2012 Formula One season

2012 Formula One season is the 63rd FIA Formula One season. The season started in Australia on 18 March and will end in Brazil on 25 November. It is being contested over twenty races – the most races in a season in the sport's history – and will see the return of the United States Grand Prix, which will be held at the Circuit of the Americas, a purpose-built circuit in Austin, Texas. After being cancelled in 2011 due to civil protests, the Bahrain Grand Prix returned to the calendar.

In addition to having the greatest number of races in a championship year, the 2012 season broke several records. Six current and former World Drivers' Champions — Sebastian Vettel, Jenson Button, Lewis Hamilton, Kimi Räikkönen, Fernando Alonso and Michael Schumacher — started the season, breaking the record of five established in 1970.The 2012 season was also the first time that the first six championship races of a season were won by six different drivers.[N 1]
Contents
 
Season report

Pre-season testing — Jerez de la Frontera and Barcelona

The 2012 season was preceded by three test sessions; one at Jerez de la Frontera and two in Barcelona. These sessions gave the teams and drivers the opportunity to familiarise themselves with their cars, though the teams downplayed the accuracy of testing times as being representative of the running order for the season.[9] At the second test in Barcelona, Lotus F1 discovered a critical fault in the build of their chassis that forced them to miss four days of running, while both HRT and Marussia were unable to complete any mileage with their 2012 cars after both the HRT F112 and Marussia MR01 failed their crash tests, though both teams were able to complete shakedowns of their cars.

"We are all terrified that somebody will unlock the secret and win everything. Unless, of course, that's us!"
2009 World Drivers' Champion Jenson Button on the competitive nature of the 2012 season.

Round 1 — Australia

The season began in Australia. Jenson Button took an early lead from pole-sitter Lewis Hamilton and the Red Bull cars while the rest of the field was bottle-necked by contact in the first corner. Button remained unchallenged throughout, even after a mid-race safety car to retrieve the stricken Caterham of Vitaly Petrov. Button went on to take his third victory at the Melbourne circuit, ahead of Sebastian Vettel, who profited from the safety car to pass Hamilton. McLaren team principal Martin Whitmarsh later admitted that Button was "more than marginal" on fuel after the team made a mistake in calculating their fuel loads for the race, forcing Button to use a "severe fuel-saving mode" from the eighth lap of the race. Hamilton came under threat from Mark Webber in the late stages of the race, but held on to secure third place. Webber finished fourth – his best result in his home Grand Prix – while Fernando Alonso finished fifth, having endured pressure from Pastor Maldonado for the last half of the race. Maldonado's race ended when he crossed onto the astroturf on the final lap and spun into the wall. Kimi Räikkönen finished seventh after a poor qualifying session saw him start the race seventeenth, taking advantage of a chaotic final lap to make up two places, while Felipe Massa and Bruno Senna both retired after a bizarre collision that saw their cars tangled up in one another. HRT failed to qualify for the race for the second consecutive season after drivers Pedro de la Rosa and Narain Karthikeyan failed to set a lap time within 107% of the fastest qualifying time.
Fernando Alonso described driving the Ferrari F2012 as "like walking on a tightrope".

Round 2 — Malaysia

McLaren locked out the front row of the grid for the second race in succession, with Lewis Hamilton once again on pole. Both HRT cars qualified for the race, but filled out the final row of the grid almost two seconds behind Marussia's Charles Pic in twenty-second position. In the race, Hamilton made a better start than Jenson Button, but his lead was short-lived; heavy rain interrupted the race, forcing the suspension of the Grand Prix. When the race re-started an hour later, Button was involved in contact with Narain Karthikeyan that forced him to make an unscheduled stop for a new front wing, while Hamilton overshot his pit box and was held in the lane while other cars passed. Fernando Alonso inherited the lead, with Sauber's Sergio Pérez a surprise second, having made an early stop for extreme wet weather tyres and then taking advantage of a rush to the pit lane to position himself in third at the restart. As the race wore on, Pérez began to quickly catch Alonso on a drying track. Daniel Ricciardo was the first driver to pit for dry-weather tyres on lap 38, triggering another round of stops. Sauber and Pérez initially looked as if they had left their stop too late when Pérez emerged from the pits five seconds behind Alonso, but he began catching the two-time World Champion at the same rate as he had before. Pérez closed to within half a second with seven laps to go, but ran wide at turn 14 and lost five seconds, later admitting that it was his mistake. He was unable to close the gap, and Alonso went on to win the race by two seconds, the win giving him a five-point lead in the championship. Pérez was second, taking his first podium and Sauber's best ever result as an independent team. Hamilton finished third ahead of Mark Webber and Kimi Räikkönen, while Button had to settle for fourteenth. Bruno Senna finished in sixth, scoring more points in a single race than his team scored in 2011. Sebastian Vettel finished outside the points after making contact with Karthikeyan and developing a puncture.

Round 3 — China
  

The championship resumed three weeks later in China, with the lead-in period to the race marked by Lotus F1 protesting the legality of Mercedes' rear wing design. The FIA rejected the protest, and with Mercedes allowed to continue racing with their car unchanged, Nico Rosberg took his — and the team's — first pole position since their return to Formula One in 2010,[29] while a penalty to Lewis Hamilton for a gearbox change promoted Michael Schumacher to second on the grid.Schumacher would ultimtely retire from the race after the first round of stops when it was discovered that one of his wheels had not been attached properly. Rosberg took an early lead in the race, and while his attempt to complete the race with only two pit stops came under threat from second-placed Jenson Button, a mistake by Button's pit crew during his final stop handed Rosberg a nineteen-second advantage over Kimi Räikkönen. Räikkönen was attempting a similar two-stop strategy, but his tyres wore out seven laps from the end of the race, and he lost eleven positions in a single lap. This forced Rosberg to drive conservatively to preserve his tyres while Button recovered from his disastrous pit stop to pass Sebastian Vettel for second. Button was held up by the incumbent World Champion long enough for Rosberg to preserve his tyres, and he became the 103rd person to win a Grand Prix. The result was also Mercedes' first win as a constructor since Juan Manuel Fangio won the 1955 Italian Grand Prix. Button was second, with Hamilton scoring his third consecutive third place, giving him a two-point championship lead over Button; Fernando Alonso, who had been leading the championship before the race, finished ninth. After two retirements in the opening rounds of the championship, Romain Grosjean scored his first points in Formula One by finishing sixth.
The Bahrain Grand Prix was overshadowed by civilian protests against the ruling Al Khalifa family.

Round 4 — Bahrain

In the face of ongoing media speculation and public pressure to cancel the race, the FIA released a statement at the Chinese Grand Prix confirming that the Bahrain Grand Prix would go ahead as planned. The week preceding the Grand Prix saw a renewed wave of protests against the government's attempts use the race to "tell the outside world that the whole thing is back to normal", while human rights organisations including Amnesty International criticised the decision to hold the race amid the violent crackdowns. Three days before the race, a group of Force India mechanics travelling in an unmarked hire car were involved in a petrol bombing incident at an impromptu roadblock and were briefly exposed to tear gas fired by security forces.There were no injuries or damage, but two of the mechanics involved chose to leave the country. The team later announced their intentions to race despite the incident.

Sebastian Vettel qualified on pole, his first since the 2011 Brazilian Grand Prix. Heikki Kovalainen qualified sixteenth, the second time Caterham (and its predecessor, Team Lotus) advanced beyond the first qualifying period in dry conditions. Vettel went on to win the race — becoming the fourth winner in as many races — after spending much of the race defending against Kimi Räikkönen. Having started eleventh, Räikkönen used an extra set of soft tyres to move up through the field. His team-mate, Romain Grosjean, finished third. Grosjean had initially shown the pace to challenge Vettel's lead, but unlike Räikkönen, he did not have an extra set of fresh tyres, and lost touch with the reigning World Champion after the first set of stops. Lewis Hamilton finished eighth, once again hampered by slow pit stops. He was later involved in an altercation with Nico Rosberg that saw Rosberg referred to the stewards for forcing Hamilton beyond the boundary of the circuit while defending his position, but he escaped without penalty. Hamilton went on to finish eighth, while team-mate Jenson Button was forced to retire two laps from the end of the race after reporting an unusual vibration from the differential. Daniel Ricciardo was involved in early contact that saw the Australian driver slide down the order from sixth at the start to fifteenth by the end of the race, having spent most of the Grand Prix caught behind Vitaly Petrov. Vettel's win gave him a four-point lead in the championship over Hamilton, while Mark Webber's fourth consecutive fourth place secured third overall. Red Bull Racing took the lead from McLaren in the World Constructors' Championship, while Lotus' double podium moved them into third overall.
Sebastian Vettel won his first race of the 2012 season in Bahrain.

The decision to hold the race despite the ongoing protests made it one of the most controversial Grands Prix in the sport's sixty-year history.

Mid-season test — Mugello

Starting on 1 May, the teams conducted a three-day test at the Mugello Circuit in Italy ahead of the Spanish Grand Prix. The test gave teams the opportunity to assess major aerodynamic upgrades before racing them. HRT elected not to take part in the test, instead choosing to concentrate on establishing themselves at their new headquarters in Caja Mágica, Madrid. Both Lotus' trackside operations director Alan Permane and Red Bull Racing driver Mark Webber questioned the value of testing at the Mugello circuit as the characteristics of the circuit were unlike any of the circuits the championship was due to visit after the test,while Caterham driver Vitaly Petrov was critical of the choice of Mugello as a testing venue as he felt it was not safe enough for Formula One.Petrov's comments came shortly after Fernando Alonso crashed on the final morning of the test.[58] Red Bull Racing and Lotus team principals Christian Horner and Éric Boullier were also critical of the test as they felt that the costs of conducting in-season testing outweighed any benefits, with Horner stating his opposition to continuing mid-season testing in the future.

"We drive like on raw eggs and I don't want to stress the tires at all. Otherwise you just overdo it and you go nowhere."
Michael Schumacher's criticism of tyre supplier Pirelli's 2012 tyre compounds.

Round 5 — Spain

Following criticism over the sensitivity of their tyre compounds, tyre supplier Pirelli announced changes to their tyre allocation for the Spanish Grand Prix, making pit strategy the focal point of the Grand Prix. Lewis Hamilton took his third pole of the season, edging out Williams driver Pastor Maldonado by half a second, while Maldonado's team-mate Bruno Senna was eliminated early when he spun.Hamilton was later excluded from the qualifying results after his car did not have enough fuel to return to the pits for scrutineering, promoting Maldonado to pole position and moving Hamilton to the back of the grid. Fernando Alonso took the lead of the race at the first corner, but Maldonado reclaimed it during the second round of pit stops when his team forced Ferrari to pit early while Alonso was held up by the Marussia of Charles Pic. Maldonado secured a seven-second lead over Alonso, but a mistake from his pit crew at the third stop cost him time and left him vulnerable to the Ferrari driver in the final stint of the race. Meanwhile, third-placed Kimi Räikkönen moved to an ambitious strategy that would see him attempt to force Maldonado and Alonso to race beyond the life expectancy of their tyres, allowing him to swoop in at the last minute to steal first place. Räikkönen's strategy failed as Maldonado withstood pressure from Alonso for fifteen laps, winning the race by three seconds. It was Williams' first win in one hundred and thirty Grand Prix starts; their previous race win was Juan Pablo Montoya's victory at the 2004 Brazilian Grand Prix. Venezuelan President Hugo Chávez declared a national holiday to celebrate Maldonado's victory. Lewis Hamilton recovered from twenty-fourth on the grid to finish eighth, while Sebastian Vettel overcame a drive-through penalty and an unscheduled stop for a technical fault that forced his team to replace his front wing to make a late move on Nico Rosberg for sixth place that would preserve his championship lead.

Ninety minutes after the race, the Williams garage caught fire. Pit crews from several teams were able to bring the blaze under control. Thirty-one people were injured,[75] with seven transferred to local hospitals. All were later released. Early accounts surfaced suggesting that the fire was caused by fuel that exploded while being prepared for a routine post-race inspection. Photographs taken at the scene showed Senna's car as being the point of origin of the fire, which ignited when a fuel rig used to drain the car started leaking. Senna's FW34 was damaged as a result; Pastor Maldonado's car was not in the garage at the time. Teams were reported as loaning equipment to Williams for the Monaco Grand Prix to replace everything that was lost in the fire.

Round 6 — Monaco

For the second consecutive race, the fastest driver in qualifying did not start the race from pole. Michael Schumacher set the fastest time, but a five-place grid penalty for causing an avoidable accident in Spain left him sixth and handed pole position to Mark Webber. Two hours before the race, several teams were reported to be preparing a protest against parts introduced onto the floor of the Red Bull RB8 ahead of the race, leaving team principal Christian Horner with a choice: to change the offending parts and start both cars from the pit lane, guaranteeing that any result the team recorded would be preserved; or to leave the parts on the car, allowing both drivers to start the race from the positions they qualified in, but risking a post-race exclusion. Horner ultimately chose the latter option, and Webber started the race from pole, establishing an early lead over Nico Rosberg after a first-corner accident eliminated four cars. The race was run under the constant threat of rain, with drivers trying to extend the life of their tyres to avoid being forced to make an additional stop and falling down the order. The rain never materialised, though Jean-Éric Vergne was observed using a set of intermediate tyres late in the race. Vergne later denied that this was a strategic gamble, instead revealing that all of his dry-weather tyres were in such poor condition that a change to the intermediate compound was the only way to ensure he made it to the finish. The variety of strategies used by the front-runners resulted in the last ten laps being contested with the top six cars running nose-to-tail. Webber visibly faded in the final laps, but held on when the following cars were momentarily pinned behind the slow-moving Heikki Kovalainen. Webber won the race — his second on the streets of Monaco — with Rosberg second and Fernando Alonso third, the result giving Alonso a three-point lead in the championship. Webber´s win caused a break of a record from the 1983 season, since he became the sixth different driver to win in the first six races of a season. Red Bull Racing maintained their lead in the Constructors' championship as rival teams chose not to follow through on the threat of their pre-race protest, while Kovalainen finshed thirteenth to see Caterham overtake Marussia for tenth place.[89] Elsewhere, Spanish Grand Prix winner Pastor Maldonado was the subject of controversy during the final practice session when he turned in early at Portier and clipped Sergio Pérez. Maldonado was summoned to the stewards and given a ten-place grid penalty for the incident which together with a five-place penalty for changing his gearbox ultimately sent him to the back row of the grid. He was subsequently eliminated in the first-corner accident when he collided with Pedro de la Rosa.

Autopilot

Autopilot panel of an older Boeing 747 aircraft,.

An autopilot is a mechanical, electrical, or hydraulic system used to guide a vehicle without assistance from a human being. An autopilot can refer specifically to aircraft, self-steering gear for boats, or auto guidance of space craft and missiles. The autopilot of an aircraft is sometimes referred to as "George".

First autopilots

In the early days of aviation, aircraft required the continuous attention of a pilot in order to fly safely. As aircraft range increased allowing flights of many hours, the constant attention led to serious fatigue. An autopilot is designed to perform some of the tasks of the pilot.

The first aircraft autopilot was developed by Sperry Corporation in 1912. The autopilot connected a gyroscopic Heading indicator and attitude indicator to hydraulically operated elevators and rudder (ailerons were not connected as wing dihedral was counted upon to produce the necessary roll stability.) It permitted the aircraft to fly straight and level on a compass course without a pilot's attention, greatly reducing the pilot's workload.

Lawrence Sperry (the son of famous inventor Elmer Sperry) demonstrated it two years later in 1914 at an aviation safety contest held in Paris. At the contest, Lawrence Sperry demonstrated the credibility of the invention were shown by flying the aircraft with his hands away from the controls and visible to onlookers of the contest. This autopilot system was also capable of performing take-off and landing, and the French military command showed immediate interest in the autopilot system. Wiley Post used a Sperry autopilot system to fly alone around the world in less than eight days in 1933.

Further development of the autopilot were performed, such as improved control algorithms and hydraulic servomechanisms. Also, inclusion of additional instrumentation such as the radio-navigation aids made it possible to fly during night and in bad weather. In 1947 a US Air Force C-53 made a transatlantic flight, including takeoff and landing, completely under the control of an autopilot.

In the early 1920s, the Standard Oil tanker J.A Moffet became the first ship to use an autopilot.

Modern autopilots

Not all of the passenger aircraft flying today have an autopilot system. Older and smaller general aviation aircraft especially are still hand-flown, while small airliners with fewer than twenty seats may also be without an autopilot as they are used on short-duration flights with two pilots. The installation of autopilots in aircraft with more than twenty seats is generally made mandatory by international aviation regulations. There are three levels of control in autopilots for smaller aircraft. A single-axis autopilot controls an aircraft in the roll axis only; such autopilots are also known colloquially as "wing levellers", reflecting their limitations. A two-axis autopilot controls an aircraft in the pitch axis as well as roll, and may be little more than a "wing leveller" with limited pitch-oscillation-correcting ability; or it may receive inputs from on-board radio navigation systems to provide true automatic flight guidance once the aircraft has taken off until shortly before landing; or its capabilities may lie somewhere between these two extremes. A three-axis autopilot adds control in the yaw axis and is not required in many small aircraft.

Autopilots in modern complex aircraft are three-axis and generally divide a flight into taxi, takeoff, ascent, level, descent, approach and landing phases. Autopilots exist that automate all of these flight phases except the taxiing. An autopilot-controlled landing on a runway and controlling the aircraft on rollout (i.e. keeping it on the centre of the runway) is known as a CAT IIIb landing or Autoland, available on many major airports' runways today, especially at airports subject to adverse weather phenomena such as fog. Landing, rollout and taxi control to the aircraft parking position is known as CAT IIIc. This is not used to date but may be used in the future. An autopilot is often an integral component of a Flight Management System.

Modern autopilots use computer software to control the aircraft. The software reads the aircraft's current position, and controls a Flight Control System to guide the aircraft. In such a system, besides classic flight controls, many autopilots incorporate thrust control capabilities that can control throttles to optimize the air-speed, and move fuel to different tanks to balance the aircraft in an optimal attitude in the air. Although autopilots handle new or dangerous situations inflexibly, they generally fly an aircraft with a lower fuel-consumption than a human pilot.

The autopilot in a modern large aircraft typically reads its position and the aircraft's attitude from an inertial guidance system. Inertial guidance systems accumulate errors over time. They will incorporate error reduction systems such as the carousel system that rotates once a minute so that any errors are dissipated in different directions and have an overall nulling effect. Error in gyroscopes is known as drift. This is due to physical properties within the system, be it mechanical or laser guided, that corrupt positional data. The disagreements between the two are resolved with digital signal processing, most often a six-dimensional Kalman filter. The six dimensions are usually roll, pitch, yaw, altitude, latitude and longitude. Aircraft may fly routes that have a required performance factor, therefore the amount of error or actual performance factor must be monitored in order to fly those particular routes. The longer the flight the more error accumulates within the system. Radio aids such as DME, DME updates and GPS may be used to correct the aircraft position.

Computer system details

The hardware of an autopilot varies from implementation to implementation, but is generally designed with redundancy and reliability as foremost considerations. For example, the Rockwell Collins AFDS-770 Autopilot Flight Director System used on the Boeing 777, uses triplicated FCP-2002 microprocessors which have been formally verified and are fabricated in a radiation resistant process.

Software and hardware in an autopilot is tightly controlled, and extensive test procedures are put in place.

Some autopilots also use design diversity. In this safety feature, critical software processes will not only run on separate computers and possibly even using different architectures, but each computer will run software created by different engineering teams, often being programmed in different programming languages. It is generally considered unlikely that different engineering teams will make the same mistakes. As the software becomes more expensive and complex, design diversity is becoming less common because fewer engineering companies can afford it. The flight control computers on the Space Shuttle uses this design: there are five computers, four of which redundantly run identical software, and a fifth backup running software that was developed independently. The software on the fifth system provides only the basic functions needed to fly the Shuttle, further reducing any possible commonality with the software running on the four primary systems.

Categories

Instrument-aided landings are defined in categories by the International Civil Aviation Organization. These are dependent upon the required visibility level and the degree to which the landing can be conducted automatically without input by the pilot.

CAT I - This category permits pilots to land with a decision height of 200 ft (61 m) and a forward visibility or Runway Visual Range (RVR) of 550 m. Simplex autopilots are sufficient.

CAT II - This category permits pilots to land with a decision height between 200 ft and 100 ft (≈ 30 m) and a RVR of 300 m. Autopilots have a fail passive requirement.

CAT IIIa -This category permits pilots to land with a decision height as low as 50 ft (15 m) and a RVR of 200 m. It needs a fail-passive autopilot. There must be only a 10−6 probability of landing outside the prescribed area.

CAT IIIb - As IIIa but with the addition of automatic roll out after touchdown incorporated with the pilot taking control some distance along the runway. This category permits pilots to land with a decision height less than 50 feet or no decision height and a forward visibility of 250 ft (76 m, compare this to aircraft size, some of which are now over 70 m long) or 300 ft (91 m) in the United States. For a landing-without-decision aid, a fail-operational autopilot is needed. For this category some form of runway guidance system is needed: at least fail-passive but it needs to be fail-operational for landing without decision height or for RVR below 100 m.

CAT IIIc - As IIIb but without decision height or visibility minimums, also known as "zero-zero".

Fail-passive autopilot: in case of failure, the aircraft stays in a controllable position and the pilot can take control of it to go around or finish landing. It is usually a dual-channel system.

Fail-operational autopilot: in case of a failure below alert height, the approach, flare and landing can still be completed automatically. It is usually a triple-channel system or dual-dual system.

Radio-controlled models

In radio-controlled modelling, and especially RC aircraft and helicopters, an autopilot is usually a set of extra hardware and software that deals with pre-programming the model's flight.

Driverless car

A driverless car is a vehicle equipped with an autopilot system, and capable of driving from one point to another without aid from an operator. Driverless passenger car programs include the 800 million EC EUREKA Prometheus Project on autonomous vehicles, the 2getthere passenger vehicles from the Netherlands, the ARGO research project from Italy, the DARPA Grand Challenge from the USA, and Google driverless car.

History

An early representation of the driverless car was Norman Bel Geddes's Futurama exhibit sponsored by General Motors at the 1933 World's Fair, which depicted electric cars powered by circuits embedded in the roadway and controlled by radio.

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 30 km/h (20 miles per hour), by tracking white street markers (special hardware was necessary, since commercial computers were much slower than they are today).

In the 1980s a vision-guided Mercedes-Benz robot van, designed by Ernst Dickmanns and his team at the Bundeswehr University of Munich in Munich, Germany, achieved 100 km/h on streets without traffic. Subsequently, the European Commission began funding the 800 million Euro EUREKA Prometheus Project on autonomous vehicles (1987–1995).

Also in the 1980s the DARPA-funded Autonomous Land Vehicle (ALV) in the United States achieved the first road-following demonstration that used laser radar (Environmental Research Institute of Michigan), computer vision (Carnegie Mellon University and SRI), and autonomous robotic control (Carnegie Mellon and Martin Marietta) to control a driverless vehicle up to 30 km/h. In 1987, HRL Laboratories (formerly Hughes Research Labs) demonstrated the first off-road map and sensor-based autonomous navigation on the ALV. The vehicle travelled over 600m at 3 km/h on complex terrain with steep slopes, ravines, large rocks, and vegetation.

In 1994, the twin robot vehicles VaMP and Vita-2 of Daimler-Benz and Ernst Dickmanns of UniBwM drove more than one thousand kilometers on a Paris three-lane highway in standard heavy traffic at speeds up to 130 km/h, albeit semi-autonomously with human interventions. They demonstrated autonomous driving in free lanes, convoy driving, and lane changes left and right with autonomous passing of other cars.

In 1995, Dickmanns´ re-engineered autonomous S-Class Mercedes-Benz took a 1600 km 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 175 km/h on the German Autobahn, with a mean time between human interventions of 9 km, or 95% autonomous driving. Again it drove in traffic, executing manoeuvres to pass other cars. Despite being a research system without emphasis on long distance reliability, it drove up to 158 km without human intervention.

In 1995, the Carnegie Mellon University Navlab project achieved 98.2% autonomous driving on a 5000 km (3000-mile) "No hands across America" trip. This car, however, was semi-autonomous by nature: it used neural networks to control the steering wheel, but throttle and brakes were human-controlled.

From 1996–2001, Alberto Broggi of the University of Parma launched the ARGO Project, which worked on enabling a modified Lancia Thema 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 vehicle had only two black-and-white low-cost video cameras on board, and used stereoscopic vision algorithms to understand its environment, as opposed to the "laser, radar - whatever you need" approach taken by other efforts in the field.

Three US Government funded military efforts known as Demo I (US Army), Demo II (DARPA), and Demo III (US Army), are currently underway. 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. James Albus at NIST provided the Real-Time Control System which is a hierarchical control system. Not only were individual vehicles controlled (e.g. throttle, steering, and brake), but groups of vehicles had their movements automatically coordinated in response to high level goals.

In 2002, the DARPA Grand Challenge competitions were announced. The 2004 and 2005 DARPA competitions allowed international teams to compete in fully autonomous vehicle races over rough unpaved terrain and in a non-populated suburban setting. The 2007 DARPA challenge, the DARPA urban challenge, involved autonomous cars driving in an urban setting.

In 2008, General Motors stated that they will begin testing driverless cars by 2015, and they could be on the road by 2018 .

In 2010 VisLab ran VIAC, the VisLab Intercontinental Autonomous Challenge, a 13,000 km test run of autonomous vehicles. The four driverless electric vans successfully ended the drive from Italy to China via the arriving at the Shanghai Expo on 28 October.

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:

Fully autonomous vehicles

Various enhancements to the infrastructure (either an entire area, or specific lanes) to create a self-driving closed system.

"assistance" systems that incrementally remove requirements from the human driver (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

Fully autonomous driving requires a car to drive itself to a pre-set target using unmodified infrastructure. The final goal of safe door-to-door transportation in arbitrary environments is not yet reached though.

Vehicles for paved roads

Google driverless car, with a test fleet of autonomous vehicles that by October 2010 have driven 140,000 miles (230,000 km) without any incidents.

The 800 million Euro EUREKA Prometheus Project on autonomous vehicles (1987–1995). Among its culmination points were the twin robot vehicles VITA-2 and VaMP of Daimler-Benz and Ernst Dickmanns, driving long distances in heavy traffic (see #History above).

The VIAC Challenge, in which 4 vehicles drove from Italy to China on a 13,000 kilometres (8,100 mi) trip with only limited occasions intervene by human, such as in the Moscow traffic jams and when passing toll stations. This is the longest-ever trip by an unmanned vehicle.

The third competition of the DARPA Grand Challenge held in November 2007. 53 teams qualified initially, but after a series of qualifying rounds, only eleven teams entered the final race. Of these, six teams completed navigating through the non-populated urban environment, and the Carnegie Mellon University team won the $2 million prize.

The ARGO vehicle (see #History above) is the predecessor of the BRAiVE vehicle, both from the University of Parma's VisLab. Argo was developed in 1996 and demonstrated to the world in 1998; BRAiVE was developed in 2008 and firstly demonstrated in 2009 at the IEEE IV conference in Xi'an, China.

Stanford Racing Team's Junior car is an autonomous driverless car for paved roads. It is intended for civilian use.

The Volkswagen Golf GTI 53+1 is a modified Volkswagen Golf GTI capable of autonomous driving. The Golf GTI 53+1 features a implemented system that can be integrated into any car. This system is based around the MicroAutoBox from dSpace. This, as it was intended to test VW hardware without a human driver (for consistent test results).

The Audi TTS Pikes Peak is a modified Audi TTS, working entirely on GPS, and thus without additional sensors. The car was designed by Burkhard Huhnke of Volkswagen Research.

Stadtpilot, Technical University Braunschweig

AutoNOMOS - part of the Artificial Intelligence Group of the Freie Universität Berlin

Free-ranging vehicles

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

US military DARPA Grand Challenge

Main article: DARPA Grand Challenge

The US Department of Defense announced on the July 30, 2002 a "Grand Challenge", for US-based teams to produce a vehicle that could 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 the second competition held in October 2005 five different teams completed the 135-mile (217 km) course, and the Stanford University team won the $2 million prize.

November 3rd, 2007, the third competition was held and $3.5 million dollar in cash prizes, trophies and medals were awarded. Six driverless vehicles were able to complete the 55 miles (89 km) of urban traffic in the 2007 DARPA Urban Challenge rally style race. 1st Place - Tartan Racing, Pittsburgh, PA; 2nd Place - Stanford Racing Team, Stanford, CA; 3rd Place - Victor Tango, Blacksburg, VA.

European Land-Robot Trial (ELROB)

The German Department of Defense held an exhibition trade show (ELROB) for demonstrating automated vehicles in May 2006. The event included various military automated and remotely-operated robots, for various military uses. Some of the systems on display could be ordered and implemented immediately. In August 2007 a civilian version of the event was held in Switzerland.

The Smart team from Switzerland presented "a Vehicle for Autonomous Navigation and Mapping in Outdoor Environments". For pictures of their ELROB demo, see this.

The Israeli Military-Industrial Complex

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.

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. Such systems already function in many airports, on railroads, and in some European towns.

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 concept along those lines, for purely public transport.)

Groups working on this concept are:

RUF (Denmark)

BiWay (UK)

ATN (New Zealand)

TriTrack (Texas, United States)

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 center 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.

One example that uses this implementation 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-kilometer, high-occupancy-vehicle (HOV) segment of Interstate 15, 16 kilometers north of downtown San Diego. The event generated much press coverage.

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.

As of 2007, a three-year project is underway to allow robot controlled vehicles, including buses and trucks, to use a special lane along 20 Interstate 805. The intention is to allow the vehicles to travel at shorter following distances and thereby allow more vehicles to use the lanes. The vehicles will still have drivers since they need to enter and exit the special lanes. The system is being designed by Swoop Technology, based in San Diego county.

Free-ranging on grid

Frog Navigation Systems (the Netherlands) applies the FROG (free-ranging on grid) technology. The technology consists of a combination of autonomous vehicles and a supervisory central system. The company's purpose-built electric vehicles locate themselves using odometry readings, recalibrating themselves occasionally using a "maze" of magnets embedded in the environment, and GPS. The cars avoid collisions with obstacles located in the environment using laser (long range) and ultra-sonic (short-range) sensors.

The vehicles are completely autonomous and plan their own routes from A to B. The supervisory system merely administers the operations and directs traffic where required. The system has been applied both indoors and outdoors, and in environments where 100+ automated vehicles are operational (container port). At this time the system is not suited yet for running the sheer number of vehicles encountered in urban settings. The company also has no intention of developing such technology at this time.

The FROG system is deployed for industrial purposes in factory sites, and is marketed as a pilot public transport system in the city of Capelle aan den IJssel by its subsidiary 2getthere. This system experienced an accident that proved to be caused by a Human error.

Frog Navigation Systems 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. This approach is slowly trickling into standard cars (e.g. improvements to cruise control).

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

Sensorial-informative

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

Lane Departure Warning System (LDWS), for example from Iteris or Mobileye N.V.

Rear-view alarm, to detect obstacles behind.

Visibility aids for the driver, to cover blind spots and enhanced vision systems such as radar, wireless vehicle safety communications and night vision.

Infrastructure-based, driver warning/information-giving systems, such as those developed by the Japanese government

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.

Anti-lock braking system (ABS) (also Emergency Braking Assistance (EBA), often coupled with Electronic brake force distribution (EBD), which prevents the brakes from locking and losing traction while braking. This shortens stopping distances in most cases and, more importantly, allows the driver to steer the vehicle while braking.

Traction control system (TCS) actuates brakes or reduces throttle to restore traction if driven wheels begin to spin.

Four wheel drive (AWD) with a centre differential. Distributing power to all four wheels lessens the chances of wheel spin. It also suffers less from oversteer and understeer.

Electronic Stability Control (ESC) (also known for Mercedes-Benz proprietary Electronic Stability Program (ESP), Acceleration Slip Regulation (ASR) and Electronic differential lock (EDL)). Uses various sensors to intervene when the car senses a possible loss of control. The car's control unit can reduce power from the engine and even apply the brakes on individual wheels to prevent the car from understeering or oversteering.

Dynamic steering response (DSR) corrects the rate of power steering system to adapt it to vehicle's speed and road conditions.

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

Driver-assistance preview from Popular Science (dated 2004).

Note: The electronic differential lock (EDL) employed by Volkswagen is not - as the name suggests - a differential lock at all. Sensors monitor wheel speeds, and if one is rotating substantially faster than the other (i.e. slipping) the EDL system momentarily brakes it. This effectively transfers all the power to the other wheel.

Systemic

Automatic parking: e.g. technology from Ford or Toyota selling for $700, with a 70% take-up rate. The Lexus LS can park itself (parallel/reverse) via the 'Advanced Parking Guidance System' – though only controlling the steering.

Follow another car on a motorway ("Enhanced" or "adaptive" cruise control), like The Ford or Vauxhall(GM).

Nissan's "Distance Control assist"

Dead Man's Switch; there is a move to introduce deadman's braking into automotive application, primarily heavy vehicles, and there may also be a need to add penalty switches to cruise controls.

See also Safety Features.

Existing and missing technologies

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

Understand its immediate environment (Sensors)

Know where it is and where it wants to go (Navigation)

Find its way in the traffic (Motion planning)

Operate the mechanics of the vehicle (Actuation)

Arguably, 2½ of these problems are already solved: Navigation and Actuation completely, and Sensors partially, but improving fast. The main unsolved part is the motion planning.

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 N.V. is a technology company that focuses on the development of vision-based Advanced Driver Assistance Systems (ADAS) providing warnings for collision prevention and mitigation. Mobileye offers a wide range of driver safety solutions combining artificial vision image processing, multiple technological applications and information technology. Mobileye's vehicle detection systems, 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.

Japanese infra-red article

some things from the DARPA challenge....

Road-sign recognition.

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. There are also sensors that greatly affect the whole nature of it.

See the main article on Automotive navigation systems.

Motion planning

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

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.

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 impact

Driverless cars may yield advantages of increasing roadway capacity by reducing the distances between cars, reduce congestion by efficiently controlling the flow of traffic, and increase safety by eliminating driver error.

According to urban designer and futurist Michael E. Arth, driverless electric vehicles—in conjunction with the increased use of virtual reality for work, travel, and pleasure—could reduce the world's vehicles (estimated to be 800,000,000) to a fraction of that number within a few decades. Arth claims that this would be possible if almost all private cars requiring drivers, which are not in use and parked 90% of the time, would be traded for public self-driving taxis that would be in near constant use. This would also allow for getting the appropriate vehicle for the particular need—a bus could come for a group of people, a limousine could come for a special night out, and a Segway could come for a short trip down the street for one person. Children could be chauffeured in supervised safety, DUIs would no longer exist, and 41,000 lives could be saved each year in the U.S. alone.

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.:

INRIA's La Route Automatisée 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 organizations are government sponsored, and they all cooperate at some level or another. Some of the countries involved are: USA, IEEE ITS Society, Australia, South Korea, Taiwan, India--(specifically Intelligent vehicles), and Japan, specifically a cruise assist effort (see below). A more complete list of its organizations can be found here.

Governments

USA:

ITS - Turner-Fairbank Highway Research Center

Ice Detection and Cooperative Curve Warning / Current AVCS Deployment - NTL Catalog

Universities and professional bodies

UC Berkeley - California PATH

MIT Media Lab CityCar

VisLab: Artificial Vision and Intelligent Systems Lab at University of Parma, Italy

Virginia Tech

Austin Robot Technology / UT Austin

IEEE has a Society (the Intelligent Transportation Systems Society), runs an important scientific Journal, and organizes conferences

Japanese Automobile Research Institution

Advanced Cruise-Assist Highway System Research Organization

Carnegie Mellon University Navlab

GrayMatter Inc. - a division of the Gray Team.

Institute of Autonomous Systems Technology: at Bundeswehr University of Munich

Private companies

Google driverless car

General Motors EN-V

Voluntary and hobbyist groups

Autonomous Robots Magazine

American Industrial Magic http://aimagic.org entered 3 vehicles in the 2004 DARPA challenge.

Open Source Driverless Car Project (Python/C++) http://bitbucket.org/djlyon/smp-driverless-car-robot

In film

KITT, the automated Pontiac TransAm in the TV series Knight Rider could drive by itself upon command

The 1989 film Batman, starring Michael Keaton, the Batmobile is shown to be able to drive itself to Batman's current location.

The 1990 film Total Recall, 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.

The 1993 film Demolition Man, starring Sylvester Stallone, set in 2032, features vehicles that can be self-driven or commanded to "Auto Mode" where a voice controlled computer operates the vehicle.

The 1994 film Timecop, starring Jean-Claude Van Damme, set in 2004 and 1994, has cars that can either be self-driven or commanded to drive to specific locations such as "home".

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.

The 2004 film I, Robot features vehicles with automated driving on future highways, allowing the car to travel safer at higher speeds than if manually controlled. An interesting concept of automated driving in this film is that people aren't trusted to drive manually, as opposed by people not trusting automated driving nowadays.

Anthropomorphic cars (capable of thinking and moving around on their own) have also shown up in movies, such as the series concerning Herbie and the movie Cars. (The name of Volkswagen's 53+1 car was a nod to Herbie;Herbie was conspicuously decorated with the number 53.)