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rFpro
DeveloperrFpro Limited
Initial release2007
EngineisiMotor 2
TypeSimulation software
LicenseCommercial software
WebsiterFpro Website

rFpro, originally rFactor Pro, is a driving simulation software used by professional motor racing teams, car manufacturers, and tier 1 suppliers for advanced driver-assistance systems, self-driving cars and vehicle dynamics.[1][2] The software was a project created within an undisclosed Formula One team, using the code from Image Space Incorporated's racing simulator rFactor as a base,[3] and was later made available for commercial release in 2007. It was originally developed for driver-in-the-loop simulations,[4] but has since been used for autonomous vehicle training as well.

History

[edit]

Developed using the code Image Space Incorporated's racing simulator rFactor as a base, rFpro started as an internal project in 2007 within an undisclosed Formula One team and was later made available for commercial release. The software is developed by rFpro Limited, based in Wiltshire, England.[1]

In 2017, rFpro Limited joined forces with Image Space Incorporated and acquired assets from their isiMotor physics engine and gMotor graphics engine, which it had been licensing for use in rFpro since its initial release.[5] British solutions company AB Dynamics acquired rFpro Limited in 2019.[6] In 2020, they partnered with German simulation company Cosin Scientific Software to enable FTire (flexible ring tire model) to run with rFpro.[7][8][9] rFpro launched AV elevate in 2024, an integrated platform created for advanced driver-assistance systems and autonomous vehicle development.[10]

A number of Formula One teams, past and present, use rFpro,[11][12] including Alpine,[13] Ferrari,[14][15] Force India,[16] Mercedes-AMG,[17] and Sauber.[6][18]

Features

[edit]

rFpro features a 120 Hz graphics engine, a library of high definition laser scanned tracks and roads, and an infrastructure in which users can plug their in-house vehicle physics through a Simulink or a C/C++ interface.[19][3][20] Alternatively, rFpro's rigid multi-body physics engine can be used, which samples suspension and drive-train at 800 Hz.[21] rFpro includes a tool called TerrainServer, which can feed the LiDAR data with a 1 cm resolution to a vehicle model running in real time up to 5 kHz.[4][22]

The library includes digital reproductions of public roads, proving grounds, and laser-scanned racing circuits, some of which are locations used in major racing series including Formula One and Formula E.[23][24][25]

In switching to rFpro for its simulator software in 2014, Scuderia Ferrari cited the high fidelity of the reproduced track surface, with an accuracy better than 1 millimetre in Z (height) and 1 centimetre in X and Y (position), which represented a ten-fold improvement over their previous solution.[14] They also cited the ability to respond to dynamic inputs faster than the driver can detect.

See also

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References

[edit]

Further reading

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

RFpro

View on Grokipedia
from Grokipedia
rFpro is a high-fidelity platform designed for engineering-grade testing and development in the automotive and motorsport sectors, enabling the validation of , advanced driver-assistance systems (ADAS), and autonomous vehicles through realistic virtual environments. Originally developed in 2007 as rFactor Pro within a Formula 1 team, rFpro evolved from the codebase of the consumer racing simulator to meet the demanding requirements of professional motorsport , focusing on high performance, rapid response, and accurate replication of dynamic road vehicles. The platform has since expanded beyond to support broader automotive applications, providing tools for driver-in-the-loop testing, scenario-based validation, and integration with various vehicle models and hardware platforms. Key features include access to the world's largest library of digital twins—encompassing thousands of kilometers of public roads, test tracks, proving grounds, and race circuits—along with photo-realistic rendering and physics-based simulations that ensure precise handling of complex interactions like tire-road dynamics and environmental conditions. rFpro is utilized by over 50 original equipment manufacturers (OEMs), Tier 1 suppliers, and AI developers, including leading F1 teams and carmakers whose production vehicles have been developed using the software, contributing to safer, more efficient R&D processes. In 2019, rFpro was acquired by AB Dynamics plc, a specialist in testing and measurement solutions, which has bolstered its position in simulation-based verification for autonomous technologies. Today, with offices in the UK, , , and the , rFpro continues to drive innovation in virtual testing, reducing physical prototyping costs and accelerating time-to-market for advanced mobility solutions.

History

Origins and founding

rFpro originated as an internal project within an undisclosed team, where engineers sought to create a capable of accurate testing for high-performance road vehicles. This initiative leveraged the codebase from Image Space Incorporated's racing simulator, building on its isiMotor engine to enhance simulation fidelity for professional applications. On November 14, 2007, rFpro Limited was incorporated in , , , to transition the project into a commercial product known as rFactor Pro, targeted exclusively at professional clients in motorsport and . The founding was driven by the need for a specialized tool that could support rapid prototyping and setup optimization in racing environments. From its inception, rFpro emphasized high-fidelity simulation to meet the demands of professional motor racing teams and car manufacturers, enabling precise modeling of vehicle behavior under dynamic conditions. Early adoption was prominent among teams, including Ferrari and , which integrated the software for testing and development.

Key acquisitions and partnerships

In 2017, rFpro acquired key assets from , including the isiMotor and gMotor engine, which it had previously licensed since ; this move enhanced the realism and performance of rFpro's core simulation engine by integrating over 25 years of ISI's expertise in and rendering. The company's growth accelerated in 2019 when it was acquired by AB Dynamics, a global supplier of advanced automotive test systems, for approximately £21.5 million; this integration positioned rFpro within a broader portfolio of physical and virtual testing technologies, enabling expanded capabilities in ADAS and autonomous vehicle verification. In , rFpro formed a with Cosin Scientific Software to integrate the FTire physical into its simulation suite, allowing for ultra-high-fidelity simulations that combine rFpro's road and environmental modeling with Cosin's advanced tire physics for more accurate handling and grip predictions. Early partnerships with original equipment manufacturers (OEMs) further solidified rFpro's role in professional applications; for instance, in 2014, adopted rFpro's software for its Formula 1 simulator, leveraging the platform's precise digital twins of Grand Prix circuits created through and validation against real-world data to support driver training and vehicle setup optimization.

Recent milestones

In 2024, rFpro launched the AV Elevate platform, a fully integrated solution designed to accelerate autonomous development through scenario-based testing for advanced driver-assistance systems (ADAS) and autonomous vehicles (AVs). This platform enables closed-loop perception testing, allowing developers to tune sensor systems and create complex driving scenarios in a high-fidelity . Building on prior collaborations such as the integration with Cosin software, rFpro continued to advance its offerings in early 2025. In January 2025, adopted the AV Elevate platform to accelerate the development of automated driving and parking technologies, utilizing its simulations to demonstrate parking assistance in diverse virtual scenarios. By July 2025, rFpro expanded the AV Elevate platform to support in-cabin simulation as part of the Sim4CamSens2 collaborative , focusing on high-fidelity testing for interior sensors to enhance occupant monitoring and safety systems. In September 2025, rFpro and jointly released a tyre-road simulation solution that integrates ' Simcenter tire models, enabling precise virtual testing of interactions with road surfaces across desktop, , and real-time environments for automotive and motorsport applications. October 2025 saw rFpro partner with Semiconductor Solutions to demonstrate next-generation camera sensors for ADAS and AV applications using the AV Elevate platform, highlighting advancements in technology through virtual showcases. Throughout 2025, rFpro's innovations gained industry recognition, with the AV Elevate platform receiving the ADAS & AV Test Innovation of the Year award at the Automotive Testing Technology International Awards in May.

Technical foundation

Core engines and simulation capabilities

rFpro's core simulation capabilities are driven by the ISIMotor physics engine, acquired from in 2017, which delivers engineering-grade modeling originally developed for high-fidelity racing simulations. This engine supports precise of vehicle handling, , and interactions, enabling real-time essential for professional development in motorsport and . The ISIMotor provides high for accurate dynamic responses without compromising computational efficiency. Complementing the physics layer, rFpro employs the gMotor graphics engine, also sourced from the 2017 acquisition, to render photorealistic driving scenarios at 120 Hz for immersive visual fidelity. This rendering rate ensures smooth, low-latency visuals that align with the physics update frequency, facilitating seamless driver-in-the-loop testing. The combined engines allow for integrated scenario simulation, where vehicle models interact with environmental data in real time, though detailed integration is handled separately. Access to rFpro's engines and capabilities is governed by a commercial licensing model that limits use to professional entities in the and automotive sectors, ensuring tools remain optimized for industrial applications rather than gaming. This restriction supports secure, high-stakes workflows, with the platform adopted by major OEMs and racing teams for validated simulation outcomes.

Terrain and environmental modeling

rFpro's TerrainServer technology utilizes LiDAR-scanned data to generate high-fidelity terrain models, providing horizontal resolution of 1 cm and vertical resolution of 1 mm for precise representation. This data is fed into the in real-time at update rates up to 5 kHz, enabling low-latency interaction with vehicle dynamics models while capturing fine details such as bumps, kerbs, and surface irregularities that influence contact patches. The system supports multiple modeling approaches, including weighted multisampling for customizable weighting and volumetric interaction for averaged surface normals, ensuring accurate ground reproduction across varied terrain types like cobbled streets or smooth circuits. The platform maintains an extensive library of over 100 high-definition digital models, encompassing race circuits from series such as and , as well as public roads and proving grounds. These models are constructed from survey-grade scans, achieving 1 cm accuracy in horizontal positioning and 1 mm vertical precision to replicate every , drain cover, and camber change. Long-range time-of-flight further captures roadside scenery and environmental features, complemented by geo-referenced for geometric and functional fidelity in elements like road markings and signage. rFpro simulations incorporate dynamic environmental elements to replicate real-world variability, including adjustable weather conditions such as or , variable from time-of-day changes to street illumination, and evolving road surfaces with features like , potholes, or reflective studs. These capabilities allow for scripted scenarios that test vehicle responses under diverse conditions, with road surface details modeled to 1 mm accuracy to simulate grip variations and surface degradation. Validation of these models has been demonstrated through industry adoption, notably Ferrari's 2014 integration of rFpro for simulator development, where the LiDAR-based accuracy—better than 1 cm in X/Y axes and 1 mm in Z—represented a ten-fold improvement over prior tools, enhancing driver realism and circuit fidelity. This precision ensures that interactions align closely with physical counterparts, supporting reliable outcomes.

Accuracy and performance specifications

rFpro's simulation accuracy is validated to sub-millimeter levels in the vertical axis (z-direction) and centimeter-level precision in the horizontal plane ( grid at 1 cm resolution), enabling precise modeling that meets OEM benchmarks for engineering-grade testing. This fidelity is achieved through survey-grade data integration for road surfaces and physically accurate material replication for objects, supporting sub-millimeter vertical accuracy essential for ride and handling simulations. Adoption by six of the top ten OEMs underscores its validation for virtual testing of vehicles, subsystems, and ADAS systems. The platform scales efficiently for multi-vehicle scenarios, handling hundreds of thousands of test variations overnight without real-time constraints, while maintaining high-speed rendering in complex environments like urban scenes or race tracks. Its proprietary rendering engines deliver real-time performance with high frame rates and low graphical latency, facilitating immersive driver-in-the-loop testing and safe exploration of edge cases such as high-speed maneuvers or adverse weather. This scalability supports synchronous modes for precise multi-sensor data alignment in non-real-time simulations, accelerating development cycles. Deployment requires high-end GPUs for optimal rendering, with compatibility for workstations, multi-screen setups, and hardware-in-the-loop systems; integration with HPC clusters via partnerships like enables parallel processing for large-scale scenario generation and validation. These capabilities ensure low latency in graphical outputs for dynamic simulations, prioritizing computational efficiency in professional automotive workflows. In 2025, rFpro's AV elevate simulation platform, which integrates these core engines for autonomous vehicle testing, received the ADAS & Innovation of the Year award, highlighting advancements in scalable, high-fidelity s.

Applications and use cases

Motorsport

rFpro plays a pivotal role in professional , particularly within , where it supports vehicle setup optimization and driver training through high-fidelity simulations. Teams such as Alpine, Ferrari, , and Sauber leverage rFpro for critical applications including validation, suspension tuning, and track strategy development. For instance, the software's high-resolution models enable early validation of aerodynamic systems by simulating airflow interactions with precise track geometries, reducing the need for costly physical testing. Similarly, its detailed modeling of road and kerb surfaces, captured via high-frequency scanning, facilitates accurate suspension tuning to optimize handling and ride characteristics under race conditions. A key feature of rFpro in is its custom track libraries, which provide race-specific s of global circuits for targeted testing. These models, including virtual representations of and , allow engineers to conduct virtual laps that replicate real-world track nuances such as resurfaced tarmac and modified kerbs. Supported by an annual circuit maintenance service, these libraries ensure ongoing accuracy for calendars, enabling teams to simulate setup adjustments and strategy scenarios like tire wear and overtaking maneuvers without on-track access. This capability has proven essential for pre-race preparation, as seen in rFpro's updated of the Las Vegas circuit, which spans 3.8 miles and includes all 17 corners for comprehensive testing ahead of Grand Prix events. Integration with team telemetry further enhances rFpro's utility by allowing seamless correlation between simulated and real-world performance data. The ReplayServer tool records laps from simulations and synchronizes them with feeds by distance or time, enabling side-by-side comparisons with "" cars or live traffic overlays to identify discrepancies in vehicle behavior. This functionality supports iterative refinements in track strategy and driver feedback, contributing to performance gains during race weekends. The adoption of rFpro marked a significant shift in simulation practices, exemplified by Ferrari's transition in 2014. Facing limitations in legacy systems, Ferrari trialed rFpro mid-season and discontinued prior technologies due to its superior track fidelity and engineering precision, a move that accelerated development workflows across and systems. This historical pivot underscored rFpro's emergence as a standard for teams seeking enhanced simulation realism over traditional in-house solutions.

Conventional vehicle development

rFpro provides an engineering-grade environment that enables tier-1 suppliers to simulate , braking, and handling characteristics for passenger and commercial vehicles, supporting both (ICE), hybrid, and electric systems. This includes testing engine control units (ECUs) and hardware-in-the-loop (HIL) dynamometers to evaluate driveline transitions, such as electric regeneration, traction control, and , while ensuring high-fidelity in extreme conditions. According to estimates from AVL, integrating rFpro in these early development stages can save up to 30% in up-front costs by identifying issues before physical prototypes are built. Virtual prototyping with rFpro significantly reduces the need for costly physical testing by allowing engineers to introduce test drivers into simulated environments early in the model-based development process. This facilitates comprehensive evaluation of , , and control systems, including scenarios for crash avoidance and stability control, where virtual models replicate real-world dynamics without risking hardware damage. For instance, rFpro's Terrain Server delivers data accurate to 1 cm horizontally and 1 mm vertically, enabling precise of contact patches for braking and handling tests on passenger vehicles. The platform supports testing in controlled virtual environments by achieving high correlation with real-world road surfaces, allowing validation of performance against standards without extensive on-road trials. In development, rFpro optimizes configurations using detailed modeling to assess and response under varied conditions. Additionally, it aids noise-vibration-harshness (NVH) through integration of high-frequency surface data into and models for ride and studies, helping refine passenger comfort in commercial applications.

Autonomous and ADAS systems

rFpro's AV Elevate is a fully integrated platform designed to accelerate the development, testing, and validation of advanced driver assistance systems (ADAS) and autonomous vehicles (AVs) by enabling the creation of complex virtual environments. It supports the generation of diverse scenarios, including edge cases such as urban , pedestrian interactions, and adverse weather conditions like or , using standards like OpenSCENARIO and OpenDRIVE to automate scalable test case variations. This allows developers to explore rare but critical situations that are challenging to replicate in real-world testing, reducing development time and costs while enhancing assessments. The platform incorporates high-fidelity models for key AV perception technologies, including (such as Velodyne HDL-32), , and cameras, facilitating accurate simulation of individual s and their fusion in virtual settings. These models account for real-world effects like lens distortion, , exposure control, and environmental interactions, enabling closed-loop testing where data feeds directly into and control algorithms. By simulating synchronous outputs, AV Elevate supports the tuning and validation of multi- fusion systems, ensuring robust performance across varied conditions without physical hardware. AV Elevate aids in (V&V) processes for autonomous systems by providing engineering-grade that is 100% accurate and free of annotation errors, which is essential for AI models and confirming system reliability. This includes generating diverse datasets for algorithm and validation, contributing to compliance in safety-critical AV development. In 2025, rFpro's AV Elevate was awarded ADAS & Innovation of the Year at the Automotive Testing Technology International Awards, recognizing its contributions to advanced testing methodologies. Recent expansions of rFpro's simulation tools, particularly through participation in the Sim4CamSens2 project, have introduced enhanced support for in-cabin perception systems, focusing on driver monitoring and human-machine interface (HMI) testing. These updates improve modeling of intra-vehicle lighting, reflections, and conditions like to simulate occupant detection, drowsiness monitoring, and passenger readiness verification more accurately. Such advancements enable comprehensive testing of interior for enhanced cabin safety and personalization in autonomous vehicles.

Adoption and integrations

Major users and clients

rFpro is widely adopted by leading teams for driver training, vehicle development, and performance optimization. The utilizes rFpro in its professional simulator to enhance engineering and driver preparation processes. switched to rFpro in 2014 for modeling Grand Prix circuits and supporting race engineering, crediting it with contributing to the team's performance resurgence. employs rFpro to create realistic track environments, integrating visual cues essential for simulation accuracy in F1 development. invested in a major simulator upgrade featuring rFpro for race car development, driver training, and performance tuning. In the automotive sector, rFpro serves major original equipment manufacturers (OEMs) and suppliers, including for road car engineering and development. Tier-1 suppliers leverage rFpro for ADAS validation, enabling efficient testing and simulation of advanced driver assistance systems to reduce real-world prototyping needs. Technology companies have also integrated rFpro into their workflows. In 2025, adopted rFpro's AV elevate platform to accelerate automated parking solution development, utilizing its capabilities for tuning and testing. Similarly, Semiconductor Solutions selected AV elevate that year to demonstrate next-generation camera sensor technologies for ADAS and autonomous applications. rFpro's impact among users is underscored by recognitions such as the 2025 ADAS & AV Test Innovation of the Year award for its AV elevate platform, highlighting its role in advancing simulation for automotive and ADAS validation.

Third-party software integrations

rFpro's open architecture facilitates seamless integration with a variety of third-party software tools, enabling users to combine its high-fidelity driving simulation with specialized models for enhanced accuracy in vehicle dynamics, control systems, and autonomous vehicle development. This modularity supports plugins, APIs, and toolboxes that allow for co-simulation environments tailored to specific engineering needs. One key integration is with /, which supports and real-time testing of control systems within rFpro's simulation framework. Through dedicated plugins, C++ APIs, and a MATLAB toolbox, engineers can import models directly into rFpro scenarios for hardware-in-the-loop (HIL) validation and rapid prototyping of vehicle controllers. For tire modeling, rFpro incorporates the FTire physical model from Cosin Scientific Software, providing detailed simulation of , , and dynamic interactions with road surfaces. This partnership enables the FTire model to run natively within rFpro, allowing for precise predictions of behavior under varying loads and conditions without compromising simulation performance. In 2025, rFpro collaborated with to integrate Simcenter Tire models, including MF-Tyre and MF-Swift, directly with its TerrainServer for advanced tyre-road interaction modeling. This interface delivers millimeter-accurate road data to the tire models, improving simulations of grip, , and wear in real-time scenarios for both and automotive applications. rFpro also offers compatibility with the (ROS) through frameworks like Autoware, facilitating the deployment and testing of autonomous vehicle algorithms in its simulation environment. This integration allows ROS-based perception, , and control modules to interface with rFpro's virtual worlds, supporting iterative development of AV systems via co-simulation setups. Additionally, rFpro supports co-simulation with IPG CarMaker via ready-to-use plugins, enabling hybrid environments where CarMaker handles while rFpro provides photorealistic scenes and traffic. This setup is particularly useful for validating ADAS features and full-vehicle maneuvers in complex, scenario-driven tests.

References

  1. https://rfpro.com/
  2. https://rfpro.com/about-events-automotive/
  3. https://www.jalopnik.com/1932281/sim-racing-tool-helps-racing-oems/
  4. https://rfpro.com/simulation-software/
  5. https://rfpro.com/digital-models/
  6. https://rfpro.com/ab-dynamics-acquires-simulation-software-specialist-rfpro/
  7. https://www.automotivetestingtechnologyinternational.com/news/appointments-partnerships-investments-acquisitions/ab-dynamics-acquires-simulation-software-specialist-rfpro.html
  8. https://find-and-update.company-information.service.gov.uk/company/06427019
  9. https://rfpro.com/autonomous-vehicle-simulation-specialist-rfpro-acquires-market-leading-graphics-engine-from-image-space-inc/
  10. https://www.vehicledynamicsinternational.com/news/simulation/rfpro-acquires-gaming-company-to-enhance-vehicle-simulation.html
  11. https://www.investegate.co.uk/announcement/rns/ab-dynamics--abdp/acquisition-of-rfpro/36283
  12. https://www.carhs.de/en/news/items/AB_Dynamics_acquires_ADAS_Simulation_Software_Specialist_rFpro_10898.html
  13. https://rfpro.com/ftire-partnership-brings-step-change-in-vehicle-simulation/
  14. https://www.automotivetestingtechnologyinternational.com/news/appointments-partnerships-investments-acquisitions/tire-simulation-partnership-enables-step-change-improvement-in-vehicle-testing.html
  15. https://rfpro.com/ferrari-f1-switched-to-rfpro-simulator-software/
  16. https://www.auto-innovations.com/communiques.php?id=74
  17. https://rfpro.com/introducing-avelevate/
  18. https://www.autonomousvehicleinternational.com/news/simulation/rfpro-introduces-av-elevate-simulation-solution-for-av-development.html
  19. https://www.automotivetestingtechnologyinternational.com/news/adas-cavs/rfpro-av-elevate-simulation-platform-chosen-by-amd.html
  20. https://rfpro.com/rfpro-supports-new-collaborative-project/
  21. https://rfpro.com/siemens-and-rfpro-launch-new-tyre-road-simulation-solution/
  22. https://rfpro.com/sony-showcases-next-generation-camera-technology-using-av-elevate/
  23. https://rfpro.com/av-elevate-wins-adas-av-test-innovation-of-the-year/
  24. https://rfpro.com/applications-autonomous-vehicle-development/automotive-driving-simulation-software/
  25. https://rfpro.com/simulation-software/terrain-server/
  26. https://rfpro.com/nismo-adopts-rfpro-for-its-driver-in-the-loop-simulation/
  27. https://rfpro.com/new-digital-twin-of-rural-uk-road-for-automated-driving-and-vehicle-dynamics-development/
  28. https://cp-catapult.s3.amazonaws.com/uploads/2021/07/00299_AV-Simulation-Testing-Report.pdf
  29. https://rfpro.com/simulation-software/rfpro-real-time-rendering/
  30. https://www.claytex.com/products/av-elevate/rfpro/
  31. https://concurrent-rt.com/portal/partners/strategic-technology/rfpro/
  32. https://rfpro.com/news/show-all/
  33. https://rfpro.com/applications-autonomous-vehicle-development/simulation-motorsport/
  34. https://www.bsimracing.com/rfpro-behind-the-scenes-at-the-alpine-simulator/
  35. https://www.mercedesamgf1.com/news/how-does-f1-simulation-work
  36. https://rfpro.com/saubers-f1-team-alfa-romeo-racing-invest-in-major-simulator-upgrade/
  37. https://rfpro.com/digital-models/digital-circuit-models-motorsport/
  38. https://rfpro.com/rfpro-unveils-hyper-realistic-digital-twin-of-las-vegas-f1-circuit/
  39. https://rfpro.com/applications-autonomous-vehicle-development/adas-autonomous-vehicles/av-elevate/
  40. https://www.claytex.com/products/av-elevate/rfpro/sensor-realistic-simulation/
  41. https://rfpro.com/sensor-tuning-using-av-elevate/
  42. https://rfpro.com/applications-autonomous-vehicle-development/adas-autonomous-vehicles/software-development-software-in-the-loop/
  43. https://rfpro.com/news/press-release/
  44. https://www.automotivetestingtechnologyinternational.com/news/adas-cavs/rfpro-supports-in-cabin-perception-development-as-part-of-sim4camsens2-project.html
  45. https://www.autonomousvehicleinternational.com/features/qa-rfpro-on-advancing-sensor-simulation-with-sim4camsens2.html
  46. https://rfpro.com/rfpro-simulator-credited-with-resurgence-at-ferrari/
  47. https://rfpro.com/applications-autonomous-vehicle-development/
  48. https://rfpro.com/news/customer-stories/
  49. https://www.mathworks.com/products/connections/product_detail/rfpro.html
  50. https://www.automotiveworld.com/news-releases/rfpro-av-elevate-simulation-platform-adopted-by-amd-to-accelerate-the-development-of-automated-driving-technologies/
  51. https://rfpro.com/simulation-software/software-integration/
  52. https://www.claytex.com/tech-blog/integrated-development-framework-for-ros-based-autonomous-vehicles-using-autoware-part-ii/
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