Articles tagged with Autonomous Vehicles
Researchers have developed a new material with high birefringence properties that can improve infrared detection in dense fog and dark conditions. This technology may enable faster deployment of autonomous vehicles and create more efficient heat sensing tools for firefighters.
A new lane-change algorithm developed by MIT allows autonomous vehicles to model an entire range of driving styles, from conservative to aggressive, with safety guarantees. The system computes buffer zones on the fly and ensures collision avoidance within a given time frame.
The AVENUE project, led by the University of Geneva, aims to develop and test autonomous vehicle services in European cities. The project will focus on optimizing itineraries, in- and out-of-vehicle services, and addressing security concerns. Geneva is one of the pilot sites for the large-scale tests.
Wiseman and Grinberg propose a system to evaluate collision potential and choose the least harmful course of action for autonomous vehicles. The system uses Spatial Data Structures and Bounding Volumes to analyze possible crashes and decide on the most destructive option.
Researchers at U of T Engineering found that optimizing for autonomous vehicles can increase parking lot capacity by 62%. A well-designed AV parking lot can accommodate more cars than a conventional one, with square-shaped lots capable of increasing capacity up to 87%.
Researchers are developing a miniature collision detection sensor system that could drastically improve the safety of autonomous vehicles. The ULTRACEPT project combines near-range collision detection, long-range hazard perception, and thermal-based collision detection tools to overcome current limitations.
A new study found that autonomous vehicles can minimize environmental impacts with energy-efficient design and operational benefits outweighing increased energy use from sensors and computers. The study showed a 40% reduction in greenhouse gas emissions for electric powertrains versus internal-combustion engines.
A UMass Lowell professor is leading a research study on the ethical dilemmas posed by autonomous vehicles. The team aims to develop decision-making algorithms that balance individual rights with societal welfare. They will also investigate cybersecurity and privacy concerns related to self-driving cars.
New research shows that a small percentage of self-driving cars can significantly impact road flow, eliminating phantom traffic jams and reducing fuel consumption by up to 40%. The study demonstrates the potential for autonomous vehicles to regulate traffic flow and improve efficiency.
A new study suggests that autonomous vehicles could facilitate pedestrian-oriented urban neighborhoods, as pedestrians can act unpredictably and force self-driving cars to stop. However, the adoption of autonomous vehicles may be hampered by their strategic disadvantage in urban traffic.
Researchers at UC Riverside have developed a reliable and accurate navigation system that exploits environmental signals like cellular and Wi-Fi to support autonomous vehicle development. The technology can be used as an alternative or complement to GPS-based systems, enabling consistent and tamper-proof navigation.
A recent study by MIT researchers found that the public takes a utilitarian approach to autonomous vehicle safety, minimizing casualties in extreme situations but prioritizing personal safety. This 'social dilemma' may lead to conditions becoming less safe for everyone as individuals act in their own self-interest.
Researchers at Chalmers University of Technology are developing a self-driving truck that uses animal-inspired behavior to improve safety and adaptability. The truck's software, OpenDLV, is designed to react to unexpected situations by mimicking the way animals respond to their environment.
A novel technique called model predictive path integral control (MPPI) helps autonomous vehicles maintain stability at the edge of handling limits. By leveraging advanced algorithms and onboard computing, MPPI enables vehicles to optimize their trajectories in real-time, reducing the risk of accidents on hazardous roads.
Researchers at UNR are developing software to connect autonomous vehicles with NASA's traffic management system for safe low-altitude operations. The University is part of the first phase of the NASA UTM project to enable safer drone delivery and humanitarian applications.
A new RAND Corporation study suggests that autonomous vehicles will outweigh the likely disadvantages, providing significant social benefits such as decreased crashes, increased mobility, and fuel economy. However, policymakers must address regulatory challenges, liability issues, and privacy concerns.
Researchers at Virginia Tech developed a step-by-step procedure for managing driverless vehicles through intersections, considering factors like location, speed, and acceleration. The proposed system aims to reduce crashes and emissions by keeping vehicles moving and optimizing traffic flow.
Computer scientist Peter Stone is developing a system that enables autonomous cars to coordinate their movements at intersections, reducing stopped traffic. The virtual intersection manager uses AI driver agents to 'call ahead' and reserve space and time, improving safety and efficiency.
Four unmanned autonomous vehicles designed by Virginia Tech engineering students using TORC Robotic Building Blocks product line will be used by the Marine Corps in Hawaii during the RIMPAC war games. The vehicles are equipped with advanced sensors, perception, planning, and control algorithms to navigate complex environments.
A Virginia Tech researcher is developing a fleet of low-cost, miniature autonomous underwater vehicles (AUVs) to collect elusive environmental data in Hog Island Bay. The AUVs will be equipped with sensors to monitor water parameters and work cooperatively to gather data that can't be collected with traditional methods.