GOOGLE DRIVERLESS CAR ppt
||GOOGLE DRIVERLESS CAR
GOOGLE DRIVERLESS CAR.pptx (Size: 165.16 KB / Downloads: 540)
The Google Driverless Car is a project by Google that involves developing technology for Driverless Cars. The project is currently being led by Google engineer Sebastian Thrum's team at Stanford created the robotic vehicle Stanley which won the 2005 DARPA challenge and its US$2 million prize from the U.S department of defense. The team developing the system consisted of 15 engineers working for Google, including Chris Rumson, Mike Montebello, and Anthony Levandowski who had worked on the DARPA Grand and Urban Challenges.
The U.S state of Nevada passed a law in June 2011 concerning the operation of driverless cars in Nevada. Google had been lobbying for driverless car laws. The Nevada law went into effect on March 1, 2012, and the Nevada department of computer vehicles issued the first license for a self-driven car in May 2012. The license was issued to a Toyota Prius modified with Google's experimental driver-less technology.
The system combines information gathered from Google Street View with artificial intelligence software that combines input from video cameras inside the car, a LIDAR sensor on top of the vehicle, radar sensors on the front of the vehicle and a position sensor attached to one of the rear wheels that helps locate the car's position on the map. As of 2010, Google has tested several vehicles equipped with the system, driving 1,609 kilometres without any human intervention, in addition to 225,308 kilometres (140,000 mi) with occasional human intervention. Google expects that the increased accuracy of its automated driving system could help reduce the number of traffic-related injuries and deaths, while using energy and space on roadways more efficiently.
LIDAR Light Detection And Ranging
LIDAR (Light Detection And Ranging, also LADAR) is an optical remote sensing technology that can measure the distance to, or other properties of a target by illuminating the target with light, often using pulses from a laser. LIDAR technology has application in Geometrics archaeology, geography geology geomorphology, seismology, forestry, remote sensing and atmospheric physics, as well as in airborne laser swath mapping (ALSM), laser altimetry and LIDAR contour mapping.
In general there are two kinds of lidar detection schema: "incoherent" or direct energy detection (which is principally an amplitude measurement) and Coherent detection (which is best for doppler, or phase sensitive measurements). Coherent systems generally use Optical heterodyne detection which being more sensitive than direct detection allows them to operate a much lower power but at the expense of more complex transceiver requirements.
In both coherent and incoherent LIDAR, there are two types of pulse models: micropulse lidarsystems and high energy systems. Micropulse systems have developed as a result of the ever increasing amount of computer power available combined with advances in laser technology. They use considerably less energy in the laser, typically on the order of one microjoule, and are often "eye-safe," meaning they can be used without safety precautions. High-power systems are common in atmospheric research, where they are widely used for measuring many atmospheric parameters: the height, layering and densities of clouds, cloud particle properties (extinction coefficient, backscatter coefficient, depolarization), temperature, pressure, wind, humidity, trace gas concentration (ozone, methane, nitrous oxide, etc.).
Laser — 600–1000 nm lasers are most common for non-scientific applications. They are inexpensive, but since they can be focused and easily absorbed by the eye, the maximum power is limited by the need to make them eye-safe. Eye-safety is often a requirement for most applications. A common alternative, 1550 nm lasers, are eye-safe at much higher power levels since this wavelength is not focused by the eye, but the detector technology is less advanced and so these wavelengths are generally used at longer ranges and lower accuracies.
SCANNER AND OPTICS
How fast images can be developed is also affected by the speed at which they are scanned. There are several options to scan the elevation, including dual oscillating plane mirrors, a combination with a polygon mirror, a dual axis scanner (see Laser scanning). Optic choices affect the angular resolution and range that can be detected. A hole mirror or a beam splitter are options to collect a return signal.
Two main photodetector technologies are used in lidars: solid state photodetectors, such as silicon avalanche photodiodes, or photomultipliers. The sensitivity of the receiver is another parameter that has to be balanced in a LIDAR design.
POSITION AND NAVIGATION SYSTEM
LIDAR sensors that are mounted on mobile platforms such as airplanes or satellites require instrumentation to determine the absolute position and orientation of the sensor. Such devices generally include a Global Positioning System receiver and an Inertial Measurement Unit(IMU).