All of us would like to drive our car with a mobile held in one hand, talking
to the other person. But we should be careful; we don't know when the car just
before us apply the break and everything are gone. A serious problem encountered
in most of the cities, National Highways, where any mistake means no 'turning
back'! There comes the tomorrows technology; Hand free driven car. Initializing
the modern technological approach in Robotics.
What is the need for safety
All around the world almost 45%
of the accidents occur by mistakes of the driver. Most of these accidents are
fatal. The victims of such accidents are either severly injured, some even risk
their life by their careless driving. This was the main reason behind this project
work put forward by the Delphi-Delco electronic systems and General Motors Corporation.
It was called the Automotive Collision Avoidance Systems (ACAS) field operation
It was aimed at integration
of the latest technology Forward Collision Warning (FCW) and Adaptive Cruise Control
(ACC). The project has two phases. The Phase I started by June 1999, it lasted
for about 27 months and II phase started immediately just after the Phase I and
expected to be complete by 32 months.
The phase I include development and
integration of ACC and FCW systems on the automotive. The phase II include the
deployment fleet on ten cars and field operation test.
Forward Collision Warning (FCW) System was one of the achievements of the Delphi-Delco
Electronic Systems, which was successfully implemented in the (a) 1994 Toyota
Lexus LS400 (b) 1994 GM Cadillac Seville, and (c) 1998 Opel Vectra. These vehicles
have been modified to provide the basic functionality of fully integrated ACC
and FCW systems. Forewarn Smart Cruise Control with Headway Alert uses a mechanically
scanning, 76 GHz, long-range radar sensor to detect objects in the vehicle's path
up to 150 meters or 402 feet ahead. The system helps to reduce the need for drivers
to manually adjust speed or disengage cruise control when encountering slower
Adaptive Cruise Control (ACC) and Forward Collision
Warning (FCW) systems require an ability to resolve and identify robustly the
existence of both stationary and moving 'target' vehicles that are in the motion
path of the Host vehicle. The performance of these systems is affected by their
ability (a) to estimate the relative inter-vehicular path motion (i.e.: range,
relative speed, radius of curvature, etc.) between the host vehicle, the roadway
ahead of the host, and all of the appropriate targets (i.e.: roadside objects,
and in-lane, adjacent lane, and crossing vehicles, etc.); and (b) to predict the
mutual intersection of these motion paths. In addition, these systems must be
robust in the presence of various types of driving behavior (e.g.: in-lane weaving/drift,
lane change maneuvers, etc.) and roadway conditions (e.g. straight roads, curved
roads, curve entry/exit transitions, intersections, etc.) that are encountered
in the 'real-world' environment.
target selection approach pursued used a single active forward looking radar sensor
augmented with a yaw rate sensor. The forward-looking radar sensor provided target
range, range rate, and angular position information. The yaw rate sensor was used
to estimate the roadway curvature ahead of the Host vehicle. Delphi's first generation
target discrimination algorithms were used to identify overhead bridge objects
and to discriminate between moving cars and trucks. The Target / Host kinematics
were evaluated to determine target motion status (i.e.: oncoming, stopped, moving,
cut-in and cut-out, etc.), and geometric relationships were employed to determine
which of the valid roadway objects fell within the Host's forward projected path.
The improved algorithms yielded very good results, but they were prone to false
alarms during curve entry/exit scenarios and during host lane changes.
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