Lane hazard mitigation strategies in advanced driver assistance systems

Abstract

A lane hazard mitigation algorithm includes a sensor to detect a first hazard in a main road lane and a second hazard in an adjacent road lane; a processor for determining, in response to the first hazard, a main lane slowdown including a main lane speed drop and in response to the second hazard, an adjacent lane slowdown including an adjacent lane speed drop, the processor further configured to generate a lane change control signal in response to the adjacent lane speed drop being less than the main lane speed drop, and generate a vehicle speed reduction control signal in response to the main lane speed reduction being less than the adjacent lane speed reduction; and a vehicle controller for controlling the host vehicle in response to the lane change control signal and the vehicle speed reduction control signal.

Description

Technical Field

[0001] The present disclosure relates generally to programming motor vehicle control systems. More specifically, aspects of the present disclosure relate to systems, methods, and apparatus for determining lane hazard mitigation strategies for a plurality of currently available lanes on a roadway and generating a vehicle control plan in an ADAS-equipped vehicle in response to the least restrictive lane hazard mitigation strategy. Background Art

[0002] Modern vehicles are becoming increasingly automated, providing driving control with less and less driver intervention. Vehicle automation has been categorized into numerical levels ranging from zero to five, with zero corresponding to no automation with full human control and five corresponding to full automation with no human control. Various advanced driver assistance systems (ADAS), such as cruise control, adaptive cruise control, and parking assist systems, correspond to lower levels of automation, while truly "driverless" vehicles correspond to higher levels of automation.

[0003] Adaptive cruise control systems have been developed that not only maintain a set speed but also automatically slow the vehicle if it detects a slower-moving vehicle ahead using various sensors, such as radar and cameras. Furthermore, some vehicle systems attempt to keep the vehicle near the center of its lane on the road. However, maintaining lane speed on rough roads or roads with other nearby hazards, such as construction obstacles, can not only cause discomfort to vehicle occupants but, in some cases, can also result in a loss of vehicle control.

[0004] Conventional implementations of active safety methods are anti-lock braking and traction control systems to help maintain vehicle stability by sensing road conditions and intervening in vehicle braking and throttle control selections. However, autonomous driving systems can be further assisted by supplementing such control systems with strategies that intervene in vehicle control when hazards are detected in or near the road. It would be desirable to address these issues and provide a method and apparatus for implementing lane hazard mitigation strategies in ADAS-equipped motor vehicles. Furthermore, other desirable features and characteristics of the present disclosure will become apparent from the subsequent detailed description and the appended claims, taken in conjunction with the accompanying drawings and the aforementioned technical and background information. Summary of the Invention

[0005] Disclosed herein are driver assistance vehicle control systems and methods for providing a vehicle driver assistance vehicle control system, as well as related control logic, methods for manufacturing such systems, and methods for operating such systems, as well as motor vehicles equipped with driver assistance vehicle control systems. Various embodiments of a system for providing lane hazard mitigation strategies in a motor vehicle equipped with an ADAS disclosed herein are presented by way of example and not limitation.

[0006] According to an exemplary embodiment, a system for executing a lane hazard mitigation algorithm includes: a sensor for detecting a first hazard in a main road lane and a second hazard in an adjacent road lane; a processor for determining a main lane mitigation including a main lane speed reduction in response to the first hazard and an adjacent lane mitigation including an adjacent lane speed reduction in response to the second hazard, the processor being further configured to generate a lane change control signal in response to the adjacent lane speed reduction being less than the main lane speed reduction, and to generate a vehicle speed reduction control signal in response to the main lane speed reduction being less than the adjacent lane speed reduction; and a vehicle controller for controlling a lane change maneuver of a main vehicle from the main road lane to the adjacent lane in response to the lane change control signal, and for reducing the main vehicle speed by the main lane speed reduction in response to the vehicle speed reduction control signal.

[0007] According to another aspect of the present disclosure, wherein the sensor is an onboard camera, and wherein the first hazard and the second hazard are detected in response to an image recognition algorithm executed by a processor.

[0008] According to another aspect of the present disclosure, at least one of the first hazard and the second hazard includes at least one of a construction zone traffic drum, a construction obstacle, a pothole, a rough road surface, a snowy road surface, an icy road surface, a pedestrian, and a stopped vehicle.

[0009] According to another aspect of the present disclosure, further including a memory for storing map data, and wherein the sensor is a global navigation satellite system sensor for detecting a host vehicle position, and wherein at least one of the first hazard and the second hazard is determined in response to the host vehicle position, the map data, and at least one of vehicle-to-vehicle communication and infrastructure-to-vehicle communication.

[0010] According to another aspect of the present disclosure, wherein the adjacent lane speed reduction is proportional to the magnitude of the roughness of the adjacent lane, and wherein the host lane speed reduction is proportional to the magnitude of the roughness of the host road lane.

[0011] According to another aspect of the present disclosure, wherein the vehicle controller is configured to control a lane change maneuver in response to an automatic lane change algorithm enabled by a host vehicle ADAS controller.

[0012] According to another aspect of the present disclosure, wherein the sensor is further operable to detect a third hazard in the main road lane, and wherein the main lane speed reduction is determined responsive to the greater of a first speed reduction associated with the first hazard or a second speed reduction associated with the third hazard.

[0013] According to another aspect of the present disclosure, the sensor is a lidar.

[0014] According to another aspect of the present disclosure, wherein the first hazard is roughness of the main road lane, and wherein the main lane mitigation includes performing a lateral stability maneuver, and wherein the main lane speed reduction is proportional to the magnitude of the roughness of the main road lane.

[0015] According to another aspect of the present disclosure, a method for providing a lane hazard mitigation algorithm includes: detecting, by a sensor, a first hazard in a main vehicle lane and a second hazard in an adjacent vehicle lane; determining, in response to the first hazard, a main lane mitigation including a main lane speed reduction and in response to the second hazard, an adjacent lane mitigation including an adjacent lane speed reduction; generating, by a processor, a lane change control signal in response to the main lane speed reduction being greater than the adjacent lane speed reduction; generating, by the processor, a vehicle speed reduction control signal in response to the adjacent lane speed reduction being greater than the main lane speed reduction; reducing, by a vehicle controller, the main vehicle speed in the main vehicle lane in response to the vehicle speed reduction control signal; and performing, by the vehicle controller, a lane change operation from the main vehicle lane to the adjacent vehicle lane in response to the lane change control signal.

[0016] According to another aspect of the present disclosure, including generating a user alert indicating a lane change maneuver on a host vehicle in-cabin display in response to a lane change control signal.

[0017] According to another aspect of the present disclosure, including generating a user alert indicating a lane hazard in response to a vehicle speed reduction control signal.

[0018] According to another aspect of the present disclosure, wherein the first hazard is a rough road surface, and wherein main lane mitigation includes executing a vehicle lateral stability algorithm.

[0019] According to another aspect of the present disclosure, the main lane speed reduction is determined in response to a user preference associated with the first hazard.

[0020] According to another aspect of the present disclosure, a lane change maneuver is performed in response to generating a user input indicating availability of an adjacent lane having a lower speed reduction and a user confirmation requesting the lane change maneuver.

[0021] According to another aspect of the present disclosure, the lane change control signal is generated in response to an adaptive cruise control function being performed by a host vehicle.

[0022] According to another aspect of the present disclosure, wherein the vehicle speed reduction control signal is generated in response to an adaptive cruise control function being performed by the host vehicle.

[0023] According to another aspect of the present disclosure, including in response to detection of the first hazard and the adaptive cruise control functionality not being activated in the host vehicle, generating a user alert indicating the first hazard.

[0024] According to another aspect of the present disclosure, a vehicle control system for executing a driver assistance algorithm includes: a sensor for detecting a first lane hazard in a host vehicle lane and for detecting a second lane hazard in an adjacent lane; a traction control system configured to detect a roughness magnitude of the host vehicle lane; a processor for determining a primary lane deceleration including a primary lane speed reduction in response to at least one of the first lane hazard and a roughness magnitude exceeding a threshold and determining an adjacent lane deceleration including an adjacent lane speed reduction in response to the second lane hazard, the processor being further configured to generate a lane change control signal in response to the adjacent lane speed reduction being less than the primary lane speed reduction, and to generate a vehicle speed reduction control signal in response to the primary lane speed reduction being less than the adjacent lane speed reduction; and a vehicle controller for controlling a lane change maneuver of the host vehicle in response to the lane change control signal, and for reducing the host vehicle speed by the primary lane speed reduction in response to the vehicle speed reduction control signal.

[0025] According to another aspect of the present disclosure, an image processor is configured to detect a first lane hazard in response to executing an object detection algorithm on a first image, and to detect a second lane hazard in response to executing the object detection algorithm on a second image, and wherein the sensor is a camera configured to capture the first image and the second image and couple the first image and the second image to the image processor. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The present disclosure will be described below with reference to the following drawings, wherein like numerals represent like elements, and wherein:

[0027] Figure 1 is a functional block diagram illustrating an ADAS-equipped motor vehicle according to various embodiments for implementing a lane hazard mitigation strategy;

[0028] Figure 2 An exemplary operating environment for implementing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle according to an exemplary embodiment of the present disclosure is shown;

[0029] Figure 3 A block diagram illustrating an exemplary system for providing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle according to an exemplary embodiment of the present disclosure is shown;

[0030] Figure 4 A flow chart illustrating a method for providing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle according to an exemplary embodiment of the present disclosure is shown;

[0031] Figure 5Another flow chart illustrating a method for providing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle according to an exemplary embodiment of the present disclosure is shown; and

[0032] Figure 6 Another flow chart illustrating a method for providing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle according to an exemplary embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0033] The following detailed description is merely exemplary in nature and is not intended to limit the present disclosure or its application and uses. Furthermore, there is no intention to be bound by any theory presented in the preceding background or the following detailed description.

[0034] Figure 1 An exemplary operating system 100 for implementing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle 10 is shown below in conjunction with Figure 1 The vehicle 10 and Figure 2 Environment 200 and Figure 3 、 Figure 4 、 Figure 5 and Figure 6 The implementation is further described in more detail.

[0035] In various embodiments, vehicle 10 comprises an automobile. Vehicle 10 can be any of a variety of different types of automobiles, such as, for example, a sedan, van, truck, or sport utility vehicle (SUV), and in some embodiments can be two-wheel drive (2WD) (i.e., rear-wheel drive or front-wheel drive), four-wheel drive (4WD), or all-wheel drive (AWD), and / or various other types of vehicles. In some embodiments, vehicle 10 can also include a motorcycle or other vehicle, such as an airplane, spacecraft, watercraft, etc., and / or one or more other types of mobile platforms (e.g., robots and / or other mobile platforms).

[0036] like Figure 1 As depicted in FIG, vehicle 10 generally includes a chassis 12, a body 14, front wheels 16, and rear wheels 18. The body 14 is disposed on the chassis 12 and substantially surrounds the components of the vehicle 10. The body 14 and chassis 12 may together form a frame. The wheels 16-18 are each rotationally coupled to the chassis 12 near a corresponding corner of the body 14.

[0037] In various embodiments, the vehicle 10 can be an ADAS-equipped vehicle having an operating system 100 for implementing a lane hazard mitigation strategy incorporated into the vehicle 10 (hereinafter referred to as the vehicle 10). For example, the vehicle 10 is a vehicle that can be automatically controlled to transport passengers from one location to another. In the illustrated embodiment, the vehicle 10 is depicted as a passenger car, but it should be understood that any other means of transportation may also be used, including motorcycles, trucks, sport utility vehicles (SUVs), recreational vehicles (RVs), marine vessels, aircraft, etc. In an exemplary embodiment, the autonomous vehicle 10 is autonomous in that it provides partial or full automatic assistance to the driver operating the vehicle 10. As used herein, the term operator includes the driver of the vehicle 10 and / or the autonomous driving system of the vehicle 10.

[0038] As shown, autonomous vehicle 10 generally includes a propulsion system 20, a transmission system 22, a steering system 24, a braking system 26, a sensor system 28, an actuator system 30, at least one data storage device 32, at least one controller 34, and a communication system 36. In various embodiments, propulsion system 20 may include an internal combustion engine, an electric motor such as a traction motor, and / or a fuel cell propulsion system. Transmission system 22 is configured to transmit power from propulsion system 20 to vehicle wheels 16-18 according to selectable speed ratios. In various embodiments, transmission system 22 may include a stepped-ratio automatic transmission, a continuously variable transmission, or other suitable transmission. Braking system 26 is configured to provide braking torque to vehicle wheels 16-18. In various embodiments, braking system 26 may include friction brakes, brake-by-wire brakes, a regenerative braking system such as an electric motor, and / or other suitable braking systems. Steering system 24 influences the position of vehicle wheels 16-18. Although depicted as including a steering wheel for illustrative purposes, in some embodiments contemplated within the scope of the present disclosure, steering system 24 may not include a steering wheel.

[0039] Sensor system 28 includes one or more sensing devices 40a-40n that sense observable conditions of the external environment and / or the internal environment of autonomous vehicle 10. Sensing devices 40a-40n may include, but are not limited to, radar, lidar, global positioning systems, optical cameras, thermal cameras, ultrasonic sensors, inertial measurement units, and / or other sensors.

[0040] The actuator system 30 includes one or more actuator devices 42a-42n that control one or more vehicle features, such as, but not limited to, the propulsion system 20, the transmission system 22, the steering system 24, and the braking system 26. In various embodiments, the vehicle features may further include interior and / or exterior vehicle features, such as, but not limited to, doors, trunks, and cabin features, such as air, music, lighting, etc. (not numbered).

[0041] The communication system 36 is configured to wirelessly communicate information to and from other entities 48, such as, but not limited to, other vehicles ("V2V" communications), infrastructure ("V2I" communications), remote systems, and / or personal devices (for Figure 2 In an exemplary embodiment, the communication system 36 is a wireless communication system configured to communicate via a wireless local area network (WLAN) using the IEEE 802.11 standard or by using cellular data communications. However, additional or alternative communication methods, such as dedicated short-range communication (DSRC) channels, are also considered within the scope of the present disclosure. A DSRC channel refers to a one-way or two-way short- to medium-range wireless communication channel designed specifically for automotive use and a corresponding set of protocols and standards.

[0042] Data storage device 32 stores data used to automatically control autonomous vehicle 10. In various embodiments, data storage device 32 stores a defined map of the navigable environment. In various embodiments, the defined map may be predefined and obtained from a remote system (e.g., a map of a vehicle). Figure 2 Detailed description is provided below.) For example, a defined map may be assembled by a remote system and transmitted to autonomous vehicle 10 (wirelessly and / or by wire), and stored in data storage device 32. It will be appreciated that data storage device 32 may be part of controller 34, separate from controller 34, or part of controller 34 and part of a separate system.

[0043] The controller 34 includes at least one processor 44 and a computer-readable storage device or medium 46. The processor 44 can be any custom or commercially available processor, a central processing unit (CPU), a graphics processing unit (GPU), a secondary processor among several processors associated with the controller 34, a semiconductor-based microprocessor (in the form of a microchip or chipset), a macroprocessor, any combination thereof, or any device generally used to execute instructions. For example, the computer-readable storage device or medium 46 can include volatile and non-volatile storage in read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is persistent or non-volatile memory that can be used to store various operating variables when the processor 44 is powered off. The computer-readable storage device or medium 46 can be implemented using any of a number of known memory devices, such as PROM (programmable read-only memory), EPROM (electrical PROM), EEPROM (electrically erasable PROM), flash memory, or any other electrical, magnetic, optical, or combination memory device capable of storing data, some of which represents executable instructions used by the controller 34 in controlling the vehicle 10.

[0044] The instructions may include one or more separate programs, each program including an ordered list of executable instructions for implementing logical functions. When executed by processor 44, the instructions receive and process signals from sensor system 28, execute logic, calculations, methods, and / or algorithms for automatically controlling components of autonomous vehicle 10, and generate control signals to actuator system 30 to automatically control components of autonomous vehicle 10 based on the logic, calculations, methods, and / or algorithms. Although Figure 1 Only one controller 34 is shown, but embodiments of autonomous vehicle 10 may include any number of controllers 34 that communicate via communication messages over any suitable communication medium or combination of communication mediums and cooperate to process sensor signals, execute logic, calculations, methods, and / or algorithms, and generate control signals to automatically control features of vehicle 10.

[0045] In various embodiments, one or more instructions of the controller 34 are embodied in the quality and safety assessment system 100 and, when executed by the processor 44, process sensor data from the sensing devices 40a-40n, message data from the communication medium and / or communication system 36, and / or data sent to or received from the actuator devices 42a-42n and calculate a score and interpretation regarding the safety and driving quality of the operator of the vehicle 10.

[0046] Now go to Figure 2 , illustrates an exemplary operating environment 200 for a lane hazard mitigation strategy in an ADAS-equipped motor vehicle 210. In this exemplary embodiment of the present disclosure, a host vehicle 210 is driven on a multi-lane road 205 having various hazards, such as neighboring vehicles 220, rough road sections 215, construction barrels 225, and potholes 230.

[0047] In some exemplary embodiments, the host vehicle 210 is equipped with ADAS features, such as adaptive cruise control and automatic lane centering. During assisted driving operations, the ADAS controller controls the throttle, brakes, and steering of the host vehicle 210 to control vehicle speed and vehicle position to keep the host vehicle 210 within the lane. The ADAS controller can be configured to maintain a constant speed, detect adjacent objects, such as vehicles approaching slowly moving within the lane, and reduce the vehicle speed appropriately. Similarly, the ADAS controller can keep the host vehicle 210 in the center of the current lane and control the steering to change the position of the host vehicle 210 within the lane in response to detected hazards, such as debris. When ADAS is activated, the ADAS can further execute a lane hazard mitigation algorithm to reduce the host vehicle speed in response to hazards detected in or near the multi-lane road 205.

[0048] For each detected drivable lane, the lane hazard mitigation algorithm can calculate a lane hazard mitigation speed that is a function of driver preference, detected lane hazards, detected hazardous speed limit signs, and vehicle handling and occupant comfort considerations. In response to the detected lane hazard, driver preference, and available lateral control, the lane hazard mitigation algorithm can reduce vehicle speed to the hazard mitigation speed for the primary lane and, if on a rough road, apply some lateral stabilization. Simultaneously, the lane hazard mitigation algorithm can determine the availability of a less hazardous adjacent lane with a higher hazard mitigation speed.

[0049] While utilizing ADAS features, degradation of handling and ride comfort on rough lanes can be mitigated by a lane hazard mitigation algorithm, which can be configured to reduce vehicle speed in response to detected lane hazards, apply lateral vehicle stabilization, and, if detected and available, move the host vehicle 210 to a less hazardous adjacent lane. The lane hazard mitigation algorithm addresses hazards on both sides of the lane, such as construction barrels 225 and / or construction barriers, workers, pedestrians, disabled vehicles, emergency vehicles, or other stopped vehicles 220, by determining an appropriate lane speed for each hazard, reducing the host vehicle speed to the slowest appropriate lane speed, and / or navigating the host vehicle 210 to the lane with the highest appropriate lane speed. In some exemplary embodiments, the appropriate lane speed for each type of hazard can be configured by the vehicle operator or in response to user preferences determined based on past driver actions associated with each type of hazard. These driver actions can include lane changes, braking, vehicle speed, lane position, etc. In some exemplary embodiments, driver preferences for interacting with common lane hazards can be assigned as a percentage speed reduction from the posted lane speed for each hazard. Quantifying the detected hazards for each lane may be performed by calculating the speed reduction for each hazard present and selecting a maximum speed reduction or vehicle speed.

[0050] Now go to Figure 3 , a block diagram illustrating an exemplary implementation of a system 300 for executing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle is shown. The exemplary system 300 may include a processor 320, a camera 240, and a GPS sensor 345. In addition, the processor 320 may receive information such as map data 350 from a memory or the like, and may receive user input via a user interface 353.

[0051] The camera 340 may be a low-fidelity camera with a forward field of view (FOV). The camera 340 may be mounted inside the vehicle behind the rearview mirror or mounted on the front fascia of the vehicle. The camera 340 may use captured images and / or video that may be used to detect preceding and adjacent vehicles, obstacles, lane markings, road edges, road features, other road markings, and road hazards during ADAS operation. The images captured by the camera 340 and the data generated from the images may be used to augment the map data stored in the memory 350.

[0052] The GPS sensor 345 may be part of a global navigation satellite system (GNSS) to receive multiple time-stamped satellite signals from satellites that include location data. The GPS controller then uses this information to determine the precise location of the GPS sensor 345. The processor 320 may be operable to receive the location data from the GPS controller and store the location data in the memory 350. The memory 350 may be operable to store map data for use by the processor 320. The memory 350 may further be operable to store the map data, wherein the map data may be high-definition map data including a detailed representation of a road including precise road location, lane location, curves, elevation, known lane hazards, and other road details.

[0053] Processor 320 is operable to engage and control the ADAS in response to activation of the ADAS by a user via user interface 353. During ADAS operation, processor 320 may be operable to generate a desired path in response to user input, among other things, where the desired path may include lane centering, curve following, lane changes, and the like. This desired path information may be determined in response to vehicle speed, yaw angle, and the lateral position of the vehicle within the lane. Once the desired path is determined, a control signal indicating the desired path is generated by processor 320 and coupled to vehicle controller 330. Vehicle controller 330 is operable to receive the control signal and generate a separate steering control signal coupled to steering controller 370, a brake control signal coupled to brake controller 360, and a throttle control signal coupled to throttle controller 355 to execute the desired path.

[0054] According to an exemplary embodiment, processor 320 is further operable to execute a lane hazard mitigation algorithm. Processor 320 may first receive data from various sensors, map data from memory 350, and telemetry data from vehicle controller 330. In response to the received data, processor 320 may then determine the location of various lane hazards, such as rough road surfaces, obstacles, or objects approaching the road lane. Processor 320 may then determine lane hazard mitigation for each available road lane. Lane hazard mitigation may include reducing speed, adjusting lateral position within the lane, activating traction control algorithms (such as suspension stiffening), and so on. Processor 320 may then determine which of the available road lanes offers the least restrictive lane hazard mitigation and then present an indication to the driver that the road lane offers the least restrictive lane hazard mitigation. In some exemplary embodiments, such as when a lane change algorithm is enabled in an ADAS algorithm, processor 320 may generate a control signal to couple to vehicle controller 330 to execute a lane change maneuver from the current vehicle lane to the road lane offering the least restrictive lane hazard mitigation.

[0055] Now go to Figure 4 , a flow chart illustrating an exemplary implementation of a method 400 for executing a lane hazard mitigation strategy in an ADAS-equipped motor vehicle is shown. The method 400 is first operable to initiate 405 a lane hazard mitigation algorithm. The lane hazard mitigation algorithm may be initiated in response to activation of a vehicle ADAS system, such as in response to user activation via a user interface, in response to detection of the vehicle entering a predefined geographic area, or in response to an emergency takeover of the vehicle control system by an ADAS controller, among others. In some exemplary embodiments, the lane hazard mitigation algorithm is activated whenever the adaptive cruise control feature is engaged.

[0056] In response to the activation of the lane hazard mitigation algorithm, method 400 may then proceed to detect objects 410 within the vehicle's host lane and other adjacent areas (such as adjacent lanes, the shoulder of the road, etc.). These objects may include dynamic objects, such as neighboring vehicles traveling on the road, as well as static objects, such as debris or obstacles in the road, disabled or stopped vehicles on the shoulder or in the lane, construction barriers, construction towers or barrels, and road surface features, such as potholes, curbs, ice, snow, and rough road sections. In some exemplary embodiments, static objects may be mapped to a coordinate system referenced to the host vehicle. Additionally, lane markings and other road indicators may be mapped to the coordinate system.

[0057] In response to detecting objects and road features in proximity to the host vehicle, method 400 next determines whether any of the objects are lane hazards 415. Lane hazards may include any objects that pose a challenge to the ADAS control system (including perception, planning, and decision-making systems), potentially leading to an accident or unsafe situation. Additionally, lane hazards may include objects in proximity to the vehicle's lane that may cause discomfort to the vehicle's occupants. For example, construction buckets lined up on one side of the lane may not pose a significant hazard to the ADAS control system, but may cause discomfort or stress to the vehicle's occupants, in which case the human driver may reduce the vehicle's speed or adjust the vehicle's position within the lane, such as by moving away from the buckets in the lane.

[0058] If any detected object is determined to be a lane hazard, method 400 then applies 420 lane hazard mitigation to the host lane. Lane hazard mitigation can be mitigation associated with a specific type of lane hazard. For example, entering a construction zone can have a vehicle speed reduction of 20% from the posted speed. Approaching a construction bucket aligned to one side of the host lane can have a vehicle speed reduction of 15% from the current vehicle speed, with the host vehicle's lateral position within the host lane shifted 10% away from the center of the lane and away from the construction bucket. In some exemplary embodiments, these lane hazard mitigations can be factory defaults, user-selected mitigation values, or identified from previous driver responses to encountering specific types of lane hazards. In some exemplary embodiments, lane hazard mitigation can be regulated mitigation associated with traffic laws in the current location. For example, a construction zone may require a maximum speed of 35 mph, so the lane hazard mitigation for detecting a construction zone is to reduce the host vehicle's speed from the current speed to 35 mph. Figure 6 The description of further discusses a method 600 for establishing lane hazard mitigation for a lane hazard mitigation strategy.

[0059] Once lane hazard mitigation has been applied, or if no objects have been identified as lane hazards, method 400 next determines whether the host road surface is a rough road 425. Rough road conditions can be determined in response to host vehicle traction control data, a vehicle controller, accelerometers, camera data, map data, and the like. The traction control system can determine the roughness of the host lane in response to wheel slip information indicating one or more vehicle wheels are slipping with low traction. Additionally, accelerometer data can indicate lateral and vertical accelerations of the host vehicle and / or the host vehicle's suspension system. The vehicle controller can then determine the roughness of the road in response to the magnitude of these accelerations. In some exemplary embodiments, the road roughness can be determined in response to map data, data from other vehicles indicating a rough road or impending rough road condition, or data received to the host vehicle from a data source via a wireless network. Figure 5The description further discusses a method 500 for establishing lane hazard mitigation for rough roads in a lane hazard mitigation strategy.

[0060] In response to the determined roughness of the road, the method may then apply 430 lateral rough road mitigation. Rough road mitigation may include reducing host vehicle speed, reducing engine power to the slipping wheel or wheels, applying brakes to reduce slip, and reducing host vehicle speed. In some exemplary embodiments, the magnitude of rough road mitigation may be proportional to the magnitude of the roughness of the road. For example, if the road is minimally rough, such as grooved asphalt, the rough road mitigation may be less than for a very rough road, such as a gravel road with excessive corrugation.

[0061] Once the rough road lane hazard mitigation has been applied, or if the primary lane has not yet been determined to be rough, the method 400 next calculates a lane hazard mitigation for each adjacent lane. In some exemplary embodiments, a lane hazard mitigation is calculated for each available lane in the road. Lane hazard mitigation for the adjacent lanes involves determining a lane hazard mitigation for any lane hazard in each adjacent lane and a rough road mitigation for each adjacent lane. The most restrictive mitigation for the adjacent lane is then designated as the mitigation for that lane. Next, the method 400 determines whether there is a greater mitigation speed or a less restrictive mitigation in any adjacent lane 435 responsive to the most restrictive mitigation for the primary lane and the most restrictive mitigation for each of the adjacent lanes. If there is no greater mitigation speed or less restrictive mitigation in the adjacent lane, the method next warns the driver 440 of the lane hazard for the primary lane and returns to detecting adjacent objects 410.

[0062] If there is a greater deceleration in the adjacent lane, the method 400 next determines whether the ADAS system has enabled 445 a lane change algorithm. If the lane change algorithm is not enabled, the method 400 alerts the driver to the lane with the highest deceleration 450, alerts the driver to lane hazards in the host lane 440, and returns to detecting neighboring objects 410.

[0063] If a lane change algorithm, such as an automatic lane change algorithm, is enabled, the method 400 then navigates the host vehicle to the adjacent lane with the highest deceleration speed 455. After performing the lane change maneuver, the adjacent lane becomes the host vehicle's current lane. The method 400 may then warn the driver of the higher deceleration speed in the current lane 450, may warn the driver of a lane hazard in the current lane 440, and return to detecting neighboring objects 410.

[0064] Now go to Figure 5, a flow chart illustrating an exemplary implementation of a method 500 for employing lane hazard mitigation for rough road conditions in an ADAS-equipped motor vehicle is shown. In some exemplary embodiments, method 500 is first initiated 510 in response to a call, such as a subroutine call, from a lane hazard mitigation algorithm and / or an ADAS control algorithm. Method 500 then determines 515 whether the current road surface is rough road conditions. Rough road conditions may be determined in response to vehicle dynamics data, such as accelerometer data indicating lateral and vertical acceleration, and may be determined in response to steering system torque, traction control information indicating wheel slip, and / or wheel speed. Furthermore, rough road conditions may be determined in response to map data stored in vehicle memory, data received from other vehicles via a vehicle-to-vehicle (V2V) communication system, or data received via an infrastructure-to-vehicle (I2V) communication system. In some exemplary embodiments, rough road conditions may include wet, snowy, or sandy roads or other road surfaces where traction is reduced due to weather conditions or other debris.

[0065] If the lane is not determined to be rough, the ADAS system sets the lane speed to the current system speed 520 or the current posted speed limit for the current road and / or lane, or it may be a user-defined lane speed. The method 500 then sets the vehicle speed 560 to the system speed, and the rough road mitigation algorithm completes 570.

[0066] If a rough road is detected 515, the method determines 540 a system speed percentage reduction for the rough road. In some exemplary embodiments, the system speed percentage reduction can be proportional to the magnitude of the road roughness. For example, a road with a lower magnitude of roughness will have a lower system speed percentage reduction than a road with a higher magnitude of roughness. In some exemplary embodiments, the roughness can be determined in response to the amount of wheel slip detected by the host vehicle. The system set speed 530 is multiplied by the system speed percentage reduction for the rough road to obtain a vehicle lane speed for the rough road 550. Next, the vehicle speed 560 of the host vehicle is set to the vehicle lane speed for the rough road, and the rough road mitigation algorithm is completed 570.

[0067] Now go to Figure 6, a flow chart illustrating an exemplary implementation of a method 600 for establishing a lane hazard mitigation strategy for an ADAS-equipped motor vehicle is shown. In some exemplary embodiments, method 600 is first initiated 610 in response to a call, such as a subroutine call, from a lane hazard mitigation algorithm and / or an ADAS control algorithm. Next, method 600 is configured to select a minimum mitigation speed 620 from a plurality of mitigation speeds corresponding to different detected lane hazards and / or rough lane conditions. The plurality of mitigation speeds may include a construction bucket mitigation speed 625, a construction obstacle mitigation speed 630, a person or vehicle on the shoulder of the road mitigation speed 635, a rough road mitigation speed 640, and / or a construction zone mitigation speed 345. Each of the plurality of mitigation speeds is considered as a minimum mitigation speed only if that particular hazard or condition is detected in or near the host vehicle's primary lane. When the minimum mitigation speed for each detected hazard is determined, the vehicle speed is set to the minimum mitigation speed 650, and the lane hazard mitigation speed algorithm completes 660.

[0068] It should be understood that the systems, vehicles, and methods may vary from those depicted in the figures and described herein. For example, Figure 1 Vehicle 10, its control system and lane hazard mitigation control system and / or Figure 1 The components thereof may vary in different embodiments. Similarly, it should be understood that the steps of processes 400, 500, and 600 may vary. Figure 2 The steps depicted in FIG. 1 and / or the various steps of process 200 may occur simultaneously and / or separately. Figure 4 、 Figure 5 and Figure 6 It should also be understood that Figure 1 、 Figure 2 and Figure 3 The implementation of may also vary in different embodiments.

[0069] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that there are a large number of variations. It should also be understood that the exemplary embodiment or multiple exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of the present disclosure in any way. On the contrary, the foregoing detailed description will provide those skilled in the art with a convenient roadmap for implementing the exemplary embodiment or multiple exemplary embodiments. It should be understood that various changes may be made to the function and arrangement of elements without departing from the scope of the present disclosure as set forth in the appended claims and their legal equivalents.

Claims

1. A system for executing a lane hazard mitigation algorithm, comprising: a sensor for detecting a first hazard in a lane of the main road and a second hazard in a lane of an adjacent road; a processor for determining a main lane deceleration including a main lane speed reduction in response to the first hazard and an adjacent lane deceleration including an adjacent lane speed reduction in response to the second hazard, the processor being further configured to generate a lane change control signal in response to the adjacent lane speed reduction being less than the main lane speed reduction, and to generate a vehicle speed reduction control signal in response to the main lane speed reduction being less than the adjacent lane speed reduction; as well as A vehicle controller is configured to control a lane change maneuver of a host vehicle from the primary road lane to an adjacent lane in response to the lane change control signal and to reduce host vehicle speed via the primary lane speed reduction in response to the vehicle speed reduction control signal.

2. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: The sensor is an onboard camera, and wherein the first hazard and the second hazard are detected in response to an image recognition algorithm executed by the processor.

3. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: At least one of the first hazard and the second hazard includes at least one of a construction zone traffic drum, a construction obstacle, a pothole, a rough road surface, a snowy road surface, an icy road surface, a pedestrian, and a stopped vehicle.

4. The system for executing a lane hazard mitigation algorithm according to claim 1 , further comprising a memory for storing map data, and wherein The sensor is a global navigation satellite system sensor for detecting a host vehicle position, and wherein at least one of the first hazard and the second hazard is determined in response to the host vehicle position, the map data, and at least one of vehicle-to-vehicle communication and infrastructure-to-vehicle communication.

5. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: The adjacent lane speed reduction is proportional to the magnitude of the roughness of the adjacent lane, and wherein the main lane speed reduction is proportional to the magnitude of the roughness of the main road lane.

6. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: The vehicle controller is configured to control the lane change maneuver in response to an automatic lane change algorithm enabled by a host vehicle ADAS controller.

7. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: The sensor is further operable to detect a third hazard in the main road lane, and wherein the main lane speed reduction is determined in response to the greater of a first speed reduction associated with the first hazard or a second speed reduction associated with the third hazard.

8. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: The sensor is a lidar.

9. The system for executing a lane hazard mitigation algorithm according to claim 1, wherein: The first hazard is roughness of the main road lane, and wherein the main lane mitigation comprises performing a lateral stability maneuver, and wherein the main lane speed reduction is proportional to a magnitude of the roughness of the main road lane.

10. A method for providing a lane hazard mitigation algorithm, comprising: detecting, by a sensor, a first hazard in a host vehicle lane and a second hazard in an adjacent vehicle lane; determining a main lane deceleration including a main lane speed reduction in response to the first hazard and determining an adjacent lane deceleration including an adjacent lane speed reduction in response to the second hazard; generating, by a processor, a lane change control signal in response to the primary lane speed reduction being greater than the adjacent lane speed reduction; generating, by the processor, a vehicle speed reduction control signal in response to the adjacent lane speed reduction being greater than the main lane speed reduction; reducing, by a vehicle controller, a host vehicle speed within the host vehicle lane in response to the vehicle speed reduction control signal; as well as A lane change maneuver from the host vehicle lane to the adjacent vehicle lane is performed by the vehicle controller in response to the lane change control signal.

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