Adaptive Trip Plan Management for Multi-Entity Vehicle Coordination
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Solution Overview
Problem
Existing vehicle trip plan management solutions are deficient in dynamically updating trip plans based on changing circumstances and lack efficient methods for managing multiple trip plan service provider responsibilities, leading to high operating costs and excess technological resource consumption.
Innovation Solution
A computer-implemented method and system for adaptive trip activity and data security management, which enables the execution of various trip activities associated with multiple entities by a vehicle during a trip plan. This involves receiving trip activity requests, generating trip activities and plans, creating rule sets, and encrypting data based on entity-selected models, allowing for dynamic updates and efficient resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If a single vehicle executes trip plans for multiple entities, then resource utilization improves and operating costs reduce, but trip plan complexity and management difficulty increase
Solution Approach 1:
The system segments trip plans into independent trip activities, where each activity can be individually managed, executed, and monitored. This allows multiple entities' requirements to be broken down into discrete tasks that can be handled separately within a unified trip plan framework, reducing management complexity while enabling multi-entity service consolidation
Solution Approach 2:
The trip plan management system is designed with universal functionality to handle diverse trip activities for multiple entities through a single unified interface. The system can accommodate different entity requirements, activity types, and execution conditions using common infrastructure, thereby reducing operating costs while managing complexity through standardized processes
2Adaptability or versatility
If trip plans are dynamically updated based on changing circumstances, then adaptability improves, but system complexity and computational resources increase
Solution Approach 1:
The system implements dynamic trip plan updates by allowing modification of trip activities based on changing conditions such as weather, traffic, or entity requirements. The trip plan structure supports real-time adjustments to activity parameters, timing, and execution conditions without requiring complete plan redesign, enabling adaptability while controlling complexity through incremental modification capabilities
Solution Approach 2:
The system incorporates feedback mechanisms that monitor trip execution status, environmental conditions, and entity responses in real-time. This feedback drives automatic or manual updates to trip activities, allowing the system to adapt to changing circumstances based on actual performance data and external inputs, improving adaptability through information-driven adjustments
3Reliability
If entities control their own trip activities and data privacy, then data security improves, but system coordination complexity increases
Solution Approach 1:
The system introduces an intermediary layer between entities and the trip execution system, where entities can specify their data privacy requirements and activity control preferences through standardized interfaces. This intermediary manages the coordination of multiple entities' requirements, translating individual preferences into coordinated trip activities while maintaining security boundaries, thereby improving data security without exposing entities to direct coordination complexity
4Productivity
If multiple trip activities are consolidated into a single trip plan, then productivity improves, but trip plan feasibility determination becomes more difficult
Solution Approach 1:
The system segments consolidated trip plans into discrete trip activities with individual feasibility criteria. Each activity can be independently assessed for feasibility based on its specific requirements, resources, and constraints, while the overall trip plan benefits from the productivity gains of consolidation. This segmentation enables systematic feasibility evaluation of complex multi-activity plans
Data Source
AI summary
Embodiments described herein provide a trip plan management system configured to facilitate the execution of various trip activities associated with multiple respective entities by a vehicle. Embodiments may receive a plurality of trip activity requests and generate a plurality of trip activities. Embodiments may also generate a trip plan based on the plurality of trip activities based on a plurality of trip activity parameters associated with each respective trip activity. Embodiments may also generate at least a first rule set based on the plurality of trip activities, where the first rule set is generated based on at least one of a condition set or an action sequence associated with at least one trip activity of the plurality of trip activities. Embodiments may also cause the vehicle to execute the trip plan based on the first rule set by inputting the trip plan and the first rule set into the vehicle.