Integrated sensors in a vehicle that detect a possible accident within a given period can reduce the chances of accidents in the shortest time possible. To ensure safety, modern cars are equipped with several sensors that enable them to detect and gather information about possible accidents, and then act accordingly to avoid these accidents. As more sensors are added for reducing accidents, society is in the process of creating safer roads.
This article discusses the types of vehicle sensors, what each of them does, and how they prevent accidents.
1. Understanding Vehicle Sensors
What Are Vehicle Sensors?
A vehicle’s sensors can be broadly defined as any electronic device that can detect a property and respond to it by transmitting a signal that is further processed into useful information (such as speed, distance to the vehicle ahead, road conditions, etc), so that decisions for safety, performance and comfort can be made in real time by the vehicle’s ECUs (ie, electronic control units).
Types of Vehicle Sensors
The sensors used in passenger cars have different functionalities, and they include: 1. Radar sensors is the most frequently used kind of sensors to prevent accidents. 2. The next popular sensors are cameras.
Radar Sensors: Detect the distance and relative speed of objects around the vehicle.
Sensor: Unlocks nearby cars for car-to-car communications Top-mounted Camera Sensors: Detect road signs, lane markings, pedestrians, animals, cars, and trucks Radar Sensor: Detects surrounding cars and motorbikes LiDAR Sensors: Create 3D surroundings and track road edges Middle Front Radar Sensor: Detects objects, bicycles, and motorbikes Side and Rear Radar Sensors: Detect objects Side and Rear Cameras: Detect objects Front Facing Camera: Detects pedestrians and objects 3D Dot Matrix LED Screen: Display warnings and vehicle information 1
Ultrasonic Sensors: Measure the proximity of objects, typically used in parking assistance systems.
Lidar Sensors: Use laser light to create high-resolution 3D maps of the vehicle’s surroundings.
Infrared Sensors: Detect heat signatures from living beings, useful in night vision systems.
2. The Role of Vehicle Sensors in Accident Prevention
1. Collision Avoidance Systems
A principal application is a collision avoidance system, which attempts to detect collisions between vehicles and takes corrective actions to avoid them. These systems typically rely on radar, lidar (an optical variant of radar) and vision band sensors for their sensing ability, monitoring the surroundings of the vehicle.
How It Works:
Forward Collision Warning (FCW): Radar or camera sensor alerts the driver to vehicles or objects ahead that make an impact in the next few seconds unlikely to avoid if no evasive action is taken.
Automatic Emergency Braking (AEB): If the driver doesn’t respond to a collision warning, the system automatically brakes to reduce the force of the soon-to-be collision.
Rear Collision Warning: Using ultra sonic sensors and rear cameras that detect objects behind the car, the system can alert you of the threat or automatically brake for you.
Impact on Safety:
Collision avoidance systems drastically reduce the likelihood of rear-end collisions where a car runs into the one in front, one of the most common types of accident. If it intervenes when a driver does not tap the brakes in time, it will at least avoid or mitigate the accident.
2. Lane Departure Warning and Lane Keeping Assist
Systems that aim to prevent side-swipe and head-on collisions include lane departure warning (LDW) and lane keeping assist (LKA) systems that use camera sensor ‘measures the lateral position of the vehicle within the lane’, according to NHTSA.
How It Works:
Lane Departure Warning: Alerts the driver if a vehicle starts to drift out of its lane without signalling. It uses camera sensors to detect lane markings.
Lane Keeping Assist: If the vehicle drifts out of its lane, it can correct back into its lane with a small steering input so that the driver isn’t surprised by a warning of an unintentional lane departure.
Impact on Safety:
Such LDW and LKA systems can help avoid accidents due to impaired driving, for example, because the driver is distracted or drowsy by keeping the vehicle in the lane and avoiding collisions with other vehicles or objects along the roadside.
3. Blind Spot Detection
In vehicles, blind spot detection systems use radar or ultrasonic sensors to monitor those areas on the sides and to the rear of the vehicle that aren’t visible from the driver’s seat, in order to reduce the accidents which can occur when changing lanes.
How It Works:
Blind Spot Monitoring: Detects vehicles located in the driver’s blind spots when rear-view mirrors do not allow for their visualization. A visual or auditory signal alerts the driver to the presence of a vehicle.
Rear Cross-Traffic Alert: This system uses radar sensors that detect vehicles approaching from either side and warn the driver if there’s a risk of collision when backing out of a parking space.
Impact on Safety:
Blind spot detection systems are a useful safety measure as they help to avert collisions experienced from the side, particularly where multiple lanes exist beside each other. By alerting drivers to the presence of cars in the blindspots of their vehicles while changing lanes or reversing, these systems help to avoid communication breakdown between adjoining lanes, thereby increasing vehicular safety.
4. Adaptive Cruise Control
Adaptive cruise control (ACC) sensors – radar and/or camera systems that track the car ahead – keep following distance constant, reducing the need to brake and restart the cruise control on highway traffic conditions.
How It Works:
Speed tuning: Radar sensors measure the relative speed and distance to the vehicle ahead, and the system brakes and accelerates to maintain a safe driving distance.
Stop-and-Go Functionality: Some versions of ACC can bring the vehicle to an absolute stop and then move the vehicle again when traffic clears, which can be especially helpful in stop-and-go traffic.
Impact on Safety:
ACC aims to avoid rear-end collisions by monitoring the vehicle ahead, keeping a safe distance from it, and this can lead to more miles being driven on motorways, which are considered safer than urban roads. This also provides the driver with more leisure in terms of driving, making journeys more relaxing and potentially reducing sources of stress for drivers.
5. Pedestrian and Cyclist Detection
The systems that detect pedestrians and cyclists, designed to help avoid collisions, combine cameras, radar and infrared sensors.
How It Works:
Detection: The vehicle’s sensors detect pedestrians or bicyclists that might be nearby during unsafe conditions, like low light or urban driving.
Automatic braking: if a pedestrian or cyclist is detected in the car’s way, the system can issue warnings or autonomously apply the brakes to prevent a collision.
Impact on Safety:
They are also indispensable in busy cities with lots of pedestrian and cycle traffic, as they can detect collisions with vulnerable road users and avoid them before they happen, preventing serious injuries and fatalities.
6. Night Vision Systems
Night vision systems are used for the purpose of helping drivers see into the dark by detecting the presence of objects and living beings using infrared sensors (that can normally be observed only in low light and darkness).
How It Works:
Infrared imaging: Infrared sensors detect the thermal signature of bodies and objects and project it on the screen of the tachometer in the dashboard.
Alerts: If the system identifies a potential risk, such as a pedestrian, an animal or some other obstacle, it can trigger an alert to the driver.
Impact on Safety:
This is especially important in low-light type situations – where there can be high risk of accidents, such as driving at night or in fog, where there is the potential for other road hazards to become visible before the driver without the night vision system has a chance to recognise them.
3. The Future of Vehicle Sensors in Accident Prevention
1. Sensor Fusion and Advanced Driver Assistance Systems (ADAS)
Sensor fusion, in which inputs from various sensors are combined, has the potential to greatly improve the capabilities of vehicle sensors, helping to usher in a new era in Advanced Driver Assistance Systems (ADAS), providing a better real-time awareness of vehicle surroundings that will help to avoid accidents.
Potential Developments:
Better Object Recognition: Sensor fusion can help the system better discriminate between vehicle and pedestrian targets, for example, potentially facilitating earlier, more accurate intervention.
360-Degree Awareness: Integrating data from multiple sensors, including cameras, radar and lidar, will provide complete coverage for a full 360-degree view around the vehicle, which eliminates blind spots and improves the safety of mobility.
2. Autonomous Driving and Accident Prevention
In fact, the question of how to prevent accidents gets even more important as we enter the era of truly autonomous vehicles – machines that use a network of sensors to travel without human intervention, make decisions and keep themselves out of other vehicles’ way.
Potential Developments:
Decision-making in real time: In response to the information coming from its sensors, the autonomous vehicle will have to determine whether to brake, accelerate or steer to avoid the obstacle.
V2X COMMUNICATION: Vehicle-to-Everything (V2X) communication means that oncoming cars will not be the only vehicles to which autonomous vehicles will share sensor data, thus extending accident-prevention capabilities to organisations in infrastructure with connected traffic systems.
3. Artificial Intelligence and Machine Learning
Artificial intelligence (AI) and machine learning (ML) will soon take the sensor sensors that communicate with vehicles to the next level, enabling them to learn over time from their experience in different contexts, and adapt to new circumstances.
Potential Developments:
Predictive Safety Systems: Sensors powered by AI algorithms could anticipate possible collisions before they occur, noting driving patterns, environmental conditions, and past data.
Machine learning algorithms will also improve the accuracy of these sensors, making it easier for them to learn how to avoid accidents. Continuous Improvement: Machine learning is set to enable accident-prevention sensors to improve over time, so that they become even better at their jobs.
Conclusion
Sensors inside the cabin carry out crucial tasks, such as monitoring the driver’s attention to