Smart OTA Scheduler for Vehicle Software Updates

The patent segments vehicles into different groups based on usage patterns, location data, and connection characteristics. This segmentation allows the system to distribute software updates in controlled batches rather than simultaneously to all vehicles, preventing network overload while maintaining update propagation. The scheduler divides the vehicle population into segments that can be updated in staggered waves.

The patent implements dynamic scheduling that adapts to real-time network conditions and vehicle usage patterns. The system continuously monitors connection quality, vehicle location, and usage state, dynamically adjusting which vehicles receive updates at any given moment. This dynamic approach optimizes the balance between update speed and completion rate by responding to changing conditions.

The patent performs preliminary analysis of vehicle usage patterns, location history, and connection characteristics before scheduling updates. The system pre-identifies optimal time windows for each vehicle segment based on historical data, preparing update schedules in advance that avoid peak usage periods while ensuring timely delivery. This preliminary planning enables the system to proactively schedule updates during favorable conditions.

The patent implements continuous feedback loops where the system monitors actual download progress, network conditions, and vehicle responses in real-time. Based on this feedback, the scheduler adjusts ongoing and future update assignments, reallocating vehicles that are experiencing difficulties and optimizing timing for subsequent batches. This feedback mechanism ensures high completion rates by adapting to actual conditions rather than relying solely on predictions.

The patent reduces computational complexity by segmenting the vehicle population into distinct groups based on usage patterns and characteristics. Rather than optimizing schedules for all vehicles simultaneously as a single complex problem, the system creates smaller, more manageable segments that can be scheduled independently. This segmentation breaks down the overwhelming computational task into tractable sub-problems while maintaining overall optimization.

The patent enables vehicles to provide self-information about their usage patterns, location preferences, and connection characteristics through onboard telematics systems. This self-service approach reduces the burden on the central scheduling system, as vehicles contribute their own data for the optimization process. The system leverages this self-provided information to make scheduling decisions with reduced computational overhead.