Tasking extends the VX-toolset for Arm with Traveo T2G support

Version 6.0r1 of the VX-Toolset compiler toolchain for Arm Cortex-M also supports Infineon’s Traveo T2G microcontroller family. 

The Traveo T2G microcontroller family is based on Arm’s Cortex-M4 / Cortex-M7. Infineon and Tasking have worked on software development tools for TriCore/Aurix (TC2x, TC3x and TC4x) and now with support for the Traveo T2G family, Tasking offers toolchains for Infineon’s entire microcontroller portfolio. Having compilers for both Traveo T2G and Aurix available from a single tool partner simplifies the work of users who use both microcontrollers. 

The VX-Toolset for Arm Cortex-M is qualified according to ISO 26262 up to ASIL D. TÜV certification is planned for this year. 

Tasking supplies a safety manual with the toolchain. As long as users follow the recommendations described there, they can use the toolchain for the development of safety-critical applications up to ASIL D without any further qualification measures, advises the company. This significantly simplifies and accelerates the certification of the system and reduces costs for the customer, says Tasking.

The VX-toolset for Arm Cortex-M v6.0r1 is available immediately. 

Tasking Germany specialises in providing embedded software development tools. The company is headquartered in Munich, Germany. Tasking development tools are used by automotive manufacturers and the world’s largest Tier 1 supplier to realise high-performance applications in safety critical areas. The tools are used to develop the latest applications to optimum reliability, functional safety and performance standards.

http://www.tasking.com

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Modular LeddarEngine software accelerates ADAS and AD sensor development

LeddarTech has revised its LCA3 SoC and modular software to reduce development time for ADAS (advanced driving assistance system) and autonomous driving sensing technology.

The LeddarEngine software sets a new standard for developing highly integrated and flexible solid state lidar solutions optimised for high-volume production, says LeddarTech. It comprises the LeddarCore LCA3 SoC and LeddarSP signal processing.

It introduces several new integration tiers for the LeddarEngine software and compatibility with new hardware platforms. LeddarTech introduces a separation of the control, signal processing and point-cloud processing, which can be used independently or in combination, for customers to maintain greater control over the final sensing systems.

Lidar developers that have signal processing toolchains implemented for their current products will benefit from using only the control kernel for easier and faster integration of the LeddarCore into products. The software is suitable for Tier 1-2s, system integrators and new lidar makers leveraging LeddarTech’s proprietary signal processing and expertise.

This version of the LeddarEngine is compatible with Xilinx Zynq UltraScale+ MPSoC, in and the Renesas R-Car SoC. The modular architecture improves the separation of hardware and software making it easier to port to other platforms and operating systems.

Founded in 2007, LeddarTech is a comprehensive end-to-end environmental sensing company that enables customers to solve critical sensing, fusion and perception challenges across the entire value chain. LeddarTech provides cost-effective perception solutions scalable from Level 2+ ADAS to Level 5 full autonomy with LeddarVision, a raw-data sensor fusion and perception platform that generates a comprehensive 3D environmental model from a variety of sensor types and configurations. 

LeddarTech also supports lidar manufacturers and Tier 1-2 automotive suppliers with  technology building blocks such as LeddarSteer digital beam steering and the lidar XLRator, a development solution for automotive-grade solid-state lidars based on the LeddarEngine and core components from global semiconductor partners. 

The company is responsible for several innovations in automotive and mobility remote-sensing applications, with over 100 patented technologies (granted or pending) enhancing ADAS and autonomous driving capabilities.

http://www.leddartech.com 

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Virtual development environment for accelerates automotive development

A virtual development environment announced by Renesas Electronics enables  development and operational evaluation of automotive application software to support the latest requirements of electrical/electronic architecture (E/E architecture). 

The environment includes a virtual turnkey platform, which allows engineers to develop application software before devices or evaluation boards are available. There is also a multi-core debug and trace tool, which enables users to analyse and evaluate software as if running on an actual chip. 

“With the evolution of E/E architecture, there is an increasing demand for software design that can maximise performance at a system level,” explains Hiroshi Kawaguchi, vice president, Automotive Software Development division at Renesas. At the same time, the increasing time and cost associated with software development have become a big challenge. “Our integrated software development environment that can be used across gateway systems, ADAS, and xEV development, enables customers to benefit from the scalability of Renesas products such as R-Car and the RH850 family for both software and hardware development.”

 The virtual turnkey platform application software development environment consists of the R-Car Virtual Platform (R-Car VPF) development environment and a software development kit (R-Car SDK) that includes pre-tested software libraries and sample code. R-Car VPF is based on Virtualizer Development Kits (VDKs) from Synopsys, and integrates virtual models of IP specific to R-Car to customise for R-Car devices. By overlaying the R-Car SDK engineers can immediately start development of application software virtually. The platform accurately recreates the behaviour of the chip and eliminates the need to build up a development environment with a physical evaluation board. Multiple users can also develop software simultaneously on separate PCs or servers.

The next step is to integrate the software and verify that it runs on a single chip. Software components share resources such as the multiple CPUs and IPs on R-Car SoCs. If operational problems are detected after the software components are integrated, it requires a tremendous amount of work to analyse and solve them, explains Renesas. The Multicore Debug and Trace tool analyses and identifies the causes of errors occurring from the interaction of the multiple hardware resources in R-Car SoCs. This enables synchronous and simultaneous debugging of the entire heterogeneous architecture of R-Car without using the actual device.

The development environment is available for the R-Car S4 SoC for automotive gateways. Renesas has plans to support the R-Car V4H as well as future versions of R-Car products and RH850 automotive MCUs.

https://www.renesas.com

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NXP drives forward with radar sensor SDK

Radar signal processing algorithms in NXP’s Premium Radar software development kit (SDK) enable developers to enhance radar system performance. It leverages tight coupling of NXP’s software algorithms with its S32R4x radar processor family for improved safety and differentiation. The proprietary radar algorithm library allows quick integration of proven algorithms into radar sensor applications, helping to speed radar sensor development and reduce R&D investment, said NXP. 

The initial release, expected to be available for evaluation during 2022, includes three algorithm packages for interference mitigation, MIMO waveform optimisation and angular resolution enhancement.

Radar is increasingly used in vehicle applications like automated emergency braking and adaptive cruise control. In addition, legislation and regulations mandate more demanding features for blind-spot detection, turn assistant, front and rear cross-traffic and people detection, requiring more radar nodes per vehicle. Another contributor is the consumer demand for a safer and more comfortable driving experience which is accelerating the transition to L2+, offering comfort features close to L3 autonomous driving, said NXP. 

In about five years, cars will carry twice as many radar sensors as today, and over 90 per cent of the radar sensors will be emitting in the same 77 to 79GHz band. 

“We expect the triple acceleration of automotive radar to continue over the next decade, with more cars equipped with radar sensors, an increasing number of sensor nodes per car and more performant sensors being deployed,” said Huanyu Gu, director product marketing and business development ADAS, NXP. For vehicle OEMs and Tier 1 suppliers, this “poses a need for interference mitigation, MIMO waveform optimisation and augmented sensor resolution,” he explained. NXP’s Premium Radar SDK’s advanced algorithms aim to address all these challenges, enabling customers to optimally leverage the S32R4x radar processor hardware, he added.

Optimised MIMO waveforms enable radar sensors with higher resolution and longer reach in modulation schemes which allow more transmitters to operate simultaneously. They code the individual transmit antenna signals to ensure they can be differentiated on the receiver side. Higher resolution sensors are used for both corner and front radar applications to support more accurate object separation and classification for use cases such as vulnerable road user detection or park assist functions. 

The Premium Radar SDK implementation complies with International Automotive Quality Management standards IATF 16949:2016 and ASPICE Level 3 requirements. 

NXP offers OEM and Tier 1 suppliers two evaluation options under an evaluation license agreement. The MATLAB-based version delivers the algorithms as compiled code to allow developers to understand what the SDK does by feeding customer test vectors, computing and visualising the output vectors. Providing bit accuracy, the microcontroller-based evaluation option includes the algorithm binary files to run on the NXP target radar processor evaluation board and demonstrates the real time performance of the SDK.

http://www.nxp.com

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