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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

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