System and method for managing following distance of a vehicle

Abstract

Systems and methods for managing a following distance of a vehicle are provided. Front vehicle sensor data associated with a front vehicle is received from a sensor system of the vehicle. The front vehicle is disposed ahead of the vehicle in a lane of a roadway. At least one front vehicle characteristic associated with the front vehicle is determined based on the front vehicle sensor data. A front vehicle characteristic-based following distance of the vehicle relative to the front vehicle is generated based on the at least one front vehicle characteristic. A final following distance is generated based at least in part on the front vehicle characteristic-based following distance. A following distance notification including the final following distance is generated.

Description

Technical Field

[0001] The technical field generally relates to vehicles, and more specifically to systems and methods for managing following distances between vehicles. Background Technology

[0002] On a road lane, the following distance of a vehicle relative to the vehicle in front of it may vary depending on the characteristics of the vehicle in front, external environmental conditions, the speed of the vehicle, and the driver's following distance preference.

[0003] Therefore, it is desirable to provide a system and method for managing following distance of vehicles. Other desirable features and characteristics will become apparent from the accompanying drawings and the foregoing technical and background information, based on the following detailed description and the appended claims. Summary of the Invention

[0004] A system for managing following distance of a vehicle includes at least one processor and at least one memory communicatively coupled to the at least one processor. The at least one memory includes instructions that, when executed by the at least one processor, cause the at least one processor to: receive forward vehicle sensor data associated with a preceding vehicle positioned in front of the vehicle in a lane of the road from the vehicle's sensor system; determine at least one forward vehicle characteristic associated with the preceding vehicle based on the forward vehicle sensor data; generate a forward vehicle characteristic-based following distance of the vehicle relative to the preceding vehicle based on the at least one forward vehicle characteristic; generate a final following distance based at least in part on the forward vehicle characteristic-based following distance; and generate a following distance notification including the final following distance.

[0005] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive a crowdsourced following distance associated with at least one characteristic of the vehicle ahead from a vehicle data collection center; and generate a final following distance based at least in part on the crowdsourced following distance.

[0006] In at least one embodiment, at least one front vehicle characteristic includes vehicle brand, vehicle model, vehicle bumper sticker, vehicle towing status, vehicle movement, vehicle condition, vehicle speed, vehicle tendency to throw debris, and vehicle type.

[0007] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive external environment data from at least one of a vehicle's sensor system, a vehicle's navigation system, and an external environment data source; generate at least one external environment condition based on the external environment data; generate a following distance of the vehicle relative to a vehicle ahead based on the external environment condition based on the external environment condition; and generate a final following distance based at least in part on the following distance based on the external environment condition.

[0008] In at least one embodiment, the external environment data includes at least one of the following: weather data, road condition data, global positioning system (GPS) data, vehicle route data, vehicle dynamics data, road construction data, luggage rack data, external noise data, and external air characteristics data.

[0009] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: make a first determination regarding whether external environmental conditions include severe weather; generate a first additional following distance based on the first determination; make a second determination regarding whether external environmental conditions include poor road conditions; generate a second additional following distance based on the second determination; make a third determination regarding whether external environmental conditions include at least one stop sign or at least one traffic light on the vehicle's route; generate a third additional following distance based on the third determination; make a fourth determination regarding whether external environmental conditions include at least one curve or at least one ramp on the vehicle's route; generate a fourth additional following distance based on the fourth determination; make a fifth determination regarding whether external environmental conditions include a detected cannabis odor; generate a fifth additional following distance based on the fifth determination; and make a sixth determination regarding whether external environmental conditions include a burnt rubber odor. A sixth additional following distance is generated based on the sixth determination; a seventh determination is made regarding whether the external environmental conditions include the presence of road debris on the road; a seventh additional following distance is generated based on the seventh determination; an eighth determination is made regarding whether the external environmental conditions include a loose luggage strap on the vehicle ahead; an eighth additional following distance is generated based on the eighth determination; a ninth determination is made regarding whether the external environmental conditions include the presence of gravel on the road; a ninth additional following distance is generated based on the ninth determination; a tenth determination is made regarding whether the external environmental conditions include an obstacle obstructing the view of at least one traffic light from the vehicle; a tenth additional following distance is generated based on the tenth determination; and a following distance based on the external environmental conditions is generated based on the sum of the first additional following distance, the second additional following distance, the third additional following distance, the fourth additional following distance, the fifth additional following distance, the sixth additional following distance, the seventh additional following distance, the eighth additional following distance, the ninth additional following distance, and the tenth additional following distance.

[0010] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive vehicle speed from a sensor system of the vehicle; generate a following distance based on a first speed when the vehicle speed is greater than 75 mph; generate a following distance based on a second speed when the vehicle speed is greater than 60 mph and less than 75 mph; generate a following distance based on a third speed when the vehicle speed is greater than 45 mph and less than 60 mph; generate a following distance based on a fourth speed when the vehicle speed is greater than 30 mph and less than 45 mph; generate a following distance based on a fifth speed when the vehicle speed is less than 30 mph; and determine a final following distance based at least in part on one of the following distances based on the first speed, the second speed, the third speed, the fourth speed, and the fifth speed.

[0011] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive a user-preferred following distance via a user input device of the vehicle; and determine a final following distance based at least in part on the user-preferred following distance.

[0012] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: generate a final following distance realization prompt for display on a display device of the vehicle; and, upon activating the final following distance realization prompt, command the vehicle's Automated Driving System (ADS) to automatically realize the final following distance, wherein the vehicle's ADS realizes the final following distance in response to the command.

[0013] A method for managing following distance of a vehicle, the method comprising: receiving forward vehicle sensor data associated with a preceding vehicle positioned in front of the vehicle in a lane of a road from the vehicle's sensor system; determining at least one forward vehicle characteristic associated with the preceding vehicle based on the forward vehicle sensor data; generating a forward vehicle characteristic-based following distance of the vehicle relative to the preceding vehicle based on the at least one forward vehicle characteristic; generating a final following distance based at least in part on the forward vehicle characteristic-based following distance; and generating a following distance notification including the final following distance for display on a display device of the vehicle.

[0014] In at least one embodiment, the method further includes: receiving a crowdsourced following distance associated with at least one characteristic of the vehicle ahead from a vehicle data collection center; and generating a final following distance based at least in part on the crowdsourced following distance.

[0015] In at least one embodiment, the method further includes: receiving external environment data from at least one of the vehicle's sensor system, the vehicle's navigation system, and an external environment data source; generating at least one external environment condition based on the external environment data; generating a following distance of the vehicle relative to a vehicle ahead based on the external environment condition based on the external environment condition; and generating a final following distance based at least in part on the following distance based on the external environment condition.

[0016] In at least one embodiment, the method further includes: making a first determination regarding whether external environmental conditions include severe weather; generating a first additional following distance based on the first determination; making a second determination regarding whether external environmental conditions include poor road conditions; generating a second additional following distance based on the second determination; making a third determination regarding whether external environmental conditions include at least one stop sign or at least one traffic light on the vehicle's route; generating a third additional following distance based on the third determination; making a fourth determination regarding whether external environmental conditions include at least one curve or at least one ramp on the vehicle's route; generating a fourth additional following distance based on the fourth determination; making a fifth determination regarding whether external environmental conditions include detected cannabis odor; generating a fifth additional following distance based on the fifth determination; making a sixth determination regarding whether external environmental conditions include a burnt rubber odor; generating a sixth additional following distance based on the sixth determination. The system determines whether the external environmental conditions include the presence of road debris; generates a seventh additional following distance based on the seventh determination; makes an eighth determination whether the external environmental conditions include a loose luggage strap on the vehicle ahead; generates an eighth additional following distance based on the eighth determination; makes a ninth determination whether the external environmental conditions include the presence of gravel on the road; generates a ninth additional following distance based on the ninth determination; makes a tenth determination whether the external environmental conditions include an obstacle obstructing the view of at least one traffic light from the vehicle; generates a tenth additional following distance based on the tenth determination; and generates a following distance based on the sum of the first additional following distance, the second additional following distance, the third additional following distance, the fourth additional following distance, the fifth additional following distance, the sixth additional following distance, the seventh additional following distance, the eighth additional following distance, the ninth additional following distance, and the tenth additional following distance.

[0017] In at least one embodiment, the method further includes: receiving vehicle speed from a sensor system of the vehicle; generating a following distance based on a first speed when the vehicle speed is greater than 75 mph; generating a following distance based on a second speed when the vehicle speed is greater than 60 mph and less than 75 mph; generating a following distance based on a third speed when the vehicle speed is greater than 45 mph and less than 60 mph; generating a following distance based on a fourth speed when the vehicle speed is greater than 30 mph and less than 45 mph; generating a following distance based on a fifth speed when the vehicle speed is less than 30 mph; and determining a final following distance based at least in part on one of the following distances based on the first speed, the second speed, the third speed, the fourth speed, and the fifth speed.

[0018] In at least one embodiment, the method further includes: receiving a user-preferred following distance via a user input device of the vehicle; and determining a final following distance based at least in part on the user-preferred following distance.

[0019] In at least one embodiment, the method further includes: generating a final following distance achievement prompt for display on a display device of the vehicle; and issuing a command to the vehicle's Autopilot System (ADS) to automatically achieve the final following distance when the final following distance achievement prompt is activated, wherein the vehicle's ADS achieves the final following distance in response to the command.

[0020] A vehicle including a system for managing following distance of a vehicle includes at least one processor and at least one memory communicatively coupled to the at least one processor. The at least one memory includes instructions that, when executed by the at least one processor, cause the at least one processor to: receive forward vehicle sensor data associated with a preceding vehicle positioned in front of the vehicle in a lane of a road from the vehicle's sensor system; determine at least one forward vehicle characteristic associated with the preceding vehicle based on the forward vehicle sensor data; generate a following distance of the vehicle relative to the preceding vehicle based on the at least one forward vehicle characteristic; generate a final following distance based at least partially on the following distance based on the forward vehicle characteristic; generate a following distance notification including the final following distance for display on a display device of the vehicle; generate a final following distance realization prompt for display on the vehicle's display device; and, upon activation of the final following distance realization prompt, command the vehicle's Automated Driving System (ADS) to automatically realize the final following distance, wherein the vehicle's ADS realizes the final following distance in response to the command.

[0021] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive external environment data from at least one of a vehicle's sensor system, a vehicle's navigation system, and an external environment data source; generate at least one external environment condition based on the external environment data; generate a following distance of the vehicle relative to a vehicle ahead based on the external environment condition based on the external environment condition; and generate a final following distance based at least in part on the following distance based on the external environment condition.

[0022] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive vehicle speed from a sensor system of the vehicle; generate a following distance based on a first speed when the vehicle speed is greater than 75 mph; generate a following distance based on a second speed when the vehicle speed is greater than 60 mph and less than 75 mph; generate a following distance based on a third speed when the vehicle speed is greater than 45 mph and less than 60 mph; generate a following distance based on a fourth speed when the vehicle speed is greater than 30 mph and less than 45 mph; generate a following distance based on a fifth speed when the vehicle speed is less than 30 mph; and determine a final following distance based at least in part on one of the following distances based on the first speed, the second speed, the third speed, the fourth speed, and the fifth speed.

[0023] In at least one embodiment, at least one memory further includes instructions that, when executed by at least one processor, cause at least one processor to: receive a user-preferred following distance via a user input device of the vehicle; and determine a final following distance based at least in part on the user-preferred following distance. Attached Figure Description

[0024] Exemplary embodiments will now be described in conjunction with the following accompanying drawings, wherein similar reference numerals denote similar elements, and in the drawings:

[0025] Figure 1 It is a functional block diagram of a vehicle including a following distance management system according to at least one embodiment;

[0026] Figure 2 This is a functional block diagram of a controller including a following distance management system according to at least one embodiment; and

[0027] Figure 3 This is a flowchart representation of an exemplary method for managing following distance of a vehicle according to at least one embodiment. Detailed Implementation

[0028] The following detailed description is exemplary in nature only and is not intended to limit application and use. Furthermore, there is no intention to be bound by any express or implied theory presented in the foregoing technical fields, background art, summary of the invention, or the following detailed description. As used herein, the term module refers to an application-specific integrated circuit (ASIC), electronic circuitry, a processor (shared, dedicated, or grouped) and memory executing one or more software or firmware programs, combinational logic circuitry, and / or other suitable components that provide the described functionality.

[0029] This document describes embodiments of the present disclosure in terms of functional and / or logical block components and various processing steps. It should be understood that such block components can be implemented by any number of hardware, software, and / or firmware components configured to perform specified functions. For example, embodiments of the present disclosure can employ various integrated circuit components, such as memory elements, digital signal processing elements, logic elements, lookup tables, etc., which can perform various functions under the control of one or more microprocessors or other control devices. Furthermore, those skilled in the art will understand that embodiments of the present disclosure can be practiced in conjunction with any number of systems, and the systems described herein are merely exemplary embodiments of the present disclosure.

[0030] For the sake of brevity, conventional techniques related to signal processing, data transmission, signaling, control, and other functional aspects of the system (and its various operating components) may not be described in detail herein. Furthermore, the connecting lines shown in the various figures included herein are intended to illustrate exemplary functional relationships and / or physical couplings between various elements. It should be noted that many alternative or additional functional relationships or physical connections may exist in the embodiments of this disclosure.

[0031] refer to Figure 1 This diagram illustrates a functional block diagram of a vehicle 10 including a following distance management system 100 according to at least one embodiment. The vehicle 10 typically includes a chassis 12, a body 14, front wheels 16, and rear wheels 18. Although the vehicle 10 is depicted as a passenger car in the illustrated embodiment, the vehicle 10 can be other types of vehicles, including trucks, sports utility vehicles (SUVs), and recreational vehicles (RVs).

[0032] In various embodiments, the body 14 is arranged on the chassis 12 and substantially surrounds the components of the vehicle 10. The body 14 and the chassis 12 may together form a frame. The wheels 16 and 18 are each rotatably coupled to the chassis 12 near a corresponding corner of the body 14.

[0033] In various embodiments, vehicle 10 is an autonomous or semi-autonomous vehicle that is automatically controlled to transport passengers and / or goods from one place to another. For example, in an exemplary embodiment, vehicle 10 is a so-called Level 2, Level 3, Level 4, or Level 5 automation system. Level 2 automation means that the vehicle assists the driver in performing various driving tasks under the supervision of the driver. Level 3 automation means that the vehicle can take over all driving functions under certain conditions. All major functions are automatic, including braking, steering, and acceleration. At this level, the driver can completely let go until the vehicle otherwise informs the driver. A Level 4 system indicates “high automation”, which refers to the driving mode-specific performance of the automated driving system for all aspects of dynamic driving tasks, even if the human driver does not respond appropriately to intervention requests. A Level 5 system indicates “full automation”, which refers to the full-time performance of the automated driving system for all aspects of dynamic driving tasks under all road and environmental conditions that can be managed by a human driver.

[0034] As shown in the figure, vehicle 10 typically 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. The controller 34 is configured to implement an automated driving system (ADS). The propulsion system 20 is configured to generate power to propel the vehicle. The propulsion system 20 includes an internal combustion engine (ICE). In various embodiments, the propulsion system 20 may also include an electric motor (such as a traction motor), a fuel cell propulsion system, and / or any other type of propulsion configuration. The transmission system 22 is configured to transmit power from the propulsion system 20 to the wheels 16, 18 according to a selectable speed ratio. According to various embodiments, the transmission system 22 may include a graded automatic transmission, a continuously variable transmission (CVT), or other suitable transmission. The braking system 26 is configured to provide braking torque to the wheels 16, 18. In various embodiments, the braking system 26 may include a friction brake, a brake-by-wire brake, a regenerative braking system (such as an electric motor), and / or other suitable braking systems.

[0035] Steering system 24 is configured to influence the position of wheels 16. Although depicted for illustrative purposes as including a steering wheel and steering column, in some embodiments contemplated within the scope of this disclosure, steering system 24 may not include a steering wheel and / or steering column. Steering system 24 includes a steering column coupled to axle 50 associated with the front wheels 16 via, for example, a rack and pinion or other mechanism (not shown). Alternatively, steering system 24 may include a steer-by-wire system including an actuator associated with each front wheel 16.

[0036] The sensor system 28 includes one or more sensing devices 40a-40n that sense observable conditions of the external and / or internal environment of the vehicle 10. The sensing devices 40a-40n may include, but are not limited to, radar, lidar, global positioning system, optical camera, thermal camera, ultrasonic sensor, steering wheel sensor, and / or other sensors.

[0037] Vehicle dynamics sensors provide vehicle dynamics data, including longitudinal velocity, yaw rate, lateral acceleration, and longitudinal acceleration. Vehicle dynamics sensors may include wheel sensors that measure information related to one or more wheels of vehicle 10. In one embodiment, the wheel sensors include wheel velocity sensors coupled to each wheel 16, 18 of vehicle 10. Furthermore, vehicle dynamics sensors may include one or more accelerometers (provided as part of an inertial measurement unit (IMU)) that measure information related to the acceleration of vehicle 10. In various embodiments, the accelerometers measure one or more acceleration values ​​of vehicle 10, including lateral and longitudinal acceleration and yaw rate. In at least one embodiment, vehicle dynamics sensors provide vehicle position and vehicle movement data.

[0038] 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, one or more wheels 16, 18, a propulsion system 20, a transmission system 22, a steering system 24, and a braking system 26. In various embodiments, vehicle features may also include interior and / or exterior vehicle features, such as, but not limited to, doors, a trunk, and cabin features such as air, music, lighting, etc. (not numbered).

[0039] The communication system 36 is configured to wirelessly transmit information to and from other entities 48, such as, but not limited to, other vehicles (vehicle-to-vehicle "V2V" communication), infrastructure (vehicle-to-infrastructure "V2I" communication), remote systems, and / or personal devices. 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 communication. However, additional or alternative communication methods, such as dedicated short-range communication (DSRC) channels, are also contemplated within the scope of this disclosure. A DSRC channel refers to a one-way or two-way short-to-medium-range wireless communication channel specifically designed for automotive use and corresponding set of protocols and standards.

[0040] Data storage device 32 stores data for use in the ADS of 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 by and obtained from a remote system. For example, the defined map may be assembled by a remote system and transmitted (wirelessly and / or wired) to vehicle 10 and stored in data storage device 32. As will be understood, data storage device 32 may be part of controller 34, separate from controller 34, or part of controller 34 and a separate system.

[0041] The controller 34 includes at least one processor 44 and a computer-readable storage device or medium 46. The processor 44 may be any custom or commercially available processor, central processing unit (CPU), graphics processing unit (GPU), auxiliary processor among several processors associated with the controller 34, semiconductor-based microprocessor (in the form of a microchip or chipset), macroprocessor, any combination thereof, or any device typically used for executing instructions. The computer-readable storage device or medium 46 may include volatile and non-volatile memory such as read-only memory (ROM), random access memory (RAM), and keep-alive memory (KAM). KAM is a persistent or non-volatile memory that can be used to store various operational variables when the processor 44 is powered off. The computer-readable storage device or medium 46 may be implemented using any of a variety 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 combined memory device capable of storing data, some of which represents executable instructions used by the controller 34 to control the vehicle 10. In at least one embodiment, the computer-readable storage device 46 is at least one memory configured to store the following distance management system 100.

[0042] The instructions may include one or more separate programs, each 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 vehicle 10, and generate control signals to actuator system 30 to automatically control components of vehicle 10 based on logic, calculations, methods, and / or algorithms. Although in Figure 1Only one controller 34 is shown, but embodiments of vehicle 10 may include any number of controllers 34 that communicate via any suitable communication medium or combination of communication media and cooperate to process sensor signals, perform logic, calculations, methods and / or algorithms, and generate control signals to automatically control the features of vehicle 10. In various embodiments, controller 34 is configured to implement ADS.

[0043] refer to Figure 2 A functional block diagram of a controller 34 including a following distance management system 100 according to at least one embodiment is shown. The controller 34 includes at least one processor 44 and at least one memory 46. The at least one processor 44 is a programmable device including one or more instructions stored in or associated with the at least one memory 46. The at least one memory 46 includes instructions that the at least one processor 44 is configured to execute. The at least one memory 46 includes embodiments of the following distance management system 100.

[0044] Controller 34 is configured to communicatively couple to sensor system 28, display device 202, user input device 204, and navigation system 206 of vehicle 10. Controller 34 is also configured to communicatively couple to vehicle data collection center 208 and external environment data source 210. In at least one embodiment, following distance management system 100 is disposed on vehicle 10. In at least one embodiment, following distance management system 100 is hosted by a cloud-based service. Controller 34 may include additional components that facilitate the operation of following distance management system 100. In at least one embodiment, controller 34 may be referred to as following distance management system 100. The operation of following distance management system 100 will be described in more detail below.

[0045] refer to Figure 3 A flowchart representation of an exemplary method 300 for managing the following distance of a vehicle 10 according to at least one embodiment is shown. The method 300 will be described with reference to exemplary implementations of an embodiment of a following distance management system 100. The vehicle 10 includes a following distance management system 100. As will be understood from this disclosure, the order of operations within method 300 is not limited to... Figure 3 The order of execution is not shown, but may be performed in one or more different orders as applicable and in accordance with this disclosure.

[0046] When vehicle 10 is operating on the road, method 300 is initiated when vehicle 10 detects a vehicle ahead. The vehicle ahead is positioned in front of vehicle 10 in the same lane as vehicle 10.

[0047] At 302, the following distance management system 100 receives the user-preferred following distance via the user input device 204. At 304, the following distance management system 100 receives forward vehicle sensor data associated with the vehicle ahead from the sensor system 28 of the vehicle 10. The sensor system 28 includes one or more of LiDAR, radar, vehicle camera, air parameter detection, and microphone. An example of forward vehicle sensor data is image data. The air parameter detection is configured to detect and identify, for example, the smell of cannabis and burnt rubber in collected air samples.

[0048] At 306, the following distance management system 100 determines one or more characteristics of the vehicle ahead. Examples of vehicle characteristics include, but are not limited to, vehicle brand, vehicle model, vehicle bumper sticker, vehicle towing status, vehicle movement, vehicle condition, vehicle speed, tendency to kick up debris, and vehicle type. An example of a vehicle bumper sticker is a "baby in the car" sign. Vehicle towing status indicates whether the vehicle ahead is attached to a trailer. An example of vehicle movement is unstable vehicle movement, which may indicate unstable driver behavior. An example of vehicle condition is a broken bumper. The vehicle ahead (such as, for example, a construction truck) may have a tendency to kick up debris that could impact vehicle 10. Examples of vehicle types include, but are not limited to, 18-wheeler trucks and motorcycles.

[0049] At point 308, the following distance management system 100 generates a following distance based on one or more characteristics of the vehicle in front. For example, the following distance based on the characteristics of the vehicle in front may be larger when the vehicle in front is a motorcycle than when the vehicle is a car.

[0050] At point 310, the following distance management system 100 receives crowdsourced following distances from the vehicle data collection center 208. In at least one embodiment, the following distance management system 100 transmits one or more forward vehicle characteristics to the vehicle data collection center 208. The vehicle data collection center 208 collects crowdsourced following distance data associated with different forward vehicle characteristics from multiple different vehicles. The vehicle data collection center 208 generates a crowdsourced following distance based on the one or more forward vehicle characteristics received from vehicle 10 and the crowdsourced following distance data associated with different forward vehicle characteristics collected from multiple different vehicles. The vehicle data collection center 208 transmits the generated crowdsourced following distance to the following distance management system 100.

[0051] At point 312, the following distance management system 100 receives external environment data from one or more of the sensor system 28, the vehicle 10's navigation system 206, and the external environment data source 210. Examples of external environment data include, but are not limited to, weather data, road condition data, Global Positioning System (GPS) data, vehicle route data, vehicle dynamics data, road construction data, luggage rack data, external noise data, and external air characteristics data.

[0052] At location 314, the following distance management system 100 generates one or more external environmental conditions based on external environmental data. Examples of external environmental conditions include, but are not limited to, severe weather, poor road conditions, vehicle routes including one or more stop signs and / or traffic lights, vehicle routes including one or more curves or one or more ramps, detected marijuana odor, detected burnt rubber odor, road debris on the road, loose luggage straps, gravel on the road, and obstacles obstructing the view of traffic lights from vehicle 10.

[0053] At point 316, the following distance management system 100 generates a following distance based on one or more external environmental conditions.

[0054] In at least one embodiment, the following distance management system 100 determines whether one or more external environmental conditions include severe weather. If the following distance management system 100 determines that one or more external environmental conditions include severe weather, the following distance management system 100 generates a first additional following distance associated with the severe weather.

[0055] The following distance management system 100 determines whether one or more external environmental conditions include poor road conditions. If the following distance management system 100 determines that one or more external environmental conditions include poor road conditions, the following distance management system 100 generates a second additional following distance associated with the poor road conditions.

[0056] The following distance management system 100 determines whether one or more external environmental conditions include one or more stop signs and / or one or more traffic lights on the vehicle route of vehicle 10. If the following distance management system 100 determines that one or more external environmental conditions include one or more stop signs and / or one or more traffic lights on the vehicle route of vehicle 10, the following distance management system 100 generates a third additional following distance associated with the presence of one or more stop signs and / or one or more traffic lights on the vehicle route.

[0057] The following distance management system 100 determines whether one or more external environmental conditions include one or more curves and / or one or more ramps on the vehicle route of vehicle 10. If the following distance management system 100 determines that one or more external environmental conditions include one or more curves and / or one or more ramps on the vehicle route of vehicle 10, the following distance management system 100 generates a fourth additional following distance associated with the presence of one or more curves and / or one or more ramps on the vehicle route.

[0058] The following distance management system 100 determines whether one or more external environmental conditions include the detected marijuana odor. If the following distance management system 100 determines that one or more external environmental conditions include the detected marijuana odor, the following distance management system 100 generates a fifth additional following distance associated with the detected marijuana odor.

[0059] The following distance management system 100 determines whether one or more external environmental conditions include a detected burnt rubber odor. If the following distance management system 100 determines that one or more external environmental conditions include a detected burnt rubber odor, the following distance management system 100 generates a sixth additional following distance associated with the detected burnt rubber odor.

[0060] The following distance management system 100 determines whether one or more external environmental conditions include the presence of road debris on the road. If the following distance management system 100 determines that one or more external environmental conditions include the presence of road debris on the road, the following distance management system 100 generates a seventh additional following distance associated with the presence of road debris on the road.

[0061] The following distance management system 100 determines whether one or more external environmental conditions include a loose luggage strap on the vehicle ahead. If the following distance management system 100 determines that one or more external environmental conditions include a loose luggage strap on the vehicle ahead, the following distance management system 100 generates an eighth additional following distance associated with the loose luggage strap on the vehicle ahead.

[0062] The following distance management system 100 determines whether one or more external environmental conditions include the presence of gravel on the road. If the following distance management system 100 determines that one or more external environmental conditions include the presence of gravel on the road, the following distance management system 100 generates a ninth additional following distance associated with the presence of gravel on the road.

[0063] The following distance management system 100 determines whether one or more external environmental conditions include obstacles that obstruct the view of traffic lights from vehicle 10. If the following distance management system 100 determines that one or more external environmental conditions include obstacles that obstruct the view of traffic lights from vehicle 10, the following distance management system 100 generates a tenth additional following distance associated with the obstacle obstructing the view of traffic lights from vehicle 10.

[0064] The following distance management system 100 generates a first additional following distance, a second additional following distance, a third additional following distance, a fourth additional following distance, a fifth additional following distance, a sixth additional following distance, a seventh additional following distance, an eighth additional following distance, a ninth additional following distance, and a tenth additional following distance based on external environmental conditions. In at least one embodiment, the first additional following distance, the second additional following distance, the third additional following distance, the fourth additional following distance, the fifth additional following distance, the sixth additional following distance, the seventh additional following distance, the eighth additional following distance, the ninth additional following distance, and the tenth additional following distance are predefined values ​​stored in the following distance management system 100 in association with the external environmental conditions detailed above.

[0065] At 318, the following distance management system 100 receives the vehicle speed of vehicle 10 from the sensor system 28 of vehicle 10. At 320, the following distance management system 100 generates a speed-based following distance based on the vehicle speed.

[0066] In at least one embodiment, the following distance management system 100 determines whether the vehicle speed is greater than 75 miles per hour (mph). If the following distance management system 100 determines that the vehicle speed is greater than 75 mph, the following distance management system 100 generates a following distance based on the first speed.

[0067] The following distance management system 100 determines whether the vehicle speed is greater than 60 mph and less than 75 mph. If the following distance management system 100 determines that the vehicle speed is greater than 60 mph and less than 75 mph, then the following distance management system 100 generates a following distance based on the second speed.

[0068] The following distance management system 100 determines whether the vehicle speed is greater than 45 mph and less than 60 mph. If the following distance management system 100 determines that the vehicle speed is greater than 45 mph and less than 60 mph, then the following distance management system 100 generates a following distance based on the third speed.

[0069] The following distance management system 100 determines whether the vehicle speed is greater than 30 mph and less than 45 mph. If the following distance management system 100 determines that the vehicle speed is greater than 30 mph and less than 45 mph, then the following distance management system 100 generates a following distance based on the fourth speed.

[0070] The following distance management system 100 determines whether the vehicle speed is less than 30 mph. If the following distance management system 100 determines that the vehicle speed is less than 30 mph, then the following distance management system 100 generates a following distance based on the fifth speed.

[0071] The following distances based on the first speed, second speed, third speed, fourth speed, and fifth speed have different values. These following distances are predefined values ​​stored in the following distance management system 100 and are associated with different vehicle speed ranges.

[0072] At point 322, the following distance management system 100 generates the final following distance based on the following: user-preferred following distance, following distance based on the characteristics of the vehicle ahead, crowdsourced following distance, following distance based on external environmental conditions, and following distance based on speed. In at least one embodiment, the user-preferred following distance is used as the baseline following distance. The final following distance is always greater than the user-preferred following distance.

[0073] In at least one embodiment, the following distance management system 100 generates a weighted average of the following distance based on the characteristics of the vehicle ahead and the crowdsourced following distance. The following distance management system 100 generates the final following distance as the sum of the user-preferred following distance, the weighted average of the following distance based on the characteristics of the vehicle ahead and the crowdsourced following distance, the following distance based on external environmental conditions, and the following distance based on speed.

[0074] At point 324, the following distance management system 100 generates a following distance notification and a final following distance achievement prompt on the display device 202 of the vehicle 10. In at least one embodiment, the following distance management system 100 generates the following distance notification as an audio notification or a haptic notification.

[0075] In at least one embodiment, the following distance management system 100 receives the actual following distance of the vehicle 10 relative to the vehicle in front from the sensor system 28 of the vehicle 10.

[0076] The following distance management system 100 determines whether the actual following distance is greater than or equal to the final following distance. If the following distance management system 100 determines that the actual following distance is greater than or equal to the final following distance, the following distance management system 100 generates a following distance notification that advises against changing the following distance.

[0077] The following distance management system 100 determines whether the actual following distance is less than the final following distance. If the following distance management system 100 determines that the actual following distance is less than the final following distance, the following distance management system 100 compares the difference between the actual following distance and the final following distance with a following distance threshold.

[0078] If the following distance management system 100 determines that the difference between the actual following distance and the final following distance is greater than the following distance threshold, the following distance management system 100 generates a following distance notification to consider increasing the following distance of vehicle 10 relative to the vehicle in front. The following distance management system 100 generates a final following distance display for display on the display device 202 of vehicle 10.

[0079] If the following distance management system 100 determines that the difference between the actual following distance and the final following distance is less than the following distance threshold, the following distance management system 100 generates a following distance notification to instruct the driver to increase the following distance of vehicle 10 relative to the vehicle in front. The following distance management system 100 generates a final following distance prompt for display on the display device 202 of vehicle 10.

[0080] At point 326, when the final following distance realization prompt is activated via the user input device 204 of vehicle 10, the following distance management system 100 sends a command to the ADS of vehicle 10 to automatically realize the final following distance. The ADS responds to the command and manipulates vehicle 10 to realize the final following distance.

[0081] In an exemplary first use case, the following distance management system 100 identifies the vehicle type of the vehicle ahead as a logging truck. The following distance management system 100 requests and receives the requested crowdsourced following distance associated with the logging truck from the vehicle data collection center 208. The following distance management system 100 generates a final following distance based on this crowdsourced following distance. The following distance management system 100 determines that the actual following distance is less than the final following distance, and determines that the difference between the actual and final following distances is greater than a following distance threshold. The following distance management system 100 generates a final following distance notification for display on the display device 202 of the vehicle 10, which requests the driver to consider increasing the following distance of the vehicle 10 relative to the logging truck.

[0082] The following distance management system 100 generates a final following distance achievement prompt on the display device 202 of the vehicle 10. When the final following distance achievement prompt is activated via the user input device 204 of the vehicle 10, the following distance management system 100 issues a command to the ADS of the vehicle 10 to automatically achieve the final following distance. The ADS responds to the command and manipulates the vehicle 10 to achieve the final following distance.

[0083] In an exemplary second use case, the following distance management system 100 determines that the movement of the vehicle ahead is unstable, which may indicate unstable driver behavior. The following distance management system 100 generates a following distance based on the characteristics of the vehicle ahead based on the unstable vehicle movement. The following distance management system 100 generates a final following distance based on the following distance based on the characteristics of the vehicle ahead. The following distance management system 100 determines that the actual following distance is less than the final following distance, and determines that the difference between the actual following distance and the final following distance is less than a following distance threshold. The following distance management system 100 generates a final following distance notification for display on a display device 202, which instructs the driver to immediately increase the following distance of vehicle 10 relative to the vehicle ahead.

[0084] The following distance management system 100 generates a final following distance achievement prompt on the display device 202 of the vehicle 10. When the final following distance achievement prompt is activated via the user input device 204 of the vehicle 10, the following distance management system 100 issues a command to the ADS of the vehicle 10 to automatically achieve the final following distance. The ADS responds to the command and manipulates the vehicle 10 to achieve the final following distance.

[0085] In an exemplary third use case, the following distance management system 100 identifies the vehicle type of the vehicle ahead as a motorcycle. The following distance management system 100 requests and receives the requested crowdsourced following distance associated with the motorcycle from the vehicle data collection center 208. The following distance management system 100 generates a final following distance based on this crowdsourced following distance. The following distance management system 100 determines that the actual following distance is greater than the final following distance. The following distance management system 100 generates a final following distance notification for display on the display device 202 of the vehicle 10, indicating that changing the following distance is not recommended.

[0086] Although at least one exemplary embodiment has been presented in the foregoing detailed description, it should be understood that numerous variations exist. It should also be understood that the exemplary embodiments or multiple exemplary embodiments are merely examples and are not intended to limit the scope, applicability, or configuration of this disclosure in any way. Rather, the foregoing detailed description will provide those skilled in the art with a convenient roadmap for implementing the exemplary embodiments or multiple exemplary embodiments. It should be understood that various changes can be made to the function and arrangement of the elements without departing from the scope of this disclosure as set forth in the appended claims and their legal equivalents.

Claims

1. A system for managing following distance of vehicles, the system comprising: At least one processor; and At least one memory, communicatively coupled to the at least one processor, the at least one memory including instructions that, when executed by the at least one processor, cause the at least one processor to: The vehicle receives sensor data of a vehicle ahead, which is positioned in front of it in the lane of the road, from its sensor system. At least one forward vehicle characteristic associated with the forward vehicle is determined based on the forward vehicle sensor data; The following distance of the vehicle relative to the vehicle in front is generated based on the characteristics of the at least one vehicle in front. The final following distance is generated at least in part based on the following distance based on the characteristics of the vehicle ahead; as well as Generate a following distance notification that includes the final following distance.

2. The system according to claim 1, wherein, The at least one memory further includes instructions that, when executed by the at least one processor, cause the at least one processor to: Receive crowdsourced following distance associated with at least one characteristic of the vehicle ahead from the vehicle data collection center; and The final following distance is generated at least in part based on the crowdsourced following distance.

3. The system according to claim 1, wherein, The at least one forward vehicle characteristic includes vehicle brand, vehicle model, vehicle bumper sticker, vehicle towing status, vehicle movement, vehicle condition, vehicle speed, tendency of the vehicle to throw debris, and vehicle type.

4. The system according to claim 1, wherein, The at least one memory further includes instructions that, when executed by the at least one processor, cause the at least one processor to: External environment data is received from at least one of the vehicle's sensor system, the vehicle's navigation system, and an external environment data source; At least one external environment condition is generated based on the external environment data; The following distance of the vehicle relative to the vehicle in front is generated based on the external environmental conditions. as well as The final following distance is generated at least in part based on the following distance based on external environmental conditions.

5. The system according to claim 4, wherein, The external environmental data includes at least one of the following: weather data, road condition data, global positioning system (GPS) data, vehicle route data, vehicle dynamics data, road construction data, luggage belt data, external noise data, and external air characteristics data.

6. The system according to claim 4, wherein, The at least one memory further includes instructions that, when executed by the at least one processor, cause the at least one processor to: Make a first determination as to whether the external environmental conditions include severe weather; Based on the first determination, a first additional following distance is generated; Make a second determination as to whether the external environmental conditions include poor road conditions; A second additional following distance is generated based on the second determination; Make a third determination regarding whether the external environmental conditions include at least one stop sign or at least one traffic light on the vehicle's route; A third additional following distance is generated based on the third determination; Make a fourth determination regarding whether the external environmental conditions include at least one curve or at least one ramp on the vehicle route; A fourth additional following distance is generated based on the fourth determination; Make a fifth determination regarding whether the external environmental conditions include the detected cannabis odor; A fifth additional following distance is generated based on the fifth determination; Make a sixth determination regarding whether the external environmental conditions include the smell of burnt rubber; A sixth additional following distance is generated based on the sixth determination; Make a seventh determination regarding whether the external environmental conditions include the presence of road debris on the road; A seventh additional following distance is generated based on the seventh determination; Make an eighth determination regarding whether the external environmental conditions include a loose luggage strap on the vehicle ahead; An eighth additional following distance is generated based on the eighth determination; Make a ninth determination regarding whether the external environmental conditions include the presence of gravel on the road; A ninth additional following distance is generated based on the ninth determination; Make a tenth determination regarding whether the external environmental conditions include an obstacle obstructing the view of the at least one traffic light from the vehicle; Based on the tenth determination, a tenth additional following distance is generated; as well as The following distance based on external environmental conditions is generated by summing the first additional following distance, the second additional following distance, the third additional following distance, the fourth additional following distance, the fifth additional following distance, the sixth additional following distance, the seventh additional following distance, the eighth additional following distance, the ninth additional following distance, and the tenth additional following distance.

7. The system according to claim 1, wherein, The at least one memory further includes instructions that, when executed by the at least one processor, cause the at least one processor to: The vehicle speed is received from the vehicle's sensor system; When the vehicle speed is greater than 75 miles per hour (mph), a following distance based on the first speed is generated; When the vehicle speed is greater than 60 mph and less than 75 mph, a following distance based on the second speed is generated; When the vehicle speed is greater than 45 mph and less than 60 mph, a following distance based on the third speed is generated; When the vehicle speed is greater than 30 mph and less than 45 mph, a following distance based on the fourth speed is generated; When the vehicle speed is less than 30 mph, a following distance based on the fifth speed is generated; as well as The final following distance is determined at least in part based on one of the following distance based on the first speed, the following distance based on the second speed, the following distance based on the third speed, the following distance based on the fourth speed, and the following distance based on the fifth speed.

8. The system according to claim 1, wherein, The at least one memory further includes instructions that, when executed by the at least one processor, cause the at least one processor to: The user's preferred following distance is received via the vehicle's user input device; as well as The final following distance is determined at least in part based on the user's preferred following distance.

9. The system according to claim 1, wherein, The at least one memory further includes instructions that, when executed by the at least one processor, cause the at least one processor to: Generate a final following distance prompt for display on the vehicle's display device; and When the final following distance realization prompt is activated, a command is issued to the vehicle's Autopilot System (ADS) to automatically realize the final following distance, wherein the vehicle's ADS responds to the command to realize the final following distance.

10. A method for managing following distance of vehicles, the method comprising: The vehicle receives sensor data of a vehicle ahead, which is positioned in front of it in the lane of the road, from its sensor system. At least one forward vehicle characteristic associated with the forward vehicle is determined based on the forward vehicle sensor data; The following distance of the vehicle relative to the vehicle in front is generated based on the characteristics of the at least one vehicle in front. The final following distance is generated at least in part based on the following distance based on the characteristics of the vehicle ahead; as well as Generate a following distance notification, including the final following distance, for display on the vehicle's display device.

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