Automotive

  • Chances and challenges for machine learning in highly automated driving, part 3: Algorithm selection criteria for functional safety

    Chances and challenges for machine learning in highly automated driving, part 3: Algorithm selection criteria for functional safety

    Criteria for selecting the right machine learning algorithm for functional safety are necessary. These criteria are described below.

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  • Five Minutes with…Rick Kreifeldt, Executive Director, eSync Alliance

    Five Minutes with…Rick Kreifeldt, Executive Director, eSync Alliance

    We keep hearing about over-the-air updates for the automotive space. Is this real or is it a pipe dream?

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  • Luxoft and Daimler co-develop technology platform that powers the MBUX infotainment system

    Luxoft and Daimler co-develop technology platform that powers the MBUX infotainment system

    Luxoft Holding, a global IT service provider, and Daimler AG, the global automotive manufacturer, have partnered to develop the software platform that powers Mercedes-Benz User Experience (MBUX),...

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  • Chances and challenges for machine learning in highly automated driving, part 2: Theoretical background

    Chances and challenges for machine learning in highly automated driving, part 2: Theoretical background

    Part two defines the theoretical background of machine learning technology, as well as the types of neural networks available to automotive developers.

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  • Managing functional safety in complex automotive supply chains

    Managing functional safety in complex automotive supply chains

    Organizations in Silicon Valley and elsewhere just entering the automotive marketplace can be taken aback by the strict requirements management and compliance needed with standards such as ISO 26262.

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  • New frontiers in automotive HMI and display design

    New frontiers in automotive HMI and display design

    HMI designs are now employing artificial intelligence (AI) technologies to reduce driver distractions through a new breed of gesture-recognition features.

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  • The future of vehicle connectivity

    The future of vehicle connectivity

    As automotive technologies continue to mature, new vehicle sensors are now capable of predicting impending collisions, identifying pedestrians and cyclists, and more.

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  • From logistics regression to self-driving cars: Chances and challenges for machine learning in highly automated driving

    From logistics regression to self-driving cars: Chances and challenges for machine learning in highly automated driving

    In part one of this three-part series, the authors investigate the drivers behind and potential applications of machine learning technology in highly automated driving scenarios.

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  • Four ways AI improves automotive design while maintaining brand identity

    How OEMs can safeguard their brand identities as technology development speeds ahead.

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  • dSPACE supports AUTOSAR 4.3 features

    dSPACE supports AUTOSAR 4.3 features

    New safety and security measures and technologies integrated in the tool chain  Easier validation of highly safety-critical driving functions  Efficient solutions and broad expertise

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  • Embedding IoT in transportation

    According to a recent market report, an increase in disposable incomes and technological production across regions is the major driving factor for the connected car market.

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  • Automotive open source virtualization: AGL virtualization architecture

    Automotive open source virtualization: AGL virtualization architecture

    The AGL Software Defined Car Architecture white paper edited by the AGL EG-VIRT and published by Linux Foundation details the AGL virtualized architecture.

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  • Automotive open source virtualization: Bringing open source virtualization in AGL

    Automotive open source virtualization: Bringing open source virtualization in AGL

    The AGL Software Defined Car Architecture white paper defines how the AGL target platform for software defined vehicles can be implemented by using virtualization techniques.

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  • An open, next-gen reference platform for tomorrow's digital cockpits

    PELUX ARP aims to be the first truly open hardware and software solution for next-generation digital cockpits.

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  • Microchip’s AEC-Q100-qualified 3D gesture recognition controller reduces HMI design costs

    Microchip’s AEC-Q100-qualified 3D gesture recognition controller reduces HMI design costs

    The MGC3140 3D is a capacitive technology-based air gesture controller that supports an operating temperature range of -40ºC to +125ºC while meeting the EMI and EMC requirements of automotive systems.

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  • Avnu Alliance Hosts Automotive TSN Workshop in Japan

    Avnu member companies and liaison organization JasPar joined Avnu Alliance to gather industry insight and address advancement of TSN at the first automotive TSN workshop in Japan co-located with...

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  • Why Daimler selected Xilinx for AI and autonomous drive

    Why Daimler selected Xilinx for AI and autonomous drive

    Daimler didn’t select Xilinx as a partner simply to join the bandwagon. Rather, the German automaker is focused on autonomous drive applications and artificial intelligence (AI).

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  • Leti, Transdev and IRT Nanoelec announce pilot program to assess new perception sensors for autonomous vehicles

    Leti, Transdev and IRT Nanoelec announce pilot program to assess new perception sensors for autonomous vehicles

    Leti and Transdev, a leading global provider of mobility services, and IRT Nanoelec, an R&D center focused on information and communication technologies using micro- and nanoelectronics, have...

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  • Artificial intelligence and automotive: Happy together

    Artificial intelligence and automotive: Happy together

    ADAS and autonomous car designs are unleashing the levels of innovation unprecedented in the technology business. At the same time, however, AI is turning the industry upside down.

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  • Automotive open source virtualization: The AGL path towards software defined connected cars

    Virtualization is a technique used to create multiple virtual execution environments by means of resource abstraction or partitioning.

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