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Driverless car - Wikipedia, the free encyclopedia

Driverless car

From Wikipedia, the free encyclopedia

The driverless car is an emerging family of technologies, ultimately aimed at a full "taxi-like" experience for car users, but without a driver. Together with alternative propulsion, it is seen as the main technological advance in car technology by 2020. These projects are also referred to as an autopilot, autonomous vehicle, auto-drive car, or automated guided vehicle (AGV).

Driverless passenger programs include the FROG passenger vehicles from the Netherlands, the ARGO research project from Italy, and the DARPA Grand Challenge from the USA. See also smart cars.

Contents

[edit] History

The history of autonomous vehicles started in 1977 with the Tsukuba Mechanical Engineering Lab in Japan. On a dedicated, clearly marked course it achieved speeds of up to 20 miles per hour, by tracking white street markers. Special hardware was necessary, since commercial computers were much slower than they are today. The breakthrough in autonomous driving came in the 1980s through the work of Ernst Dickmanns and his team at Bundeswehr Universität München. Their vision-guided Mercedes-Benz robot van achieved 60 miles per hour on streets without traffic. The subsequent 800 million Euro EU project Prometheus on autonomous vehicles (1987-1995) brought further progress. A culmination point was achieved in 1995, when Dickmanns´ re-engineered autonomous S-Class Mercedes-Benz took a 1000 mile trip from Munich in Bavaria to Copenhagen in Denmark and back, using saccadic computer vision and transputers to react in real time. The robot achieved speeds exceeding 110 miles per hour on the German Autobahn. Unlike the early robot cars it drove in traffic, executing manoeuvres to pass other cars. It was, however, designed as a research system without emphasis on long distance reliability. On the 1000-mile trip, it achieved a mean time between human interventions of 9km, or 95% autonomous driving. Also in 1995, the CMU Navlab project achieved 98.2% autonomous driving on a 3000-mile "No hands across America" trip. The abilities of these early vehicles heavily influenced research world-wide, including three DARPA efforts known as Demo I, Demo II, Demo III. Demo III (2001) demonstrated the ability of unmanned ground vehicles to navigate miles of difficult off-road terrain, avoiding obstacles such as rocks and trees.

[edit] The challenge

Though the vision of a fully autonomous vehicle is clear, it would be such an upheaval in technology and lifestyle that few dare contemplate a 'Big Bang' new technology that would simply do it. From a scientific/engineering point of view, this looks like a case of an AI-complete problem, meaning that it is so complex that it can only be solved completely by a program that has human-level intelligence.

However, some are attempting to solve bits and pieces of the problem — either for the benefit of the limited invention created, or explicitly as stepping stones towards a fully driverless car. Though most of the projects are government-sponsored, there is already a significant involvement from the private sector.

The challenges involved in realising this vision can broadly be divided into the technical and the social. The technical problems are broadly in the design of the sensors and control system required to make such a car work. The social challenge is in getting people to trust the car, getting legislators to permit the car onto the public roads, and untangling the legal issues of liability for any mishaps with no person in charge.

[edit] The elements of any solution

The dream of a driverless car seems fantastic, and therefore remote. However, any solution can be broken down to four sub-systems:

  • sensors: the car knows where an obstacle is and what is around it;
  • navigation: how to get to the target location from the present location;
  • motion planning: getting through the next few meters, steering, and avoiding obstacles while also abiding by rules of the road and avoiding harm to the vehicle and others;
  • control of the vehicle itself: actuating the system's decisions.

In examining every proposed solution, one should look at the following questions:

  • Is this truly a complete system? Does it drive itself door-to-door?
  • To what degree is the proposed solution a step towards the complete vision, or is it just a trick?
  • Is the car 'autonomous', or would it need changes to the infrastructure?
  • How feasible (technically, economically, and politically) would it be to deploy the entire solution?
  • Can the system allow for and include existing vehicles driven by humans, or does it need an open field?
  • How would it cope with unexpected circumstances?

[edit] Recent projects

The work done so far varies significantly in its ambition and its demands in terms of modification of the infrastructure. Broadly, there are three approaches. The first group to be discussed here is the fully autonomous vehicles (DARPA, ARGO) —which are the most ambitious, but none are deployed. The second approach uses various enhancements to the infrastructure (either an entire area, or specific lanes) to create a self-driving closed system. Such systems already function in many airports, on railroads, and in some European towns. The third approach is to incrementally remove requirements from the human driver, by various "assistance" systems. This approach is slowly trickling into standard cars (e.g. improvements to cruise control).

An important concept that cuts across several of the efforts is vehicle platoons. In order to better utilize road-space, vehicles are assembled into ad-hoc train-like "platoons", where the driver (either human or automatic) of the first vehicle makes all decisions for the entire platoon. All other vehicles simply follow the lead of the first vehicle.

[edit] Fully autonomous

These technologies are the most ambitious: They allow a car to drive itself following a pre-set target, until it gets there all on its own. The downside of these seeming marvels is that they are very limited in terms of the environment in which they can operate: either a desert (free of any human or human-made obstacle), or a clearly-marked, well-painted (in this case Italian) Autostrada (motorway). Therefore, the real benefits of door-to-door are as remote as ever.

[edit] Free-ranging military vehicles

There are three clusters of activity relating to free-ranging off-road cars. All these projects are military-oriented.

  • US military DARPA Grand Challenge
Main article: DARPA Grand Challenge
The US Department of Defence announced on the July 30, 2002 a "Grand Challenge", for US-based teams to produce a vehicle that can autonomously navigate and reach a target in the desert of the south western USA.
In March 2004, the first competition was held, for a prize-money of $1 million. Not one of the 25 entrants completed the course. However, in October 2005 five different teams completed the 135-mile (217 km) course, and the Stanford University team won the $2 million prize.
Following the 2004 failure, in which several cars were distracted by the "race" to the detriment of basic technology that would allow for actual completion, the 2005 teams were focused on the challenge at hand, and did not seek to develop generic solutions, or a particularly speedy car.
The sensors were based on visual, Radar, and laser technologies. The navigational course was pre-programmed, and the motion planning and obstacle avoidance were handled by on-board computers - many of the entrants used eight or more computers to manage the car. Though the vehicles were equipped to avoid collision, they did not have any notion of rules-of-the road - but simply regarded each other as static obstacles.
For a more complete description the DARPA Grand Challenge see the official web site and the press coverage.[1][2][3] The US military has several projects applying autonomous vehicle technologies for military purposes.[4][5]
Not to be outdone by the USA, the German Dept. of Defence announced an event similar to the DARPA Grand Challenge, held in May 2006. Unlike the DARPA event, it is not in the spirit of a challenge, but of a demonstration or trade show. The event included various military autonomous and remotely-operated robots, for various military uses. ELROB is less cutting-edge than the Grand Challenge, but more practical, in that some of the systems on display could be ordered and implemented immediately.
In August 2007 a civilian version of the event will be held in Switzerland.
The most impressive effort in the fully driverless category was The Smart team from Switzerland, presenting "a Vehicle for Autonomous Navigation and Mapping in Outdoor Environments". For pictures of their ELROB demo, see this.
As a followup from its success with Unmanned Combat Air Vehicles, and following the construction of the Israeli West Bank barrier there has been significant interest in developing a fully automated border-patrol vehicle. Two projects, by Elbit Systems and Israel Aircraft Industries are both based on the locally-produced Armored "Tomcar" and have the specific purpose of patrolling barrier fences against intrusions.
The "SciAutonics II" team in the 2004 DARPA Challenge used Elbit's version of the Tomcar.

[edit] ARGO

ARGO is an Italian project (1996-2001) to allow a car to follow the normal (painted) lane marks in an unmodified highway. The culmination of the project was a journey of 2,000 km over six days on the motorways of northern Italy dubbed MilleMiglia in Automatico, with an average speed of 90 km/h. 94% of the time the car was in fully automatic mode, with the longest automatic stretch being 54 km.

The ARGO vehicle, a modified Lancia Thema, had only two black-and-white low-cost video cameras on board, and used stereoscopic vision algorithms to understand its environment. This is in stark contrast to the "laser, radar - whatever you need" approach taken by other efforts in the field.

The project was run by the universities of Parma and Pavia, coordinated by Alberto Broggi, and financed by the Italian government.

[edit] Pre-built infrastructure

The following projects were conceived as practical attempts to use available technology in an incremental manner to solve specific problems, like transport within a defined campus area, or driving along a stretch of motorway. The technologies are proven, and the main barrier to widespread implementation is the cost of deploying the infrastructure.

[edit] Dual mode transit - monorail

There is a family of projects, all currently still at the experimental stage, that would combine the flexibility of a private automobile with the benefits of a monorail system. The idea is that privately-owned cars would be built with the ability to dock themselves onto a public monorail system, where they become part of a centrally managed, fully computerized transport system—more akin to a driverless train system (as already found in airports) than to a driverless car. This idea is also known as Dual mode transit. (See also Personal rapid transit for another interesting concept along those lines, for purely public transport.)

Groups working on this concept are:

[edit] Automated highway systems

Automated highway systems (AHS) are an effort to construct special lanes on existing highways that would be equipped with magnets or other infrastructure to allow vehicles to stay in the centre of the lane, while communicating with other vehicles (and with a central system) to avoid collision and manage traffic. Like the dual-mode monorail, the idea is that cars remain private and independent, and just use the AHS system as a quick way to move along designated routes. AHS allows specially equipped cars to join the system using special 'acceleration lanes' and to leave through 'deceleration lanes'. When leaving the system each car verifies that its driver is ready to take control of the vehicle, and if that is not the case, the system parks the car safely in a predesignated area.

Some implementations use radar to avoid collisions and coordinate speed.

The most impressive system of this type built so far is the AHS demo of 1997 near San Diego, sponsored by the US government, in coordination with the State of California and Carnegie Mellon University. The test site is a 12-kilometre, high-occupancy-vehicle (HOV) segment of Interstate 15, 16 kilometres north of downtown San Diego. The event generated much press coverage. The technology is the subject of a book.

This concerted effort by the US government seems to have been pretty much abandoned because of social and political forces, above all else the desire to create a less futuristic and more marketable solution.

[edit] Free-ranging on grid

The FROG (free-ranging on grid) company from the Netherlands uses a combination of a low-autonomy vehicle with a supervisory central system. The company's purpose-built electric vehicles locate themselves using odometry, recalibrating themselves occasionally using a "maze" of magnets embedded in the environment, and dGPS. The cars avoid collisions using infra-red and laser sensors.

The supervision of the vehicles, their navigation and adherence the any rules of the road are done by a centralised computer system. Such a system is well suited to managing the traffic in a limited space (as is the reliance on magnets) but unsuited for running tens or hundreds of thousands of cars in a full city.

The FROG system is deployed for industrial purposes in factory sites, and as a pilot public transport system in several cities, not least Rotterdam, where the system experienced an accident that proved to be caused by a Human error(!).

FROG is one of few fully commercial companies in this field.

[edit] Driver-assistance

Though these products and projects do not aim explicitly to create a fully autonomous car, they are seen as incremental stepping-stones in that direction. Many of the technologies detailed below will probably serve as components of any future driverless car — meanwhile they are being marketed as gadgets that assist human drivers in one way or another.

Driver-assistance mechanisms are of several distinct types, sensorial-informative, actuation-corrective, and systemic.

[edit] Sensorial-informative

These systems warn or inform the driver about events that may have past unnoticed, such as

[edit] Actuation-corrective

These systems modify the driver's instructions so as to execute them in a more effective way, for example the most widely deployed system of this type is ABS; conversely power steering is not a control mechanism, but just a convenience - it is not involved in decision making.

A review of the overall "feel" to actuation-correction in a Jaguar XK convertible.

Driver-assistance preview from Popular Science.

[edit] Systemic

A good collection of these technologies is available at Automotive component manufacturers' sites, such as Siemens VDO Automotive or http://delphi.com/manufacturers/auto/safesecure/warning/ Delphi (Ford)].

Interesting stuff from GM-Opel.

A good summary of how far things have progressed without any true automated driving is provided by The Economist

See also Safety Features.

[edit] Existing and missing technologies

In order to drive a car, a system would need to:

  1. Understand its immediate environment (Sensors)
  2. Know where it is and where it wants to go (Navigation)
  3. Find its way in the traffic (Motion planning)
  4. Operate the mechanics of the vehicle (Actuation)

Arguably, 2 1/2 of these problems are already solved: Navigation and Actuation completely, and Sensors partially, but improving fast. The main unsolved part is the motion planning.

[edit] Sensors

Sensors employed in driverless cars vary from the minimalist ARGO project's monochrome stereoscopy to mobileye's inter-modal (video, infra-red, laser, radar) approach. The minimalist approach imitates the human situation most closely, while the multi-modal approach is "greedy" in the sense that it seeks to obtain as much information as is possible by current technology, even at the occasional cost of one car's detection system interfering with another's.

Mobileye is a well respected company who makes detection systems for cars, which are currently only used for driver assistance, but are eminently suitable for a full-fledged driverless car. This video demonstrates the capabilities of the system: all pedestrians, cars, motorbikes etc. are clearly displayed in video, with a frame around them and the distance between "our" car and the object observed. The system also detects the objects' motion (direction and speed) and can so calculate relative speeds, and predict collisions.

[edit] Navigation

The ability to plot a route from where the vehicle is to where the user wants to be has been available for several years. These systems, based on the US military's Global Positioning System are now available as standard car fittings, and use satellite transmissions to ascertain the current location, and an on-board street database to derive a route to the target. The more sophisticated systems also receive radio updates on road blockages, and adapt accordingly.

See the main article on Automotive navigation systems.

[edit] Motion Planning

http://www.youtube.com/watch?v=R8EWHndSn34

This is current research problem. See the main article on the subject Motion planning.

[edit] Control of vehicle

As automotive technology matures, more and more functions of the underlying engine, gearbox etc. are no longer directly controlled by the driver by mechanical means, but rather via a computer, which receives instructions from the driver as inputs and delivers the desired effect by means of electronic throttle control, and other drive-by-wire elements. Therefore, the technology for a computer to control all aspects of a vehicle is well understood.

[edit] Work done in simulation

While developing control systems for real cars is very costly in terms of both time and money, much work can be done in simulations of various complexity. Systems developed using simpler simulators can gradually be transferred to more complex simulators, and in the end to real vehicles. Some approaches that rely on learning requires starting in a simulation to be viable at all, for example evolutionary robotics approaches - see this example.

[edit] Social issues

  • Getting people to trust the car
  • Getting legislators to permit the car onto the public roads
  • Untangling the legal issues of liability for any mishaps with no person in charge.

Despair of progress in the foreseeable future: The UK government seems to see little progress until 2056. See Silicon Networks article and CNET.co.uk News.

[edit] Motivations

As nearly all car crashes (particularly fatal ones) are caused by human driver error, driverless cars would effectively eliminate nearly all hazards associated with driving as well as driver fatalities and injuries (travelling by car is currently one of the most deadly forms of transportation, with over a million deaths annually worldwide). This would be especially helpful to people that drive to bars and inebriate themselves; the ability for a car to shuttle them home would practically eliminate drunk driving crashes.

Having the equivalent of a personal chauffeur would be a great convenience:

  • Time spent commuting could be used for work, leisure, or rest.
  • Parking in difficult areas becomes less of a concern as the car can park itself away from a busy airport, for example, and come back when called on a cell-phone.
  • Taxiing children to school, activities and friends would become solely a matter of granting permission for the car to handle the child's request.
  • Allow the visually (and otherwise) impaired to travel independently.

A driverless car would also be a boon to economic efficiency, as cars can be made lighter and more space efficient with the absence of safety technologies rendered redundant with computerized driving. Also the technology would make transportation more efficient and reliable: there may be autonomous or remote-controlled delivery trucks dispatched around the clock to pick up and deliver goods. Moreover, driverless cars would reduce traffic congestion by allowing cars to travel faster and closer together.

[edit] Social Costs

The social costs of this innovation are similar to those of other past technologies: Unemployment, expense and the elimination of the "old way of doing things". See also Luddites.

As with any new labour-saving technology, this would lead to mass layoffs in the driving, cargo, and distribution industries. Taxis would also be automated, effectively eliminating a source of income for the less skilled. A similar if smaller impact is expected in the roadside-catering and other ancillary businesses. However, history shows that any such economic impact on jobs leads to economic benefits elsewhere that create employment, though often not for the exact same people displaced by the new technology.

In order to recoup the development costs, and in order to maximise the profit opportunity that any exciting novelty presents, driverless cars will initially be significantly more expensive than manual cars.

Driving as a personal hobby and sport, and indeed the entire car-oriented sub-culture would be effectively eliminated. However, for those willing to pay for the extra feature, there could be an option to switch between manual and automated driving to make up for that.

[edit] Discussion & Future

Some systems control everything centrally, and in some the vehicle is truly autonomous in the sense that it "thinks" about its own situation in the first person - such a system can integrate with Humans that think in first person.

Conversely. a system that centrally manages everything, though easier to build from a conceptual and engineering point of view, would face horrendous economic barriers because of the costs of converting an entire city or country to the new system at once. In order to be compatible with humans the "first person" point of view is key. This is for three reasons:

  1. a distributed scheme in which each component (car) takes care of itself reduces complexity
  2. a system that has the concept of first-person operation can understand what a human driver is up to.
  3. for the human driver to understand what the driverless car is doing, it needs to operate and "think" in as similar a way to a human as practical (and safe).

See also Coping, see Heidegger.

[edit] Key players

[edit] International

The European Union has a multi-billion Euro programme to support Research and Development by ad-hoc consortia from the various member countries, called Framework Programmes for Research and Technological Development. Several of these projects pertain to the subject of driverless cars, e.g.:

  • The CyberCars project gathered much useful data about the actual and possible deployments of Driverless Cars for public transport. The main system discussed is based on FROG.

Many of the EU-sponsored projects are coordinated by a group called Ertico.

There are several national associations around the world that are active in research in the field of intelligent transportation systems, a term that seems to encompass anything which applies technology to the improvement of transport. In recent years there has been a trend in this field to move efforts away from the more visionary projects, such as driverless cars, to the more short-term, such as public transport and traffic management. Many of these organisations are government sponsored, and they all cooperate at some level or another. Some of the countries involved are: the USA, Australia, Korea (south), Taiwan, India--(specifically Intelligent vehicles), and Japan, specifically a cruise assist effort (see below). A more complete list of its organisations can be found here.

[edit] Governments

[edit] Universities and professional bodies

[edit] Commercial interests

[edit] Voluntary and hobbyist groups

[edit] In film

  • The 1990 film Total Recall (film), starring Arnold Schwarzenegger, features taxis apparently controlled by artificial intelligence; it is not clear, however, whether these are truly autonomous vehicles or simply conventional vehicles driven by androids.
  • Another Arnold Schwarzenegger movie, The 6th Day (2000), features a driverless car in which Michael Rapaport sets the destination and vehicle drives itself while Rapaport and Schwarzenegger converse.
  • The 2002 film Minority Report, set in Washington, D.C. in 2054, features an extended chase sequence involving driverless personal cars. The vehicle of protagonist John Anderton is transporting him when its systems are overridden by police in an attempt to bring him into custody; Anderton is unable to control the vehicle, and has to break out of it to evade the authorities.
  • The 2004 film I, Robot (movie) also features advanced driverless cars.

[edit] See also

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