Autonomous driving vehicles have been a focus area for investments not just in the automobile industry but also from renowned names in the tech world. While mainstream self-driving vehicles are already dotting the roads in major cities worldwide, their degree of maturity is still not universally accepted. But with the level of advancements being made in AI, it won’t be long before every new vehicle launched is fitted with self-driving features. But to go mainstream, automakers need to sharpen their focus on Light Detection and Ranging or LiDAR, often called “The eye of autonomous vehicles.”
What Is LiDAR?
LiDAR leverages a combination of laser light sensors and GPS systems to enable vehicles to drive ahead safely. It works by continuously detecting any objects or obstacles that may fall in the driving path and signal the car to take corrective actions like stopping or steering away at the right time and distance from the object. LiDAR systems emit hundreds of thousands of light pulses every second. They compute metrics like distance to objects, object category, dimension of objects, etc., from the reflection received from the emitted light pulses after they strike an object in the path.
How Does LiDAR Empower Autonomous Vehicles with Safer Self-Driving?
The way LiDAR communicates to a vehicle control system to take driving actions based on the line of sight of the laser requires a deeper understanding of the technology. We all know that a safe journey requires not just disciplined driving habits but also impulsive skills to quickly recognize danger and act at lightning speed. Achieving this trait for digital control systems requires significant engineering and computing expertise. This is where LiDAR becomes critical for autonomous vehicles.
Let us explore four ways in which LiDAR makes self-driving vehicles safer to be in:
Identification of the Right Object
The computation done by a control system in self-driving vehicles must be highly precise as it must be able to respond according to the nature of objects in its path. A random object like a fallen tree branch or a car slowing down invites a different response than a situation where a human jumps in front of the vehicle out of nowhere. This brings in the feeling of impulsive driving control that is often exhibited by skilled drivers.
Computational models used by LiDAR systems can be powered by highly intelligent AI systems that are trained on a diverse range of data pertaining to physical objects and their dimensions and motion patterns.
LiDAR systems ensure that there is a 360-degree coverage of objects in the vehicle’s surroundings to ensure that the vehicle not just focuses on going straight safely but is also prevented from accidental collisions happening from the sides or rear. Sensors emit and track light reflections from all directions of a vehicle and continuously monitor threats.
Disciplined Lane Traffic
Safety is a critical ability that is enabled by LiDAR systems. But it also enables self-driving vehicles to observe and operate on standard best-lane movement practices. LiDAR systems can also monitor road lanes and vehicular traffic on the roads. This helps instruct the vehicle to maintain a disciplined pace and steady progression, leaving enough room on all sides to prepare for any events or mishaps that may disrupt movement.
Improved Ride Quality
The benefits of having an eye on the road continuously extend to more areas than just safety. It can even be used from a comfort perspective on long drives on roads that have unpredictable drivability trends. LiDAR can help self-driving vehicles sense undulations or uneven road deformations well in advance and command the vehicle to adjust its suspension system accordingly. This will ensure that passengers do not experience jerks or uncomfortable bumps while on the journey.
In addition to ensuring a collision-free journey, LiDAR makes it smooth and memorable as well.
Analytics at the Core of Success with LiDAR
LiDAR offers a plethora of benefits that automakers can leverage to make their vehicles more intelligent and safer. However, a large part of this depends on how well LiDAR systems can be configured with the right AI systems and analytics to understand road behavior from visual reference data. This requires a high level of predictive, cognitive, and prescriptive analytics to be run across a wide spectrum of driving and object inference data.
Building models that can drill deep into data patterns to uncover insights necessitates automakers to partner with experienced technology specialists who understand how different class of automotive analytical data works. This is where a partner like Ascentt can make a huge impact on the ROI of LiDAR technology for self-driving vehicles.
Our expertise in high-end AI services and data analytics enables automakers to help their LiDAR systems deliver precise results that can guide the driving dynamics of the vehicle. Get in touch with us to learn more.