What sensors are used in modern vehicles

Modern cars feature over 70 sensors that monitor various aspects of the vehicle, with 15 to 30 solely dedicated to tracking engine functions. As the automotive industry moves toward automation, the role of sensors will only increase.

For example, Level 2+ autonomous vehicles require environmental awareness akin to that of a human driver, using a variety of sensors to detect other vehicles, pedestrians, roadside infrastructure, and unexpected obstacles. Each sensor has distinct functions, advantages, and limitations, making it essential for OEMs to select the optimal combination to achieve the vehicle’s purpose at an efficient cost.

In this article, we’ll explore the various types of sensors used in modern cars, focusing on those enabling vehicle autonomy. We’ll also look at the challenges and factors influencing sensor selection in the automotive industry.

Vehicle sensors

Today’s vehicles have several sensors that monitor internal functions and external surroundings. Some track engine and transmission performance, while others enhance vehicle safety and comfort. With automation levels ranging from partial to full autonomy, sensors are critical to enabling different levels of autonomous driving.

Below, we outline some of the key sensors driving these advancements in modern vehicles.

Oxygen sensor: Measures oxygen levels in exhaust gases to optimize fuel efficiency and reduce emissions.
Mass air-flow (MAF) sensor: Tracks the amount of air entering the engine, helping to determine the correct fuel injection for efficient combustion.
Throttle position sensor: Monitors the throttle valve’s position to help control engine power output.
Engine knock sensor: Detects engine knocking, ensuring the air-fuel mixture is ignited properly to prevent damage.
Engine speed sensor: Measures the crankshaft’s rotational speed (in RPM) to monitor engine speed and position.
Crankshaft position sensor: Tracks crankshaft speed and position, enabling the ECU to synchronize fuel injection and ignition timing based on cylinder position and firing order.
Engine coolant temperature sensor: Monitors engine coolant temperature to regulate and maintain optimal engine temperature.
Fuel temperature sensor: Detects fuel temperature before it enters the engine, influencing fuel efficiency.
Engine oil-pressure sensor: Monitors oil pressure to ensure proper engine lubrication, preventing wear and tear.
Manifold absolute pressure (MAP) sensor: Measures pressure within the intake manifold to gauge the amount of air entering the engine, helping determine engine load.
Camshaft position sensor: Monitors the camshaft’s position to control valve timing accurately.
Transmission temperature sensor: Tracks transmission fluid temperature to prevent overheating and ensure optimal performance.
Voltage sensor: Assists in regulating the car’s idling speed.
NOx sensor: Detects nitrogen oxides in the exhaust gases to monitor emissions and maintain compliance with environmental standards.
Tire-pressure monitoring system (TPMS): Continuously monitors tire pressure, contributing to vehicle safety and performance.
Anti-lock braking system (ABS) sensor: Monitors wheel speed to prevent wheel lockup during braking, enhancing control.
Electronic stability control (ESC) sensors: Includes multiple sensors (yaw rate, wheel speed, lateral acceleration, and steering angle) to assess vehicle stability and prevent loss of control.
Yaw rate sensor: Measures the vehicle’s rotational speed around its vertical axis, helping to detect skidding or sudden directional changes.
Speed sensor: Tracks the rotational speed of each wheel to identify wheel slip or lockup, aiding in control.
Lateral acceleration sensor: Monitors the vehicle’s sideways acceleration, assisting in detecting aggressive cornering or excessive lateral force.
Steering angle sensor: Measures the angle of the steering wheel to compare the driver’s input with the vehicle’s actual response.
Rain sensor: Detects rain and automatically activates the windshield wipers.
Light sensor: Monitors ambient light intensity to adjust headlight brightness automatically.
Parking sensor: Uses ultrasonic technology to detect obstacles during parking.
Backup camera: Provides a rear view on the dashboard display to assist with parking and reversing.
Driver monitoring system: Uses a camera to track driver alertness and attention.
Blind spot sensor: Detects hidden traffic or obstacles and alerts the driver.
Night vision sensor: Infrared camera that improves visibility in dark conditions.
Remote keyless entry sensor: Detects radio signals from a remote key for opening or closing doors.
Humidity sensor: Monitors humidity levels inside the vehicle.
Air-quality sensor: Measures cabin air quality.
Accelerometer: Measures acceleration forces, activating safety features like airbags.
Gyroscope: Tracks rotational motion to assist with stability control.
Barometric pressure sensor: Measures atmospheric pressure for altitude and engine performance calculations.
GPS receiver: Provides vehicle location for navigation and tracking.
Seatbelt sensor: Detects if passengers are wearing seatbelts.
Airbag sensor: Detects impacts to trigger airbag deployment.
Sunload sensor: Measures solar radiation to adjust climate control settings.

These sensors play a vital role in modern automotive engines, contributing to efficiency, performance, and longevity.

Sensors for autonomy

All modern vehicles are equipped with basic driver assistance features (Level 1 automation). Many also support Level 2 automation, which includes capabilities like adaptive cruise control (ACC), lane-keeping assist (LKA), and advanced features such as autopilot or super-cruise.

Higher-level vehicle automation, which includes conditional (L3), high (L4), and full automation (L5), are significantly more advanced. It relies on sensors that detect and interpret the surrounding environment, enabling informed driving decisions. A host of sensors work in concert to enable self-driving vehicles.

Each sensor has advantages and limitations. OEMs are continuously experimenting with various sensor combinations to develop innovative systems for vehicle automation. While some manufacturers focus on achieving full automation using only camera sensors, others combine cameras with LiDAR or ultrasonic sensors.

Below are some commonly used sensors in testing and production models to implement vehicle automation.

Cameras: Cameras are among the most practical sensor options for detecting and recognizing objects around a vehicle. They capture detailed visual information about the environment, including traffic signals, lane markings, pedestrians, and other vehicles. Many OEMs are developing autonomous vehicles using only camera sensors. A network of cameras provides a 360-degree view of the surroundings, enabling informed driving decisions.

Cameras excel at providing rich visual data that are essential for object recognition and understanding scenes; however, they struggle with depth perception and accurately estimating distances. Additionally, camera performance can be impacted by adverse weather conditions such as rain, fog, snow, low light, and other environmental factors.

LiDAR: Light Detection and Ranging (LiDAR) technology uses laser beams to measure distances, creating a highly accurate 3D point cloud map of the surrounding environment. LiDAR excels at precise distance measurements and object detection, even in challenging lighting conditions, and it remains unaffected by most weather conditions.

While LiDAR provides impressive 3D mapping, it lacks object recognition and scene interpretation capabilities. The equipment also tends to be bulky and expensive, limiting its potential for widespread adoption in vehicle automation.

RADAR: Radio Detection and Ranging (RADAR) technology maps the vehicle’s surroundings by emitting radio waves to detect objects and measure their distance, speed, and direction. Like LiDAR, radar functions effectively in all weather conditions (including fog and darkness) and is more affordable. However, it has lower resolution than LiDAR, making it less precise in identifying objects. Additionally, like LiDAR, radar does not capture visual information, so it cannot be used for object recognition or scene interpretation.

Ultrasonic sensors: Ultrasonic sensors emit high-frequency sound waves to detect nearby objects and are commonly used for parking assistance and obstacle detection. They’re inexpensive and reliable for short-range detection, although limited in mapping a vehicle’s overall surroundings. Despite this, ultrasonic sensors play a crucial role in collision avoidance.

GPS: GPS technology provides precise location information for the vehicle, essential for navigation and route planning in autonomous vehicles. It’s critical for long-range navigation and mapping, although it can experience inaccuracies in urban areas due to weak signals. Despite these limitations, GPS remains indispensable for route tracking and navigation in self-driving and pilot-mode vehicles.

Inertial Measurement Unit (IMU): The IMU measures the vehicle’s acceleration, deceleration, rotation, and orientation to help maintain stability and control. This unit provides real-time data on the car’s movement, which allows autonomous vehicles to track and follow routes accurately when combined with GPS information. Inertial sensors are vital for detecting the vehicle’s state and orientation, though they may experience sensor drift over time and require periodic calibration.

Sensors for connectivity

The new generation of autonomous vehicles will be connected, actively sharing real-time data on their position, speed, and orientation to minimize collision risks. These vehicles will also feature robust internet connectivity, enabling them to exchange information with roadside infrastructure and access internet services.

Vehicles are equipped with cellular modems for internet access that provide real-time traffic updates, remote diagnostics, and over-the-air updates. Wi-Fi is widely used for communication with smartphones and smart home systems. Additionally, vehicles will incorporate V2X (Vehicle-To-Everything) communication modules for interaction with other vehicles and road infrastructure, utilizing cellular modems, Wi-Fi, or dedicated short-range communication (DSRC) for seamless data exchange.

Sensor fusion

Sensors are essential in modern vehicles for tracking information and ensuring safety. Automation and connectivity sensors are recent additions to the automotive landscape.

While choosing sensors for tracking and safety is straightforward, selecting sensors for vehicle automation — a developing technology — presents new challenges. Different OEMs are taking varied approaches: some rely solely on camera networks, others combine cameras with LiDAR, and more affordable setups use radar or ultrasonic sensors. Each manufacturer tailors its sensor fusion to meet specific goals and requirements for implementing automation.

Cost challenges

The cost of automation is one of the biggest challenges facing the adoption of self-driving technology in vehicles. Sensor prices range from $15 to as much as $1,000, with high-end sensors like LiDAR providing more effective capabilities for automation.

However, the high cost of advanced sensors hinders large-scale adoption. As sensor technologies evolve, so will there prices, making automation more accessible. Optimized sensor fusion could reduce the total number of sensors required for automation to four to eight, although full automation will likely still demand a dozen or more.

Connected cars

Connected car technology, though still in its early stages, holds promise for reducing the number of sensors needed for vehicle automation. By enabling vehicles to communicate with each other and roadside infrastructure, they may rely less on capturing data independently about their surroundings. However, V2X (vehicle-to-everything) communication alone is insufficient for reliable automation; in cases of communication lag or failure, onboard sensors remain essential for enabling safe self-driving functionality.