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The car will predict the traffic situation

28.01.2014

American automaker Ford Motor has announced a collaboration with specialists from the Massachusetts Institute of Technology and Stanford University in the development of unmanned vehicle control technologies. Scientists will create algorithms with the help of which cars will be able to independently navigate in space.

At the end of 2013, Ford announced an autonomous version of the Fusion Hybrid, which is capable of driving on the roads without the participation of a driver. The car is equipped with circular video cameras, laser radars and various sensors that scan the traffic situation, and the on-board computer builds a three-dimensional map of space based on this information and, using special algorithms developed at the University of Michigan, controls the movement of the car in a specific situation.

MIT employees are tasked with creating road prediction technologies that will predict the behavior of people and cars in order to avoid collisions with them. It is assumed that robotic vehicles will be able to “see” in advance the sudden appearance of a pedestrian on the roadway or the passage of a car at an intersection at a red traffic light.

Stanford engineers are also working on technologies that can expand the view of the road when it is blocked by large objects, such as a truck. On narrow roads, when driving behind a truck or bus, drivers often drive into oncoming traffic to assess the situation ahead and overtake. Sometimes such “peeping” is very dangerous, but with the help of cameras, sensors and a “smart” computer, according to the developers, such maneuvers can be secured.

Earlier, Auto.CNews talked about a virtual windshield that allows you to literally see "through" the cars ahead. The system, called the See-Through System, involves the use of special car DVRs and high-speed image volume.

The development of unmanned vehicle control systems or some of its functions at Ford is carried out as part of the Blueprint for Mobility project, launched in 2012 to predict the development of the transport system in the near future. The automaker promises to have self-driving cars on public roads by 2025, which is later than some competitors.

For example, Audi, BMW and General Motors have announced plans to begin production of self-driving cars by 2020. Tesla, a premium electric car manufacturer, expects to introduce a civilian self-driving car in two years, but specifies that driver intervention will still be required at first.

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Efficient artificial photosynthesis 18.11.2022

A team of chemists has developed an artificial photosynthesis system many times more efficient than any current solution. It can produce ethanol, methane or other fuel. Through this process, we may soon be fueling cars.

In nature, photosynthesis is carried out by several complex complexes and systems that are difficult to direct to perform other tasks. They take in water and carbon dioxide, break down molecules, and redistribute atoms to make carbohydrates. Over the production of methane instead of them, chemists have been fighting for decades. A group of scientists from the University of Chicago decided to add to the reaction something that is not found in natural photosynthesis - amino acids.

It is based on metal-organic framework structures (MOFs), a class of materials made of metal ions bound by organic molecules. Then a layer was created from it, which became a surface for chemical reactions, and it was immersed in a solution with cobalt. Finally, amino acids were added.

The result showed that both halves of the reaction can be improved in this way: the process of splitting water and the process of combining electrons and protons with carbon dioxide. In both cases, the amino acids increased the efficiency of the reaction by one order of magnitude compared to similar methods.

Artificial photosynthesis has a long way to go before it can produce enough fuel to be relevant for widespread use. However, this is an important step in the right direction. In addition, the discovery can be applied to other chemical reactions, such as pharmaceuticals or the production of nylon.

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