Autonomous Vehicle Navigation Using Multilateration and Object Recognition
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Solution Overview
Problem
Current autonomous vehicles are limited in collecting information beyond their line of sight, relying on fixed satellite signals and unable to communicate with dynamic objects like smartphones and IoT devices, which restricts their navigation capabilities in environments with obstructed GPS signals.
Innovation Solution
A system that uses multilateration with external transmitting devices and a camera system for object recognition, combining signals from various sources, including RF, cellular, and satellite modules, to determine vehicle location and classify objects, expanding the vehicle's awareness beyond its line of sight for navigation decisions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles use fixed satellite signals for location determination, then the navigation system can operate with simple infrastructure, but the system cannot collect information beyond line of sight and fails in environments with obstructed GPS signals
Solution Approach 1:
The patent introduces intermediary devices (smartphones, IoT devices, roadside units) that act as mediators between the vehicle and the environment. These devices transmit signals containing location and object information, enabling the vehicle to determine positions and detect objects beyond its line of sight through multilateration and signal processing
Solution Approach 2:
The system uses universal communication protocols allowing the vehicle to communicate with diverse devices (smartphones, IoT devices, roadside units) that have different functions. These devices can serve multiple purposes: location determination, object detection, and environmental information provision, making the navigation system adaptable to various environments
2Adaptability or versatility
If autonomous vehicles rely on fixed location-based signals, then the system structure remains simple, but the system cannot communicate with dynamic objects like smartphones and IoT devices
Solution Approach 1:
The system employs universal communication protocols that enable interaction with diverse dynamic objects (smartphones, IoT devices, roadside units). The vehicle's processing device can interpret signals from these various sources, allowing adaptable communication without requiring specialized interfaces for each device type
Solution Approach 2:
Dynamic objects in the environment (smartphones, IoT devices) autonomously transmit their location and status information without requiring direct control or configuration by the vehicle system. The vehicle simply receives and processes these self-generated signals, reducing the complexity of active management
3Loss of information
If the vehicle uses only line-of-sight sensors for environmental detection, then the sensor system remains simple, but the vehicle cannot detect objects around corners or in obstructed areas
Solution Approach 1:
The system uses intermediary devices (smartphones, IoT devices, roadside units) positioned in the environment to detect and transmit information about objects beyond the vehicle's line of sight. These intermediaries act as distributed sensors that expand the vehicle's detection capability without requiring complex active sensing systems on the vehicle itself
Solution Approach 2:
The patent replaces mechanical line-of-sight sensing with electromagnetic signal processing. Instead of using physical sensors to directly detect objects, the system uses radio frequency signals from intermediary devices to infer object locations and characteristics, substituting a simple electronic system for complex mechanical sensing
Data Source
AI summary
A system for providing navigational guidance through an environment is provided that includes a vehicle, a processing device, a memory, a transceiver module, a sensor module, and a camera system. The system determines a location of the vehicle by communicating with at least two external transmitting devices and determines the location of the vehicle by using multilateration. The system also utilizes the camera system to detect objects in the environment via object recognition and classifies the detected objects according to characteristics of the objects, as well as locating the object in the environment. The system utilizes the location of the vehicle and the detected objects for making navigation decisions.