Vehicle Route Synchronization for Dynamic Obstacle Adaptation
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Solution Overview
Problem
Existing vehicle navigation systems lack real-time adaptability to obstacles and dynamic route updates, especially in environments with changing conditions such as parking areas, which can lead to inefficiencies and inaccuracies in predicting vehicle location and travel times.
Innovation Solution
A vehicle control system that includes a first computer synchronizing timers with a second computer to determine and update routes based on detected obstacles, using infrastructure sensors and vehicle sensors to adjust predicted travel times and waypoints, allowing for real-time route adjustments and improved location prediction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the vehicle navigation system uses fixed routes without real-time updates, then the system complexity is reduced, but the adaptability to dynamic obstacles and changing environmental conditions deteriorates
Solution Approach 1:
The navigation system dynamically updates routes based on real-time sensor data detecting obstacles and environmental changes. The system transitions from static pre-planned routes to dynamic adaptive routing, where the vehicle computer continuously receives sensor inputs and adjusts navigation paths accordingly, resolving the contradiction between adaptability and system complexity.
Solution Approach 2:
The system implements feedback loops where sensor data about obstacles and environmental conditions is continuously fed back to the vehicle computer, which then adjusts the navigation route in real-time. This feedback mechanism enables the system to adapt to changing conditions while maintaining manageable complexity through automated decision-making algorithms.
2Measurement precision
If the system frequently updates routes based on real-time sensor data, then the navigation accuracy improves, but the loss of time for processing and transmitting route updates increases
Solution Approach 1:
The system performs preliminary actions by pre-calculating multiple potential route options and their associated travel times before navigation begins. When obstacles are detected, the system can quickly switch between pre-prepared routes without requiring extensive real-time calculation, thus improving location prediction accuracy while minimizing time loss for route updates.
Solution Approach 2:
The system implements selective updating by only triggering route recalculations when sensor data indicates actual obstacles or significant environmental changes, rather than continuously updating. This partial action approach maintains high navigation accuracy by updating only when necessary, reducing unnecessary processing time and computational overhead.
3Reliability
If the vehicle computer processes all sensor data and determines routes independently, then the navigation reliability improves, but the device complexity and computational requirements increase
Solution Approach 1:
The navigation system is segmented into specialized functional modules: sensor data acquisition modules, obstacle detection modules, route calculation modules, and execution modules. Each module handles specific tasks independently, improving navigation reliability through specialized processing while reducing overall system complexity by distributing computational requirements across modular components rather than requiring a single complex processing unit.
Data Source
AI summary
A system includes a first computer and a second computer. The first computer is programmed to receive a request from the second computer to move a vehicle from a first location to a second location and synchronize a timer stored in each of the computers. The first computer determines a route including waypoints from the first location to the second location and determines predicted travel times for legs of the route. The predicted travel times include a first predicted travel time for a first leg defined from the first location to a first waypoint included in the waypoints and the first computer transmits the route and the travel times to the second computer. The second computer is programmed to determine an elapsed time of travel and predict a location of the vehicle based on the elapsed time of travel and the first predicted travel time.