Master Autonomous Driving (AD) Development with RTMaps

20 Years of RTMaps: Real-Time Multisensor Applications

RTMaps was initially developed at The Center of Robotics of Mines ParisTech (CAOR) in 1998. At the time, a team under former Director Claude Laurgeau was working on robotics and intelligent transport systems (ITS). The team participated in the Eureka Prometheus project (1987-1995), one of the very first and largest EU-funded R&D projects focusing on automated driving. The aim was to develop computer vision algorithms and Bayesian-network-based data fusion for vehicle perception and accurate positioning. Their objective was to execute these algorithms in real time in a prototype vehicle equipped with a front camera, a radar, and the very first models of lidar scanners.

But the team quickly realized they spent 90% of their time working on their software architecture rather than algorithms.

Since no development tools on the market met their requirements, the team developed their own modular and component-based software solution, called RTMaps (Real-Time Multisensor applications) – more than 20 years ago.

RTMaps: Trusted Middleware

Optimized by design with its multithreaded architecture, RTMaps gets the most out of your multicore and multi-CPU architectures without introducing any overhead work. Time coherence is a key asset of the software: RTMaps developers long identified the need for synchronizing the various sensors and data sources in a vehicle, where several processing channels are executed in parallel and with different latencies. The accurate time-stamping mechanism in RTMaps and the built-in features for data stream resynchronization will maintain causality and time coherence in your complex real-time architecture with multiple tasks or ECUs. RTMaps supports operating systems such as Windows®, Linux (Ubuntu™ LTS), and QNX®.

The tried and tested RTMaps technology is used in R&D teams and prototype vehicles all over the world, for example, at research centers such as Queensland University of Technology, or at Vicomtech, and in many EU projects, respectively. It is also used by development teams at OEMs and Tier-1 suppliers such as Navya and Valeo.

Minimize Development Risks

With the rise of autonomous driving, which basically means creating robots on wheels, the focus in the automotive industry successively shifted from mechanics towards electronics and software. Most OEMs and Tier-1 suppliers have taken a deep dive into this new kind of mobility. Many industry and consulting experts agree: The use of software will drastically transform the automotive industry and turn mechanical engineering companies into high-tech and IT companies.

This transition requires great effort, especially from classical OEMs, as most automotive engineers are not software experts.

Complex real-time systems require great expertise and a thorough understanding of software mechanisms. RTMaps enables automotive engineering teams to focus on the implementation of their algorithms rather than the software architecture, letting them define accurate strategies for their autonomous applications. The modular structure and intuitive user interface of RTMaps reduce development risks because they minimize efforts and errors during code copying and rewriting.

RTMaps gives you access to a full software stack for the development of an autonomous vehicle. In addition, RTMaps strips the underlying hardware, sensor interfaces, and drivers of their complexity, giving you an intuitive user interface for component-based development via drag & drop.

The full software stack offered by RTMaps includes over 120 packages and more than 600 software components that are ready to use as is. Among them, many sensor interface components for cameras, radars, lidars, GPS, IMU, CAN decoders, and more. For instance, RTMaps supports more than 60 lidar models from over 15 brands, including Velodyne, Leddartech, Ouster, IBEO, Valeo, Robosense, Sick, Hesai, Quanergy, Livox, AEye, Hokyuyo, and Slamtech.

Ready for Use:


NAVYA: Autonomous Shuttle Bus

The NAVYA ARMA is considered to be the world's first driverless production vehicle for regular traffic. NAVYA relies on the RTMaps multisensor development environment from Intempora to develop the complex functions that make autonomous driving possible.

Indiana University – Purdue University Indianapolis (IUPUI): Algorithms for autonomous driving

Indiana University – Purdue University Indianapolis (IUPUI) is researching ways to improve road transport safety for autonomous applications by analyzing the benefits of high-speed sensor data processing. RTMaps Embedded and NXP BlueBox are serving as the core real-time execution platform for embedded computing capabilities.
​​​​​​​(dSPACE Magazine 2/2019)

From Code to the Road

As lightweight software, the RTMaps run-time execution engine can be used in all development stages of autonomous vehicle applications: in the cloud or docker containers, on PCs, and even on ECUs and embedded targets. You can also use RTMaps as a postprocessing framework in hardware data replay validation and using cloud computing architectures to validate perception and deep learning algorithms or complex software functions for automated driving.

RTMaps is versatile, modular, and highly scalable. It is widely used for next-generation autonomous vehicles, from prototyping to validation.

The software can be deployed and executed on embedded systems in real time. RTMaps supports ARM-based architectures and embedded targets dedicated to advanced driver assistance systems (ADAS) and highly automated driving (HAD). It provides extensive data crunching capabilities for tomorrow’s vehicles that rely on systems on a chip (SoCs) as developed by major silicon vendors such as NVIDIA, Renesas, and NXP. This means it lets you use the exact same designs and applications from the early prototyping stages on PCs on the most recent ECUs designed for mass production. It significantly reduces the number of development cycles and simplifies the deployment of complex algorithms on embedded targets.

RTMaps accelerates time to market by increasing the productivity and the efficiency of your R&D engineering team — a decisive factor in the ongoing mobility revolution.

Personal Demo

Are you interested in an in-depth tool demonstration and insights into other RTMaps success stories?  Book a personal presentation and video demo.

Video (Example)

The ibeo Evaluation Suite is a modular software for automatic object labeling, post-processing of the recorded data of large test drives, as well as the generation of a map of lane markings. It has been integrated in RTMaps in order to provide ground truth streams

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