One of the largest accident studies yet suggests self-driving cars may be safer than human drivers in routine circumstances – but it also shows the technology struggles more than humans during low-light conditions and when performing turns. The findings come at a time when autonomous vehicles are already driving in several US cities. The GM-owned company Cruise is trying to restart driverless car testing after a pedestrian-dragging incident in March led California to suspend its operating permit. Meanwhile, Google spin-off Waymo has been gradually expanding robotaxi operations in Austin, Los Angeles, Phoenix and San Francisco. "It is important to improve the safety of autonomous vehicles under dawn and dusk or turning conditions," says Shengxuan Ding at the University of Central Florida.

In recent years, numerous researchers have begun investigating how virtual reality (VR) tracking and interaction data can be used for a variety of machine learning purposes, including user identification, predicting cybersickness, and estimating learning gains. One constraint for this research area is the dearth of open datasets. In this paper, we present a new open dataset captured with our VR-based Full-scale Assembly Simulation Testbed (FAST). This dataset consists of data collected from 108 participants (50 females, 56 males, 2 non-binary) learning how to assemble two distinct full-scale structures in VR. In addition to explaining how the dataset was collected and describing the data included, we discuss how the dataset may be used by future researchers.

Artificial Intelligence (AI) refers to the simulation of human intelligence in machines that are programmed to think and act like humans. AI technologies enable computers to perform tasks that typically require human intelligence, such as visual perception, speech recognition, decision-making, and language translation. A study led by a professor from the University of Central Florida has identified six challenges that must be overcome in order to improve our relationship with artificial intelligence (AI) and guarantee its ethical and fair utilization. A professor from the University of Central Florida and 26 other scientists have published a study highlighting the obstacles that humanity must tackle to guarantee that artificial intelligence (AI) is dependable, secure, trustworthy, and aligned with human values. The study was published in the International Journal of Human-Computer Interaction.

Speeding has been and continues to be a major contributing factor to traffic fatalities. Various transportation agencies have proposed speed management strategies to reduce the amount of speeding on arterials. While there have been various studies done on the analysis of speeding proportions above the speed limit, few studies have considered the effect on the individual's journey. Many studies utilized speed data from detectors, which is limited in that there is no information of the route that the driver took. This study aims to explore the effects of various roadway features an individual experiences for a given journey on speeding proportions. Connected vehicle trajectory data was utilized to identify the path that a driver took, along with the vehicle related variables. The level of speeding proportion is predicted using multiple learning models. The model with the best performance, Extreme Gradient Boosting, achieved an accuracy of 0.756. The proposed model can be used to understand how the environment and vehicle's path effects the drivers' speeding behavior, as well as predict the areas with high levels of speeding proportions. The results suggested that features related to an individual driver's trip, i.e., total travel time, has a significant contribution towards speeding. Features that are related to the environment of the individual driver's trip, i.e., proportion of residential area, also had a significant effect on reducing speeding proportions. It is expected that the findings could help inform transportation agencies more on the factors related to speeding for an individual driver's trip.

Florida's population recently surpassed 22 million and is growing at the eighth-fastest rate in the country, thanks largely to a flood of Northeasterners and Midwesterners moving south for better weather and lower taxes. This influx is good for the state's economy. But it's also creating tremendous infrastructure challenges -- especially when it comes to transportation. As anyone who has sat in Miami's or Orlando's infamous bumper-to-bumper traffic can attest, the Sunshine State has some of the worst congestion in the country. Fortunately, traffic might not bedevil Floridians much longer. Artificial intelligence, machine learning, and advanced sensor technology are poised to make public transit far more convenient and attractive to potential riders currently stuck with the 10th-worst commute times in the United States.

ORLANDO, Fla. (Ivanhoe Newswire) – Our computers, devices, smart watches, video monitoring systems – we rely on connectivity to the internet and don't think twice about it. Now, scientists are developing technology for artificial intelligence that will allow it to work even in remote areas. Self-driving cars, drone helicopters, medical monitoring equipment – it's all cutting-edge technology that requires connection to the cloud. Now, researchers at the University of Central Florida are developing devices that won't rely on internet connection. "What we are trying to do is make small devices, which will mimic the neurons and synapses of the brain," researcher at the University of Central Florida, Tania Roy, PhD, explains.

ORLANDO, Fla. (Ivanhoe Newswire) – Our computers, devices, smart watches, video monitoring systems – we rely on connectivity to the internet and don't think twice about it. Now, scientists are developing technology for artificial intelligence that will allow it to work even in remote areas. Self-driving cars, drone helicopters, medical monitoring equipment – it's all cutting-edge technology that requires connection to the cloud. Now, researchers at the University of Central Florida are developing devices that won't rely on internet connection. "What we are trying to do is make small devices, which will mimic the neurons and synapses of the brain," researcher at the University of Central Florida, Tania Roy, PhD, explains.

Researchers at the University of Central Florida have unveiled a new artificial intelligence capable of seeing and recognizing shapes and identifying objects. This technology can be used in or improved robotics Autonomous Vehicle Systems. So will sight be a new sense that will soon be unlocked for artificial intelligence? It is anyway a project of her researchers from the University of Central Florida. Thanks to a device capable of reproduction Retina from one eye Human, its creation could lead to a new and more efficient artificial intelligence with new capabilities.

Researchers at the University of Central Florida have created AI technology that mimics the human eye. The technology might result in highly developed artificial intelligence that can instantaneously understand what it sees and has uses in robotics and self-driving cars. Researchers at the University of Central Florida (UCF) have built a device for artificial intelligence that replicates the retina of the eye. The research might result in cutting-edge AI that can identify what it sees right away, such as automated descriptions of photos captured with a camera or a phone. The technology could also be used in robots and self-driving vehicles.

We're delighted to welcome University of Central Florida students to our next round of lightning talks. Intelligent Tutoring Systems: Why use one model when you can use them all? Adaptation is a key element that enhances students' learning experience in Intelligent Tutoring Systems (ITS). In ITS, student responses serve as input for predictive student performance models that trigger adaptation. Our research proposes that a customized prediction model (i.e., customized to each student) performs better than one-size-fits-all models. Another tangent of our research focuses on the impact of choice in ITS.