Autonomous Vehicle Route Scoping for Stranding-Prone Service Areas
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Solution Overview
Problem
Autonomous vehicles face stranding situations due to geographical restrictions and maneuver limitations, leading to inability to reach destinations, which can impact cargo or passenger transport.
Innovation Solution
Simulate potential routes and maneuvers for autonomous vehicles to identify problematic areas by running simulations that assume the vehicle cannot complete certain maneuvers, flagging these areas, and carving them out to prevent stranding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If autonomous vehicles are programmed to avoid unsafe maneuvers and stay within service areas, then safety is improved, but the vehicle may become stranded and unable to reach destinations
Solution Approach 1:
The system performs preliminary actions by identifying and flagging problematic areas before the autonomous vehicle operates in them. Simulations are run in advance to detect locations where maneuver restrictions would prevent reaching destinations, allowing the vehicle to avoid these areas proactively rather than becoming stranded reactively.
Solution Approach 2:
The system introduces an intermediary layer between the vehicle's safety constraints and its navigation decisions. By simulating routes and identifying problematic areas, the system creates a intermediate map or dataset that guides the vehicle around restricted zones, mediating between safety requirements and destination reachability.
2Loss of time
If human drivers take the fastest or most direct route to destination, then travel time is reduced, but autonomous vehicles may not be able to follow these routes due to maneuver limitations
Solution Approach 1:
The system performs preliminary route simulations to identify areas where direct routes would fail for autonomous vehicles. By pre-detecting problematic maneuvers and locations, the system can plan alternative routes in advance that account for the vehicle's maneuver limitations, avoiding time loss from unexpected detours or strandings.
Solution Approach 2:
The system uses feedback from simulation results to improve route planning. By analyzing which maneuvers cause strandings and which areas are problematic, the routing system learns to avoid these patterns, continuously improving its ability to find reliable routes that balance speed with the vehicle's operational constraints.
Data Source
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AI summary
Aspects of the disclosure provide for identifying problematic areas within a service area for an autonomous vehicle transportation service. For instance, a starting location within the service area corresponding to a potential pickup location for passengers or cargo for the service may be identified. A destination within the service area may be identified. A simulation may be run in order to determine a route (710) for a simulated vehicle to travel between the starting location and the destination. That the route includes a particular type of maneuver may be determined. A new simulation without allowing the simulated vehicle to complete the particular type of maneuver may be run. Whether the simulated vehicle reaches the destination in the new simulation may be determined. Based on the determination of whether the simulated vehicle reaches the destination in the new simulation, the starting location and destination location may be flagged as potentially problematic areas.