driverless cars

ROBOT CARS-DRIVERLESS/AUTONOMUS CARS

CONCEPT OF DRIVERLESS CAR

• It is an ‘AUTOMATED’ computer driven vehicle.• Runs on ‘AUTO-PILOT’ mode.• Capable of sensing its environment and

navigating without human input.• Advanced control systems interpret sensory

information to identify appropriate navigation paths, as well as obstacles and relevant signage.

ROBOTIC car works on coordination of several sensory inputs combined together from sensing positioning of vehicle on a real time basis installed at

different points on vehicle.

STARTING OF ROBOTIC VEHICLE• Since 1920s work on automating

cars have begun.• 1st self sufficient-automated car

came in 1980 by Carnegie Mellon University's Navlab and ALV projects in 1984 and Mercedes-Benz and Bundeswehr University Munich's EUREKA Prometheus Project in 1987.

• Apple, Alphabet, Uber and other tech companies are all working on self-driving car projects.

• Latest entry of GOOGLE in testing of self-driven vehicles has gathered momentum of this technology making to roads by 2020.

• UK govt. has formally assigned £19million as an self-driving research grant.

• The Greenwich self-drive project is being led by Britain's world-renowned Transport Research Laboratory (TRL) along with the RAC Foundation.

NEED OF THE HOUR

• An average of 6 working weeks can be saved for a car been driven for 365 days

• In addition, automated vehicles that never get tired or distracted could hold the key to substantially improving road safety.

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WORKING OF ROBOT CAR

Laser Range Finder

• The heart of Google’s self driving car is the rotating roof top camera, Lidar, which is a laser range finder. With its array of 64 laser beams, this camera creates 3D images of objects helping the car see hazards along the way. This device calculates how far an object is from the moving vehicle based on the time it takes for the laser beams to hit the object and come back. These high intensity lasers can calculate distance and create images for objects in an impressive 200m range.

Front Camera for Near Vision

• A camera mounted on the windshield takes care of helping the car ‘see’ objects right in front of it. These include the usual suspects- pedestrians, and other motorists. This camera also detects and records information about road signs and traffic lights, which is intelligently interpreted by the car’s in built software.

Bumper Mounted Radar

• 4 radars mounted on the car’s front and rear bumpers enable the car to be aware of vehicles in front of it and behind it. The radar sensor on the car’s bumpers keeps a ‘digital eye’ on the car ahead. The software is programmed to vis-a-vis the car ahead of it. So with this technology the car will automatically speed up or slow down depending on the behaviour of the car/driver ahead. This is used to keep passengers and other motorists safe by avoiding bumps and crashes.

Aerial that Reads Precise Geo-Location

• An aerial on the rear of the car receives information about the precise location of the car, by GPS satellites. The car’s GPS inertial navigation unit works with the sensors to help the car localise itself. To minimise the degree of uncertainty, the GPS data is compared with sensor map data previously collected from the same location. As the vehicle moves, the vehicle’s internal map is updated with new positional information displayed by the sensors

Ultrasonic Sensors on Rear Wheels

• An ultrasonic sensor on one of the rear wheels helps keep track of movements of car and will alert car about obstacles in the rear. Cars that offer automatic ‘Reverse Park Assist’ technology utilise such sensors to help navigate the car into tight reverse parking spots. Typically, these sensors get activated when the car is engaged in the reverse gear.

Synergistic Combining of Sensors

• All the data gathered by these sensors is collated and interpreted together by the car’s CPU or in built software system to

create a safe driving experience.

Programmed to Interpret Common Road Signs

• The software is programmed to interpret common road behaviour and motorist signs. For ex, if a cyclist gestures that he intends to make a manoeuvre, the driverless car interprets it correctly and slows down to allow the motorist to turn. Predetermined shape and motion descriptors are programmed into system to help the car make intelligent decisions. For instance, if car detects a 2 wheel object and determines speed of the object as 10mph rather than 50 mph, car instantly interprets that this vehicle is a bicycle and not a motorbike and behaves accordingly. Several such programs fed into the car’s central processing unit will work simultaneously, helping the car make safe and intelligent decisions on busy roads.

Mapping in Advance

• before a self-driven car is tested, a regular car is driven along the route and maps out route and it’s road conditions including poles, road markers, road signs and more. This map is fed into car’s software helping the car identify what is a regular part of the road. As the car moves, its Velodyne laser range finder kicks in and generates a detailed 3D map of the environment at that moment. The car compares this map with the pre-existing map to figure out the non-standard aspects in the road, rightly identifying them as pedestrians and/or other motorists, thus avoiding them.

Programming Real Life Road Behaviour

• Google engineers have programmed some real life behaviour in these cars. While the vehicle does slow down to allow other motorists to go ahead, especially in 4 way intersections, the car has also been programmed to advance ahead if it detects that the other vehicle is not moving.

FEASIBILITY ANALISIS

1 Adoption • (a) Cost: Although the cost involved in achieving the goal of autonomous

vehicle is very high but the infrastructure cost here is only the one time initial cost, once the infrastructure has been established there is just the requirement of time to time maintenance. Also in upcoming future with the help of convergence we can reduce its cost.

• (b) Driver Education: There is need to educate drivers in-case of limited self-driving so that the driver could understand the messages exchanged and can also send messages to the other vehicles for efficient travelling.

• (c) Consumer Acceptence: In Global surveyof 1,514 consumers 18year or older, Cisco found that 57 percent would put their trust ina driverless vehice. The answer varied widely depending on country, with 95 percent Brazillians embracingthe concept of silicon chauffer. In Japan skepticismis still very high with only 28 percent willing to give up direct control of their cars

(d) Legislation:Various legislations are being already prepared by government of different countries.For e.g. Brazil’s government is already preparing legislation that will require all cars to have a beacon.