How ADAS Handles Pedestrians, Animals, and Non-Motorised Traffic on Indian Roads
- 2 days ago
- 4 min read
Table of contents
Indian roads are complex.
Cars, trucks, two-wheelers, pedestrians, cyclists, carts, and animals share the same space. Lane discipline is weak. Movement is unpredictable. This makes road safety a serious challenge.
Advanced Driver Assistance Systems, or ADAS, aim to reduce accidents. But their real test is simple:
Can ADAS detect and respond to pedestrians, animals, and non-motorised traffic in India?
The answer depends on how the system is built.
Why Pedestrians and Non-Motorised Users Face the Highest Risk
Pedestrians and cyclists are the most vulnerable road users.
According to the Ministry of Road Transport and Highways, pedestrians, cyclists, and two-wheeler riders form a large share of road fatalities in India. Their movements are unprotected and unpredictable.
Animals increase the risk further. Cattle often cross highways without warning. These incidents are common at night and on rural roads.
ADAS must handle these realities to improve safety.
Why Indian Traffic Is Hard for ADAS Systems
Most ADAS systems are designed outside India.
They assume:
Clear lane markings
Defined pedestrian crossings
Predictable traffic flow
Indian roads do not follow these patterns.
Research on mixed traffic shows that non-lane-based movement reduces the accuracy of perception systems.
This is why India needs ADAS systems trained for local traffic behavior.
How ADAS Detects Pedestrians, Animals, and Cyclists
Radar Is the Foundation
Radar is critical for Indian conditions.
Radar works well because it:
Detects objects in rain, fog, and darkness
Measures distance and speed accurately
Detects slow or stationary objects
This is why 77GHz radar is now the global standard for safety systems.
Radar is especially useful for detecting animals standing still on highways.
Cameras Add Object Understanding
Cameras help identify what the object is.
They can tell:
A pedestrian from a vehicle
A cyclist from a motorcycle
A cart from a car
But cameras struggle at night or in glare.
Euro NCAP testing shows reduced camera performance in low-light conditions without radar support.
This is why sensor fusion is essential.
AI Models Must Understand Indian Behaviour
Detection alone is not enough.
ADAS must predict what happens next.
For example:
A pedestrian walking along the road is low risk
A pedestrian turning toward traffic is high risk
Animals often change direction suddenly
AI models trained on local data perform better in such cases.
India-specific training improves accuracy and reduces false alerts.
How ADAS Responds to Vulnerable Road Users
ADAS systems respond in steps.
Forward Collision Warning (FCW)
FCW alerts the driver when a collision risk appears.
These alerts help drivers react faster in mixed traffic.
Pedestrian and Cyclist Emergency Braking
Automatic Emergency Braking applies brakes if the driver does not react.
Studies by the Insurance Institute for Highway Safety show that pedestrian AEB reduces crashes significantly.🔗 https://www.iihs.org/news/detail/pedestrian-aeb-reduces-crashes-study-finds
This feature is critical on Indian roads.
Driver Monitoring System Integration
ADAS works best with driver monitoring.
DMS checks if the driver is alert. It ensures warnings are noticed.
Driver distraction is a known cause of pedestrian accidents worldwide.
Why Many ADAS Systems Struggle in India
Many systems underperform due to:
Camera-only designs
Poor calibration
Too many false alerts
Lack of local training data
False alerts reduce trust. Drivers start ignoring warnings.
Trust is essential for safety systems to work.
How Starkenn Solves These Problems
Starkenn designs ADAS for Indian roads from the start.
Radar-Led System Design
Starkenn uses automotive-grade radar as the core sensor.
This ensures:
Reliable detection of pedestrians and animals
Strong performance in low visibility
Accurate speed and distance estimation
AI Trained on Indian Roads
Starkenn trains its AI models using real Indian driving data.
This includes:
City congestion
Highway animal crossings
Mixed traffic with carts and cyclists
The system understands intent, not just objects.
Intelligent Sensor Fusion
Radar and camera data are fused in real time.
This:
Reduces false alerts
Improves detection accuracy
Builds driver confidence
This matters for fleets operating long hours.
OEM-Ready and Regulation-Aligned
Starkenn’s ADAS stack is built for OEM integration.
It aligns with Indian testing and validation practices supported by ARAI.🔗 https://www.araiindia.com/CMVR_TAP.aspx
This helps OEMs and fleets meet safety goals efficiently.
Why This Matters for OEMs and Fleets
For OEMs:
Better safety performance
Lower liability risk
Stronger product differentiation
For fleets:
Fewer pedestrian and animal accidents
Reduced downtime and costs
Improved driver confidence
Final Thoughts
Indian roads need ADAS that works in real conditions.
Pedestrians, animals, and non-motorised traffic are the true test of safety systems.
By combining radar-first sensing, India-trained AI, and OEM-ready design, Starkenn delivers ADAS that solves today’s road safety challenges, where it matters most.
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