06-07-2012, 04:36 PM
Use of Video Technology To Improve Automotive Safety Becomes More Feasible with Blackfin™ Processors
[attachment=27011]
VIDEO IN AUTOMOTIVE SAFETY SYSTEMS
In many ways, car safety can be greatly enhanced by video-based
systems that use high-performance media processors. Because
short response times are critical to saving lives, however, image
processing and video filtering must be done deterministically in
real time. There is a natural tendency to use the highest video
frame rates and resolution that a processor can handle for a given
application, since this provides the best data for decision making.
In addition, the processor needs to compare vehicle speeds and
relative vehicle-object distances against desired conditions—again
in real time. Furthermore, the processor must interact with many
vehicle subsystems (such as the engine, braking, steering, and
airbag controllers), process sensor information from all these
systems, and provide appropriate audiovisual output to the driver.
Finally, the processor should be able to interface to navigation
and telecommunication systems to react to and log malfunctions,
accidents, and other problems.
Smart Airbags
An emerging use of media processors in automotive safety is for
“intelligent airbag systems,” which base deployment decisions on
who is sitting in the seat affected by the airbag. At present, weightbased
systems are in widest use, but video sensing will become
popular within five years. Either thermal or regular cameras
may be used, at rates up to 200 frames per second, and more
than one might be employed—to provide a stereo image of each
occupant. The goal is to characterize the position and posture of
the occupants—not just their size. In the event of a collision, the
system must choose whether to restrict deployment entirely, deploy
with a lower force, or deploy fully. In helping to determine body
position, image-processing algorithms must be able to differentiate
between a person’s head and other body parts.
Collision Avoidance and Adaptive Cruise Control
Another high-profile safety application is adaptive cruise control
(ACC), a subset of collision avoidance systems. ACC is a convenience
feature that controls engine and braking systems to regulate the
speed of the car and its distance from the vehicle ahead. The
sensors employed involve a combination of microwave, radar,
infrared, and video technology. A media processor might
process between 17 and 30 frames per second in real time
from a camera—focused on the roadway—mounted near the
car’s rear-view mirror. The image-processing algorithms may
include frame-to-frame image comparisons, object recognition,
and contrast equalization for varying lighting scenarios. Goals
of the video sensor input are to provide information about lane
boundaries and road curvature, and to categorize obstacles,
including vehicles ahead of the car.
LANE DEPARTURE—A SYSTEM EXAMPLE
In addition to the role that a media processor can play in videobased
automotive safety applications, it is instructive to analyze
typical components of just such an application. To that end, let’s
probe further into a lane-departure monitoring system that could
employ the Blackfin media processor.
Memory and Data Movement
Efficient memory usage is an important consideration for system
designers because external memories are expensive, and their
access times can have high latencies. While Blackfin processors
have an on-chip SDRAM controller to support the cost-effective
addition of larger, off-chip memories, it is still important to
be judicious in transferring only the video data needed for the
application. By intelligently decoding ITU-R 656 preamble codes,
the PPI can aid this “data-filtering” operation.
[attachment=27011]
VIDEO IN AUTOMOTIVE SAFETY SYSTEMS
In many ways, car safety can be greatly enhanced by video-based
systems that use high-performance media processors. Because
short response times are critical to saving lives, however, image
processing and video filtering must be done deterministically in
real time. There is a natural tendency to use the highest video
frame rates and resolution that a processor can handle for a given
application, since this provides the best data for decision making.
In addition, the processor needs to compare vehicle speeds and
relative vehicle-object distances against desired conditions—again
in real time. Furthermore, the processor must interact with many
vehicle subsystems (such as the engine, braking, steering, and
airbag controllers), process sensor information from all these
systems, and provide appropriate audiovisual output to the driver.
Finally, the processor should be able to interface to navigation
and telecommunication systems to react to and log malfunctions,
accidents, and other problems.
Smart Airbags
An emerging use of media processors in automotive safety is for
“intelligent airbag systems,” which base deployment decisions on
who is sitting in the seat affected by the airbag. At present, weightbased
systems are in widest use, but video sensing will become
popular within five years. Either thermal or regular cameras
may be used, at rates up to 200 frames per second, and more
than one might be employed—to provide a stereo image of each
occupant. The goal is to characterize the position and posture of
the occupants—not just their size. In the event of a collision, the
system must choose whether to restrict deployment entirely, deploy
with a lower force, or deploy fully. In helping to determine body
position, image-processing algorithms must be able to differentiate
between a person’s head and other body parts.
Collision Avoidance and Adaptive Cruise Control
Another high-profile safety application is adaptive cruise control
(ACC), a subset of collision avoidance systems. ACC is a convenience
feature that controls engine and braking systems to regulate the
speed of the car and its distance from the vehicle ahead. The
sensors employed involve a combination of microwave, radar,
infrared, and video technology. A media processor might
process between 17 and 30 frames per second in real time
from a camera—focused on the roadway—mounted near the
car’s rear-view mirror. The image-processing algorithms may
include frame-to-frame image comparisons, object recognition,
and contrast equalization for varying lighting scenarios. Goals
of the video sensor input are to provide information about lane
boundaries and road curvature, and to categorize obstacles,
including vehicles ahead of the car.
LANE DEPARTURE—A SYSTEM EXAMPLE
In addition to the role that a media processor can play in videobased
automotive safety applications, it is instructive to analyze
typical components of just such an application. To that end, let’s
probe further into a lane-departure monitoring system that could
employ the Blackfin media processor.
Memory and Data Movement
Efficient memory usage is an important consideration for system
designers because external memories are expensive, and their
access times can have high latencies. While Blackfin processors
have an on-chip SDRAM controller to support the cost-effective
addition of larger, off-chip memories, it is still important to
be judicious in transferring only the video data needed for the
application. By intelligently decoding ITU-R 656 preamble codes,
the PPI can aid this “data-filtering” operation.