Autonomous Vehicle Fleet Control for Predicted Impact Maneuvers
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Solution Overview
Problem
Conventional approaches to developing driverless vehicles are sub-optimal, inefficient, and poorly suited for managing vehicle inventories, detecting and navigating interactions with pedestrians and other vehicles, and providing safe and reliable transportation services.
Innovation Solution
A fleet of autonomous vehicles communicatively networked to an autonomous vehicle service platform, which includes advanced sensors, redundant communication channels, and teleoperation capabilities to ensure safe and efficient operation, and to optimize vehicle deployment and maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional approaches to developing driverless vehicles are used, then vehicle ownership and traditional transportation models are maintained, but vehicle inventory management becomes inefficient and resource allocation is sub-optimal
Solution Approach 1:
The patent segments the vehicle fleet into a managed inventory system where individual vehicles can be independently tracked, deployed, and maintained. The fleet is divided into operational vehicles, vehicles undergoing maintenance, and vehicles in transit, allowing efficient resource allocation and improved productivity in vehicle management.
Solution Approach 2:
The autonomous vehicles serve multiple functions: they can be deployed for ride-hailing services, food delivery, package delivery, and other transportation tasks. This multi-functionality allows the same vehicle inventory to serve diverse transportation needs, improving resource allocation efficiency and service reliability.
2Difficulty of detecting and measuring
If conventional driverless vehicles without advanced sensor systems are used, then device complexity is reduced, but detection and navigation capabilities with pedestrians and other vehicles are insufficient
Solution Approach 1:
The patent combines multiple sensor types (cameras, LIDAR, radar, ultrasonic sensors) into an integrated sensor system. These diverse sensors merge their detection capabilities to provide comprehensive environmental perception, allowing the vehicle to detect and navigate interactions with pedestrians and other vehicles with high accuracy despite the increased complexity.
Solution Approach 2:
The sensor system acts as an intermediary between the autonomous vehicle and the external environment. It captures and processes information about pedestrians, other vehicles, and road conditions, translating physical environmental data into actionable information for the vehicle's navigation and safety systems.
3Reliability
If autonomous vehicles operate without teleoperation capabilities, then extent of automation is increased, but safety and reliability during critical situations are compromised
Solution Approach 1:
The patent implements a feedback mechanism where the autonomous vehicle continuously monitors its operational status and environmental conditions, and can request teleoperation assistance when confidence levels drop below thresholds or critical situations arise. This feedback loop maintains high automation levels during normal operation while ensuring safety through human intervention when needed.
Solution Approach 2:
The system performs preliminary actions by pre-configuring teleoperation capabilities and establishing communication channels before critical situations occur. The vehicle is prepared to seamlessly transition from autonomous to teleoperated mode, ensuring safety readiness without compromising the extent of automation during routine operations.
4Reliability
If advanced sensor systems and communication channels are integrated, then detection and navigation capabilities are enhanced, but device complexity and manufacturing costs increase
Solution Approach 1:
The complex sensor and communication systems are segmented into modular units that can be independently developed, tested, and maintained. Each sensor type and communication channel is treated as a separate module, reducing integration complexity while maintaining overall system reliability for detection and navigation functions.
Data Source
AI summary
Systems, apparatus, and methods implemented in algorithms, software, firmware, logic, or circuitry may be configured to process data and sensory input in real-time to detect an object. In particular, a method may include determining a predicted object path of the object. The method may further include determining a predict point of impact between the autonomous vehicle and the object based in part on the predicted object path. The method may further include identifying a preferred point of impact that is associated with a safety system disposed on the autonomous vehicle. The method may further include causing the autonomous vehicle to perform a maneuver based in part on the preferred point of impact.