Autonomous vehicle navigation – current status, issues, and prospects
Scope of autonomous vehicle navigation
There are three ways a car may be navigated: totally in autonomous mode – without any driver intervention, semi-autonomously with some driver intervention, and completely driver controlled. A vehicle may be guided autonomously by the Global Positioning System (GPS), cameras, laser detectors, radar, wires in or lines on the road, or by transponders strategically located along a route. While road sensors or wires provide a more accurate navigation there are practical limits to installing them, given the number of roads involved. Navigational software includes pre-programmed routes, driving rules (such as stopping for red lights and lane changes), and user interfaces. Mechanical control is done by servo motors, relays, sensors, automated steering and braking, throttle management, and so forth.
With the improvement of automotive systems aided by computers and artificial intelligence, it should not be surprising to see the emergence of vehicles that drive themselves. Various names have been given to autonomously driven vehicles: uninhabited autonomous vehicle (UAV), autopilot vehicle, driverless car, auto-drive car, or automated/autonomously guided vehicle (AGV). An autonomously-driven vehicle is a true automobile, i.e., mobile on its own – self-propelled and navigated. A semi-autonomous vehicle can use any navigational method, but the driver intervenes to determine the routing and otherwise control the car. A person in a completely driver-controlled vehicle most often uses a map interfacing with GPS or a hand held device, such as a personal digital assistant (PDA) that displays locations via GPS. Routes ultimately are determined by the driver and may be charted by means such as on-board maps, web interface, or PDAs. Assisted navigation already is a reality. Smart cars have the capability of detecting empty parking spaces, thus obviating having to drive a long time searching. Already, in many cities there are timed traffic lights, where by maintaining an optimal speed, a driver can “make” every light without stopping. With forward-looking traffic control (automatic positioning), a driver is warned via a human-machine interface (HMI) of accidents, congestion, and construction, and is given the choice of different routes. A final step is intelligent and automated street or highway systems, where cars are integrated into an overall system and coordinated to result in a smooth and optimal traffic flow. High Occupancy Vehicle (HOV) lanes are precursors to this.
Feasibility of autonomously-driven vehicles
Pilotless vehicles are not new. Hydrogen balloons were guided by spark transmitters towards the end of the 19th century, and the British flew a monoplane called the Larynx  in the 1920s. During World War Two, radio controlled planes came more into vogue. Today we see remotely operated tractors tilling and seeding fields using the GPS, or even a cell phone.
Tractor driven by student in India using a cell phone 
We have remotely monitored and controlled systems such as OnStar for Chevrolet cars and Qualcomm for semi-trucks. Mostly everyone has heard of the Predator drones used by the U.S. military as “state-of-the-art”, although there are numerous problems of errors in targeting . Especially since 1977, when Tsukuba Mechanical engineering lab built the first self-driving vehicle, development and sophistication has continued for autonomous ground vehicles. Another example of autonomous vehicle development was Carsense a project sponsored from 2000-20002 by the European Commission consisting of twelve European car manufacturing companies to illustrate the efficacy of autonomous vehicles. Long and short radar, cameras, and various sensors were used to pilot the vehicle.
The Defense Advanced Projects Research Agency (DARPA) of the U.S. Department of Defense (DoD), sponsored three DARPA challenges to build autonomously driven vehicles in March 2004, October 2005, and November 2007. The 2004 and 2005 ones involved vehicles running overland in off-road desert environments up to 240 km and up to 80 km per hour. In the first, only five vehicles traveled more than a couple of kilometers. Three vehicles completed more than 212 km in the second. The third challenge was in an urban environment and six vehicles traveled 60 miles.
Stanford Autonomous Vehicle Project 
From 26 July to 28 October 2010 four vehicles drove themselves 15,000 km from Parma Italy to Shanghai, China . In the same year Google had seven driven for a total of 140,000 miles between Los Angeles and San Francisco with humans intervening only occasionally . Routes were reprogrammed, along with essential data like speed limits. Google has gone so far as to ask Nevada to allow autonomous vehicles and texting in them . As late as the middle of June 2011 Nevada approved the use of autonomous vehicles on its roads . Volkswagen is testing vehicles in Europe, as the following video displays so graphically: http://techie-buzz.com/tech-news/google-approval-self-driving-cars-nevada.html.
Stanford University, one of the winners of the U.S. Defense Research Projects Agency (DARPA) urban challenge in 2007, is carrying forth research on LIght Detection And Ranging, or Laser Imaging Detection and Ranging (LIDER) to create maps of a car’s environment and use that to navigate. Maps with locations of people and objects are continuously generated from this with centimeter accuracy and the data are used to determine an actual path.