Autonomous Vehicles - KPIT
Autonomous Vehicles - KPIT
Autonomous Vehicles - KPIT
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Radar<br />
needs an attention, there exists an ADAS<br />
feature to assist the driver. There are many<br />
such systems available as the aftermarket<br />
solution or in the new cars.<br />
Lidar/<br />
Laser<br />
NIR/FIR<br />
Optical<br />
Figure 3: Commonly used Sensors in ADAS<br />
Adaptive Front Light System<br />
Automatic high Beam<br />
High Beam Assist<br />
Night vision Enhancement<br />
Adaptive Cruise Control<br />
Lane Keep Assist<br />
Automatic Parking<br />
3-D surround view<br />
Ultrasonic<br />
Blind spot Monitoring<br />
Driver Status Monitoring System<br />
Forward Collision Warning<br />
Pedestrian Detection System<br />
Intersection Collision Warning<br />
Lane Departure Warning<br />
Reversing Collision Avoidance<br />
Traffic sign Recognition<br />
Figure 4: Advanced Driver Assist Systems<br />
Existing ADAS uses different sensors and<br />
each one has its pros and cons. Out of these,<br />
cameras are perceived as being more popular<br />
and reasonably reliable sensors to build ADAS<br />
features. The reason being cameras can see<br />
and recognize objects. There are some<br />
specific tasks that only camera can do such as<br />
detection of lanes, reading traffic signs,<br />
classifying a vehicle and a pedestrian.<br />
Whether it's a vehicle, pedestrian, traffic sign,<br />
lanes, etc. camera can detect and classify<br />
them. Other sensors can detect some of these<br />
objects, rather more precisely in terms of<br />
distance and consistency, but can't recognize<br />
them as a particular type. Thus, with the fusion<br />
of camera with other sensors most of the<br />
driving scenarios can be sensed and relevant<br />
information can be provided to the driver.<br />
So far what we have talked about in ADAS was<br />
about 'sensing' and now the second important<br />
thing in driving is the 'control'. Based on the<br />
alerts received from the sensors, the driver<br />
controls longitudinal and latitudinal movement<br />
of the car. He performs different operations<br />
like, decelerates the engine speed, applies<br />
brakes, controls steering, etc. However, the<br />
control depends entirely on his personal<br />
judgment about how much of a deceleration is<br />
required, the amount of brakes to be applied<br />
and how much a steering wheel to be turned.<br />
This, however, does not save the driver from<br />
accidents every time, as the decision made by<br />
the driver to control the vehicle is based on his<br />
experience, reflexes, mental state and the<br />
type of vehicle, brakes and engine. The<br />
reaction from the driver may not be<br />
appropriate and it varies time to time and from<br />
driver to driver.<br />
Sensor<br />
Signal<br />
Processing<br />
Sensing<br />
Detection<br />
Control<br />
Decision<br />
Control<br />
Figure 5:Typical flow of operation for ADAS<br />
Send Control<br />
Signal<br />
ADAS extends its support in controlling the<br />
vehicle by reducing human intervention in<br />
case of an emergency. Systems like AEB<br />
(<strong>Autonomous</strong> Emergency Braking), ACC<br />
(Adaptive Cruise Control), and LKA (Lane<br />
Keep Assist) are safety critical systems that<br />
take the control of the vehicle. This extension<br />
of ADAS, to certain extent, has been<br />
successful in reducing fatalities. Control is<br />
crucial and is designed to avoid collisions or<br />
reduce the impact in case of inevitable<br />
collisions.<br />
III. Towards an <strong>Autonomous</strong><br />
Vehicle<br />
ADAS with the coordination of sensors and<br />
the control mechanism has contributed to<br />
providing eyes and brain to the car; an aid that<br />
can sense the situation and react by<br />
controlling brakes, powertrain, chassis and<br />
infotainment. This amazing coordination has<br />
paved the ways to realize a car without a driver<br />
and give a strong belief that not only in case of<br />
hazardous situations but also under normal<br />
circumstances a car can be operated<br />
automatically and does not need a driver.<br />
However, there are more challenges to make<br />
a fully autonomous vehicle than providing<br />
assistance to the driver.<br />
Nissan has recently announced the plan to<br />
launch their autonomous vehicle by 2020.<br />
Steve Yaeger, a Nissan spokesman, also<br />
iterated “providing assistance when a driver<br />
fails to react is a technical challenge, but<br />
developing a foolproof artificial intelligence<br />
system that can make all driving decisions is<br />
far more complex” [1]. It clearly indicates that<br />
the transition, from ADAS to an autonomous<br />
car, is not going to be an easy one. However,<br />
ADAS has provided a technology to an<br />
automotive world that is leading us to an<br />
autonomous vehicle.<br />
A report from Navigant Research has<br />
predicted “the first autonomous car sales to<br />
take place in 2020 and growing to over 95<br />
million vehicles some fifteen years later,<br />
representing around three quarters of all light<br />
vehicle sales in 2035” [2].<br />
An autonomous vehicle uses information<br />
coming out of cameras, Infrared, LIDAR,<br />
RADAR, other vehicle sensors and global<br />
positioning sensors to maneuver the vehicle<br />
TechTalk@<strong>KPIT</strong>, Volume 6, Issue 4, 2013 529