According to the buzz, you could be sitting in your car, sipping coffee and reading Ask Fuzzy while a robot pilots you smoothly and efficiently around the city.
So why aren't we seeing any?
The best way to understand this is through the lens of the Gartner Hype Cycle which describes how a new technology is received.
Right now, driverless cars are heading towards The Peak of Inflated Expectations. The website TechRadar gushes, ''It's only a matter of time before fully driverless vehicles appear on public streets.''
At some point, however, hype evaporates into the Trough of Disillusionment. Eventually though, the hype catches up with reality and technology matures into the Plateau of Productivity.
Note that ''driverless'' isn't an either-or option because we already have technology such as cruise control, ABS and so on. On a scale from zero to five, a fully self-driving vehicle is level 4 or 5. Level 3 is 'eyes off', where the driver only needs occasional or emergency intervention.
There are over two dozen companies in this field, so it's certainly getting a lot of attention. Facing them is an array of formidable technical challenges. Not least is the volume of data from a range of sensors.
These includes cameras, ultrasonic, LIDAR (laser) and RADAR Sensors. Level 4/5 vehicles will need 8 or more cameras with a mix of 10 short-, medium- and long-range radar devices. Data from ''the cloud'' (internet) can tell the car about location, other connected vehicles and so on.
Processing this requires considerable computing power, measured in Teraflops. This is available in high-end computers but of course that also draws current from the vehicle.
The more complicated problem is the logic of how to navigate a busy, messy traffic environment.
It's tricky because the inputs are buried within a mass of confounding information. The partially obscured object behind the truck could be a cyclist, a child or someone pushing a pram. A human intuitively knows that the pram usually moves slowly. The cyclist is faster while the child can be erratic.
The poster on the truck depicts a woman pushing a pram. The truck is moving from a dark shadow into full sunlight. Ahead is a stop sign, hidden by a tree.
If this is complicated for a human, it's even harder for a computer. Still, considerable progress has been made and companies are doing extensive testing in a range of environments.
This all adds up to a very expensive solution, placing it well out of reach for most people. However the history of technology shows that once a critical market mass is reached, costs can fall rapidly.
That leaves a critical part of the driverless car equation for next week: people.
The Fuzzy Logic Science Show is 11am Sundays on 2xx 98.3FM.
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