Table of Contents
1 Introduction
2 How ADAS Works
3 Types of ADAS
4 Sensor technology in ADAS
5 ADAS Features
6 Advantages
7 challenges
8 Application
9 Future scope
10 Conclusion
11 References
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Introduction
ADAS
Advanced Driver Assistance Systems (ADAS) technologies designed to enhance
vehicle safety and driver experience.
ADAS is to mitigate the risk of accidents, improve road safety, and provide
additional comfort to drivers through intelligent automation and assistance.
ADAS has evolved from basic systems like cruise control to sophisticated
technologies using sensors, AI, and machine learning.
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Evolution and historical context
Pre-2000s : cruise control and anti-lock braking systems (ABS).
Late 20th Century : Electronic stability control (ESC) , Adaptive cruise control
Early 21st Century : Sensor technology led to the integration of Radar , camera ,
ultrasonic sensor
Mid-2010s : Automatic emergency breaking , advanced parking
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How ADAS Works
fig.1
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How ADAS Works
fig.2
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Types of ADAS
Passive ADAS
features that provide warnings or alerts to the driver but don’t actively intervene in
the vehicle’s operation
These systems aim to enhance driver awareness and safety without directly
controlling the vehicle.
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Types of ADAS
Active ADAS
ADAS are technologies that not only provide warnings but also actively intervene in
the vehicle’s operation to enhance safety
These systems can autonomously adjust the vehicle’s speed, apply brakes, or assist
with steering to prevent or mitigate collisions.
Active ADAS plays a more direct role in influencing the vehicle’s dynamics compared
to passive systems.
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Sensor technology in ADAS
CAMERA
Optical cameras capture visual information to identify lane markings, traffic signs,
pedestrians, and other vehicles.
They play a crucial role in systems like lane departure warning and forward collision
warning.
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Sensor technology in ADAS
RADAR
Radar sensors use radio waves to detect objects around the vehicle. .
They are effective in various weather conditions and are often used for adaptive
cruise control and collision avoidance systems
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Sensor technology in ADAS
LIDAR
Lidar sensors use laser beams to measure distances and create detailed 3D maps of
the vehicle’s surroundings.
Lidar is valuable for object detection and mapping in autonomous driving and
advanced parking assistance.
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Sensor technology in ADAS
Ultra Sonic Sensor
Ultrasonic sensors use sound waves to detect obstacles in close proximity to the
vehicle.
They are commonly used for parking assistance and object detection at low speeds.
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Sensor technology in ADAS
GPS
GPS receivers provide location data, which, when combined with other sensor data,
contributes to navigation systems and certain ADAS functions.
Current GPS tracking hardware can use AI and navigation data to direct drivers to
roads where hard-braking is less likely
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ADAS Features
Adaptive Cruise Control
Automatic Emergency Braking
Lane Departure Warning (LDW) and Lane-Keeping Assist (LKA)
Forward Collision Warning
Blind Spot Detection
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Advantages
Improved Driver Awareness
Reduced Fatigue
Enhanced Safety
Increased Comfort
Traffic Sign Recognition
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challenges
Integration Complexity
Reliability and Safety
Cost
Data Security
Environmental Factors
Driver Understanding and Trust
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Application
fig.3
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Future scope
Autonomous Driving Features
Enhanced Sensor Technology
Artificial Intelligence Integration
Extended Communication Capabilities
Augmented Reality Displays
Cybersecurity Enhancements
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Conclusion
Advanced Driver Assistance Systems (ADAS) represent a transformative evolution
in automotive technology, aiming to enhance road safety, improve driver
convenience, and pave the way for increased vehicle autonomy. With a diverse
range of features such as collision avoidance systems, adaptive cruise control, and
lane-keeping assistance, ADAS contributes to mitigating the risks associated with
driving.
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References
[1] S. Raviteja and R. Shanmughasundaram, “Advanced driver assitance system
(adas),” in 2018 Second International Conference on Intelligent Computing and
Control Systems (ICICCS), 2018, pp. 737–740. doi:
10.1109/ICCONS.2018.8663146.
[2] J. Nidamanuri, C. Nibhanupudi, R. Assfalg, and H. Venkataraman, “A progressive
review: Emerging technologies for adas driven solutions,” IEEE Transactions on
Intelligent Vehicles, vol. 7, no. 2, pp. 326–341, 2022. doi:
10.1109/TIV.2021.3122898.
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Thank you!
Questions?
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