Advanced driver-assistance system

Advanced driver-assistance systems (ADAS) are technologies that assist drivers with the safe operation of a vehicle. Through a human-machine interface, ADAS increases car and road safety. ADAS uses automated technology, such as sensors and cameras, to detect nearby obstacles or driver errors and respond accordingly. ADAS can enable various levels of autonomous driving.

As most road crashes occur due to human error, ADAS are developed to automate, adapt, and enhance vehicle technology for safety and better driving. ADAS is proven to reduce road fatalities by minimizing human error. Safety features are designed to avoid crashes and collisions by offering technologies that alert the driver to problems, implementing safeguards, and taking control of the vehicle if necessary. ADAS may provide adaptive cruise control, assist in avoiding collisions, alert drivers to possible obstacles, warn of lane departure, assist in lane centering, incorporate satellite navigation, provide traffic warnings, provide navigational assistance through smartphones, automate lighting, or provide other features.

According to a 2021 research report from Canalys, approximately 33% of new vehicles sold in the United States, Europe, Japan, and China had ADAS. The firm also predicted that 50% of all automobiles on the road by the year 2030 would be ADAS-enabled.

Terminology

Some groups advocate standardization of the name, such as "forward collision warning" and "automatic emergency braking", rather than "forward collision alert" or "smart city brake support".

Such standardization is promoted by AAA, Consumer Reports, J.D. Power, National Safety Council, PAVE, and SAE International.

Concept, history and development

After WWII, an engineer named Nathaniel Korman, who worked on radar systems during WWII, experimented with a system to control the speed of a train based on the speed of a train in front of it, using radar. He noted that it could also be used for on-road vehicles.

In 1948, Ralph Teetor applied for a US patent in a "speed control device for resisting operation of the accelerator", or what is now known as cruise control, granted in 1950. General Motors later displayed a concept car in 1959, which used some variation of the system, with radar embedded in the front nacelles of the car. Early ADAS include electronic stability control, anti-lock brakes, blind spot information systems, lane departure warning, adaptive cruise control, and traction control. These systems can be affected by mechanical alignment adjustments or damage from a collision. This has led many manufacturers to require automatic resets for these systems after a mechanical alignment is performed.

Technical concepts

The reliance on data that describes the outside environment of the vehicle, compared to internal data, differentiates ADAS from driver-assistance systems (DAS). Modern cars have ADAS integrated into their electronics; manufacturers can add these new features during the design process or after production via over-the-air (OTA) updates.

ADAS are considered real-time systems since they react quickly to multiple inputs and prioritize the incoming information to prevent crashes. The systems use preemptive priority scheduling to organize which task needs to be done first.

Forward Collision Warning (FCW)
Lane Departure Warning (LDW)
Pedestrian Collision Warning (PCW)

These systems are often a component of modern video telematics, as they not only provide safety alerts but also record video footage of the events. This data is then transmitted via a telematic control unit to a fleet management platform, where it can be used for driver coaching and incident analysis.

Feature examples

This list is not a comprehensive list of all of the ADAS. Instead, it provides information on critical examples of ADAS that have progressed and become more commonly available since 2015.

<!--Please organize feature examples into one of the four areas:

1. Alerts and warnings

2. Crash mitigation

3. Driving task assistance

4. Visual and environmental monitoring

Within each area, please arrange in alphabetical order.-->=== Alerts and warnings ===

Blind spot monitor involves cameras that monitor the driver's blind spots and notify the driver if any obstacles come close to the vehicle.
Driver drowsiness detection aims to prevent collisions due to driver fatigue. The vehicle obtains information, such as facial patterns, steering movement, driving habits, turn signal use, and driving velocity, to determine if the driver's activities correspond with drowsy driving. If drowsy driving is suspected, the vehicle will typically sound off a loud alert and may vibrate the driver's seat. These systems use biological and performance measures to assess the driver's alertness and ability to conduct safe driving practices, which can be used for driver scoring. This technology was developed in response to the U.S. National Highway Traffic Safety Administration ruling that issued 50 percent of quiet vehicles must have a device implemented into their systems that sound off when the vehicle travels at speeds less than 30 km/h (18.6 mph) by September 2019.
Forward collision warning (FCW) monitors the speed of the vehicle and, the vehicle in front of it, and the open distance around the vehicle. FCW systems will send an alert to the driver of a possible impending collision if gets too close to the vehicle in front of it. Some ISA systems allow the vehicle to adjust its speed to adhere to the relative speed limit. This system alerts the driver of any upcoming traffic from the vehicle's sides. It can enact the vehicle's emergency braking system to prevent a collision. An LDW system uses cameras to monitor lane markings to determine if the driver unintentionally begins to drift. Audio warnings can notify the driver of the distance between the vehicle and its surrounding objects. The driver can monitor the tire pressure and is notified when there is a sudden drop through a pictogram display, gauge, or low-pressure warning signal.
Wrong-way driving warning issue alerts to drivers when it is detected that they are on the wrong side of the road. Vehicles with this system enacted can use sensors and cameras to identify the direction of oncoming traffic flow. This system uses cameras and sensors to determine when the front of a vehicle strikes a pedestrian. ACC systems with stop and go features can come to a complete stop and accelerate back to the specified speed. This system still requires an alert driver to take in their surroundings, as it only controls speed and the distance between you and the car in front of you. Alongside helping drivers in emergencies, such as when their car starts to skid on ice, ABS systems can also assist drivers who may lose control of their vehicle. Depending on the relative cars and obstacles, the vehicle positions itself safely into the available parking spot. These systems can account for any sudden changes to the car's environment that may cause a collision. This system distributes the wheel load in relation to the velocity and direction of the crosswind. The car will maintain the speed the driver sets until the driver hits the brake pedal, clutch pedal, or disengages the system. Understeer occurs when the car's front wheels do not have enough traction to make the car turn and oversteer occurs when the vehicle turns more than intended, causing the vehicle to spin out. After a specified period, if the driver has not interacted with the accelerator, brake, or steering wheel, the car will send audio, visual, and physical signals to the driver. These systems are typically enacted if the vehicle moves faster than 15 to 20 mph when driving down. When a change in grade is sensed, hill descent control automates the driver's speed to descend down the steep grade safely. This feature holds the brake for you while you transition between the brake pedal and the gas pedal. A lane-centering system may autonomously take over the steering when it determines the driver is at risk of deterring from the lane.
Lane change assistance helps the driver through the safe completion of a lane change by using sensors to scan the vehicle's surroundings and monitor the driver's blind spots. When a driver intends to make a lane change, the vehicle will notify the driver through an audio or visual alert when a vehicle is approaching from behind or is in the vehicle's blind spot. Several kinds of lane change assistance might exist, for instance, UNECE regulation 79 considers:
"ACSF (Automatically commanded steering function) of Category C" (...) a function which is initiated/activated by the driver and which can perform a single lateral manoeuvre (e.g., lane change) when commanded by the driver.
"ACSF of Category D" (...) a function which is initiated/activated by the driver and which can indicate the possibility of a single lateral manoeuvre (e.g. lane change) but performs that function only following a confirmation by the driver.
"ACSF of Category E" (...) a function which is initiated/activated by the driver and which can continuously determine the possibility of a manoeuvre (e.g. lane change) and complete these manoeuvres for extended periods without further driver command/confirmation.
Rain sensors detect water and automatically trigger electrical actions, such as the raising of open windows and the closing of open convertible tops. A rain sensor can also take in the frequency of rain droplets to automatically trigger windshield wipers with an accurate speed for the corresponding rainfall. By limiting tire slip, or when the force on a tire exceeds the tire's traction, this limits power delivery and helps the driver accelerate the car without losing control. Currently, the majority of the auto-HUD systems on the market display system information on a windshield using LCDs. Through an embedded receiver, an automotive navigation system can send and receive data signals transmitted from satellites regarding the current position of the vehicle in relation to its surroundings. This camera offers driver's aid when backing up by providing a viewpoint that is typically a blind spot in traditional cars. When the driver puts the car in reverse, the camera automatically turns on. This allows oncoming vehicles coming in the opposite direction not to be affected by the light of the high-beams. In 2010, the VW Touareg introduced the first glare-free high beam headlamp system, which used a mechanical shutter to cut light from hitting specific traffic participants. This system can accurately provide 3D peripheral images of the car's surroundings through a video telematics display outputted to the driver. This system takes into account the sign's shape, such as hexagons and rectangles, and the color to classify what the sign is communicating to the driver. V2I systems occur when the vehicle exchanges information with nearby infrastructure elements, such as street signs.

! Brand !! Vehicle number !! ADAS suite name !! VMT (hands-free) !! Traveled distance (miles)

| Ford || || BlueCruise || 100 million || 150 million

| General Motors || || Super Cruise || 77 million || ~100 millions

According to a 2021 research report from Canalys, approximately 33 percent of new vehicles sold in the United States, Europe, Japan, and China had ADAS features. The firm also predicted that fifty percent of all automobiles on the road by the year 2030 would be ADAS-enabled. and Drive Pilot from Mercedes-Benz.

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{|class="wikitable sortable" style="font-size:100%;text-align:center;"

|+Advanced driver-assistance system branding

! Manufacturer !! Brand !! Level !! class="unsortable" | Notes !! class="unsortable" | Refs.

! Audi !! Driver Assistance Plus

| 2

| style="text-align:left;" |

! BMW !! Active Driving Assistance Pro

| 2

| style="text-align:left;" |

! Ford (Lincoln) !! Co-Pilot 360

| 2

| style="text-align:left;" |

! GM (Buick / Chevy) !! Driver Confidence

| 2

| style="text-align:left;" |

! GM (Cadillac) !! Super Cruise

| 2

| style="text-align:left;" |

| <

! GM !! Ultra Cruise

| 2

| style="text-align:left;" |

! Honda !! Sensing (AcuraWatch)

| 2

| style="text-align:left;" |

! Hyundai & Kia !! Smart Sense (Hyundai)<br />Drive Wise (Kia)

| 2

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! Land Rover !! Driver Assist

| 2

| style="text-align:left;" |

! Mazda !! i-ACTIVSENSE

| 2

| style="text-align:left;" |

! Mercedes-Benz !! Driver Assistance

| 2

| style="text-align:left;" |

! Nissan & Infiniti !! ProPILOT Assist

| 2

| style="text-align:left;" |

! Porsche !! Active Safe

| 2

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! Subaru !! EyeSight

| 2

| style="text-align:left;" |

! Tesla !! Autopilot

| 2

| style="text-align:left;" |

! Tesla !! Full Self-Driving

| 2

| style="text-align:left;" |

! Toyota (Lexus) !! Safety Sense 2.0

| 2

| style="text-align:left;" |

! Toyota (Lexus) !! Teammate

| 2

| style="text-align:left;" |

! Volkswagen !! Driver Assistance

| 2

| style="text-align:left;" |

! Volvo !! Pilot Assist

| 2

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Crash statistics

On June 29, 2021, the National Highway Traffic Safety Administration (NHTSA), the branch of the United States Department of Transportation responsible for federal motor vehicle regulations, issued Standing General Order 2021-01 (SGO 2021-01), which required manufacturers of ADAS (Levels 1 or 2) and Automated Driving Systems (ADS) (Levels 3 through 5) to promptly report crashes that occurred when driver-assistance or automation systems were in use. SGO 2021-01 subsequently was amended on August 5, 2021. Under the amended SGO 2021-01, a crash involving ADS or Level 2 ADAS is reportable to the NHTSA if it meets the following criteria: The data are subject to several caveats and limitations; for instance, manufacturers are not required to report the number of vehicles that have been built and equipped with ADS/ADAS, the number of vehicles operating with ADS/ADAS, or the total distance traveled with ADS/ADAS active, which would be helpful to normalize the incident report data. Of the 130 crashes, 108 had no associated injuries reported; there was only one serious injury associated with the remaining crashes. Of the 392 crashes, 98 included injury reporting; of the 98, 46 had no injuries reported, 5 resulted in serious injuries and 6 resulted in fatalities. Button names and locations, as well as dashboard symbols, change from car to car due to lack of standardization.

ADAS might have many limitations, for instance a pre-collision system might have 12 pages to explain 23 exceptions where ADAS may operate when not needed and 30 exceptions where ADAS may not operate when a collision is likely.

ADAS behavior might change from car to car as well; for instanc,e ACC speed might be temporarily overridden in most cars, while some switch to standby after one minute. Auto insurance for ADAS has directly affected the global economy, and many questions have arisen within the general public. ADAS allow autonomous vehicles to enable self-driving features, but there are associated risks with ADAS. AV companies and manufacturers are recommended to have insurance in the following areas in order to avoid any serious litigations. Depending on the level, ranging from 0 to 5, each car manufacturer would find it in its best interest to find the right combination of different insurances to best match their products. Note that this list is not exhaustive and may be constantly updated with more types of insurances and risks in the years to come.

Technology errors and omissions – This insurance will cover any physical risk if the technology itself has failed. These usually include all of the associated expenses of a car crash.
Auto liability and physical damage – This insurance covers third-party injuries and technology damage.
Cyber liability – This insurance will protect companies from any lawsuits from third parties and penalties from regulators regarding cybersecurity.
Directors and officers – This insurance protects a company's balance sheet and assets by protecting the company from bad management or misappropriation of assets.

With the technology embedded in autonomous vehicles, these self-driving cars are able to distribute data if a car crash occurs. This, in turn, will invigorate the claims administration and their operations. Fraud reduction will also disable any fraudulent staging of car crashes by recording the car's monitoring of every minute on the road. ADAS are expected to streamline the insurance industry and its economic efficiency with capable technology to fight off fraudulent human behavior. In September 2016, the NHTSA published the Federal Automated Vehicles Policy, which describes the U.S. Department of Transportation's policies related to highly automated vehicles (HAV) which range from vehicles with ADAS features to autonomous vehicles.

Ethical issues and current solutions

In March 2014, the US Department of Transportation's National Highway Traffic Safety Administration (NHTSA) announced that it will require all new vehicles under 10,000 pounds (4,500 kg) to have rear view cameras by May 2018. The rule was required by Congress as part of the Cameron Gulbransen Kids Transportation Safety Act of 2007. The Act is named after two-year-old Cameron Gulbransen. Cameron's father backed up his SUV over him, when he did not see the toddler in the family's driveway

The advancement of autonomous driving is accompanied by ethical concerns. The earliest moral issue associated with autonomous driving can be dated back to as early as the age of the trolleys. The trolley problem is one of the most well-known ethical issues. Introduced by English philosopher Philippa Foot in 1967, the trolley problem asks that under a situation which the trolley's brake does not work, and there are five people ahead of the trolley, the driver may go straight, killing the five persons ahead, or turn to the side track killing the one pedestrian, what should the driver do? Before the development of autonomous vehicles, the trolley problem remains an ethical dilemma between utilitarianism and deontological ethics. However, as the advancement in ADAS proceeds, the trolley problem becomes an issue that needs to be addressed by the programming of self-driving cars. The crashes that autonomous vehicles might face could be very similar to those depicted in the trolley problem. Although ADAS make vehicles generally safer than only human-driven cars, crashes are unavoidable. Such a method is useful when the rules cannot be articulated because the computer can learn and identify the ethical elements on its own without precisely programming whether an action is ethical. However, there are limitations to this approach. For example, many human actions are done out of self-preservation instincts, which is realistic but not ethical; feeding such data to the computer cannot guarantee that the computer captures the ideal behavior. Furthermore, the data fed to an artificial intelligence must be carefully selected to avoid producing undesired outcomes. Their criteria were: Their criteria were:

{| class="wikitable sortable"

!Rating

!Manufacturer

!System

|data-sort-value="2-Acceptable" | Acceptable

|Lexus

|Teammate with Advanced Drive

|data-sort-value="3-Marginal" | Marginal

|General Motors

|Super Cruise

|data-sort-value="4-Marginal" | Marginal

|Nissan

|ProPILOT Assist with Navi-link