ADAS Development Environment

Accelerate ADAS development time

Drako ADAS Development Environment (ADE) accelerates ADAS development by eliminating the friction of integrating across multiple ECUs, operating systems, or custom communication layers — reducing integration complexity while delivering measurable gains in end-to-end system responsiveness, safety, and reliability.

Rather than spending months integrating disparate systems, ADE removes integration and revalidation bottlenecks by aligning software design with DriveOS from the start — streamlining the path from prototype to volume production deployments.

This eliminates the overhead and latency introduced by middleware or cross-OS bridging. ADAS Development Environment also eliminates integration complexity through several key architectural enablers:

- Dedicated real-time and ML subsystems that communicate via hardware-enforced shared memory
- Deterministic communication between Linux and real time control subsystems via Drako SymbiOSis
- Single deployment pipeline that manages perception, planning, and control modules as unified applications
- Native support for hardware-in-the-loop testing and CARLA simulation with consistent timing behavior

Unlock superior responsiveness

OEMs achieve breakthrough ADAS responsiveness because the ADAS Development Environment leverages the DriveOS real-time operating system to manage all subsystems on a single multicore processor — delivering the lowest‑latency full Perception–Decision–Execution (PDE) stack while enabling seamless scaling toward full autonomy.

ADAS systems must respond instantly, even when the rest of the vehicle is under peak system and network load.

The DriveOS separation kernel enforces this architecture through spatial and temporal partitioning: time-critical logic runs in a dedicated real-time environment with guaranteed CPU cores and memory allocation, while perception, UI, and legacy code operate in Linux without the ability to disrupt control loop timing or access safety-critical resources.

ADE’s validation-ready architecture with timing you can prove

Comprehensive validation includes end-to-end pipeline testing in the CARLA simulator using real driving datasets like Laguna Seca Raceway, plus hardware-in-the-loop simulation.

DriveOS maintains measurable, repeatable performance characteristics — enabling production-grade safety validation before hardware is finalized.

A real-time CAN gateway manages secure, deterministic communication with sensors and actuators, delivering ultra-low latency and nanosecond-level jitter.

Hardware-enforced shared memory enables fast, predictable data flow — orders of magnitude more efficient than RPC or networked IPC for safety-relevant systems. DriveOS coordinates scheduling across subsystems with mathematical precision, enabling deterministic execution for control loops during ADAS development:

- Linux-based ML preprocessing and real-time actuation run in parallel without interference
- Background tasks in Linux are spatially and temporally isolated from safety-critical control timing
- Nanosecond-level scheduling maintains consistent performance under maximum system load

OpenPilot reference design for ADAS development

Drako ADAS Development Environment includes a reference ADAS design based on OpenPilot that runs natively on DriveOS, without middleware or OS bridging.

The reference design integrates sensor data and planning outputs via hardware-enforced shared memory with OEM machine learning components in Linux and real-time control systems — leveraging DriveOS’s unified, low-latency architecture.

OpenPilot has the following ADAS functionality available:

Vehicle Control Assistance

Adaptive Cruise Control – Maintains a safe following distance from the vehicle ahead by automatically accelerating and braking, supporting stop-and-go traffic conditions.

Automated Lane Centering – Keeps the vehicle centered within its lane through continuous active steering assistance.

Lane Change Assist – Upon driver prompting, automatically executes a lane change; can integrate with the vehicle’s blind spot monitoring system to prevent unsafe maneuvers.

Safety & Hazard Warnings

Forward Collision Warning – Alerts the driver to potential frontal collisions by analyzing sensor and camera data to continuously monitor for imminent risks.

Lane Departure Warning – Alerts the driver when the vehicle drifts out of its lane without an active turn signal.

Driver Monitoring – Uses a cabin-facing camera to detect distraction or inattention, issuing warnings and potentially initiating deceleration if the driver remains inattentive for more than six seconds.

Navigation & Contextual Adaptation

Navigate – Enables the system to follow a navigation route, actively steering and adjusting speed based on road context (dependent on specific OpenPilot version and options).

Additional Integrations – Supports map-based speed adaptation, enabling the system to proactively decelerate for turns or road curvature by analyzing map and sensor data.