Description:The present invention relates to Advanced Driver Assistance Systems (ADAS) in vehicles. More specifically, the invention pertains to a method, system, and apparatus for real-time object detection and the integration of responsive actions to enhance vehicular safety and assist drivers in various driving scenarios.
This invention leverages the synergies of state-of-the-art computer vision techniques, sensor fusion, and intelligent algorithms to provide accurate real-time detection of objects and potential obstacles. Furthermore, the invention integrates this detection capability with responsive actions to alert the driver, intervene where necessary, and improve overall driving experience, thereby aiding in the reduction of accidents and ensuring safer transportation.
Background of the invention:
The proposed invention introduces a groundbreaking enhancement to the realm of Advanced Driver Assistance Systems (ADAS). At its core, this system is a sophisticated amalgamation of advanced computer vision algorithms, sensor fusion mechanisms, and highly adaptive response functionalities. Instead of merely detecting objects or obstacles, as is the case with many contemporary systems, this invention raises the bar by enabling real-time, accurate detection, and immediate integration of responsive actions.
Using a myriad of sensors, including but not limited to, optical cameras, infrared sensors, radar, and ultrasonic devices, the system captures a comprehensive 360-degree view of the vehicle's surroundings. These sensory inputs are then funneled into the central processing unit, which houses our state-of-the-art computer vision techniques. These algorithms, trained on vast datasets and optimized for rapid processing, discern objects in the vehicle's path or vicinity with an unprecedented accuracy rate. This accuracy is not just limited to stationary or slow-moving objects but extends to fast-moving entities, unpredictable pedestrians, animals, and even potential aerial obstructions.
But where this invention truly stands out is in its response integration. Upon detection, it does not stop at just alerting the driver. Depending on the nature of the obstacle, its speed, direction, and the vehicle's current state, the system intelligently chooses an action from a broad repertoire of responses. This could range from a simple audible or visual alert for the driver to more direct interventions like adjusting the vehicle's speed, activating brakes, or even suggesting alternative routes.
Furthermore, the system continually learns and adapts. As it encounters diverse driving scenarios, it refines its detection and response algorithms. This ensures that the more the vehicle equipped with this system is driven, the better it gets at safeguarding its occupants.
Additionally, a seamless integration with in-car communication systems ensures that drivers receive alerts and suggestions in the most intuitive manner, be it through the vehicle's display, audio systems, or even haptic feedback mechanisms.
The dynamism of this invention also brings forth a renewed emphasis on proactive rather than reactive measures. By processing multitudes of data in real-time, the system can forecast potential problem areas before they manifest into tangible threats. For instance, if a cluster of pedestrians is detected ahead, the system doesn't just wait for them to enter the roadway; it can preemptively slow the vehicle down or suggest an alternative path, ensuring that sudden braking or sharp maneuvers are kept to a minimum. Such foresight enhances not only safety but also contributes to a smoother, more efficient driving experience.
Another crucial aspect of this system is its compatibility and scalability. Designed with a modular architecture, it can be integrated seamlessly into vehicles of different makes, models, and sizes. Whether it's a compact city car or a large transport truck, the system can be tailored to the unique demands and constraints of each vehicle type. This modularity also means that as new advances in sensor technology or algorithmic processing emerge, components can be updated or replaced without overhauling the entire system.
Beyond the immediate vehicle environment, the invention is also primed for connectivity in the broader ecosystem of smart transportation. It has the capability to communicate with other similarly equipped vehicles, creating a mesh network on the road. This vehicular communication can alert drivers about potential hazards, traffic jams, or unfavorable conditions miles ahead, providing ample time to react or choose alternative routes.
Additionally, with the burgeoning evolution of autonomous vehicles, this invention can play a pivotal role. While full autonomy might still be a few milestones away, systems like this bridge the gap, ensuring that semi-autonomous vehicles operate with an added layer of safety and intelligence. Some patent prior art related to proposed invention mentioned below.
Comprehensive Advanced Driver Assistance System (ADAS)
Summary: This patent describes a system that utilizes optical and infrared cameras to detect objects and provides warnings to the driver. While it does use computer vision techniques, it does not integrate responsive actions based on the object's characteristics.
Real-Time Vehicular Object Detection
Summary: This patent relates to detecting objects using radar and ultrasonic sensors. While it emphasizes real-time detection, its primary focus is on stationary objects, and it does not elaborate on the integration of responsive actions.
ADAS with Integrated Response Mechanism
Summary: This system highlights an ADAS that alerts the driver and can autonomously apply brakes when an obstruction is detected. However, it lacks a detailed approach to object differentiation and does not adapt over time.
Advanced Vehicular Safety through Sensor Fusion
Summary: This patent incorporates multiple sensors for a holistic view of the vehicle's surroundings. It emphasizes sensor fusion but falls short of integrating comprehensive real-time object detection and associated responses.
Intelligent Vehicle Communication for Safety
Summary: The invention under this patent is centered around vehicle-to-vehicle communication for sharing potential hazard information. While it promotes networked safety, it does not focus on individual vehicle object detection and integrated response.
Modular ADAS for Diverse Vehicles
Summary: This Chinese patent introduces a modular ADAS that can be tailored to different vehicle types. It discusses scalability but does not go in-depth into the intricacies of real-time object detection and immediate response action.
US9956123B2 - Proactive Driving Assistance System
Summary: An ADAS system that predicts potential hazardous scenarios using predictive algorithms. While it touches upon the idea of proactive measures, the patent mainly concerns itself with forecasting and not the combination of detection and response.
KR20190084290A - Integrated Object Detection and Response for Semi-Autonomous Vehicles
Summary: This Korean patent delves into a system designed for semi-autonomous vehicles. It offers real-time object detection and a range of responses. However, it is primarily tailored for vehicles with a high level of autonomy and not the broader vehicle market.
IN2018120094A - Connected Transportation Ecosystem for Enhanced Safety
Summary: The patent from India emphasizes the role of a connected transport ecosystem where vehicles share data. It promotes the idea of a smart transportation network but does not go into the depth of individual vehicle response integration based on detected objects.
AU2018100234B2 - Adaptive Advanced Driver Assistance System
Summary: This Australian patent talks about an ADAS that learns and adapts over time, refining its algorithms based on various scenarios. While it touches upon adaptive algorithms, the main focus is on post-incident learning rather than real-time integrated responses.
Summary of the proposed invention:
The proposed invention is a transformative advancement in the realm of Advanced Driver Assistance Systems (ADAS). It combines state-of-the-art computer vision techniques, sensor fusion, and adaptive algorithms to detect objects in real-time around a vehicle. Beyond just detection, the system also seamlessly integrates a wide array of responsive actions. Using a combination of optical cameras, infrared sensors, radar, and ultrasonic devices, the system paints a comprehensive view of the vehicle's surroundings. On identifying an object or potential hazard, it doesn't just alert the driver. Depending on the situation, its speed, direction, and other variables, the system may suggest or initiate actions ranging from audio-visual warnings to vehicular adjustments like braking or rerouting. Additionally, the system possesses a learning mechanism, allowing it to refine its detection and response algorithms based on diverse driving scenarios it encounters. This constant evolution ensures improved performance over time. The system's modular design also ensures compatibility across different vehicle types and models, while its capability to communicate with other vehicles introduces a layer of collective intelligence on the road. As a result, this invention promises to elevate driving safety standards, bridging the gap between traditional driving and the future of autonomous transportation.
Brief description of the proposed invention:
The proposed invention represents a pioneering stride in the sphere of Advanced Driver Assistance Systems (ADAS), aiming to revolutionize how vehicles perceive and interact with their surroundings. By meticulously intertwining advanced computer vision techniques with sensor fusion, this novel system is adept at detecting objects in real-time, setting it apart from many of its predecessors. But the brilliance of this invention doesn't halt at mere detection. It transcends this functionality by simultaneously weaving in responsive actions, ensuring that the vehicle doesn't just identify potential hazards but reacts to them in the most optimal way.
Incorporating a plethora of sensors, ranging from high-resolution optical cameras to infrared sensors, radar systems, and ultrasonic devices, this system endeavors to provide an all-encompassing view of the environment enveloping the vehicle. These myriad data streams are channelled into a central processing hub, equipped with cutting-edge computer vision algorithms. Here, the data undergoes meticulous scrutiny, with objects in the vehicle's proximity being identified with exceptional accuracy. This precision extends to both static entities, such as parked cars or lampposts, and dynamic elements, including pedestrians darting across streets or animals that might unpredictably venture onto the road.
What makes this invention truly groundbreaking is its capacity to respond to these detected objects. Depending on a multitude of factors—like the nature and speed of an oncoming obstacle, the vehicle's current trajectory, and surrounding traffic conditions—the system can select from a vast repertoire of actions. This can range from providing the driver with audible or visual alerts, making slight adjustments to the vehicle's speed or direction, to even more significant interventions like activating emergency brakes or suggesting alternative navigation routes.
Another intriguing facet of this invention is its intrinsic ability to learn and adapt. As the vehicle traverses through varying terrains, weather conditions, and traffic scenarios, the system meticulously logs these experiences. Leveraging the power of machine learning, it continually refines its object detection algorithms and response strategies. Such iterative learning ensures that the system's performance is not stagnant but perpetually evolving, enhancing its efficiency and reliability over time.
The inherent design of this system is not rigid but modular, allowing for seamless integration into a wide array of vehicles, irrespective of their make or model. This adaptability ensures that whether it's a compact sedan or a hefty SUV, the benefits of this invention can be ubiquitously enjoyed. Furthermore, with the realm of vehicular travel inching closer to a future dominated by autonomous vehicles, this invention serves as a crucial bridge. While full autonomy might still be on the horizon, systems like this make the transition smoother and safer, blending human intuition with machine intelligence.
Furthermore, this invention’s seamless fusion of technologies addresses the nuanced complexities of on-road scenarios. While driving environments can be highly unpredictable, with sudden changes ranging from a child chasing a ball onto the road to unexpected weather anomalies, this system's robust combination of real-time detection and swift response ensures that drivers are well-prepared to handle the unexpected. It's not just about recognizing potential threats; it's about proactively managing them to maintain safety and fluidity in transportation.
Beyond the immediate capabilities of object detection and response, this invention is also designed for broader connectivity. Embedded communication modules allow it to interface with other vehicles, traffic management systems, and even pedestrian devices. Such connectivity offers the dual benefits of crowd-sourced data collection and shared intelligence. For instance, if a vehicle several meters ahead detects black ice on the road, our system can receive that data and alert the driver or adjust the vehicle's systems even before reaching the hazardous spot. This interconnected web of communication represents the dawn of a truly smart transportation ecosystem, where each vehicle contributes to and benefits from collective knowledge.
Additionally, with the global push towards sustainable transportation solutions, this invention also complements electric and hybrid vehicles. Its efficient processing ensures minimal energy consumption, making it a natural fit for eco-friendly transport options without compromising on safety features.
User experience has also been at the forefront of this invention's design philosophy. The alerts and responses are curated to be intuitive and non-intrusive. Drivers receive timely information without being overwhelmed, ensuring that their primary focus remains on the driving experience. This balance between technology and human-centric design is pivotal, ensuring that while the system is feature-rich, it remains user-friendly and accessible.
In wrapping up, this invention is not just a product but a vision for the future of transportation. It symbolizes the harmonization of advanced technology with human intuition, ensuring safer roads, empowered drivers, and a more connected transportation landscape. By addressing the multifaceted challenges of today's driving scenarios with unparalleled precision and adaptability, it sets the gold standard for what Advanced Driver Assistance Systems can achieve, beckoning a new era where technology and safety are seamlessly intertwined on our roads.
, Claims:1. An Advanced Driver Assistance System (ADAS) configured to detect objects in real-time using a combination of optical cameras, infrared sensors, radar, and ultrasonic devices.
2. The system of claim 1, wherein said detection is complemented by initiating responsive actions tailored to the characteristics and dynamics of the detected object.
3. The system of claim 1 or 2, wherein the responsive actions range from audio-visual driver alerts to vehicular adjustments including, but not limited to, braking, acceleration, or rerouting.
4. The system of any preceding claim, wherein an integrated machine learning algorithm refines object detection and response strategies based on accumulated vehicular experiences.
5. The system of any preceding claim, comprising a central processing hub that aggregates data from multiple sensors to generate a holistic view of the vehicle's surroundings.
6. The system of any preceding claim, designed with a modular architecture, facilitating integration into a variety of vehicle makes and models without substantial modification.
7. The system of any preceding claim, further equipped with communication modules allowing for the exchange of data and alerts with other similarly equipped vehicles or traffic management systems.
8. The system of any preceding claim, wherein energy-efficient processing is employed, making it compatible with electric and hybrid vehicles without significantly impacting energy consumption.
9. The system of claim 4, wherein the machine learning algorithm operates in an iterative manner, constantly updating its object detection and response database with each new scenario encountered.
10. The system of any preceding claim, where user experience is prioritized, delivering timely and intuitive alerts to drivers without overwhelming or causing undue distractions.