|
The driverless car is an emerging family of technologies, ultimately aimed at a full "taxi-like" experience for car users. This, together with alternative propulsion is seen as the main technological advance expected leading into 2020. These projects are also referred to as an autopilot, autonomous vehicle, autodrive car, or an automated guided vehicle (AGV). Driverless passenger programs include the FROG passenger vehicles from Holland, the ARGO research project from Italy, and the DARPA Grand Challenge from the USA. See also smart cars. History The history of autonomous vehicles starts 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 maneuvers 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. 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 it "can never be done". 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. 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: In examining every proposed solution, one should look at the following questions: 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, underground commuter railroads, and 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. 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. Free-ranging military vehicles There are 3 clusters of activity relating to free-ranging off-road cars. All these projects are military-oriented. The US Department of Defense 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 southwestern 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. By and large, the sensors used were stabilised in order to avoid the vibration of desert driving. The sensors were based on Visual, Radar, and laser techniologies. The navigational course was pre-programmed, and the motion planning and obstacle avoidance were handled by on-board computers - many of the entrants used 8 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 moving obstacles. For a more complete description the DARPA Grand Challenge see the official web site and the press coverage.*** The US military has several projects applying autonomous vehicle technologies for military purposes.** Not to be outdone by the USA, the German Dept. of Defense announced an event similar to the DARPA Grand Challenge, held in May 2006. The event included both desert-like scenarios like in the USA, and also urban scenarios in which the vehicle will explore streets and buildings. In August 2007 a civilian version of the event will be held in Switzerland. 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-partol 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 partolling barrier fences against intrusions. The "SciAutonics II" team in the 2004 DARPA Challenge used Elbit's version of the Tomcar. 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 voyage of 2,000 km during 6 days in the motorways of northern Italy, 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 long. The ARGO vehicle, a modified Lancia Thema, had only two Black-and-White 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. 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 infrastrcuture. 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: 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'. While 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 comprised of a 12-kilometer, high-occupancy-vehicle (HOV) segment of Interstate 15 located 16 kilometers 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. 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 infrared 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 manageing the traffic in a limited space (as is the reliance on magnets) but unsuited for running 10s or 100s 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. 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, actualtion-corrective, and systemic. Sensorial-informative These systems warn or inform the driver about events that may have past unnoticed, such as 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 makeing. A review of the overall "feel" to actuation-correction in a Jaguar XK convertible. Driver-assistance preview from Popular Science. Systemic A good collection of these technologies is available at Automotive component manufacturer's sites, such as SiemensVDO or 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. Existing and missing technologies In order to drive a car, a system would need to: Sensors Sensors employed in diverless cars vary from the minimalist ARGO project's monochrome stereoscopy to mobileye's intermodal (video, infrared, laser, radar) appoach. The minimalist approach immitates the human situation most closely, while the multimodal 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 demonstartes the capabilities of the system: all pedestrains, cars, motrbikes 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. 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 onboard 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. Motion Planning http://www.youtube.com/watch?v=R8EWHndSn34 This is current research problem. See the main article on the subject Motion planning. Control of vehicle As automative 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. 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. Social issues 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. Motivations As nearly all car accidents (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 (driving 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 accidents. Having the equivalent of a personal chauffeur would be a great convenience: 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. 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. 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 horrendeous 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" POV is key. This is for 3 reasons: See also Coping, see Heidegger. Key players 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.: 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 assit effort (see below). A more complete list of its organisations can be found here. Governments Universities and professional bodies Commercial interests Voluntary and hobbyist groups In film See also | |||||||
|
| ||||||||
 |
|
| |