When it comes to creative design, there's something to be said for just getting your ideas up and out there.Imaginactive.org
is a non-profit idea-sharing project, founded by Canadian inventor and engineer Charles Bombardier, in which industrial designers collaborate with Bombardier to publish early-stage concepts for futuristic vehicles. New designs are rendered and posted each week in various categories: Road & Urban, Aviation & Space, Marine, Powersports and Transportation. ThePixi
microbus, pictured here is a compact public transportation vehicle that uses modular video screens to give the illusion of transparency.
vehicle works like a radically scaled-down food truck, with a biodiesel engine that runs off the same cooking oil used in meal preparation.
Two vehicles designed to work in unison, thisurban combat unit
features a main armored vehicle that can be piloted remotely, along with a "robotic stretcher" deployed to extract wounded soldiers from the battlefield.
saucer drone autonomously patrols forests and parks, putting out small fires with a built-in acoustic extinguisher that uses sound waves to douse flames.
A kind of underwater bicycle for scuba divers, theDolfido
isn't a sealed submarine -- rather it's a biomimetic propulsion system that divers can climb into for moving around rapidly underwater.
An all-season vehicle for traversing swamps or arctic terrains, the Maskek is also an amphibious vehicle that can cross bodies of water when needed.Maskek
is the Cree word for "bogland."
electric hearse --with refrigerated coffin -- is designed to be an all-in-one funeral procession and multimedia memorial.
Inspired by the Light Cycles in the sci-fi franchise "Tron," theExocycle
features an enclosed cockpit with twin rubber tracks powered by a self-contained magnetic levitation system.
concept vehicle is loosely based on those "flying car" designs from old Popular Mechanics magazines, but with futuristic turbine technology enabling vertical takeoff and lateral flight via the four swiveling fan engines.
It's all about horse power with theStagecoach
, which aims to update a very old vehicle template with high-tech design elements including composite body panels, an alloy frame, panoramic windows, digital disk brakes, and a sensory-feedback comfort harness for the horses.
One of the busiest research areas in artificial intelligence concerns teaching machines to truly see and comprehend their surroundings. Massively complex neural network systems are working on the issue in labs all over the planet.
Researchers at the University of Cambridge this week unveiled two newly developed programs in this area that could have a significant impact on the development of driverless cars. The complementary systems can analyze visual information from a passenger’s smartphone or an onboard vehicle camera, then use that data to help a car “see” and make decisions about its immediate surroundings.
The visual data system could augment or in some instances even replace existing GPS and laser sensor systems, researchers say. The key is in the neural network technology, which is designed to create a task-specific artificial intelligence for vehicle navigation.
One of the busiest research areas in artificial intelligence, these days, concerns teaching machines to truly see and comprehend their surroundings. Massively complex neural network systems are working on the issue in labs all over the planet.
The first system, known as SegNet, analyzes live video feed from a vehicle camera and instantly sorts objects from the field of view into 12 different categories — such as road, building, vehicle, pedestrian, bike, tree or sign. The developers say this new system currently labels more than 90 percent of pixels correctly, and is more accurate than expensive laser or radar-based systems.
SegNet’s image recognition features are the result of an intensive machine learning process. Undergraduates at Cambridge trained the neural network system by manually labeling every pixel in 5000 different example images.
“It’s remarkably good at recognizing things in an image, because it’s had so much practice,” says researcher Alex Kendall, in press materials regarding the announcement.
The second system is built on similar architecture as Segnet, but is designed to ascertain a vehicle’s location and orientation. This system uses the precise colors and geometry of incoming imagery to determine where the vehicle is, relative to the objects it sees.
The localization system also works in places where GPS doesn’t — for example, inside tunnels or in dense urban areas where GPS in unreliable. Details are a little fuzzy on exactly how this would work as a navigational tool, but the developers have posted an interactive online demo on the technology, if you’re curious.