How Many Sensors For Autonomous Driving?


With the cost of sensors ranging from $15 to $1,000, carmakers are beginning to question how many sensors are needed for vehicles to be fully autonomous at least part of the time. Those sensors are used to collect data about the surrounding environment, and they include image, lidar, radar, ultrasonic, and thermal sensors. One type of sensor is not sufficient, because each has its limitation... » read more

Designing Crash-Proof Autonomous Vehicles


Autonomous vehicles keep crashing into things, even though ADAS technology promises to make driving safer because machines can think and react faster than human drivers. Humans rely on seeing and hearing to assess driving conditions. When drivers detect objects in front of the vehicle, the automatic reaction is to slam on the brakes or swerve to avoid them. Quite often drivers cannot react q... » read more

What’s At Stake In System Design?


What You Will Gain From This eBook: Power and Signal Integrity Insights into harmonic balancing and crosstalk analysis Learning about loop gain and transmission rates Examining the necessity of power-aware systems Electromagnetic Analysis Knowledge about the state of electromagnetics in wireless networks Insight into RADAR and LiDAR EM profiles Tips for bending, meshin... » read more

Week In Review: Auto, Security, Pervasive Computing


Automotive Ambarella will use Samsung's 5nm process technology for its new CV3-AD685 automotive AI central domain controller, bringing "new levels of AI acceleration, system integration and power efficiency to ADAS and L2+ through L4 autonomous vehicles.” Renesas introduced four technologies for automotive communication gateway SoCs: (1) an architecture that dynamically changes... » read more

Research Bits: Feb. 21


High-quality ‘chirps’ for automotive, industrial mmWave radar Imec demonstrated a low-power phase-locked loop (PLL) that generates high-quality frequency-modulated continuous-wave (FMCW) signals for mmWave radar, which can be used in short-range automotive and industrial radar applications. The FMCW radars popular in healthcare, automotive, and industrial send out sinusoidal waves that get... » read more

Simulating Reality: The Importance Of Synthetic Data In AI/ML Systems For Radar Applications


Artificial intelligence and machine learning (AI/ML) are driving the development of next-generation radar perception. However, these AI/ML-based perception models require enough data to learn patterns and relationships to make accurate predictions on new, unseen data and scenarios. In the field of radar applications, the data used to train these models is often collected from real-world meas... » read more

Fixed-Point And Floating-Point FMCW Radar Signal Processing With Tensilica DSPs


Automotive Advanced Driver Assistance Systems (ADAS) applications are increasingly demanding radar modules with better capability and performance. These applications require sophisticated radar processing algorithms and powerful Digital Signal Processors (DSPs) to run them. Because these embedded systems have limited power and cost budgets, the DSP’s Instruction Set Architecture (ISA) needs t... » read more

Physics-Based Radar Modeling: Driving Toward Increased Safety


Autonomous driving is revolutionizing the global automotive industry. With every new model, cars are smarter and more capable of independently responding to external signals like lane markings, road signs, other cars and pedestrians. However, formulating a correct response via artificial intelligence depends on the flawless performance of the car’s perception systems, including radar-ba... » read more

Auto Safety Tech Adds New IC Design Challenges


The role of AI/ML in automobiles is widening as chipmakers incorporate more intelligence into chips used in vehicles, setting the stage for much safer vehicles, fewer accidents, but much more complex electronic systems. While full autonomy is still on the distant horizon, the short-term focus involves making sure drivers are aware of what's going on around them — pedestrians, objects, or o... » read more

Synergies And Limitations Between Road Infrastructure And Automated Driving


This new technical paper titled "Road Infrastructure Challenges Faced by Automated Driving: A Review" was published by researchers at Graz University of Technology (Austria), University of Zagreb (Croatia), AKKA I&S (France). Abstract "Automated driving can no longer be referred to as hype or science fiction but rather a technology that has been gradually introduced to the market. The recen... » read more

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