Autonomous Vehicle Controller Trajectory Logic
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Solution Overview
Problem
Conventional autonomous vehicles are sub-optimally designed, inefficient in resource usage, and poorly suited for managing inventory and navigation in complex environments, particularly in city settings, due to their reliance on human drivers and limited self-driving capabilities, which hinders effective ride-sharing and safety in interactions with pedestrians and other vehicles.
Innovation Solution
The development of bidirectional autonomous vehicles equipped with advanced sensors and communication systems, capable of real-time trajectory calculations and teleoperation, allowing for efficient navigation and fleet management, including redundant sensor systems and communication channels to ensure reliable operation and safety.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If conventional autonomous vehicles are designed to accommodate a licensed driver, then the vehicle can be controlled manually when needed, but the vehicle design becomes sub-optimal and resources are not conserved
Solution Approach 1:
The patent removes the driver's seat and steering wheel from the vehicle, extracting the manual control components entirely. The vehicle is designed as a fully autonomous system without human driving interfaces, eliminating the need to accommodate licensed drivers while reducing vehicle complexity and resource usage.
Solution Approach 2:
The autonomous vehicle controller performs multiple functions including navigation, obstacle detection, communication with the fleet manager, and teleoperation reception. This multi-functional controller replaces the need for manual control components, allowing the vehicle to operate autonomously in all conditions without requiring driver accommodation.
2Ease of operation
If conventional transportation services use privately-owned vehicles, then passengers can access transportation, but inventory management becomes inefficient and vehicles are under-utilized
Solution Approach 1:
The autonomous vehicle controller continuously communicates with the fleet manager, providing feedback on vehicle location, status, and passenger requests. The fleet manager uses this feedback to optimize vehicle dispatch, routing, and inventory distribution, ensuring high utilization rates and efficient resource allocation across the fleet.
Solution Approach 2:
The system dynamically adjusts vehicle deployment based on real-time demand patterns. The fleet manager receives passenger requests and dynamically routes available autonomous vehicles to pick up passengers, optimizing inventory utilization without requiring fixed parking locations or manual driver coordination.
3Device complexity
If autonomous vehicles lack advanced sensor systems, then the vehicle design is simpler, but safety in complex environments is compromised
Solution Approach 1:
The patent integrates multiple sensor types (cameras, LIDAR, radar, ultrasonic sensors) into a unified sensor system that provides comprehensive environmental perception. These diverse sensors are merged to detect pedestrians, cyclists, vehicles, and road conditions, achieving high reliability in complex urban environments while managing system complexity through integrated processing.
Solution Approach 2:
The autonomous vehicle controller continuously processes sensor data to identify potential hazards before they become critical threats. The system maintains safety margins by detecting obstacles early and planning avoidance trajectories, cushioning against potential collisions through proactive hazard detection and response.
4Device complexity
If autonomous vehicles do not have teleoperation capability, then the system is simpler, but safety in uncertain situations is reduced
Solution Approach 1:
The fleet manager acts as an intermediary between the autonomous vehicle controller and human operators. When the vehicle encounters uncertain or complex situations beyond its autonomous decision-making capability, the controller requests teleoperation assistance. The fleet manager relays control commands from remote operators to the vehicle, providing human judgment as needed while maintaining automated operation for routine tasks.
Data Source
AI summary
Various embodiments relate generally to autonomous vehicles and associated mechanical, electrical and electronic hardware, computer software and systems, and wired and wireless network communications to provide an autonomous vehicle fleet as a service. More specifically, systems, devices, and methods are configured to generate trajectories to influence navigation of autonomous vehicles. In particular, a method may include receiving path data to navigate from a first geographic location to a second geographic location, generating data representing a trajectory with which to control motion of the autonomous vehicle based on the path data, generating data representing a contingent trajectory, monitoring generation of the trajectory, and implementing the contingent trajectory subsequent to an absence of the trajectory.