 with a gradient of 18 degrees. If it is determined that the host vehicle is not on a mixed-grade road (block 103=NO), method 100 may proceed to method block 123 and temporarily terminate, or return to method block 101 and run in a continuous loop.

[0035] In response to determining that the host vehicle is currently traversing a mixed-grade path (block 103 = YES), the method 100 may execute decision block 105 TARGET DETECTED to determine whether or not a leading vehicle is in front of the host vehicle. An affirmative determination in block 105 may require that at least two of the host vehicle's forward-facing vehicle-side sensors detect at least one leading target vehicle substantially simultaneously after the AV / ADAS control module confirms that the host vehicle is traversing a mixed-grade path. At time t1 in Fig. 3A, for example, the forward-facing monocular camera 62' and the wide-range radar system 64' of the host vehicle simultaneously capture a target vehicle 10 TV in front of the host vehicle 10 HVon the hilly road 11. After detecting the target, the camera 62' and the LRR 64' jointly generate real-time target proximity, distance, azimuth position, type, size, speed, and other related data for the target vehicle 10 TV By aggregating, preprocessing, combining and evaluating this data generated by the sensors, the host vehicle's AV / ADAS module can confirm that the target vehicle 10 TV a vehicle with a short distance and is on a path 10 HVsplit lane. If it is determined that there is no lead target vehicle in front of the host vehicle, that the target vehicle is not a CIPV target, and / or that the target vehicle is in another lane (block 105=NO), the method 100 may responsively execute the STANDARD OPERATION subroutine (block 107) and resume normal AV / ADAS vehicle operation until the host vehicle approaches another mixed-grade lane.

[0036] With further reference to Fig. 2, the method 100 may respond to the detection of a CIPV target vehicle sharing the same lane as the host vehicle (block 105=YES) by monitoring the target to determine whether the host vehicle's forward-facing vehicle-side sensors subsequently lose the target vehicle, as indicated in the "Target Lost" decision block 109. After the target vehicle 10 TVfor example at time t1 of Fig. 3A, the host system's AV / ADAS control module can systematically combine radar and camera data to continuously track the target. At time t2 in Fig. 3A has the target vehicle 10 TV leave the hilly road 11 and is out of the immediate line of sight of the host vehicle 10 HV"disappeared." Consequently, the host vehicle's monocular camera 62' and LRR array 64' no longer perceive the target vehicle; new sensor data generated by these two forward-facing sensors indicates that the CIPV target is no longer detected and was therefore lost at t2. Concluding that a CIPV target vehicle has been "lost" by the host vehicle's forward-facing sensors may also require the AV / ADAS control module to aggregate, preprocess, fuse, and analyze available sensor data (e.g., from cameras 62, range sensors 64, speed sensors 66, dynamic sensors 68, etc.) to confirm that neither the host vehicle nor the target vehicle changed lanes or exited the path at substantially the same time as the target vehicle was lost.Determining that a CIPV target vehicle has been lost may also require determining that one or more dynamic properties of the target are within a predefined, calibratable range (e.g., that the removal rate does not exceed a preset threshold). If the CIPV target vehicle is not lost (block 109=NO), method 100 may loop back through method block 107 to method blocks 103 and 105.

[0037] In response to the conclusion that the detected CIPV target vehicle has been lost by the host vehicle (block 109=YES), the method 100 may automatically execute the TIME TO LOST LOCATION subroutine in block 111 to predict an estimated travel time for the host vehicle to reach a fixed location where the target vehicle has been lost. While the AV / ADAS control module of the host vehicle 10 HV still the CIPV target vehicle 10 TVtracked, which is perceived, for example, at time t1, the target vehicle disappears 10 TV then at time t2 suddenly from the sensor detection of the host vehicle 10 HV (the crest of the hill 11 obscures the target detection). Upon confirmation of target loss, the AV / ADAS control module marks the last detected geographical position of the target vehicle 10 TV within the existing camera / radar fused target data; this position is temporarily stored in the resident cache memory as loss position H DP in conjunction with a corresponding distance D DP to the loss position H DP stored. Using the loss position H DP and the loss distance D DP (e.g. retrieved from the resident vehicle memory 38), the current (real-time) position P HV (e.g. retrieved from the GPS transmitter / receiver44) and the current (real-time) speed and course V HV(e.g. retrieved from the vehicle speed and dynamic sensors 66, 68) the AV / ADAS control module calculates an estimated travel time for the host vehicle 10 HV to the loss position D DP to reach.

[0038] In parallel with subroutine block 111, the method 100 may execute the Own Speed ​​subroutine in block 113 to limit large changes in own speed until the host vehicle reaches the lost position of the target vehicle. After determining that the detected target vehicle 10 TV was lost (Block 109=YES), for example, the AV / ADAS control module of the host vehicle 10 HV give the command to the powertrain control module of the host vehicle (e.g. speed command signal sent to the PCM 52 of Fig. 1), to maintain a current vehicle speed for at least the estimated time calculated in block 111, ie until the host vehicle 10HV the loss position D DP achieved. During Level 3 ACC driving or Level 4 or 5 AV driving, the host vehicle's set airspeed can be limited or locked to prevent the AV / ADAS control module from unnecessarily increasing / decreasing airspeed after jettison. Subroutine block 113 can allow minor controlled changes to airspeed, such as slowly ramping up or down the host vehicle's speed to a preset ACC speed until the estimated travel time has elapsed.

[0039] The method 100 proceeds from subroutine block 113 to the CIPV camera-only decision block 115 to determine whether the lost CIPV target is subsequently reacquired, and if so, whether it is reacquired by only one or only selected ones of the forward-facing vehicle sensors. For example, the AV / ADAS module of the host vehicle 10 HV active after the target vehicle 10 TV after it has been detected by both the monocular camera 62' and the LRR arrangement 64' at time = t2 of Fig. 3A was lost. At time t3 of Fig. 3B becomes the target vehicle 10 TV for example, subsequently again from the host vehicle 10 HVcaptured and initially revealed and detected only by the monocular camera 62'; at time t3, the target is not revealed or otherwise detectable by the LRR array 64'. This is due, in part, to the fact that the first sensor—the digital video camera 62'—is mounted at a specific (first) height at a specific (first) location on the vehicle body (e.g., on the roof structure of the passenger compartment), while the second sensor—the LRR array 64'—is mounted at a lower (second) height at a corresponding (second) location on the vehicle body (e.g., behind the front grille). At this location, inaccurate camera reporting may occur for a brief period (e.g., 1 to 2 seconds) before the LRR array stabilizes for camera-radar fusion and reacquires data.

[0040] At least in some applications, concluding that the lost target vehicle has been reacquired may also include confirming that the host vehicle is traveling through the mixed-grade path at the same time as the target vehicle is reacquired. On the other hand, decision block 115 may provide a negative answer if multiple forward-facing, vehicle-mounted sensors simultaneously reacquire the lost CIPV target vehicle. For example, method 100 may loop back to block 103 or terminate at terminal block 123 if it is determined that the target vehicle is reacquired by both monocular camera 62' and LRR assembly 64' at substantially the same time.Upon confirmation that the dropped CIPV target has not been re-detected by only one or only selected ones of the host vehicle's forward-facing on-board sensors (block 115=NO), the method 100 may responsively loop back through method block 107 to method blocks 103 and 105.

[0041] In response to determining that the CIPV has been re-acquired as a camera-only target while the host vehicle is still traveling on the varying grade road (block 115=YES), the method 100 may execute decision block 117 FORWARD WARNING to determine whether the target vehicle is at least a predefined minimum distance ahead of the host vehicle. Again, referring to the Fig. 3B, the AV / ADAS control module of the host vehicle 10 HVactively track the now recovered target and evaluate sensor-generated target data to determine whether the target vehicle 10 TV within a vehicle-calibratable CIPV dimensional criteria range (e.g. 50-150 meters) in front of the host vehicle 10 HV is or not. If the target vehicle 10 TV is outside the CIPV dimensional criteria (block 117 = NO), the method 100 may reactively return to method block 107 and resume standard vehicle operation. For example, if the newly detected target is not at least the predefined minimum distance in front of the host vehicle (e.g., relative range of the target of 25 meters), the AV / ADAS control module may command the host vehicle's braking system to immediately perform a braking action (e.g., send a brake command signal to immediately activate CIB).

[0042] If it is confirmed that the distance to the newly detected CIPV target exceeds the predefined minimum distance (block 117=YES), the method 100 may, in response, clear the internal memory block 119 of Fig. 2 and set a flag in internal memory indicating that the resulting visual ring data (VISR) of the vehicle may not be reliable. In conjunction with internal memory block 119, method 100 may also respond to a captured-lost-recaptured CIPV target vehicle by activating AV / ADAS SUPPRESS RESPONSE subroutine 121 and simultaneously commanding one or more resident subsystems of the host vehicle to suppress one or more automated driving operations of the host vehicle. At time t3 of Fig. 3B, the AV / ADAS control module may, for example, command the host vehicle's braking system to temporarily limit or deny control-automated braking commands, while also commanding the host vehicle's steering system to temporarily limit or deny control-automated steering changes. In a more specific, but non-limiting, example, the host vehicle 10 HV suppress ACC / CAS braking to prevent a false-positive reaction from the CIB system.

[0043] It may be desirable that subroutine 121 of Fig. 2 suppress one or more selected responses of the control-automated AV / ADAS only for a limited time and / or only under predefined circumstances. For example, the command signals issued by the AV / ADAS control module to the on-board subsystem(s) suppress the automated driving operation(s): (1) for at least a vehicle-calibratable, predefined suppression period; (2) until the LRR array or another forward-facing sensor re-detects the target vehicle after the camera sensor re-detects the target vehicle; and / or (3) until the target vehicle is not at least a predefined minimum distance in front of the host vehicle.For example, ACC-assisted braking may be restricted to maintain the airspeed for a suppression period determined based on the changing road gradient, the current airspeed, the current CIPV target speed, changes in the CIPV target speed, etc. At time = t4 in . Fig. 3B can allow the host vehicle 10 HV For example, it may be permitted to resume standard driving operations because the target vehicle 10 TV is recaptured by both the forward-facing monocular camera 62' and the LRR assembly 64' of the host vehicle.

[0044] Aspects of this description may, in some embodiments, be implemented by a computer-executable program of instructions, such as program modules, generally referred to as software applications or application programs, executed by any control device or the control variants described herein. Software may include, by way of non-limiting example, routines, programs, objects, components, and data structures that perform particular tasks or implement particular data types. The software may provide an interface that enables the computer to respond according to an input source. The software may also cooperate with other code segments to initiate a variety of tasks in response to received data associated with the source of the received data. The software may be implemented on a variety of storage media, such as CD-ROM, magnetic disk, and semiconductor memory (e.g.,different types of RAM or ROM).

[0045] Furthermore, aspects of the present description may be practiced with a variety of computer system and computer network configurations, including multiprocessor systems, microprocessor-based or programmable consumer electronics, minicomputers, mainframe computers, and the like. Furthermore, aspects of the present description may be applied in distributed computing environments in which tasks are performed by stationary and remote processing devices connected via a communications network. In a distributed computing environment, program modules may be located in both local and remote computer storage media, including memory devices. Aspects of the present description may therefore be implemented in conjunction with various hardware, software, or a combination thereof in a computer system or other processing system.

[0046] Each of the methods described herein may include machine-readable instructions for execution by (a) a processor, (b) a controller, and / or (c) any other suitable processing device. Any algorithm, software, control logic, protocol, or method described herein may be embodied as software stored on a tangible medium, such as flash memory, solid-state drive (SSD), hard disk drive (HDD), CD-ROM, digital versatile disk (DVD), or other storage devices. The entire algorithm, control logic, protocol, or method, and / or portions thereof, may alternatively be executed by a device other than a controller and / or embodied in firmware or dedicated hardware in an available manner (e.g.,implemented by an application-specific integrated circuit (ASIC), a programmable logic device (PLD), a field-programmable logic device (FPLD), discrete logic, etc.). Although specific algorithms may be described with reference to the flowcharts and / or workflow diagrams presented herein, many other methods for implementing the example machine-readable instructions may alternatively be used.

Claims

[1] Method (100) for operating a host vehicle (10 HV ) having a vehicle body (12) and a forward-facing first sensor and a forward-facing second sensor mounted at first and second locations of the vehicle body (12), respectively, the method (100) comprising: Receiving gradient data via a vehicle control of the host vehicle (10 HV ), indicating that the host vehicle (10 HV ) travels a route with mixed gradients; Detecting a target vehicle (10 TV ) in front of the host vehicle (10 HV ) on the mixed gradient path via the first sensor and the second sensor after receiving the gradient data; Determine the vehicle control after detecting the target vehicle (10 TV ), whether both the first sensor and the second sensor detect the target vehicle (10 TV ) have lost; Determining, via the vehicle control in response to determining that the target vehicle (10 TV ) was lost, whether the target vehicle (10 TV ) is re-detected by the first sensor and not by the second sensor, and Transmitting a command signal to a resident subsystem of the host vehicle (10 HV ) via the vehicle control in response to determining that the target vehicle (10 TV ) is detected again by the first sensor and not by the second sensor in order to enable automated driving of the host vehicle (10 HV ) to suppress. [2] The method (100) of claim 1, further comprising: Determining a loss position (H DP ), where the target vehicle (10 TV ) was lost, via the vehicle control in response to determining that the target vehicle (10 TV ) was lost by the first sensor and the second sensor, and Determination of an estimated time for the host vehicle (10 HV ) to reduce the loss position (H DP ) via the vehicle control system. [3] The method (100) of claim 2, further comprising transmitting a speed command signal via the vehicle controller to a powertrain control module of the host vehicle (10 HV ) to maintain a current vehicle speed for at least the estimated time. [4] The method (100) of claim 1, wherein determining that the target vehicle (10 TV ) is detected again by the first sensor, the confirmation, via the vehicle control, comprises that the host vehicle (10 HV ) simultaneously travels the route with mixed gradients when the target vehicle (10 TV ) is recorded again. [5] The method (100) of claim 1, further comprising: Determining, via the vehicle control in response to determining that the target vehicle (10 TV ) is detected again by the first sensor, whether the target vehicle (10 TV ) at least a predefined minimum distance in front of the host vehicle (10 HV ) is located; wherein transmitting the command signal to the resident subsystem for suppressing automated driving operation is further performed in response to determining that the target vehicle (10 TV ) at least the predefined minimum distance in front of the host vehicle (10 HV ) is located. [6] The method (100) of claim 5, further comprising transmitting a brake command signal via the vehicle controller to a braking system of the host vehicle (10 HV ), in response to the target vehicle (10 TV ) is not at least at the predefined minimum distance in front of the host vehicle (10 HV) to immediately perform a braking operation. [7] The method (100) of claim 1, further comprising not transmitting the command signal to the resident subsystem to suppress the automated driving operation if it is determined that the target vehicle (10 TV ) is again detected by both the first sensor and the second sensor essentially at the same time. [8] The method (100) of claim 1, wherein determining that the target vehicle (10 TV ) was lost from both the first sensor and the second sensor, involves the vehicle control confirming that neither the host vehicle (10 HV ) nor the target vehicle (10 TV ) essentially at the same time as the loss of the target vehicle (10 TV )s changed lanes. [9] The method (100) of claim 1, wherein the command signal causes the resident subsystem to suppress the automated driving operation: (1) for at least one predefined suppression time frame; (2) until the second sensor detects the target vehicle (10 TV ) is detected again after the first sensor has detected the target vehicle (10 TV ) has been detected again; and / or (3) until the vehicle control determines that the target vehicle (10 TV ) does not maintain at least a predefined minimum distance in front of the host vehicle (10 HV ) lies. [10] Method (100) according to claim 1, wherein the detection of the target vehicle (10 TV ) in front of the host vehicle (10 HV ) involves the vehicle control confirming that the target vehicle (10 TV ) is a vehicle that is closest to the host vehicle (10 HV ) and is located on a platform controlled by the host vehicle (10 HV ) shared lane.

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