SMART MULTI-CONTROL AUTONOMOUS VEHICLE

Abstract

The advent of smart multi-control autonomous vehicles represents a revolutionary leap in transportation technology, promising to reshape urban mobility and road safety. This cutting-edge innovation combines advanced sensors, artificial intelligence, and multi-modal control systems to create vehicles capable of navigating complex environments without human intervention. Recent market projections underscore the rapid growth and potential of this sector. The global autonomous vehicles market is estimated to grow by USD 974.5 billion from 2024-2028, with a remarkable CAGR of 58.78%1. This explosive growth is driven by increasing demand for vehicle autonomy from OEMs and the development of autonomous vehicles for cab and parcel delivery services. The market for near-autonomous passenger cars is similarly poised for significant expansion, with an estimated growth of USD 962.1 billion from 2024-2028 and a CAGR of 60.29%5. This growth is fueled by the rising popularity of semi-autonomous vehicles and increased fundin

Specification

Description:At the core of this invention is a comprehensive sensor suite that combines RADAR, LiDAR, high-resolution cameras, and GPS. These sensors work in concert to provide a 360-degree perception of the vehicle's environment, enabling accurate detection of obstacles, road conditions, and other vehicles. The system's brain is an advanced artificial intelligence unit powered by a state-of-the-art processor, such as Nvidia's Thor SoC, capable of 2,000 TOPS (trillion operations per second). This AI processes the vast amounts of sensor data in real-time, making complex decisions for navigation, obstacle avoidance, and route optimization. A key innovation is the hybrid control architecture. For longitudinal control, the system employs Model Predictive Control (MPC), which anticipates future states and optimizes vehicle speed and acceleration. Lateral control is managed by a Stanley-based system, providing precise steering adjustments. This dual approach ensures optimal performance in various driving scenarios, from highwa , Claims:The authors claimed that,
1. The smart multi-control autonomous vehicle incorporates a comprehensive suite of sensors including RADAR, LiDAR, cameras, and GPS to provide real-time environmental data for accurate navigation and obstacle detection.
2. The vehicle utilizes advanced AI algorithms and neural networks to process sensor data and make real-time decisions for steering, braking, and route optimization, enhancing overall safety and efficiency.
3. The vehicle employs a hybrid control architecture that integrates Model Predictive Control (MPC) for longitudinal control and Stanley-based control for lateral control, optimizing performance in various driving scenarios.
4. The smart multi-control system incorporates V2X technology to enable communication with other vehicles and infrastructure, improving navigation and road safety.

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