SYSTEMS AND METHODS FOR COMPUTER-ASSISTED SHUTTLES, BUSES, ROBO-TAXIS, RIDE-SHARING AND ON-DEMAND VEHICLES WITH SITUATIONAL AWARENESS

Smart overview of the Invention

The patent application describes a system and method for operating autonomous and semi-autonomous shuttles, buses, robo-taxis, and on-demand vehicles with enhanced situational awareness. These vehicles can operate on both private and public roads, providing safe and efficient transportation. The system is designed to dynamically adjust routes based on demand while maintaining the option to follow predefined paths or "virtual rails." Passengers can request rides using various interfaces such as mobile devices, desktop computers, or kiosks.

Technological Components

Each vehicle is equipped with an in-vehicle controller, which is an AI supercomputer optimized for autonomous functionality. This includes features like computer vision, deep learning, and real-time ray tracing accelerators. An AI Dispatcher is also part of the system, performing simulations to optimize performance based on specified parameters. The technology aims to replicate and even exceed human perception capabilities through a comprehensive sensor suite.

Situational Awareness

The vehicles are equipped with advanced situational awareness capabilities both inside and outside the passenger compartment. The sensor suite includes cameras, LIDARs, RADARs, ultrasonic sensors, and more. These sensors enable the vehicle to perceive its environment comprehensively, allowing it to interact with passengers and external entities like pedestrians and other vehicles. This awareness is crucial for navigating complex environments safely.

Operational Flexibility

The system allows vehicles to operate along predefined routes known as "virtual rails." These routes can be altered minimally based on specific conditions or past experiences. Vehicles are not restricted to these virtual rails and can deviate when necessary. The system uses stored data from previous routes to generate virtual rails automatically, reducing complexity in navigation across familiar terrains like parking lots.

Self-Calibration and Adaptability

Vehicles are equipped to calibrate and map their own virtual rails using their sensor suites. This adaptability is essential as different vehicles may have varying sensor configurations. The system continually updates the virtual rail based on environmental changes and dynamic objects such as parked cars or pedestrians. This ensures that the vehicle can safely navigate through temporary obstacles while maintaining efficient operation.