The future of Android in vehicles
David Kleidermacher (Green Hills Software) and Brad Ballard (Texas Instruments Inc.)
Android was initially geared for smartphones and tablets but is quickly expanding into automotive and embedded markets. With its open-source flexibility, powerful content delivery system, and consumer device ubiquity, Android is a tempting choice for center stack designs, but presents significant challenges for designers. This article discusses these benefits and challenges, highlighting the importance of marrying in-vehicle infotainment bells and whistles with safety and security mechanisms.
Modern Automotive Electronics
One of the first computer systems in an automobile was the 1978 Cadillac Seville’s trip computer, run by a Motorola 6802 microprocessor with 128 bytes of RAM and two kilobytes of ROM. The printed source code could not have occupied more than a handful of pages. In contrast, today's automobiles contain massive aggregate compute power and millions of lines of code.
To read the full article, click here
Related Semiconductor IP
- 8MHz / 40MHz Pierce Oscillator - X-FAB XT018-0.18µm
- UCIe RX Interface
- Very Low Latency BCH Codec
- 5G-NTN Modem IP for Satellite User Terminals
- 400G UDP/IP Hardware Protocol Stack
Related Articles
- The Future of Embedded FPGAs - eFPGA: The Proof is in the Tape Out
- Paving the way for the next generation of audio codec for True Wireless Stereo (TWS) applications - PART 5 : Cutting time to market in a safe and timely manner
- MIPI in next generation of AI IoT devices at the edge
- The Future of Safe and Secure Aerospace Systems
Latest Articles
- SNAP-V: A RISC-V SoC with Configurable Neuromorphic Acceleration for Small-Scale Spiking Neural Networks
- An FPGA Implementation of Displacement Vector Search for Intra Pattern Copy in JPEG XS
- A Persistent-State Dataflow Accelerator for Memory-Bound Linear Attention Decode on FPGA
- VMXDOTP: A RISC-V Vector ISA Extension for Efficient Microscaling (MX) Format Acceleration
- PDF: PUF-based DNN Fingerprinting for Knowledge Distillation Traceability