Invention Overview
ByRyde has developed a comprehensive AI-driven rideshare driver optimization platform that represents a significant advance over the current state of the art. This nonprovisional utility patent application covers the core innovations across artificial intelligence, dynamic pricing, vehicle integration, safety systems, and driver engagement.
Full Title
System and Method for AI-Driven Rideshare Driver Optimization with Integrated Real-Time Decision Intelligence, Predictive Demand Analytics, Dynamic Fare Computation, Autonomous Vehicle Fleet Management, and Multi-Modal Safety Monitoring
International Patent Classification
| IPC Code | Classification |
|---|---|
| G06Q 10/04 | Forecasting or Optimization for Administrative Purposes |
| G06Q 50/30 | Transportation / Logistics |
| G06N 20/00 | Machine Learning |
| G08G 1/123 | Traffic Control Systems |
Eight Patentable Innovations
| # | Innovation | Claims | Technical Advance | Risk |
|---|---|---|---|---|
| 1 | AI Copilot Suite | 1-5 | 15 concurrent GPT-powered inference endpoints for driver optimization with subscription-tiered access control | Low |
| 2 | Smart Ride Filtering | 6-8 | 7-parameter server-side cascading filter pipeline with $/mile and $/minute computation | Medium |
| 3 | Cryptographic Fare Integrity | 9-12 | HMAC-SHA256 signed fare quotes with timing-safe validation and temporal expiration | Low |
| 4 | Tesla Fleet API Bridge | 12-14 | OAuth2 PKCE vehicle telemetry and command integration within rideshare context | Low |
| 5 | Crash Detection System | 15-16 | Accelerometer-based crash detection with timed emergency response and severity classification | Medium |
| 6 | Fatigue Monitoring | 15, 17 | AI-driven wellness assessment with mandatory break enforcement and longitudinal tracking | Low |
| 7 | IRS Mileage Tracking | 15 | Background GPS mileage tracking with Haversine computation and IRS-compliant documentation | Medium |
| 8 | Gamification Engine | 18 | 4-category streaks, 4-tier progression, stackable bonuses, and competitive leaderboards | Medium |
Three Independent Claims (Summary)
A computer-implemented system comprising a server computing device that executes an artificial intelligence copilot suite with fifteen (15) distinct inference endpoints, each generating structured recommendation outputs by submitting engineered prompt templates to a large language model. The system receives real-time operational data from driver devices and transmits optimization recommendations for earnings, surge prediction, wellness assessment, ride decisions, and conversational coaching.
A computer-implemented method for generating cryptographically signed fare quotes using HMAC-SHA256 over a canonical string of fare amount, user ID, and timestamp. The method computes multi-variate fares (base + distance + time + surge + fees), signs them with a server-side key, and validates upon ride completion using timing-safe comparison to prevent both fare tampering and side-channel attacks.
A non-transitory computer-readable storage medium implementing a multi-modal driver safety system comprising: (1) crash detection via continuous accelerometer/gyroscope sampling with G-force threshold analysis and timed emergency response; (2) fatigue monitoring with AI wellness assessment and mandatory break enforcement; and (3) IRS-compliant mileage tracking with background GPS sampling, Haversine distance computation, and tax deduction calculation.
Technical Drawings Summary
| Figure | Title | Description |
|---|---|---|
| FIG. 1 | System Architecture | Three-tier architecture: Client (Expo RN, 67 screens), Server (Express.js, 7 modules), Data (PostgreSQL, Firebase, Stripe) |
| FIG. 2 | AI Copilot Suite | Fifteen AI inference endpoints with data flow through GPT-5.2 model layer |
| FIG. 3 | Smart Ride Filtering | Seven-parameter sequential cascading filter pipeline flowchart |
| FIG. 4 | Fare Quote Signing | HMAC-SHA256 signature generation and timing-safe validation process |
| FIG. 5 | Tesla Fleet API | OAuth2 PKCE authentication, telemetry retrieval, and command execution data flow |
| FIG. 6 | Crash Detection | Sensor sampling, G-force analysis, countdown timer, and emergency protocol decision tree |
| FIG. 7 | Gamification Engine | Streak calculation, tier evaluation, bonus stacking, and leaderboard system |
| FIG. 8 | Mileage Tracking | GPS sampling, Haversine computation, trip categorization, and IRS compliance |
| FIG. 9 | Language Translation | Per-message translation, auto-translate, and translate-before-send architecture |
| FIG. 10 | Fatigue Monitoring | Session tracking, break enforcement, and wellness metric visualization |
| FIG. 11 | Demand Forecasting | Hourly prediction, surge forecasting, and spatial hotspot clustering |
| FIG. 12 | EV Charging | Battery monitoring, range estimation, station routing, and carbon tracking |
Filing Strategy and Costs
Recommended Filing Timeline
| Phase | Action | Timeline | Estimated Cost |
|---|---|---|---|
| 1 | File Provisional Application (12-month priority) | Immediate | $1,500 - $3,000 |
| 2 | Nonprovisional Filing (this application) | Within 12 months of Phase 1 | $8,000 - $15,000 |
| 3 | PCT International Filing | Within 12 months of Phase 1 | $4,000 - $8,000 |
| 4 | National Phase Entries (US, EU, UK, India) | 30 months from priority date | $10,000 - $25,000 per country |
| 5 | Prosecution / Office Actions | 12-36 months after filing | $3,000 - $8,000 per action |
| 6 | Continuation-in-Part (new features) | Ongoing | $5,000 - $12,000 each |
Fee Estimates (USPTO)
No excess claims fees required: application contains exactly 3 independent claims and 20 total claims, within the standard fee thresholds of 37 C.F.R. §1.16(a)-(c).
IP Portfolio Value
This patent application, if granted, would provide ByRyde with broad protection over its core technology innovations for a period of 20 years from the filing date. The estimated IP portfolio value, based on comparable patents in the transportation technology sector, ranges from $5M to $15M, considering:
- Defensive value: Prevents competitors from implementing similar AI-driven driver optimization systems
- Licensing potential: Enables licensing of individual claim groups to non-competing platforms (delivery, logistics, fleet management)
- M&A value: Patent portfolio significantly increases acquisition value for strategic acquirers
- Investor confidence: Demonstrates technological moat and protectable competitive advantages