Autonomous Vehicle Motion Constraints for Collision-Avoiding Routing
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Solution Overview
Problem
Traditional route selection algorithms for vehicles are impractical in complex environments due to factors like vehicle overload, parked vehicles, construction zones, and pedestrians, leading to inefficient navigation and potential collisions.
Innovation Solution
An autonomous vehicle system uses sensors to detect objects and generate motion constraints, including minimum speed, to avoid collisions by adjusting its operation based on detected obstacles and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If traditional greedy algorithms are used for route selection, then the route selection process is simple, but the selected route may become overloaded and travel slows to a crawl
Solution Approach 1:
The patent implements feedback mechanisms where vehicles report their selected routes and travel times back to the system. This feedback is used to dynamically adjust route recommendations, avoiding overloaded routes and distributing traffic more evenly across the network, thereby maintaining travel speed while keeping the selection process manageable.
Solution Approach 2:
The system performs preliminary route analysis and prediction before vehicles actually travel. By predicting future route conditions and pre-calculating alternative routes, the system prevents route overload before it occurs, maintaining both simplicity and productivity.
2Ease of manufacture
If traditional route selection algorithms are used, then the algorithm is easy to implement, but it cannot account for parked vehicles, construction zones, and pedestrians
Solution Approach 1:
The patent merges multiple data sources including sensor data from vehicles, map data, and real-time environmental information into a unified route selection framework. This combination allows the system to account for parked vehicles, construction zones, and pedestrians while maintaining algorithmic efficiency through integrated processing.
Solution Approach 2:
The system transitions from static route selection to dynamic route adjustment. It continuously updates route recommendations based on real-time conditions such as moving pedestrians, parked vehicles, and construction zones, enabling the algorithm to adapt to changing environments while maintaining ease of implementation through modular design.
3Reliability
If complex route selection is performed to avoid collisions, then collision avoidance improves, but the decision-making process becomes too complex for practical use
Solution Approach 1:
The patent segments the route selection decision-making process into multiple independent modules: hazard detection, risk assessment, alternative route generation, and selection. Each module handles a specific aspect of collision avoidance, reducing overall system complexity while maintaining high reliability through specialized processing in each segment.
Data Source
AI summary
Techniques are provided for operation of a vehicle using multiple motion constraints. The techniques include identifying an object using one or more processors of a vehicle. The vehicle has a likelihood of collision with the object that is greater than a threshold. The processors generate multiple motion constraints for operating the vehicle. At least one motion constraint includes a minimum speed of the vehicle greater than zero to avoid a collision of the vehicle with the object. The processors identify one or more motion constraints for operating the vehicle to avoid a collision of the vehicle with the object. The processors operate the vehicle in accordance with the identified motion constraints.