Autonomous Vehicle Safety Improved with Lidar

point cloud Autonomous Vehicle Safety Depends on Lidar

Autonomous Vehicle Safety Depends on Lidar

Optical sensing will play an increasingly important role in the evolving autonomous vehicle safety landscape. The greater the level of automation, the more information—and more precise information—the vehicle requires. Currently, automotive OEMs are focused on designing accurate and reliable advanced driver assistance systems (ADAS) for consumers, representing an automation level of 2 and up. In addition, they are developing fully autonomous vehicles with an automation of level of 4+. Both of these types of systems rely heavily upon optical sensors to identify environmental factors such
as other vehicles and oncoming objects quickly and accurately.

Optical sensors can track objects within a certain range of the
vehicle. A simple use of this information is to alert the driver of
any movement within the range (driver assistance). With more
information, such as how fast the object is moving and its
direction of travel, the vehicle can better assess a situation. For
example, the vehicle could slow itself or stop if the driver fails to
notice an object moving behind the vehicle when backing up.

When more precise information is available, objects can be
recognized and their behaviors more accurately predicted. If the
object is a ball, its path of motion is readily discernible. If the
object is a child, the vehicle can take immediate preemptive
action (i.e., braking and/or turning). The greater the availability
and precision of information available, the better the decisions
the vehicle can make.

There are several technologies—radar, imaging, LiDAR, and
thermal—being used to capture information about the
environment around a vehicle. Each provides data that is useful
at different ranges for different use cases.

It has become clear that LiDAR-based 3D sensing is an essential
technology for enabling the evolution from driver assistance to
fully autonomous vehicles. LiDAR provides critical data about the
surrounding environment that ADAS requires to be able to offer
reliable safety. As vehicles become more autonomous and take
over additional driving functions, ADAS will become increasingly
dependent upon LiDAR to enhance perception capabilities in all
operating conditions.

To meet the high-volume, high-quality, and cost-sensitive
requirements of the automotive industry, OEMs need to
implement LiDAR sensors in a way that efficiently integrates
functionality without sacrificing capabilities. This article will
outline a practical approach for utilizing innovative LiDAR
technology while balancing cost, manufacturability, performance,
and reliability.

LiDAR Basics
A basic LiDAR-based system includes a light source, beam
steering capabilities, image components, detection, and
packaging (see Figure 2). Currently, LiDAR is used to gather
environmental information for both short range and long range
applications.

Given the complexities and variances of vehicles and the
environments in which they must operate, LiDAR must meet
stringent requirements to be useful in automotive applications.
The detection system must have immunity to light and other
LiDAR signals (such as those from oncoming cars). For reliability,
the system must also be robust to ever-changing environmental
factors such as vibration and thermal changes.

For the complete white paper on autonomous vehicle safety click here.

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1 Response to Autonomous Vehicle Safety Improved with Lidar

  1. ASTM D7953 says:

    This optimal senses technology is very helpful in many fields. It ensures safety standards to a great level by helping to prevent accidents. Whether it is about the field of vehicle safety, construction safety or anything else, optimal senses technology is there to help people. Thanks.

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