While autonomous driving technologies continue to advance, current Advanced Driver Assistance Systems (ADAS) remain limited in their ability to interpret scene context or engage with drivers through natural language. These systems typically rely on predefined logic and lack support for dialogue-based interaction, making them inflexible in dynamic environments or when adapting to driver intent. This paper presents Scene-Aware Conversational ADAS (SC-ADAS), a modular framework that integrates Generative AI components including large language models, vision-to-text interpretation, and structured function calling to enable real-time, interpretable, and adaptive driver assistance. SC-ADAS supports multi-turn dialogue grounded in visual and sensor context, allowing natural language recommendations and driver-confirmed ADAS control. Implemented in the CARLA simulator with cloud-based Generative AI, the system executes confirmed user intents as structured ADAS commands without requiring model fine-tuning. We evaluate SC-ADAS across scene-aware, conversational, and revisited multi-turn interactions, highlighting trade-offs such as increased latency from vision-based context retrieval and token growth from accumulated dialogue history. These results demonstrate the feasibility of combining conversational reasoning, scene perception, and modular ADAS control to support the next generation of intelligent driver assistance.

Teleoperation of mobile manipulators within a home environment can significantly enhance the independence of individuals with severe motor impairments, allowing them to regain the ability to perform self-care and household tasks. There is a critical need for novel teleoperation interfaces to offer effective alternatives for individuals with impairments who may encounter challenges in using existing interfaces due to physical limitations. In this work, we iterate on one such interface, HAT (Head-Worn Assistive Teleoperation), an inertial-based wearable integrated into any head-worn garment. We evaluate HAT through a 7-day in-home study with Henry Evans, a non-speaking individual with quadriplegia who has participated extensively in assistive robotics studies. We additionally evaluate HAT with a proposed shared control method for mobile manipulators termed Driver Assistance and demonstrate how the interface generalizes to other physical devices and contexts. Our results show that HAT is a strong teleoperation interface across key metrics including efficiency, errors, learning curve, and workload. Code and videos are located on our project website.

In a promotional video actress Michelle Yeoh walks through a bustling urban landscape at night with a smart phone in her hand as she talks to us about a coming transformation. "Every day Qualcomm is transforming the way we work, live and communicate, pushing the limits of technologies like artificial intelligence," she says. It's a dramatic statement by Qualcomm, as they try to connect the company to artificial intelligence in the mind of the market. "Whether our technology is going into a smartphone or whether it's going into a factory or a robot or a drone flying around Mars, our AI is a horizontal that permeates all of those device categories and applications," said Don McGuire, Qualcomm's chief marketing officer. The technology Qualcomm brings to artificial intelligence is a digital platform, based on Snapdragon computer chips.

When (and if) if the Afeela electric car from Sony Honda Mobility goes on sale, it will use the Snapdragon Digital Chassis from Qualcomm -- an automotive technology platform that combines safety and connectivity systems, entertainment, customization, and upgradability all into one product. For automakers, finding the right technology partner means simplifying a vehicle's architecture and unlocking new revenue streams in the form of passenger entertainment and downloadable upgrades. The Qualcomm Snapdragon Digital Chassis is comprised of four automotive systems -- Snapdragon Auto Connectivity includes connected systems like 5G and vehicle-to-vehicle technologies, Snapdragon Cockpit Platform supplies the digital instrument clusters and infotainment controls, Snapdragon Car-to-Cloud makes over-the-air software updates possible, and the Snapdragon Ride Platform supplies driver assistance technologies and autonomous driving capability. "There is a tremendous amount of opportunity to reinvent the car," Nakul Duggal, Qualcomm's senior vice president and general manager for automotive, tells Wired. "And a tremendous amount of that reinvention is happening because the car is becoming a truly digital product."

It is a lack of knowledge about the AV due to confusing terminology from the industry. Industry stakeholders must work together to ensure clear and consistent messaging and the use of consumer-facing terminology is part of this. Understanding which words and phrases resonate with consumers can help manage misconceptions and improve consumer understanding of AV. Some 56% of study respondents thought current driver technologies are the same as fully automated #selfdrivingcars systems. Consumers showed further confusion when asked about terminology used to describe different levels of #automation.

As Tesla faces a federal investigation and lawsuits over fatal accidents involving its Autopilot system, shaking public confidence in robotic cars, could a pared-down approach like the one described -- variously called "partial autonomy" or "driver assistance" systems -- be the more realistic future of hands-free driving? This type of system, more like a no-nonsense chaperone than one you would find in a fully robotic car, is a necessary component for top scores from the Insurance Institute for Highway Safety's forthcoming ratings of partial-autonomous tech; high ratings from the independent nonprofit are prized. And though General Motors is taking the lead with their Super Cruise system, they not alone; Ford, BMW and Mercedes-Benz are making similar attempts. Super Cruise combines minutely detailed, 3-D laser-scanned roadway maps with cameras, radar and onboard GPS. By the end of this year, the company intends to expand the system's network to two-way highways for the first time and double its total operational domain to 400,000 miles.

Autonomous self-driving cars have now become a trend in the world. There are big automakers and technology companies involved in the automation industry, but it is the start-ups that are making their place in the industry with new inventions. In a populous field of more than 300 start-ups in self-driving cars, let's take a closer look at the top autonomous self-driving car companies that have achieved unicorn status. Velodyne Lidar provides smart, powerful lidar solutions for autonomous vehicles, driver assistance, delivery solutions, robotics, navigation, mapping, and more. Headquartered in San Jose, Calif, Velodyne is known worldwide for its portfolio of breakthrough lidar sensor technologies.

Staying ahead of the technology curve means strengthening your competitive advantage. That is why we give you data-driven innovation insights into the mobility industry. This time, you get to discover 5 hand-picked startups developing artificial intelligence (AI) solutions. The insights of this data-driven analysis are derived from the Big Data & Artificial Intelligence-powered StartUs Insights Discovery Platform, covering 1.379.000 The platform gives you an exhaustive overview of emerging technologies & relevant startups within a specific field in just a few clicks.

Velodyne is the first lidar technology company to become part of this influential group. ITS America members are at the forefront of driving progress in autonomous vehicles and smart city solutions to help save lives, improve mobility and promote sustainability. Velodyne's lidar sensors can be used in a variety of Intelligent Transportation Systems to measure and monitor conditions in areas such as pedestrian safety, vehicle traffic and parking space management, and more. They can collect reliable, detailed traffic data about road users, including vehicles, pedestrians and bicyclists, while preserving anonymity. Velodyne's lidar sensors do not identify individuals' facial characteristics, a growing requirement for civic applications.

Velodyne Lidar, Inc. today announced a multi-year sales agreement with NAVYA, a leading company in autonomous driving systems. Since 2015, NAVYA has been using Velodyne lidar sensors in production for its autonomous shuttle fleet that provides mobility services to cities and private sites. This press release features multimedia. Since 2015, NAVYA has been using Velodyne lidar sensors in production for its autonomous shuttle fleet that provides mobility services to cities and private sites. NAVYA plans to pursue the worldwide expansion of its shuttle with Velodyne's state-of-the-art sensors for precise real-time localization and object detection.