3 Key Automotive Technology Advances To Watch


What we’ve been witnessing in the past few years—particularly with automakers and Tier 1 suppliers investing in software-defined vehicle development—means the automotive industry will grow tremendously both upward in the total number of vehicles as well as horizontally with different innovations in the space coming to fruition. The only way forward is for technology firms and automakers t... » read more

Where And Why AI Makes Sense In Cars


Experts at the Table: Semiconductor Engineering sat down to talk about where AI makes sense in automotive and what are the main challenges, with Geoff Tate, CEO of Flex Logix; Veerbhan Kheterpal, CEO of Quadric; Steve Teig, CEO of Perceive; and Kurt Busch, CEO of Syntiant. What follows are excerpts of that conversation, which were held in front of a live audience at DesignCon. Part two of this... » read more

Automotive E/E Architectures with Safety Related Availability (SaRa) Requirements For Highly Autonomous Driving


A technical paper titled "Multi-objective optimization for safety-related available E/E architectures scoping highly automated driving vehicles" was written by researchers at Robert Bosch GmBbH and University of Luxembourg. Abstract: "Megatrends such as Highly Automated Driving (HAD) (SAE ≥ Level-3), electrification, and connectivity are reshaping the automotive industry. Together with th... » read more

Software-Defined Vehicles: The Automotive Revolution With Silicon At Its Heart


The automotive sector is undergoing immense change. The retirement of the internal combustion engine (ICE) in favor of electrified powertrains and a shift towards autonomy has provided carmakers the opportunity to reimagine and redefine the entire automotive experience: how a car looks, works, and behaves, from the tires up. But such change isn’t easy. An industry founded on the manufactur... » 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

Are We Too Hard On Artificial Intelligence For Autonomous Driving?


I recently attended and presented at Detroit's "Implementation of ISO 26262 & SOTIF" conference. Its subtitle was "Taking an Integrated Approach to Automotive Safety." After three days, my head was spinning with numbers of ISO/SAE and other standards. And at the end of day two, after yet another example that tricked autonomous driving prototypes into behaving wrongly, I sighed and asked whe... » read more

Driver Monitoring Raises Complexity, Adds Privacy Concerns


While you watch the road, your car may be watching you back. The automotive industry’s transition toward self-driving technology means cars increasingly are equipped with features that measure driver alertness and engagement, among many other data points. Executives say such features save lives and spur innovation, while simultaneously raising significant technical, legal, and ethical questio... » read more

Automotive Bandwidth Issues Grow As Data Skyrockets


Bandwidth requirements for future vehicles are set to explode as the amount of data moving within vehicles, between vehicles, and between vehicles and infrastructure, continues to grow rapidly. That data will be necessary for a variety of functions, some of which are here today and many of which are still in development. On the safety side, that includes everything from early warning systems... » read more

Evolving Your ADAS And AV Tests With Emulation Capability


Creating safe and robust autonomous driving (AD) systems is a complex task. Autonomous vehicles (AVs) have hundreds of sensors, all of which need to work with one another inside the car and with other smart vehicles. The software algorithms enabling autonomous driving features will ultimately need to synthesize all the information collected from these sensors to ensure that the vehicle responds... » read more

Data Fusion Scheme For Object Detection & Trajectory Prediction for Autonomous Driving


New research paper titled "Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving" from researchers at Uber. Abstract "We present an end-to-end method for object detection and trajectory prediction utilizing multi-view representations of LiDAR returns. Our method builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized featur... » read more

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