Advanced driver assistance

Truly driverless cars aren’t for sale yet. More vehicles are incorporating a degree of automation with technologies such as adaptive cruise control and lane centering, but the driver will continue to share driving responsibilities for the foreseeable future. In theory, fully automated driving could eliminate the vast majority of crashes, but that level of automation won’t be parked in your driveway anytime soon.

Advanced crash avoidance features are becoming widespread. Many of today’s vehicles have technologies that monitor driver input and the environment around the vehicle and warn the driver when they detect the possibility of a crash. They may automatically brake or steer the vehicle if the driver does not act to avoid the collision.

Some driver assistance technologies are reducing crashes. Front crash prevention, lane departure prevention, blind spot detection and rear crash prevention also show real-world crash reductions.

Real-world benefits of crash avoidance technologies

Summary of IIHS-HLDI findings

Front crash prevention systems are designed to intervene when the vehicle is about to rear-end another vehicle. The technology uses various types of sensors, such as cameras, radar or lidar — short for light detection and ranging — to detect when the vehicle is getting too close to one in front of it. The systems generally issue a warning and precharge the brakes to maximize their effect. Most also apply the brakes if the driver doesn’t respond.

Many front crash prevention systems can detect pedestrians, and some also recognize cyclists and animals. These systems use advanced algorithms coupled with sensors and cameras to spot nonmotorists who are in or about to enter the vehicle’s path.

Front crash prevention is becoming more universal and its capabilities more consistent across brands, thanks to a voluntary commitment by 20 automakers, representing 99% of U.S. light vehicle sales, to make the technology standard by September 2022. The commitment, brokered by IIHS and the National Highway Traffic Safety Administration (NHTSA), called for vehicles to have systems with both a forward collision warning component that met NHTSA criteria and automatic braking that achieved certain minimum speed reductions in IIHS track tests.

In 2024, NHTSA finalized a requirement for front crash prevention on nearly all new vehicles with a gross vehicle weight rating of 10,000 pounds or less by September 2029 (NHTSA, 2024). Under the rule, systems must be operable in both daylight and dark conditions. They must provide a warning and automatically brake in response to a vehicle ahead at speeds up to 90 mph and in response to a pedestrian at speeds up to 45 mph.

Vehicles equipped with front crash prevention are much less likely to rear-end other vehicles than the same models without the technology (Cicchino, 2017; Fildes et al., 2015; Isaksson-Hellman & Lindman, 2016; Partnership for Analytics Research in Traffic Safety, 2025). An Institute study found that systems with forward collision warning and automatic braking cut rear-end crashes in half, while forward collision warning alone reduces them by 27% (Cicchino, 2017). The autobrake systems also greatly reduce rear-end crashes involving injury.

A separate IIHS study showed that automatic braking systems that recognize pedestrians cut pedestrian crashes by 27% (Cicchino, 2022).

Passenger vehicles are not the only vehicles that benefit from front crash prevention systems. Similar rear-end crash reduction effects have been found for large trucks equipped with front crash prevention systems (Teoh, 2021).

HLDI has conducted studies comparing insurance claim rates for passenger vehicles equipped with front crash prevention with claim rates for the same models without the technology. Vehicles equipped with these systems consistently show lower rates of claims for damage to other vehicles and for injuries to people in other vehicles (HLDI, 2023).

Similarly, HLDI found that Subaru’s EyeSight system with pedestrian detection cut the rate of likely pedestrian-related insurance claims by 35%, compared with the same vehicles without the system (Wakeman et al., 2019).

Even if a front crash prevention system doesn’t avoid a crash altogether, it may still reduce the impact speed, thereby making a crash less severe.

To show why reducing speed is important, IIHS conducted two demonstration crash tests at different speeds in 2013. In each test, a 2013 Mercedes-Benz C-Class ran into the back of a stationary 2012 Chevrolet Malibu. The tests illustrated what happens in a 25 mph crash when the striking vehicle doesn’t have autobrake, compared with what happens when the speed is reduced by 13 mph, the amount by which the C-Class's autobrake system reduced the impact speed in IIHS track testing. Damage in the higher speed crash test was about $28,000. The Malibu was a complete loss. Lowering the speed to 12 mph trimmed the damage to $5,700 (IIHS, 2013).

A similar speed reduction in a higher-speed crash could significantly reduce injury risk as well as vehicle damage (Kraft et al., 2009).

Front crash prevention systems with automatic braking have resulted in bigger reductions in rear-end crashes with injuries than in rear-end crashes of all severities, which suggests that these systems are preventing injuries in some rear-end crashes that aren’t avoided (Cicchino, 2017).

IIHS has rated front crash prevention systems since 2013 and began rating pedestrian detection systems in 2019.

These systems use cameras to track the vehicle’s position within the lane, alerting the driver if the vehicle is in danger of inadvertently straying across lane markings when the turn signal is not activated.

Some lane departure warning systems use haptic feedback, such as steering wheel or seat vibration, while others use audible and/or visual alerts. Lane departure prevention systems cause the vehicle to actively resist moving out of the lane or help direct the vehicle back into the lane through light braking or minor steering adjustments.

Lane departure warning has not brought down insurance claim rates (HLDI, 2023) but has reduced rates of single-vehicle, sideswipe and head-on crashes reported to the police (Cicchino, 2018; Partnership for Analytics Research in Traffic Safety, 2025; Sternlund et al., 2017).

This feature uses sensors to monitor the side of the vehicle for vehicles approaching blind spots. In many systems, a visual alert appears on or near the side mirrors if a vehicle is detected. An audible alert may activate if the driver signals a turn and there is a vehicle in the blind spot. Some systems also may activate the brake or steering controls to keep the vehicle in its lane.

Blind spot detection has been shown to reduce lane-change crashes by 14% (Cicchino, 2018). HLDI research has also found that blind spot detection lowers rates of insurance claims covering injuries and damage to other vehicles (HLDI, 2023).

There are many different technologies designed to help drivers back up safely. Rearview cameras display what is behind the vehicle, projecting a much larger field than is visible in mirrors or even by looking directly out the back windshield. Since May 2018, rearview cameras have been essentially required on new vehicles in order to reduce backover crashes, in which young children are frequently the victims (Office of the Federal Register, 2014).

Some camera systems, as well as systems that use radar or ultrasonic sensors, warn the driver if there are objects in the way when the vehicle is in reverse. Systems with rear automatic braking apply the brakes to keep the vehicle from backing into or over an object. A rear cross-traffic alert system detects vehicles approaching from either side that may cross the path of a backing vehicle, warns the driver, and may automatically brake to prevent a collision.

Rear automatic braking is associated with the largest reductions in insurance claims and backing crashes reported to the police of any type of rear crash prevention system (Cicchino, 2019; HLDI, 2023).

IIHS has issued ratings for some rear crash prevention systems.

Crash avoidance technologies can’t be effective unless they are used. Appropriate driver responses and acceptance of these technologies are critical to their success. If drivers don’t trust the systems or find them annoying or not useful, they may disable them. Similarly, if drivers experience warnings but don’t understand them, are overwhelmed by them, or don’t take an appropriate corrective action, then the systems will be ineffective.

Observations of over 2,000 vehicles that arrived at dealerships of six automakers in 2023 found that automatic emergency braking systems were activated in 93% (Cox et al., 2025).

Among vehicles in the study that were equipped with lane departure warning but not lane departure prevention, 57% had the warning system active.

Most vehicles were equipped with both lane departure warning and prevention. Of those, 87% had either the warning only (11%) or both warning and prevention (76%) activated.

A similar study conducted in 2016 found lane departure systems that warned by vibration were more likely to be activated than those that beeped, and almost all vehicles equipped with blind spot detection and rear-cross traffic alert systems had those systems switched on (Reagan et al., 2018).

Drivers need to be ready and able to respond to a vehicle's warnings or interventions in order for these crash avoidance technologies to work. Many drivers involved in lane departure crashes are asleep or otherwise incapacitated, making it hard to respond (Cicchino & Zuby, 2017; Wiacek et al., 2017). Systems that only warn the driver are not as effective as those that act on behalf of the driver, such as automatic braking (Cicchino, 2017). However, even systems that intervene will likely require a follow-up response from the driver.

In addition to driver challenges, the technology itself can have limitations. For example, lane departure warning and prevention systems use sensors to register lane markings or the road edge, which may be problematic on roads that aren’t well-marked or are covered with snow.

Sensors may not function well in low light or inclement weather. Some systems only work at certain speeds. While pedestrian crash avoidance systems are effective during the day or on lighted roads, they can struggle to detect pedestrians in the dark (Cicchino, 2022). However, systems on newer vehicles have been improving in nighttime performance since IIHS began testing vehicles for pedestrian crash prevention in the dark in 2022.

In driving, automation involves using radar, cameras, and other sensors to perform parts or all of the driving task on a sustained basis. One example is adaptive cruise control, which continually adjusts the vehicle’s speed to maintain a set minimum following distance.

Features such as automatic braking, which acts as a back-up if the human driver fails to brake, or blind spot detection, which provides additional information to the driver, aren’t considered automation under this definition because they provide only temporary assistance.

Not all forms of driving automation are capable of driving the vehicle on their own. Some types of automation require human involvement.

The National Highway Traffic Safety Administration uses definitions of different levels of automation developed by SAE International (SAE International, 2021). The levels range from no automation, or Level 0, to full driving automation, or Level 5. The levels are differentiated by the roles and responsibility that the human and automation have for safely operating the vehicle.

Levels of driving automation

In vehicles in which only some elements of driving, such as steering or controlling speed or following distance, are assisted by the automation (Levels 1-2), drivers are still expected to be actively engaged and to continuously monitor the automation and driving environment. Adaptive cruise control and lane centering are each examples of Level 1 systems. When combined, as in Tesla’s Autopilot software, they are Level 2. At no point can a Level 2 system, also known as partial driving automation, ever replace the driver.

Level 3 driving automation, also called conditional driving automation, is able to operate without driver involvement under certain conditions within certain areas. When it approaches the boundaries of its operation area or if the driving conditions change within its operating area, it will require the driver to take over control of the vehicle.

Level 4 driving automation has total control of the vehicle within a defined area, and it does not operate outside of that area.

Level 5 systems can operate on their own without driver involvement anywhere.

Most automakers now offer partial (Level 2) driving automation in at least some of their vehicles. Mercedes-Benz became the first automaker to offer conditional (Level 3) driving automation to consumers in the United States in the 2024 model year (Mercedes-Benz, 2023).

At present, there are no Level 5 systems on our roads. All of the technology that is currently available to consumers, either in personal vehicles or as part of ride-hailing services, is constrained to specific road and environmental conditions.

While partial driving automation may be convenient, we don’t know if it improves safety.

Recent studies by HLDI have yielded mixed findings about any safety benefits beyond the crash avoidance features typically included on vehicles with such systems (HLDI, 2019; HLDI, 2019; HLDI, 2022).

Similarly, using police-reported crash data, IIHS did not find any crash-reduction advantage for vehicles equipped with partial driving automation compared with vehicles from the same automakers that were only equipped with crash avoidance technologies (Cicchino, 2025).

Much of the technology available in current vehicles, such as adaptive cruise control and lane centering, typically works only on higher-speed roadways where crashes are relatively infrequent. Even if all interstate miles were logged by vehicles driven entirely by automation that did not crash, the maximum overall benefit would be 17% fewer crash deaths and 9% fewer crash injuries than when driven by a human without automation assistance (IIHS, 2016).

Partially automated systems may also have unintended consequences, as drivers become disengaged because the vehicle is handling more of the driving (Reagan et al., 2021). System misuse has already been implicated in fatal crashes (NTSB, 2017; NTSB, 2020; NTSB, 2020; NTSB, 2024).

Automakers use various driver monitoring and alert strategies to help drivers return their attention to the road if they get distracted while using partially automated systems. Some of these strategies work better than others (Mueller et al., 2021). In addition, some automakers use more proactive solutions to help drivers stay engaged, such as by designing the automation so that drivers can make minor steering adjustments within the travel lane without it deactivating, also known as cooperative steering (Mueller et al., 2025).

IIHS began rating the safeguards built in to partial automation systems, including driver monitoring, escalating attention alerts and fail-safe procedures, in 2024.

Partial automation safeguard ratings

Drivers also need to understand the limits of Level 2 systems so that they don’t expect the technology to handle more than it was designed to. An IIHS study found that people who regularly use these systems often have a false sense of security about what the technology can do (Mueller et al., 2024). Other studies have shown that over-trusting these systems can prevent people from intervening even when they see a hazardous situation occurring in front of them (Schneider et al., 2022; Victor et al., 2018).

It is often assumed that higher levels of driving automation will come with improved safety, but that is not a guarantee (Mueller et al., 2020). The potential injury and fatality reductions associated with vehicles that can drive themselves will ultimately depend on whether the technology is designed to avoid crashes or to prioritize consumer preferences, even if doing so comes at the cost of safety — for example, by exceeding the speed limit.

Highly automated vehicles — those with an automated driving system that falls within Levels 3-5 — are challenging to regulate due to the pace of innovation. By the time laws and regulations are enacted, the technology has changed and the laws and regulations may be obsolete.

The U.S. Department of Transportation has issued guidance to help state lawmakers address testing and deployment of automated vehicle technology and to encourage a consistent legislative approach nationwide. Many states, though, have chosen to be more prescriptive.

In 2011, Nevada became the first state to enact legislation specifically permitting research and testing of vehicles with partial and full automation on public roads. Today 35 states and the District of Columbia have laws, regulations or policies that establish specific parameters for testing or deploying highly automated vehicles. They typically require such vehicles to comply with existing laws on motor vehicle operation as well as to meet federal motor vehicle safety standards. In many cases, they prohibit local governments from imposing additional requirements.

Some states allow operation without a licensed driver in the vehicle. Those that do generally require the vehicle to be capable of bringing the vehicle to a stop on the shoulder or otherwise achieve a “minimal risk condition.”

Vehicles that drive themselves (Levels 4 and 5) are only available right now as part of ride-hailing, freight or delivery services and are not available to consumers for purchase. In August 2016, the world’s first taxi service featuring high levels of automation debuted in Singapore (Watts, 2016). In 2016, Uber began allowing select customers in Pittsburgh to hail a vehicle that drives itself with a human supervisor, marking the first time the public could ride in this type of vehicle in the United States (Hawkins, 2017). On October 8, 2020, Waymo began its driverless ride-hailing service in the Phoenix metro area (Waymo, 2020) and, along with other companies (e.g., Zoox and Nuro), has expanded its service to other cities, such as San Francisco, Los Angeles and Austin, Texas.

Regardless of when vehicles equipped with high levels of automation become available to the private consumer to purchase, it will be decades before most vehicles on the road drive themselves. It takes a long time for new vehicle features to penetrate the vehicle fleet. For example, electronic stability control was introduced in the United States in 1995 models, but it was not until more than 20 years later in the 2017 model year that it became standard on all new vehicle models (HLDI, 2025). Since most people don’t drive brand new vehicles, it won’t be before the 2030s that 95% of the vehicles on the road have ESC.

Vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, collectively known as connected vehicle technology (V2X), are safety systems in which vehicles and roadway infrastructure communicate with each other over a wireless network.

With V2V communication, vehicles transmit information regarding their actions to other vehicles. For example, in a long chain of vehicles, if the lead vehicle suddenly brakes, this information will be transmitted to every other vehicle in the chain so that the other vehicles are notified. It also could be possible for the trailing vehicles to automatically begin braking when the lead vehicle’s signal is received.

With V2I communication, cars receive from and transmit information to roadway infrastructure. For example, highway systems could monitor vehicle location within a lane. If a vehicle is detected to be drifting out of a lane, the system could alert neighboring vehicles. In urban environments, traffic signals can alert vehicles of an impending light change so drivers can prepare to stop or the vehicle can automatically slow down if the driver does not.

Two V2V functions, intersection movement assist and left turn assist, warn drivers or intervene on their behalf when they are at risk of crashing with another vehicle when entering or turning left at an intersection. NHTSA estimates that together these functions could potentially prevent up to nearly 600,000 crashes and about 1,300 fatalities annually when fully deployed through the light vehicle fleet (Office of the Federal Register, 2017). IIHS research shows they could be of particular benefit for older drivers, who are more often involved in intersection crashes (Cox et al., 2023).

However, there are some barriers to wide adoption, such as the FCC’s regulatory restrictions that limit the spectrum available for the technology.