DESC:FIELD OF INVENTION
The present disclosure generally relates to the field of collision avoidance systems. More particularly, the present disclosure relates to a collision avoidance system with scenario-based disablement of automated braking and a method thereof.
DEFINITIONS
As used in the present disclosure, the following terms are generally intended to have the meaning as set forth below, except to the extent that the context in which they are used to indicates otherwise.
The term “vehicle” hereinafter refers to an ego vehicle that contains a plurality of sensors that perceive the environment around the vehicle.
The term “set of predefined rules” is a set of instructions used to determine the oncoming and ongoing traffic and further detect the traffic condition by identifying the difference between the number of stationary objects/obstacles.
The term “predefined threshold value” hereinafter refers to the speed threshold value of the vehicle.
BACKGROUND
The background information herein below relates to the present disclosure but is not necessarily prior art.
Collision avoidance is one of the principal components of safe driving. Collision avoidance systems are emerging in the marketplace to warn drivers of potential collision threats in the forward, side (left and right), and rear directions. Current collision avoidance systems utilize visual and/or auditory alerts to warn a vehicle driver of a potential collision. There are various scenarios and techniques used for collision avoidance like forward collision warning, reverse collision warning system, adaptive cruise control collision mitigation, and lane-keeping devices.
The challenge with a Collision Avoidance system is deciding the speed threshold below which automated braking will be disabled while starting from stationary. If this is set too low, it may cause unnecessary braking. If it is set too high, then a driver may not have enough time to take corrective action in case of an impending collision. The specific value of the speed threshold depends on the traffic condition and is dynamic in nature due to which it cannot be set to optimal value beforehand.
Hence, to strike a balance between these two extremes, a system/mechanism for scenario-based disablement of automated braking uses a combination of factors such as the speed of the surrounding vehicle(s), the distance between them, and the overall traffic density.
Therefore, there is felt a need for a collision avoidance system with scenario-based disablement of automated braking and a method thereof that alleviates the aforementioned drawbacks.
OBJECTS
Some of the objects of the present disclosure, which at least one embodiment herein satisfies, are as follows:
It is an object of the present disclosure to ameliorate one or more problems of the prior art or to at least provide a useful alternative.
An object of the present disclosure is to provide a system for collision avoidance with scenario-based disablement of automated braking.
Another object of the present disclosure is to provide a system for dynamic collision avoidance.
Still another object of the present disclosure is to provide a system for better-automated emergency braking (AEB) control.
Yet another object of the present disclosure is to provide a system for collision avoidance in complex driving environments.
Another object of the present disclosure is to provide a system for detecting stationary objects/obstacles and the number of moving objects/obstacles.
Still another object of the present disclosure is to provide a system for operating the braking of the vehicle automatically for the desired duration.
Yet another object of the present disclosure is to provide a system for re-enabling the vehicle automatically in the desired duration.
Still another object of the present disclosure is to provide a system for providing warnings in real-time to the driver while avoiding unintended automated braking.
Yet another object of the present disclosure is to provide a method for collision avoidance with scenario-based disablement of automated braking.
Other objects and advantages of the present disclosure will be more apparent from the following description, which is not intended to limit the scope of the present disclosure.
SUMMARY
The present disclosure envisages a collision avoidance system with scenario-based disablement of automated braking and a method thereof.
The system comprises a controlling module, a region detection module, a traffic detection module, a traffic density module, and a collision avoidance module.
The controlling module of a vehicle has a plurality of sensors configured to detect the surrounding area in 360-degrees in which objects/obstacles are detected in real-time.
The region detection module is configured to cooperate with the controlling module to detect a region of interest (ROI) from the detected surrounding area in real-time, where the region of interest (ROI) is determined based on a moving direction of the vehicle.
The traffic detection module is configured to cooperate with the region detection module to detect a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in the region of interest (ROI) by means of a set of object/ obstacles detection rules, and further configured to determine a distance of the vehicle from the moving and stationary objects/obstacles by means of a set of distance determining rules.
The traffic density module is configured to cooperate with the traffic detection module to determine a state of a traffic condition in accordance with the determined distance by means of a set of predefined rules.
The collision avoidance module is configured to cooperate with the traffic density module to determine a heavy traffic condition in real-time by means of a set of traffic detection rules applied on the determined state of the traffic condition and further configured to accurately disable the automated braking until the vehicle moves in the heavy traffic condition and further configured to re-enable the automated braking once the vehicle moves out of the heavy traffic condition.
In an aspect, the system comprises a memory and a microprocessor.
In an aspect, the memory is configured to store predefined commands, the set of distance determining rules, the set of object/ obstacle detection rules, the set of predefined rules, the set of traffic detection rules, and a predefined threshold value.
In an aspect, the microcontroller is configured to fetch the predefined commands to operate and execute one or more modules of the system.
In an aspect, the traffic condition is detected when the difference between the number of stationary objects/obstacles and the number of moving objects/obstacles in the direction of the vehicle is positive in the region of interest (ROI).
In an aspect, the heavy traffic condition is determined in real-time by analyzing the max speed of all objects/obstacles in the ROI is less than the predefined threshold value and the number of objects/obstacles is more than the predefined number.
In an aspect, the heavy traffic condition consists of oncoming traffic and ongoing traffic of vehicles and objects/obstacles, and further, the oncoming traffic and ongoing traffic are determined based on the sign of the relative velocity, wherein the relative velocity is a velocity of an object with respect to another object.
In an aspect, the automated braking of the vehicle automatically operates in the desired duration by means of the set of predefined rules and is further configured to disable the braking of the vehicle for the desired duration during heavy traffic conditions in the ROI.
In an aspect, the plurality of sensors determines the region of interest (ROI) from the center of the vehicle in the range of between a field of view of positive 30 degrees and negative 30 degrees and a distance of 60 m from the front of the vehicle.
In an aspect, the predefined threshold value is a speed threshold value of the vehicle speed value used for disabling the automated emergency braking (AEB).
In an aspect, the collision avoidance module is configured to provide a warning in real-time to the driver of the vehicle while avoiding unintended automated braking.
The present disclosure also envisages a method for collision avoidance with scenario-based disablement of automated braking. The method comprises the following steps:
• detecting, by a controlling module of a vehicle having a plurality of sensors, the surrounding area in 360-degrees in which objects/obstacles are being detected in real-time;
• detecting, by a region detection module, a region of interest (ROI) from the detected surrounding area in real-time, wherein the region of interest (ROI) is determined based on a moving direction of the vehicle;
• detecting, by a traffic detection module, a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in the region of interest (ROI) by means of a set of object/ obstacles detection rules, and determining a distance of the vehicle from the moving and stationary objects/obstacles by means of a set of distance determining rules;
• determining, by a traffic density module, a state of a traffic condition in accordance with the determined distance by means of a set of predefined rules; and
• determining, by a collision avoidance module a heavy traffic condition in real-time by means of a set of traffic detection rules applied to the determined state of the traffic condition and accurately disabling the automated braking until the vehicle move in the heavy traffic condition and re-enable the automated braking once the vehicle moves out of the heavy traffic condition.
In an aspect, the method further comprises the steps:
• storing, by a memory, predefined commands, the set of distance determining rules, the set of object/ obstacles detection rules, the set of predefined rules, the set of traffic detection rules, and a predefined threshold value; and
• fetching, by a microcontroller, the predefined commands to operate and execute one or more modules of the system.
BRIEF DESCRIPTION OF THE ACCOMPANYING DRAWING
A collision avoidance system with scenario-based disablement of automated braking and a method thereof of the present disclosure will now be described with the help of the accompanying drawing, in which:
Figure 1 illustrates a collision avoidance system with scenario-based disablement of automated braking in accordance with an embodiment of the present disclosure; and
Figure 2A and Figure 2B illustrate a flow chart depicting steps involved in method 200 for collision avoidance with scenario-based disablement of automated braking in accordance with an embodiment of the present disclosure.
LIST OF REFERENCE NUMERALS
100 - System
102 - Controlling Module
102a - Plurality of Sensors
104 - Region Detection Module
106 - Traffic Detection Module
108 - Traffic Density Module
110 - Collision Avoidance Module
112 - Memory
114 - Microcontroller
116 - Vehicle
DETAILED DESCRIPTION
Embodiments, of the present disclosure, will now be described with reference to the accompanying drawing.
Embodiments are provided so as to thoroughly and fully convey the scope of the present disclosure to the person skilled in the art. Numerous details, are set forth, relating to specific components, and methods, to provide a complete understanding of embodiments of the present disclosure. It will be apparent to the person skilled in the art that the details provided in the embodiments should not be construed to limit the scope of the present disclosure. In some embodiments, well-known processes, well-known apparatus structures, and well-known techniques are not described in detail.
The terminology used, in the present disclosure, is only for the purpose of explaining a particular embodiment and such terminology shall not be considered to limit the scope of the present disclosure. As used in the present disclosure, the forms "a,” "an," and "the" may be intended to include the plural forms as well, unless the context clearly suggests otherwise. The terms “including,” and “having,” are open ended transitional phrases and therefore specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not forbid the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof. The particular order of steps disclosed in the method and process of the present disclosure is not to be construed as necessarily requiring their performance as described or illustrated. It is also to be understood that additional or alternative steps may be employed.
When an element is referred to as being “engaged to,” "connected to," or "coupled to" another element, it may be directly engaged, connected, or coupled to the other element. As used herein, the term "and/or" includes any and all combinations of one or more of the associated listed elements.
Collision avoidance is one of the principal components of safe driving. Collision avoidance systems are emerging in the marketplace to warn drivers of potential collision threats in the forward, side (left and right), and rear directions. Current collision avoidance systems utilize visual and/or auditory alerts to warn a vehicle driver of a potential collision. There are various scenarios and techniques used for collision avoidance like forward collision warning, reverse collision warning system, adaptive cruise control collision mitigation, and lane-keeping devices.
The challenge with a Collision Avoidance system is deciding the speed threshold below which automated braking will be disabled while starting from stationary. If this is set too low, it may cause unnecessary braking. If it is set too high, then a driver may not have enough time to take corrective action in case of an impending collision. The specific value of the speed threshold depends on the traffic condition and is dynamic in nature due to which it cannot be set to optimal value beforehand.
Hence, to strike a balance between these two extremes, a system/mechanism for scenario-based disablement of automated braking uses a combination of factors such as the speed of the surrounding vehicle(s), the distance between them, and the overall traffic density.
To address the issues of the existing systems and methods, the present disclosure envisages a collision avoidance system with scenario-based disablement of automated braking (hereinafter referred to as “system 100”) and a method for a collision avoidance system with scenario-based disablement of automated braking (hereinafter referred to as “method 200”). The system 100 will now be described with reference to Figure 1 and the method 200 will be described with reference to Figure 2A and Figure 2B.
Referring to Figure 1, the system 100 comprises a controlling module 102, a region detection module 104, a traffic detection module 106, a traffic density module 108, and a collision avoidance module 110.
The controlling module 102 of a vehicle 116 has a plurality of sensors 102a configured to detect the surrounding area in 360-degrees in which objects/obstacles are detected in real-time.
In an aspect, the plurality of sensors 102a determines the region of interest (ROI) from the center of the vehicle in the range of between a field of view of positive 30 degrees and negative 30 degrees and a distance of 60 m from the front of the vehicle.
The region detection module 104 is configured to cooperate with the controlling module 102 to detect a region of interest (ROI) from the detected surrounding area in real-time, where the region of interest (ROI) is determined based on the moving direction of the vehicle.
The traffic detection module 106 is configured to cooperate with the region detection module 104 to detect a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in the region of interest (ROI) by means of a set of object/ obstacles detection rules.
The traffic detection module 106 is further configured to determine the distance of the vehicle from the moving and stationary objects/obstacles by means of a set of distance determining rules.
The traffic density module 108 is configured to cooperate with the traffic detection module 106 to determine a state of a traffic condition in accordance with the determined distance by means of a set of predefined rules.
In an aspect, the set of predefined rules is used to detect the traffic condition by identifying the difference between the number of stationary objects/obstacles and the number of moving objects/obstacles, further, the set of predefined rules is used to determine the oncoming and ongoing traffic.
In an aspect, the traffic condition is detected when the difference between the number of stationary objects/obstacles and the number of moving objects/obstacles in the direction of the vehicle is positive in the region of interest (ROI).
The collision avoidance module 110 is configured to cooperate with the traffic density module 108 to determine a heavy traffic condition in real-time by means of a set of traffic detection rules applied to the determined state of the traffic condition.
The collision avoidance module 110 is further configured to accurately disable the automated braking until the vehicle moves in heavy traffic conditions and further configured to re-enable the automated braking once the vehicle moves out of the heavy traffic condition.
In an aspect, the heavy traffic condition is determined in real-time by analyzing the max speed of all objects/obstacles in the ROI is less than the predefined threshold value and the number of objects/obstacles is more than the predefined number.
In an aspect, the predefined threshold value is a speed threshold value of the vehicle speed value used for disabling the automated emergency braking (AEB).
In an aspect, the heavy traffic condition consists of oncoming traffic and ongoing traffic of vehicles and objects/obstacles, and further, the oncoming traffic and ongoing traffic are determined based on the sign of the relative velocity, wherein the relative velocity is a velocity of an object with respect to another object.
In an aspect, the automated braking of the vehicle automatically operates in the desired duration by means of the set of predefined rules and is further configured to disable the braking of the vehicle for the desired duration during heavy traffic conditions in the ROI.
In an aspect, the ROI is determined from the center of the vehicle and the distance from the front of the vehicle.
In an aspect, the collision avoidance module 110 is configured to provide a warning in real-time to the driver of the vehicle while avoiding unintended automated braking.
In an aspect, the warning may be selected from a group of warnings consisting of a text, video, haptic, display, light indication, voice, and the like.
In an aspect, the system 100 further comprises a memory 112 and a microprocessor 114.
In an aspect, the memory 112 is configured to store predefined commands, the set of distance determining rules, the set of objects/ obstacles detection rules, the set of predefined rules, the set of traffic detection rules, and a predefined threshold value.
In an aspect, the memory 112 may be a memory that can store one or more computer-readable instructions or routines, which may be fetched and executed to avoid collision with scenario-based disablement of automated braking. The memory may include any non-transitory storage device including, for example, volatile memory such as RAM, or non-volatile memory such as EPROM, flash memory, and the like.
In an alternative aspect, the memory 112 may be an external data storage device coupled to the system 100 directly or through one or more data servers.
In an aspect, the microcontroller 114 is configured to fetch the predefined commands to operate and execute one or more modules of the system 100.
In an aspect, the microcontroller 114 may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the microprocessor 114 may fetch and execute computer-readable instructions stored in a memory. The functions of the microcontroller 114 may be provided through the use of dedicated hardware as well as hardware capable of executing machine-readable instructions. In other examples, the microcontroller 114 may be implemented by electronic circuitry or printed circuit board. The microcontroller 114 may be configured to execute functions of various modules of the system 100 such as the controlling module 102, the region detection module 104, the traffic detection module 106, the traffic density module 108, and the collision avoidance module 110.
In an aspect, the system 100 may also include a communication interface. The communication interface may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, transceivers, storage devices, and the like. The communication interface may facilitate communication of the system 100 with various devices coupled to the system 100 or the microcontroller 114. The communication interface may also provide a communication pathway for one or more components of the system 100 and the microcontroller 114.
Also, the system 100 or the microcontroller 114 may include, or be coupled with, one or more transceivers to communicate with various devices coupled to the system 100 or the microcontroller 114.
In an aspect, the system 100 provides a mechanism for scenario based automated brake disablement. The challenge with a Collision Avoidance system is deciding the speed threshold below which automated braking will be disabled while starting from stationary. If this is set too low, it may cause unnecessary braking. If it is set too high, then a driver may not have enough time to take corrective action in case of an impending collision. The specific value of the speed threshold depends on the traffic condition and is dynamic in nature due to which it cannot be set to optimal value beforehand. In order to strike a balance between these two extremes, a mechanism for scenario based disablement of automated braking uses a combination of factors such as the speed of the surrounding vehicle(s), the distance between them, and the overall traffic density. The mechanism proposed allows the system to accurately disable the automated braking until the vehicle is out of the heavy traffic conditions, providing the driver with the warnings on time while avoiding unintended automated braking.
In an aspect, the system 100 provides scenario based disablement of automated braking mechanism that determines the heavy traffic condition by analyzing the obstacle density in the region of interest. The region of interest is defined in terms of the sensors’ Field of View (+-3000) from the center of the vehicle and a distance of 60 m from the front of the vehicle. The heavy traffic condition is determined if the difference between the number of stationary objects and the number of moving objects in the direction of the vehicle is positive in the region of interest. The oncoming and ongoing traffic is determined based on the sign of the relative velocity. The heavy traffic condition is determined based on whether the max speed of all the obstacles in the region of interest is less than the predefined threshold value and the number of such obstacles is more than the predefined number. The automated braking will be disabled in all heavy traffic conditions and re-enabled once the vehicle is out of heavy traffic conditions.
The following are the set of instructions used for collision avoidance systems with scenario-based disablement of automated braking:
• Initialization:
o Load necessary data and rules into the system.
o Activate sensors and modules.
• Detect Surrounding Area:
o Continuously scan 360 degrees around the vehicle.
o Update the data in real-time.
• Identify ROI:
o Determine ROI based on the vehicle's current trajectory and position.
• Object and Distance Detection:
o Classify objects within ROI into stationary and moving categories.
o Calculate the distance of each object from the vehicle.
• Traffic Condition Assessment:
o Analyze the density and movement patterns of objects in the ROI.
o Apply traffic condition rules to assess the current traffic state.
• Collision Avoidance Decision Making:
o Based on traffic condition, decide whether to disable or enable automated braking.
o Implement real-time decision-making to adapt to changing traffic conditions.
• Braking System Control:
o If in heavy traffic, temporarily disable automated braking to prevent unnecessary stops.
o Re-enable automated braking when traffic conditions improve.
o Ensure driver is alerted in real-time about system decisions.
• Special Conditions and Exceptions:
o Adjust system behavior based on special traffic patterns and predefined exceptional conditions.
• Feedback and Adjustment:
o Continuously monitor system performance.
o Adjust parameters and rules as needed for optimal operation
Figure 2A and Figure 2B illustrate a flow chart depicting steps involved in method 200 for collision avoidance with scenario-based disablement of automated braking in accordance with an embodiment of the present disclosure. The order in which method 200 is described is not intended to be construed as a limitation, and any number of the described method steps may be combined in any order to implement method 200, or an alternative method. Furthermore, method 200 may be implemented by processing resource or computing device(s) through any suitable hardware, non-transitory machine-readable medium/instructions, or a combination thereof. The method 200 comprises the following steps:
At step 202, the method 200 includes detecting, by a controlling module 102 of a vehicle 116 having a plurality of sensors 102a, the surrounding area in 360-degree in which objects/obstacles are detected in real-time.
At step 204, the method 200 includes detecting, by a region detection module 104, a region of interest (ROI) from the detected surrounding area in real-time, where the region of interest (ROI) is determined based on a moving direction of the vehicle.
At step 206, the method 200 includes detecting, by a traffic detection module 106, a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in the region of interest (ROI) by means of a set of object/ obstacles detection rules and determining a distance of the vehicle from the moving and stationary objects/obstacles by means of a set of distance determining rules.
At step 208, the method 200 includes determining, by a traffic density module 108, a state of a traffic condition in accordance with the determined distance by means of a set of predefined rules.
At step 210, the method 200 includes determining, by a collision avoidance module 110, a heavy traffic condition in real-time by means of a set of traffic detection rules applied on the determined state of the traffic condition and accurately disabling the automated braking until the vehicle move in the heavy traffic condition and re-enable the automated braking once the vehicle moves out of the heavy traffic condition.
An exemplary pseudo-code depicting the implementation of method 200 for collision avoidance with scenario-based disablement of automated braking.
// Collision Avoidance System (CAS)
// Modules
ControllingModule sensors[] // Array of sensors for 360-degree detection
RegionDetectionModule regionDetector
TrafficDetectionModule trafficDetector
TrafficDensityModule trafficDensity
CollisionAvoidanceModule collisionAvoider
Memory memory // Memory for storing rules and commands
Microcontroller microcontroller // Microcontroller for executing commands

// Main operation loop
while (vehicle is operational) {
// Detect surrounding area
surroundingArea = ControllingModule.detectSurroundings(sensors)
// Detect Region of Interest (ROI) based on vehicle's moving direction
ROI = RegionDetectionModule.detectRegion(surroundingArea)
// Detect objects in ROI and determine distance
objects = TrafficDetectionModule.detectObjects(ROI)
distances = TrafficDetectionModule.determineDistances(objects)
// Determine traffic condition
trafficCondition = TrafficDensityModule.determineTrafficState(distances)
// Determine heavy traffic condition
isHeavyTraffic = CollisionAvoidanceModule.determineHeavyTraffic(trafficCondition)
// Disable/Enable automated braking based on traffic condition
if (isHeavyTraffic) {
CollisionAvoidanceModule.disableAutomatedBraking()
} else {
CollisionAvoidanceModule.enableAutomatedBraking()
}
// Provide real-time warning to driver
CollisionAvoidanceModule.provideWarningToDriver()
// Fetch and execute predefined commands
commands = Memory.fetchPredefinedCommands()
Microcontroller.executeCommands(commands)
}
// Additional Functions
function detectTrafficCondition(objects) {
// Detect traffic condition based on the difference between moving and stationary objects
}
function determineHeavyTrafficCondition(maxSpeed, numberOfObjects) {
// Determine heavy traffic condition based on max speed and number of objects
}
function determineOncomingOngoingTraffic(relativeVelocity) {
// Determine oncoming and ongoing traffic based on relative velocity
}
function operateAutomatedBraking(duration, rules) {
// Operate automated braking for a specified duration based on rules
}
In an operative configuration, the system 100 comprises a controlling module 102 of a vehicle 116 having a plurality of sensors 102a is configured to detect the surrounding area in 360-degree in which objects/obstacles being detected in real-time. The region detection module 104 is configured to cooperate with the controlling module 102 to detect a region of interest (ROI) from the detected surrounding area in real-time, wherein the region of interest (ROI) being determined based on a moving direction of the vehicle. The traffic detection module 106 is configured to cooperate with the region detection module 104 to detect a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in the region of interest (ROI) by means of a set of object/ obstacles detection rules and further configured to determine a distance of the vehicle from the moving and stationary objects/obstacles by means of a set of distance determining rules. The traffic density module 108 is configured to cooperate with the traffic detection module 106 to determine the state of a traffic condition in accordance with the determined distance by means of a set of predefined rules. The collision avoidance module 110 is configured to cooperate with the traffic density module 108 to determine a heavy traffic condition in real-time by means of a set of traffic detection rules applied on the determined state of the traffic condition and further configured to accurately disable the automated braking until the vehicle moves in the heavy traffic condition and configured to re-enable the automated braking once the vehicle moves out of the heavy traffic condition.
Advantageously, the system 100 provides for collision avoidance with scenario-based disablement of automated braking. The system 100 provides a mechanism for scenario-based disablement of automated braking using a combination of factors such as the speed of the surrounding vehicle(s), the distance between them, and the overall traffic density. The system 100 accurately disables the automated braking until the vehicle is out of the heavy traffic conditions, providing the driver with the warnings on time while avoiding unintended automated braking. The system 100 provides the collision avoidance system’s pre-defined speed threshold for disabling the (AEB) as the driving conditions are dynamic in nature and have a lot of complex inputs due to which a pre-defined threshold can lead to either unnecessary braking or no braking when required. The system 100 provides the dynamic setting of the speed threshold for disabling based on important factors/conditions like the speed of surrounding vehicle(s), distance of ego vehicle with surrounding vehicles, and overall traffic density.
The functions described herein may be implemented in hardware, software executed by a processor, firmware, or any combination thereof. If implemented in software executed by a processor, the functions may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Other examples and implementations are within the scope and spirit of the disclosure and appended claims. For example, due to the nature of software, functions described above can be implemented using software executed by a processor, hardware, firmware, hardwiring, or combinations of any of these. Features implementing functions may also be physically located at various positions, including being distributed such that portions of functions are implemented at different physical locations.
The foregoing description of the embodiments has been provided for purposes of illustration and is not intended to limit the scope of the present disclosure. Individual components of a particular embodiment are generally not limited to that particular embodiment, but are interchangeable. Such variations are not to be regarded as a departure from the present disclosure, and all such modifications are considered to be within the scope of the present disclosure.
TECHNICAL ADVANCEMENTS
The present disclosure described herein above has several technical advantages including, but not limited to, the realization of a collision avoidance system with scenario-based disablement of automated braking that:
• are scalable;
• are dynamic;
• are safe;
• keep the driver alert;
• have better AEB control;
• have a better understanding of complex driving environments; and
• can automatically operate the braking of the vehicle and re-enable the vehicle.
The embodiments herein and the various features and advantageous details thereof are explained with reference to the non-limiting embodiments in the following description. Descriptions of well-known components and processing techniques are omitted so as to not unnecessarily obscure the embodiments herein. The examples used herein are intended merely to facilitate an understanding of ways in which the embodiments herein may be practiced and to further enable those of skill in the art to practice the embodiments herein. Accordingly, the examples should not be construed as limiting the scope of the embodiments herein.
The foregoing description of the specific embodiments so fully reveals the general nature of the embodiments herein that others can, by applying current knowledge, readily modify and/or adapt for various applications such specific embodiments without departing from the generic concept, and, therefore, such adaptations and modifications should and are intended to be comprehended within the meaning and range of equivalents of the disclosed embodiments. It is to be understood that the phraseology or terminology employed herein is for the purpose of description and not of limitation. Therefore, while the embodiments herein have been described in terms of preferred embodiments, those skilled in the art will recognize that the embodiments herein can be practiced with modification within the spirit and scope of the embodiments as described herein.
The use of the expression “at least” or “at least one” suggests the use of one or more elements or ingredients or quantities, as the use may be in the embodiment of the disclosure to achieve one or more of the desired objects or results.
While considerable emphasis has been placed herein on the components and component parts of the preferred embodiments, it will be appreciated that many embodiments can be made and that many changes can be made in the preferred embodiments without departing from the principles of the disclosure. These and other changes in the preferred embodiment as well as other embodiments of the disclosure will be apparent to those skilled in the art from the disclosure herein, whereby it is to be distinctly understood that the foregoing descriptive matter is to be interpreted merely as illustrative of the disclosure and not as a limitation.
,CLAIMS:WE CLAIM:
1. A method (200) for collision avoidance with scenario-based disablement of automated braking, said method (200) comprises the following steps:
• detecting, by a controlling module (102) of a vehicle (116) having a plurality of sensors (102a), the surrounding area in 360-degree in which objects/obstacles are being detected in real-time;
• detecting, by a region detection module (104), a region of interest (ROI) from said detected surrounding area in real-time, wherein said region of interest (ROI) being determined based on a moving direction of the vehicle;
• detecting, by a traffic detection module (106), a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in said region of interest (ROI) by means of a set of object/ obstacles detection rules, and determining a distance of the vehicle from said moving and stationary objects/obstacles by means of a set of distance determining rules;
• determining, by a traffic density module (108), a state of a traffic condition in accordance with the determined distance by means of a set of predefined rules; and
• determining, by a collision avoidance module (110), a heavy traffic condition in real-time by means of a set of traffic detection rules applied to the determined state of the traffic condition for accurately disabling the automated braking until the vehicle moves in said heavy traffic condition and re-enable said automated braking once the vehicle moves out of said heavy traffic condition.
2. The method (200) claimed in claim 1, wherein said method (200) further comprises the following steps:
• storing, by a memory (112), predefined commands, said set of distance determining rules, said set of object/ obstacles detection rules, said set of predefined rules, said set of traffic detection rules, and a predefined threshold value; and
• fetching, by a microcontroller (114), said predefined commands to operate and execute one or more modules of said system (100).
3. The method (200) claimed in claim 1, wherein detecting said traffic condition when the difference between the number of stationary objects/obstacles and the number of moving objects/obstacles in the direction of the vehicle is positive in said region of interest (ROI).
4. The method (200) claimed in claim 1, wherein determining said heavy traffic condition in real-time by analyzing the max speed of all objects/obstacles in the ROI is less than the predefined threshold value and the number of objects/obstacles is more than the predefined number.
5. The method (200) claimed in claim 1, wherein said heavy traffic condition consisting of oncoming traffic and ongoing traffic of vehicles and objects/obstacles and further said oncoming traffic and ongoing traffic are determined based on the sign of the relative velocity, wherein said relative velocity is a velocity of an object with respect to another object.
6. The method (200) claimed in claim 1, wherein operating said automated braking of the vehicle automatically in the desired duration by means of said set of predefined rules and disabling said braking of the vehicle for the desired duration during heavy traffic conditions in the ROI.
7. The system (100) claimed in claim 1, wherein said collision avoidance module (110) is configured to provide a warning in real-time to the driver of the vehicle while avoiding unintended automated braking.
8. A collision avoidance system (100) with scenario-based disablement of automated braking, said system (100) comprising:
• a controlling module (102) of a vehicle (116) having a plurality of sensors (102a) configured to detect the surrounding area in 360-degree in which objects/obstacles are being detected in real-time;
• a region detection module (104) configured to cooperate with said controlling module (102) to detect a region of interest (ROI) from said detected surrounding area in real-time, wherein said region of interest (ROI) being determined based on a moving direction of the vehicle;
• a traffic detection module (106) configured to cooperate with said region detection module (104) to detect a number of stationary objects/obstacles and a number of moving objects/obstacles in the direction of the vehicle in a forward or backward direction in said region of interest (ROI) by means of a set of object/ obstacles detection rules, and further configured to determine a distance of the vehicle from said moving and stationary objects/obstacles by means of a set of distance determining rules;
• a traffic density module (108) configured to cooperate with said traffic detection module (106) to determine a state of a traffic condition in accordance with the determined distance by means of a set of predefined rules; and
• a collision avoidance module (110) configured to cooperate with said traffic density module (108) to determine a heavy traffic condition in real-time by means of a set of traffic detection rules applied on the determined state of the traffic condition and further configured to accurately disable the automated braking until the vehicle move in said heavy traffic condition and further configured to re-enable said automated braking once the vehicle moves out of said heavy traffic condition.
9. The system (100) claimed in claim 8, wherein said system (100) further comprises:
• a memory (112) configured to store predefined commands, said set of distance determining rules, said set of object/ obstacles detection rules, said set of predefined rules, said set of traffic detection rules, and a predefined threshold value; and
• a microcontroller (114) configured to fetch said predefined commands to operate and execute one or more modules of said system (100).
10. The system (100) claimed in claim 8, wherein, said plurality of sensors (102a) determines the region of interest (ROI) from the center of the vehicle in the range of between a field of view of positive 30 degrees and negative 30 degrees and a distance of 60 m from the front of the vehicle.
11. The system (100) claimed in claim 8, wherein said predefined threshold value is a speed threshold value of the vehicle speed value used for disabling the automated emergency braking (AEB).
Dated this 07th Day of February, 2024

_______________________________
MOHAN RAJKUMAR DEWAN, IN/PA – 25
of R.K. DEWAN & CO.
Authorized Agent of Applicant

TO,
THE CONTROLLER OF PATENTS
THE PATENT OFFICE, AT MUMBAI