Phantom Vehicle Route Simulation for Policy-Compliant AV Planning
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current systems lack efficient methods for managing permissions and authorizing access to services for fleets of autonomous vehicles, particularly in dynamic environments where real-time adjustments are necessary.
Innovation Solution
The system employs a processor remote from the vehicle to generate a planned path by selecting a phantom vehicle with a corresponding motion planning system, accessing high-definition maps, and simulating the phantom vehicle's movement along the planned route, while also considering tenant-specific policies and operating restrictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a phantom vehicle simulation system is implemented for route planning, then route planning efficiency and policy compliance are improved, but system complexity increases
Solution Approach 1:
The patent creates a phantom vehicle as a virtual copy of the real autonomous vehicle. This phantom vehicle replicates the motion planning system, sensor suite, and operational parameters of the physical vehicle, allowing simulations to be run in the cloud without requiring the actual vehicle hardware. This copying approach enables efficient route planning and policy compliance testing while keeping the physical vehicle simple.
Solution Approach 2:
The phantom vehicle acts as an intermediary between the route planning system and the real autonomous vehicle. It receives route requests, simulates travel along candidate routes, and returns compliance assessments without the real vehicle needing to physically test each route. This intermediary layer handles the computational complexity of simulations and policy checks.
2Speed
If cloud-based simulation is used for route planning, then real-time route optimization is improved, but data transmission requirements and latency increase
Solution Approach 1:
The system performs preliminary actions by pre-loading high-definition map data, tenant policies, and motion planning algorithms into the cloud-based simulation environment before route requests arrive. When a route request is received, the phantom vehicle can immediately begin simulations using pre-configured data, reducing transmission latency and enabling real-time optimization.
3Measurement precision
If tenant-specific policies are enforced through simulation, then compliance accuracy is improved, but processing time increases
Solution Approach 1:
The system changes parameters by adjusting the level of simulation detail and policy check depth based on route characteristics and tenant priorities. For simple routes or low-priority requests, the simulation uses simplified models and fewer policy checks. For complex routes or high-priority requests, full-fidelity simulations with comprehensive policy enforcement are performed, optimizing the balance between accuracy and processing time.
Data Source
AI summary
Methods and systems that use a phantom vehicle to help generate a planned path for a real-world vehicle are described. The system will identify a starting point and a destination for a trip of the real-world vehicle. The system will select, from the data store of vehicle profiles, a phantom vehicle having an associated motion planning system that corresponds to a system that is deployed on the real-world vehicle. The system will use a high definition map to generate a planned route for the real-world vehicle from the starting point to the destination in the map. The system will run a simulation in which the phantom vehicle moves along the planned route in the map. The system will then output a record of the simulation to a user of the real world-vehicle or to a system of the real-world vehicle.