Automotive

Siemens integrates the u-blox ZED-F9K module into its V2X test fleet

Mon, Jun 10, 2019

The ZED-F9K turnkey solution minimizes the effort required to achieve decimeter-level positioning accuracy in automotive applications.

Thalwil, Switzerland – June 7, 2019 – u-blox (SIX:UBXN), a global provider of leading positioning and wireless communication technologies for the automotive, industrial, and consumer markets, is announcing that Siemens has integrated the u‑blox ZED-F9K (https://www.u-blox.com/en/product/zed-f9k-module) high precision dead reckoning module into its Toyota Prius V2X (vehicle-to-everything) test fleet. Siemens carried out live demonstrations of the technology at the ITS European Congress 2019 (https://2019.itsineurope.com/) in Eindhoven, the Netherlands.

As the only available source of absolute position, satellite-based positioning plays a crucial role in advanced driver automation systems and driverless vehicles. The same is true in V2X communication, in which vehicles continuously share their location and other information with other traffic participants – cars and pedestrians – as well as surrounding infrastructure,  improving road safety and reducing traffic congestion.

V2X test vehicles typically determine their position using high-end, expensive GNSS (Global Navigation Satellite Systems) receivers. While these provide highly accurate position information, they fail to realistically represent the hardware that will be deployed in vehicles produced for the mass market. By opting to use the ZED-F9K turnkey solution for high precision dead reckoning, Siemens was able to align the performance of their test fleet with real world conditions while also reducing the cost and the engineering effort required to develop their vehicles.

“We’ve had a very positive experience with u-blox’s ZED-F9K high precision dead reckoning solution. The product delivered strongly from the initial design-in to the data and performance in our first tests,” says Igor Passchier, Engineering fellow, Connected and Automated Driving at Siemens PLM Software. “It underscores the reputation of u‑blox as a trusted innovator in GNSS technology.”

“Our collaboration with Siemens shows the extent to which the ZED-F9K turnkey solution saves OEMs time, cost, and engineering effort while providing decimeter-level positioning performance,” says Alex Ngi, Product Strategy for Dead Reckoning, Product Center Positioning, u-blox. “For us, it has also been a welcome opportunity to contribute to solving the challenges in the autonomous driving ecosystem.”

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Quick-start software to develop embedded ADAS

Tue, Jun 04, 2019

Software has been developed specifically to use the hardware accelerators in Renesas Electronics’ R-Car V3H SoC for advanced driver assistance systems (ADAS) in automotive design.

To accelerate the development of ADAS, the Perception Quick Start software,  based on the R-Car V3H SoC delivers reference software for camera obstacle detection (COD), lidar obstacle detection (LOD), and road feature detection (RFD), deemed as three key recognition areas for sensor-based Level 2+ autonomous vehicle systems.

The COD reference software uses convolutional neural network (CNN) IP, a computer vision engine (CV-E), and image rendering (IMR) technology to detect 2D objects such as cars, trucks, buses, and pedestrians. It achieves approximately 30 frames per second.

The LOD software uses CNN-IP and CV-E to detect 3D objects, including cars and trucks. The LOD achieves approximately 15 frames per second with 3D bounding boxes at 50m.

The RFD reference software uses CNN-IP, CV-E, IMR, and a versatile pipeline engine (IMP) to identify drivable free space, lanes (crossable and uncrossable), road boundaries, and distances to lanes and nearest objects to support NCAP 2020. The RFD achieves approximately 30 frames per second.

The R-Car V3H SoCs deliver a combination of high computer vision performance and artificial intelligence (AI) processing at low power levels, for automotive front cameras in Level 2+ autonomous vehicles. To advance recognition technology, Renesas designed the SoCs with dedicated hardware accelerators for key algorithms including convolutional neural networks, dense optical flow, stereo disparity, and object classification. The Perception software provides an end-to-end pipeline reference for developers working with these complex accelerators which are both cost-effective and power-efficient, thereby allowing customers to advance an application design even if they have limited experience at using the accelerators. The reference software covers input from sensor or recorded data, all stages of processing and display output on a screen.

“Specialised hardware accelerators play an essential role in achieving the computer vision performance and accuracy required in embedded ADAS and autonomy applications while still meeting stringent in-vehicle power consumption limits,” said Tim Grai, director or automotive advanced systems innovation department, Renesas. “However, the complexity of these accelerators can present a steep learning curve. With the Perception Quick Start software, we are able to offer a set of application software along with the underlying primitives to simplify the use of these complex accelerators needed to achieve embedded ADAS.”

Renesas will demonstrate the Perception software at TU-Automotive Detroit (Booth C190, 5-6 June, Novi, Michigan, USA).

http://www.renesas.com

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Quick-start software to develop embedded ADAS

Tue, Jun 04, 2019

Software has been developed specifically to use the hardware accelerators in Renesas Electronics’ R-Car V3H SoC for advanced driver assistance systems (ADAS) in automotive design.

To accelerate the development of ADAS, the Perception Quick Start software,  based on the R-Car V3H SoC delivers reference software for camera obstacle detection (COD), lidar obstacle detection (LOD), and road feature detection (RFD), deemed as three key recognition areas for sensor-based Level 2+ autonomous vehicle systems.

The COD reference software uses convolutional neural network (CNN) IP, a computer vision engine (CV-E), and image rendering (IMR) technology to detect 2D objects such as cars, trucks, buses, and pedestrians. It achieves approximately 30 frames per second.

The LOD software uses CNN-IP and CV-E to detect 3D objects, including cars and trucks. The LOD achieves approximately 15 frames per second with 3D bounding boxes at 50m.

The RFD reference software uses CNN-IP, CV-E, IMR, and a versatile pipeline engine (IMP) to identify drivable free space, lanes (crossable and uncrossable), road boundaries, and distances to lanes and nearest objects to support NCAP 2020. The RFD achieves approximately 30 frames per second.

The R-Car V3H SoCs deliver a combination of high computer vision performance and artificial intelligence (AI) processing at low power levels, for automotive front cameras in Level 2+ autonomous vehicles. To advance recognition technology, Renesas designed the SoCs with dedicated hardware accelerators for key algorithms including convolutional neural networks, dense optical flow, stereo disparity, and object classification. The Perception software provides an end-to-end pipeline reference for developers working with these complex accelerators which are both cost-effective and power-efficient, thereby allowing customers to advance an application design even if they have limited experience at using the accelerators. The reference software covers input from sensor or recorded data, all stages of processing and display output on a screen.

“Specialised hardware accelerators play an essential role in achieving the computer vision performance and accuracy required in embedded ADAS and autonomy applications while still meeting stringent in-vehicle power consumption limits,” said Tim Grai, director or automotive advanced systems innovation department, Renesas. “However, the complexity of these accelerators can present a steep learning curve. With the Perception Quick Start software, we are able to offer a set of application software along with the underlying primitives to simplify the use of these complex accelerators needed to achieve embedded ADAS.”

Renesas will demonstrate the Perception software at TU-Automotive Detroit (Booth C190, 5-6 June, Novi, Michigan, USA).

http://www.renesas.com

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Farnell extends semiconductor range with Osram Opto family

Fri, May 24, 2019

LEDs, infra red emitters, photodiodes and optical sensors from Osram Opto Semiconductor have been added to the semiconductor portfolio by Farnell.

The Osram range extends Farnell’s line card to provide customers with products to support applications in markets such as automotive, mobile, smart grid, metering, industrial, office and building automation, energy management and network infrastructure.

The distributor now ships the Olson Black family of infra red LEDs. Now with dedicated automotive versions that include the 850nm version for exterior applications such as night vision, pedestrian protection, pre-field recognition and lane detection. The 940nm version is targeted at interior automotive applications such as driver monitoring, seat occupancy detection and gesture recognition. The LEDs have different wavelengths and lenses and can be operated at up to 5A in pulse mode.

There is also the SFH 2200 family of photodiodes. The package allows them to be soldered without any damage for up to one year after initial contact with air, compared to only three days for typical standard products, reports Farnell. The package is approved up to an operating temperature of 125 degrees C. The SFH 2200 devices meet the requirements for AEC-Q101-C qualification and are particularly suitable for use in rain sensors.

The TOPLED E1608 family of low-power LEDs is also in a smaller package and are particularly suited to automotive applications such as displays, ambient lighting and backlighting of switches and instruments.

Other LEDs are the SFH 4776 broadband infra red LED range. They are suitable for near-infra red spectroscopy techniques for measuring parameters such as the water, fat, sugar and protein content of food and pharmaceutical products.

The SYNIOS P2720 platform consists of 15 LED products with different chip sizes, power ratings and colours which can be configured within a single footprint. The LEDs have high thermal reliability and high brightness and the devices can be scaled for cost-effective automotive and light design.

http://www.element14.com

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